Prime NumbersPrime Numbers highlights prime numbers (no surprise there 😅), tokens and the recent "active" feature in "input".
🔸 CONCEPTS
🔹 What are Prime Numbers?
A prime number (or a prime) is a natural number greater than 1 that is not a product of two smaller natural numbers.
Wikipedia: Prime number
🔹 Prime Factorization
The fundamental theorem of arithmetic states that every integer larger than 1 can be written as a product of one or more primes. More strongly, this product is unique in the sense that any two prime factorizations of the same number will have the same number of copies of the same primes, although their ordering may differ. So, although there are many different ways of finding a factorization using an integer factorization algorithm, they all must produce the same result. Primes can thus be considered the "basic building blocks" of the natural numbers.
Wikipedia: Fundamental theorem of arithmetic
Math Is Fun: Prime Factorization
We divide a given number by Prime Numbers until only Primes remain.
Example:
24 / 2 = 12 | 24 / 3 = 8
12 / 3 = 4 | 8 / 2 = 4
4 / 2 = 2 | 4 / 2 = 2
|
24 = 2 x 3 x 2 | 24 = 3 x 2 x 2
or | or
24 = 2² x 3 | 24 = 2² x 3
In other words, every natural/integer number above 1 has a unique representation as a product of prime numbers, no matter how the number is divided. Only the order can change, but the factors (the basic elements) are always the same.
🔸 USAGE
The Prime Numbers publication contains two use cases:
Prime Factorization: performed on "close" prices, or a manual chosen number.
List Prime Numbers: shows a list of Prime Numbers.
The other two options are discussed in the DETAILS chapter:
Prime Factorization Without Arrays
Find Prime Numbers
🔹 Prime Factorization
Users can choose to perform Prime Factorization on close prices or a manually given number.
❗️ Note that this option only applies to close prices above 1, which are also rounded since Prime Factorization can only be performed on natural (integer) numbers above 1.
In the image below, the left example shows Prime Factorization performed on each close price for the latest 50 bars (which is set with "Run script only on 'Last x Bars'" -> 50).
The right example shows Prime Factorization performed on a manually given number, in this case "1,340,011". This is done only on the last bar.
When the "Source" option "close price" is chosen, one can toggle "Also current price", where both the historical and the latest current price are factored. If disabled, only historical prices are factored.
Note that, depending on the chosen options, only applicable settings are available, due to a recent feature, namely the parameter "active" in settings.
Setting the "Source" option to "Manual - Limited" will factorize any given number between 1 and 1,340,011, the latter being the highest value in the available arrays with primes.
Setting to "Manual - Not Limited" enables the user to enter a higher number. If all factors of the manual entered number are in the 1 - 1,340,011 range, these factors will be shown; however, if a factor is higher than 1,340,011, the calculation will stop, after which a warning is shown:
The calculated factors are displayed as a label where identical factors are simplified with an exponent notation in superscript.
For example 2 x 2 x 2 x 5 x 7 x 7 will be noted as 2³ x 5 x 7²
🔹 List Prime Numbers
The "List Prime Numbers" option enables users to enter a number, where the first found Prime Number is shown, together with the next x Prime Numbers ("Amount", max. 200)
The highest shown Prime Number is 1,340,011.
One can set the number of shown columns to customize the displayed numbers ("Max. columns", max. 20).
🔸 DETAILS
The Prime Numbers publication consists out of 4 parts:
Prime Factorization Without Arrays
Prime Factorization
List Prime Numbers
Find Prime Numbers
The usage of "Prime Factorization" and "List Prime Numbers" is explained above.
🔹 Prime Factorization Without Arrays
This option is only there to highlight a hurdle while performing Prime Factorization.
The basic method of Prime Factorization is to divide the base number by 2, 3, ... until the result is an integer number. Continue until the remaining number and its factors are all primes.
The division should be done by primes, but then you need to know which one is a prime.
In practice, one performs a loop from 2 to the base number.
Example:
Base_number = input.int(24)
arr = array.new()
n = Base_number
go = true
while go
for i = 2 to n
if n % i == 0
if n / i == 1
go := false
arr.push(i)
label.new(bar_index, high, str.tostring(arr))
else
arr.push(i)
n /= i
break
Small numbers won't cause issues, but when performing the calculations on, for example, 124,001 and a timeframe of, for example, 1 hour, the script will struggle and finally give a runtime error.
How to solve this?
If we use an array with only primes, we need fewer calculations since if we divide by a non-prime number, we have to divide further until all factors are primes.
I've filled arrays with prime numbers and made libraries of them. (see chapter "Find Prime Numbers" to know how these primes were found).
🔹 Tokens
A hurdle was to fill the libraries with as many prime numbers as possible.
Initially, the maximum token limit of a library was 80K.
Very recently, that limit was lifted to 100K. Kudos to the TradingView developers!
What are tokens?
Tokens are the smallest elements of a program that are meaningful to the compiler. They are also known as the fundamental building blocks of the program.
I have included a code block below the publication code (// - - - Educational (2) - - - ) which, if copied and made to a library, will contain exactly 100K tokens.
Adding more exported functions will throw a "too many tokens" error when saving the library. Subtracting 100K from the shown amount of tokens gives you the amount of used tokens for that particular function.
In that way, one can experiment with the impact of each code addition in terms of tokens.
For example adding the following code in the library:
export a() => a = array.from(1) will result in a 100,041 tokens error, in other words (100,041 - 100,000) that functions contains 41 tokens.
Some more examples, some are straightforward, others are not )
// adding these lines in one of the arrays results in x tokens
, 1 // 2 tokens
, 111, 111, 111 // 12 tokens
, 1111 // 5 tokens
, 111111111 // 10 tokens
, 1111111111111111111 // 20 tokens
, 1234567890123456789 // 20 tokens
, 1111111111111111111 + 1 // 20 tokens
, 1111111111111111111 + 8 // 20 tokens
, 1111111111111111111 + 9 // 20 tokens
, 1111111111111111111 * 1 // 20 tokens
, 1111111111111111111 * 9 // 21 tokens
, 9999999999999999999 // 21 tokens
, 1111111111111111111 * 10 // 21 tokens
, 11111111111111111110 // 21 tokens
//adding these functions to the library results in x tokens
export f() => 1 // 4 tokens
export f() => v = 1 // 4 tokens
export f() => var v = 1 // 4 tokens
export f() => var v = 1, v // 4 tokens
//adding these functions to the library results in x tokens
export a() => const arraya = array.from(1) // 42 tokens
export a() => arraya = array.from(1) // 42 tokens
export a() => a = array.from(1) // 41 tokens
export a() => array.from(1) // 32 tokens
export a() => a = array.new() // 44 tokens
export a() => a = array.new(), a.push(1) // 56 tokens
What if we could lower the amount of tokens, so we can export more Prime Numbers?
Look at this example:
829111, 829121, 829123, 829151, 829159, 829177, 829187, 829193
Eight numbers contain the same number 8291.
If we make a function that removes recurrent values, we get fewer tokens!
829111, 829121, 829123, 829151, 829159, 829177, 829187, 829193
//is transformed to:
829111, 21, 23, 51, 59, 77, 87, 93
The code block below the publication code (// - - - Educational (1) - - - ) shows how these values were reduced. With each step of 100, only the first Prime Number is shown fully.
This function could be enhanced even more to reduce recurrent thousands, tens of thousands, etc.
Using this technique enables us to export more Prime Numbers. The number of necessary libraries was reduced to half or less.
The reduced Prime Numbers are restored using the restoreValues() function, found in the library fikira/Primes_4.
🔹 Find Prime Numbers
This function is merely added to show how I filled arrays with Prime Numbers, which were, in turn, added to libraries (after reduction of recurrent values).
To know whether a number is a Prime Number, we divide the given number by values of the Primes array (Primes 2 -> max. 1,340,011). Once the division results in an integer, where the divisor is smaller than the dividend, the calculation stops since the given number is not a Prime.
When we perform these calculations in a loop, we can check whether a series of numbers is a Prime or not. Each time a number is proven not to be a Prime, the loop starts again with a higher number. Once all Primes of the array are used without the result being an integer, we have found a new Prime Number, which is added to the array.
Doing such calculations on one bar will result in a runtime error.
To solve this, the findPrimeNumbers() function remembers the index of the array. Once a limit has been reached on 1 bar (for example, the number of iterations), calculations will stop on that bar and restart on the next bar.
This spreads the workload over several bars, making it possible to continue these calculations without a runtime error.
The result is placed in log.info() , which can be copied and pasted into a hardcoded array of Prime Number values.
These settings adjust the amount of workload per bar:
Max Size: maximum size of Primes array.
Max Bars Runtime: maximum amount of bars where the function is called.
Max Numbers To Process Per Bar: maximum numbers to check on each bar, whether they are Prime Numbers.
Max Iterations Per Bar: maximum loop calculations per bar.
🔹 The End
❗️ The code and description is written without the help of an LLM, I've only used Grammarly to improve my description (without AI :) )
Recherche dans les scripts pour "20日线角度大于0的股票"
Market Zone Analyzer[BullByte]Understanding the Market Zone Analyzer
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1. Purpose of the Indicator
The Market Zone Analyzer is a Pine Script™ (version 6) indicator designed to streamline market analysis on TradingView. Rather than scanning multiple separate tools, it unifies four core dimensions—trend strength, momentum, price action, and market activity—into a single, consolidated view. By doing so, it helps traders:
• Save time by avoiding manual cross-referencing of disparate signals.
• Reduce decision-making errors that can arise from juggling multiple indicators.
• Gain a clear, reliable read on whether the market is in a bullish, bearish, or sideways phase, so they can more confidently decide to enter, exit, or hold a position.
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2. Why a Trader Should Use It
• Unified View: Combines all essential market dimensions into one easy-to-read score and dashboard, eliminating the need to piece together signals manually.
• Adaptability: Automatically adjusts its internal weighting for trend, momentum, and price action based on current volatility. Whether markets are choppy or calm, the indicator remains relevant.
• Ease of Interpretation: Outputs a simple “BULLISH,” “BEARISH,” or “SIDEWAYS” label, supplemented by an intuitive on-chart dashboard and an oscillator plot that visually highlights market direction.
• Reliability Features: Built-in smoothing of the net score and hysteresis logic (requiring consecutive confirmations before flips) minimize false signals during noisy or range-bound phases.
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3. Why These Specific Indicators?
This script relies on a curated set of well-established technical tools, each chosen for its particular strength in measuring one of the four core dimensions:
1. Trend Strength:
• ADX/DMI (Average Directional Index / Directional Movement Index): Measures how strong a trend is, and whether the +DI line is above the –DI line (bullish) or vice versa (bearish).
• Moving Average Slope (Fast MA vs. Slow MA): Compares a shorter-period SMA to a longer-period SMA; if the fast MA sits above the slow MA, it confirms an uptrend, and vice versa for a downtrend.
• Ichimoku Cloud Differential (Senkou A vs. Senkou B): Provides a forward-looking view of trend direction; Senkou A above Senkou B signals bullishness, and the opposite signals bearishness.
2. Momentum:
• Relative Strength Index (RSI): Identifies overbought (above its dynamically calculated upper bound) or oversold (below its lower bound) conditions; changes in RSI often precede price reversals.
• Stochastic %K: Highlights shifts in short-term momentum by comparing closing price to the recent high/low range; values above its upper band signal bullish momentum, below its lower band signal bearish momentum.
• MACD Histogram: Measures the difference between the MACD line and its signal line; a positive histogram indicates upward momentum, a negative histogram indicates downward momentum.
3. Price Action:
• Highest High / Lowest Low (HH/LL) Range: Over a defined lookback period, this captures breakout or breakdown levels. A closing price near the recent highs (with a positive MA slope) yields a bullish score, and near the lows (with a negative MA slope) yields a bearish score.
• Heikin-Ashi Doji Detection: Uses Heikin-Ashi candles to identify indecision or continuation patterns. A small Heikin-Ashi body (doji) relative to recent volatility is scored as neutral; a larger body in the direction of the MA slope is scored bullish or bearish.
• Candle Range Measurement: Compares each candle’s high-low range against its own dynamic band (average range ± standard deviation). Large candles aligning with the prevailing trend score bullish or bearish accordingly; unusually small candles can indicate exhaustion or consolidation.
4. Market Activity:
• Bollinger Bands Width (BBW): Measures the distance between BB upper and lower bands; wide bands indicate high volatility, narrow bands indicate low volatility.
• Average True Range (ATR): Quantifies average price movement (volatility). A sudden spike in ATR suggests a volatile environment, while a contraction suggests calm.
• Keltner Channels Width (KCW): Similar to BBW but uses ATR around an EMA. Provides a second layer of volatility context, confirming or contrasting BBW readings.
• Volume (with Moving Average): Compares current volume to its moving average ± standard deviation. High volume validates strong moves; low volume signals potential lack of conviction.
By combining these tools, the indicator captures trend direction, momentum strength, price-action nuances, and overall market energy, yielding a more balanced and comprehensive assessment than any single tool alone.
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4. What Makes This Indicator Stand Out
• Multi-Dimensional Analysis: Rather than relying on a lone oscillator or moving average crossover, it simultaneously evaluates trend, momentum, price action, and activity.
• Dynamic Weighting: The relative importance of trend, momentum, and price action adjusts automatically based on real-time volatility (Market Activity State). For example, in highly volatile conditions, trend and momentum signals carry more weight; in calm markets, price action signals are prioritized.
• Stability Mechanisms:
• Smoothing: The net score is passed through a short moving average, filtering out noise, especially on lower timeframes.
• Hysteresis: Both Market Activity State and the final bullish/bearish/sideways zone require two consecutive confirmations before flipping, reducing whipsaw.
• Visual Interpretation: A fully customizable on-chart dashboard displays each sub-indicator’s value, regime, score, and comment, all color-coded. The oscillator plot changes color to reflect the current market zone (green for bullish, red for bearish, gray for sideways) and shows horizontal threshold lines at +2, 0, and –2.
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5. Recommended Timeframes
• Short-Term (5 min, 15 min): Day traders and scalpers can benefit from rapid signals, but should enable smoothing (and possibly disable hysteresis) to reduce false whipsaws.
• Medium-Term (1 h, 4 h): Swing traders find a balance between responsiveness and reliability. Less smoothing is required here, and the default parameters (e.g., ADX length = 14, RSI length = 14) perform well.
• Long-Term (Daily, Weekly): Position traders tracking major trends can disable smoothing for immediate raw readings, since higher-timeframe noise is minimal. Adjust lookback lengths (e.g., increase adxLength, rsiLength) if desired for slower signals.
Tip: If you keep smoothing off, stick to timeframes of 1 h or higher to avoid excessive signal “chatter.”
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6. How Scoring Works
A. Individual Indicator Scores
Each sub-indicator is assigned one of three discrete scores:
• +1 if it indicates a bullish condition (e.g., RSI above its dynamically calculated upper bound).
• 0 if it is neutral (e.g., RSI between upper and lower bounds).
• –1 if it indicates a bearish condition (e.g., RSI below its dynamically calculated lower bound).
Examples of individual score assignments:
• ADX/DMI:
• +1 if ADX ≥ adxThreshold and +DI > –DI (strong bullish trend)
• –1 if ADX ≥ adxThreshold and –DI > +DI (strong bearish trend)
• 0 if ADX < adxThreshold (trend strength below threshold)
• RSI:
• +1 if RSI > RSI_upperBound
• –1 if RSI < RSI_lowerBound
• 0 otherwise
• ATR (as part of Market Activity):
• +1 if ATR > (ATR_MA + stdev(ATR))
• –1 if ATR < (ATR_MA – stdev(ATR))
• 0 otherwise
Each of the four main categories shares this same +1/0/–1 logic across their sub-components.
B. Category Scores
Once each sub-indicator reports +1, 0, or –1, these are summed within their categories as follows:
• Trend Score = (ADX score) + (MA slope score) + (Ichimoku differential score)
• Momentum Score = (RSI score) + (Stochastic %K score) + (MACD histogram score)
• Price Action Score = (Highest-High/Lowest-Low score) + (Heikin-Ashi doji score) + (Candle range score)
• Market Activity Raw Score = (BBW score) + (ATR score) + (KC width score) + (Volume score)
Each category’s summed value can range between –3 and +3 (for Trend, Momentum, and Price Action), and between –4 and +4 for Market Activity raw.
C. Market Activity State and Dynamic Weight Adjustments
Rather than contributing directly to the netScore like the other three categories, Market Activity determines how much weight to assign to Trend, Momentum, and Price Action:
1. Compute Market Activity Raw Score by summing BBW, ATR, KCW, and Volume individual scores (each +1/0/–1).
2. Bucket into High, Medium, or Low Activity:
• High if raw Score ≥ 2 (volatile market).
• Low if raw Score ≤ –2 (calm market).
• Medium otherwise.
3. Apply Hysteresis (if enabled): The state only flips after two consecutive bars register the same high/low/medium label.
4. Set Category Weights:
• High Activity: Trend = 50 %, Momentum = 35 %, Price Action = 15 %.
• Low Activity: Trend = 25 %, Momentum = 20 %, Price Action = 55 %.
• Medium Activity: Use the trader’s base weight inputs (e.g., Trend = 40 %, Momentum = 30 %, Price Action = 30 % by default).
D. Calculating the Net Score
5. Normalize Base Weights (so that the sum of Trend + Momentum + Price Action always equals 100 %).
6. Determine Current Weights based on the Market Activity State (High/Medium/Low).
7. Compute Each Category’s Contribution: Multiply (categoryScore) × (currentWeight).
8. Sum Contributions to get the raw netScore (a floating-point value that can exceed ±3 when scores are strong).
9. Smooth the netScore over two bars (if smoothing is enabled) to reduce noise.
10. Apply Hysteresis to the Final Zone:
• If the smoothed netScore ≥ +2, the bar is classified as “Bullish.”
• If the smoothed netScore ≤ –2, the bar is classified as “Bearish.”
• Otherwise, it is “Sideways.”
• To prevent rapid flips, the script requires two consecutive bars in the new zone before officially changing the displayed zone (if hysteresis is on).
E. Thresholds for Zone Classification
• BULLISH: netScore ≥ +2
• BEARISH: netScore ≤ –2
• SIDEWAYS: –2 < netScore < +2
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7. Role of Volatility (Market Activity State) in Scoring
Volatility acts as a dynamic switch that shifts which category carries the most influence:
1. High Activity (Volatile):
• Detected when at least two sub-scores out of BBW, ATR, KCW, and Volume equal +1.
• The script sets Trend weight = 50 % and Momentum weight = 35 %. Price Action weight is minimized at 15 %.
• Rationale: In volatile markets, strong trending moves and momentum surges dominate, so those signals are more reliable than nuanced candle patterns.
2. Low Activity (Calm):
• Detected when at least two sub-scores out of BBW, ATR, KCW, and Volume equal –1.
• The script sets Price Action weight = 55 %, Trend = 25 %, and Momentum = 20 %.
• Rationale: In quiet, sideways markets, subtle price-action signals (breakouts, doji patterns, small-range candles) are often the best early indicators of a new move.
3. Medium Activity (Balanced):
• Raw Score between –1 and +1 from the four volatility metrics.
• Uses whatever base weights the trader has specified (e.g., Trend = 40 %, Momentum = 30 %, Price Action = 30 %).
Because volatility can fluctuate rapidly, the script employs hysteresis on Market Activity State: a new High or Low state must occur on two consecutive bars before weights actually shift. This avoids constant back-and-forth weight changes and provides more stability.
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8. Scoring Example (Hypothetical Scenario)
• Symbol: Bitcoin on a 1-hour chart.
• Market Activity: Raw volatility sub-scores show BBW (+1), ATR (+1), KCW (0), Volume (+1) → Total raw Score = +3 → High Activity.
• Weights Selected: Trend = 50 %, Momentum = 35 %, Price Action = 15 %.
• Trend Signals:
• ADX strong and +DI > –DI → +1
• Fast MA above Slow MA → +1
• Ichimoku Senkou A > Senkou B → +1
→ Trend Score = +3
• Momentum Signals:
• RSI above upper bound → +1
• MACD histogram positive → +1
• Stochastic %K within neutral zone → 0
→ Momentum Score = +2
• Price Action Signals:
• Highest High/Lowest Low check yields 0 (close not near extremes)
• Heikin-Ashi doji reading is neutral → 0
• Candle range slightly above upper bound but trend is strong, so → +1
→ Price Action Score = +1
• Compute Net Score (before smoothing):
• Trend contribution = 3 × 0.50 = 1.50
• Momentum contribution = 2 × 0.35 = 0.70
• Price Action contribution = 1 × 0.15 = 0.15
• Raw netScore = 1.50 + 0.70 + 0.15 = 2.35
• Since 2.35 ≥ +2 and hysteresis is met, the final zone is “Bullish.”
Although the netScore lands at 2.35 (Bullish), smoothing might bring it slightly below 2.00 on the first bar (e.g., 1.90), in which case the script would wait for a second consecutive reading above +2 before officially classifying the zone as Bullish (if hysteresis is enabled).
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9. Correlation Between Categories
The four categories—Trend Strength, Momentum, Price Action, and Market Activity—often reinforce or offset one another. The script takes advantage of these natural correlations:
• Bullish Alignment: If ADX is strong and pointed upward, fast MA is above slow MA, and Ichimoku is positive, that usually coincides with RSI climbing above its upper bound and the MACD histogram turning positive. In such cases, both Trend and Momentum categories generate +1 or +2. Because the Market Activity State is likely High (given the accompanying volatility), Trend and Momentum weights are at their peak, so the netScore quickly crosses into Bullish territory.
• Sideways/Consolidation: During a low-volatility, sideways phase, ADX may fall below its threshold, MAs may flatten, and RSI might hover in the neutral band. However, subtle price-action signals (like a small breakout candle or a Heikin-Ashi candle with a slight bias) can still produce a +1 in the Price Action category. If Market Activity is Low, Price Action’s weight (55 %) can carry enough influence—even if Trend and Momentum are neutral—to push the netScore out of “Sideways” into a mild bullish or bearish bias.
• Opposing Signals: When Trend is bullish but Momentum turns negative (for example, price continues up but RSI rolls over), the two scores can partially cancel. Market Activity may remain Medium, in which case the netScore lingers near zero (Sideways). The trader can then wait for either a clearer momentum shift or a fresh price-action breakout before committing.
By dynamically recognizing these correlations and adjusting weights, the indicator ensures that:
• When Trend and Momentum align (and volatility supports it), the netScore leaps strongly into Bullish or Bearish.
• When Trend is neutral but Price Action shows an early move in a low-volatility environment, Price Action’s extra weight in the Low Activity State can still produce actionable signals.
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10. Market Activity State & Its Role (Detailed)
The Market Activity State is not a direct category score—it is an overarching context setter for how heavily to trust Trend, Momentum, or Price Action. Here’s how it is derived and applied:
1. Calculate Four Volatility Sub-Scores:
• BBW: Compare the current band width to its own moving average ± standard deviation. If BBW > (BBW_MA + stdev), assign +1 (high volatility); if BBW < (BBW_MA × 0.5), assign –1 (low volatility); else 0.
• ATR: Compare ATR to its moving average ± standard deviation. A spike above the upper threshold is +1; a contraction below the lower threshold is –1; otherwise 0.
• KCW: Same logic as ATR but around the KCW mean.
• Volume: Compare current volume to its volume MA ± standard deviation. Above the upper threshold is +1; below the lower threshold is –1; else 0.
2. Sum Sub-Scores → Raw Market Activity Score: Range between –4 and +4.
3. Assign Market Activity State:
• High Activity: Raw Score ≥ +2 (at least two volatility metrics are strongly spiking).
• Low Activity: Raw Score ≤ –2 (at least two metrics signal unusually low volatility or thin volume).
• Medium Activity: Raw Score is between –1 and +1 inclusive.
4. Hysteresis for Stability:
• If hysteresis is enabled, a new state only takes hold after two consecutive bars confirm the same High, Medium, or Low label.
• This prevents the Market Activity State from bouncing around when volatility is on the fence.
5. Set Category Weights Based on Activity State:
• High Activity: Trend = 50 %, Momentum = 35 %, Price Action = 15 %.
• Low Activity: Trend = 25 %, Momentum = 20 %, Price Action = 55 %.
• Medium Activity: Use trader’s base weights (e.g., Trend = 40 %, Momentum = 30 %, Price Action = 30 %).
6. Impact on netScore: Because category scores (–3 to +3) multiply by these weights, High Activity amplifies the effect of strong Trend and Momentum scores; Low Activity amplifies the effect of Price Action.
7. Market Context Tooltip: The dashboard includes a tooltip summarizing the current state—e.g., “High activity, trend and momentum prioritized,” “Low activity, price action prioritized,” or “Balanced market, all categories considered.”
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11. Category Weights: Base vs. Dynamic
Traders begin by specifying base weights for Trend Strength, Momentum, and Price Action that sum to 100 %. These apply only when volatility is in the Medium band. Once volatility shifts:
• High Volatility Overrides:
• Trend jumps from its base (e.g., 40 %) to 50 %.
• Momentum jumps from its base (e.g., 30 %) to 35 %.
• Price Action is reduced to 15 %.
Example: If base weights were Trend = 40 %, Momentum = 30 %, Price Action = 30 %, then in High Activity they become 50/35/15. A Trend score of +3 now contributes 3 × 0.50 = +1.50 to netScore; a Momentum +2 contributes 2 × 0.35 = +0.70. In total, Trend + Momentum can easily push netScore above the +2 threshold on its own.
• Low Volatility Overrides:
• Price Action leaps from its base (30 %) to 55 %.
• Trend falls to 25 %, Momentum falls to 20 %.
Why? When markets are quiet, subtle candle breakouts, doji patterns, and small-range expansions tend to foreshadow the next swing more effectively than raw trend readings. A Price Action score of +3 in this state contributes 3 × 0.55 = +1.65, which can carry the netScore toward +2—even if Trend and Momentum are neutral or only mildly positive.
Because these weight shifts happen only after two consecutive bars confirm a High or Low state (if hysteresis is on), the indicator avoids constantly flipping its emphasis during borderline volatility phases.
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12. Dominant Category Explained
Within the dashboard, a label such as “Trend Dominant,” “Momentum Dominant,” or “Price Action Dominant” appears when one category’s absolute weighted contribution to netScore is the largest. Concretely:
• Compute each category’s weighted contribution = (raw category score) × (current weight).
• Compare the absolute values of those three contributions.
• The category with the highest absolute value is flagged as Dominant for that bar.
Why It Matters:
• Momentum Dominant: Indicates that the combined force of RSI, Stochastic, and MACD (after weighting) is pushing netScore farther than either Trend or Price Action. In practice, it means that short-term sentiment and speed of change are the primary drivers right now, so traders should watch for continued momentum signals before committing to a trade.
• Trend Dominant: Means ADX, MA slope, and Ichimoku (once weighted) outweigh the other categories. This suggests a strong directional move is in place; trend-following entries or confirming pullbacks are likely to succeed.
• Price Action Dominant: Occurs when breakout/breakdown patterns, Heikin-Ashi candle readings, and range expansions (after weighting) are the most influential. This often happens in calmer markets, where subtle shifts in candle structure can foreshadow bigger moves.
By explicitly calling out which category is carrying the most weight at any moment, the dashboard gives traders immediate insight into why the netScore is tilting toward bullish, bearish, or sideways.
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13. Oscillator Plot: How to Read It
The “Net Score” oscillator sits below the dashboard and visually displays the smoothed netScore as a line graph. Key features:
1. Value Range: In normal conditions it oscillates roughly between –3 and +3, but extreme confluences can push it outside that range.
2. Horizontal Threshold Lines:
• +2 Line (Bullish threshold)
• 0 Line (Neutral midline)
• –2 Line (Bearish threshold)
3. Zone Coloring:
• Green Background (Bullish Zone): When netScore ≥ +2.
• Red Background (Bearish Zone): When netScore ≤ –2.
• Gray Background (Sideways Zone): When –2 < netScore < +2.
4. Dynamic Line Color:
• The plotted netScore line itself is colored green in a Bullish Zone, red in a Bearish Zone, or gray in a Sideways Zone, creating an immediate visual cue.
Interpretation Tips:
• Crossing Above +2: Signals a strong enough combined trend/momentum/price-action reading to classify as Bullish. Many traders wait for a clear crossing plus a confirmation candle before entering a long position.
• Crossing Below –2: Indicates a strong Bearish signal. Traders may consider short or exit strategies.
• Rising Slope, Even Below +2: If netScore climbs steadily from neutral toward +2, it demonstrates building bullish momentum.
• Divergence: If price makes a higher high but the oscillator fails to reach a new high, it can warn of weakening momentum and a potential reversal.
---
14. Comments and Their Necessity
Every sub-indicator (ADX, MA slope, Ichimoku, RSI, Stochastic, MACD, HH/LL, Heikin-Ashi, Candle Range, BBW, ATR, KCW, Volume) generates a short comment that appears in the detailed dashboard. Examples:
• “Strong bullish trend” or “Strong bearish trend” for ADX/DMI
• “Fast MA above slow MA” or “Fast MA below slow MA” for MA slope
• “RSI above dynamic threshold” or “RSI below dynamic threshold” for RSI
• “MACD histogram positive” or “MACD histogram negative” for MACD Hist
• “Price near highs” or “Price near lows” for HH/LL checks
• “Bullish Heikin Ashi” or “Bearish Heikin Ashi” for HA Doji scoring
• “Large range, trend confirmed” or “Small range, trend contradicted” for Candle Range
Additionally, the top-row comment for each category is:
• Trend: “Highly Bullish,” “Highly Bearish,” or “Neutral Trend.”
• Momentum: “Strong Momentum,” “Weak Momentum,” or “Neutral Momentum.”
• Price Action: “Bullish Action,” “Bearish Action,” or “Neutral Action.”
• Market Activity: “Volatile Market,” “Calm Market,” or “Stable Market.”
Reasons for These Comments:
• Transparency: Shows exactly how each sub-indicator contributed to its category score.
• Education: Helps traders learn why a category is labeled bullish, bearish, or neutral, building intuition over time.
• Customization: If, for example, the RSI comment says “RSI neutral” despite an impending trend shift, a trader might choose to adjust RSI length or thresholds.
In the detailed dashboard, hovering over each comment cell also reveals a tooltip with additional context (e.g., “Fast MA above slow MA” or “Senkou A above Senkou B”), helping traders understand the precise rule behind that +1, 0, or –1 assignment.
---
15. Real-Life Example (Consolidated)
• Instrument & Timeframe: Bitcoin (BTCUSD), 1-hour chart.
• Current Market Activity: BBW and ATR both spike (+1 each), KCW is moderately high (+1), but volume is only neutral (0) → Raw Market Activity Score = +2 → State = High Activity (after two bars, if hysteresis is on).
• Category Weights Applied: Trend = 50 %, Momentum = 35 %, Price Action = 15 %.
• Trend Sub-Scores:
1. ADX = 25 (above threshold 20) with +DI > –DI → +1.
2. Fast MA (20-period) sits above Slow MA (50-period) → +1.
3. Ichimoku: Senkou A > Senkou B → +1.
→ Trend Score = +3.
• Momentum Sub-Scores:
4. RSI = 75 (above its moving average +1 stdev) → +1.
5. MACD histogram = +0.15 → +1.
6. Stochastic %K = 50 (mid-range) → 0.
→ Momentum Score = +2.
• Price Action Sub-Scores:
7. Price is not within 1 % of the 20-period high/low and slope = positive → 0.
8. Heikin-Ashi body is slightly larger than stdev over last 5 bars with haClose > haOpen → +1.
9. Candle range is just above its dynamic upper bound but trend is already captured, so → +1.
→ Price Action Score = +2.
• Calculate netScore (before smoothing):
• Trend contribution = 3 × 0.50 = 1.50
• Momentum contribution = 2 × 0.35 = 0.70
• Price Action contribution = 2 × 0.15 = 0.30
• Raw netScore = 1.50 + 0.70 + 0.30 = 2.50 → Immediately classified as Bullish.
• Oscillator & Dashboard Output:
• The oscillator line crosses above +2 and turns green.
• Dashboard displays:
• Trend Regime “BULLISH,” Trend Score = 3, Comment = “Highly Bullish.”
• Momentum Regime “BULLISH,” Momentum Score = 2, Comment = “Strong Momentum.”
• Price Action Regime “BULLISH,” Price Action Score = 2, Comment = “Bullish Action.”
• Market Activity State “High,” Comment = “Volatile Market.”
• Weights: Trend 50 %, Momentum 35 %, Price Action 15 %.
• Dominant Category: Trend (because 1.50 > 0.70 > 0.30).
• Overall Score: 2.50, posCount = (three +1s in Trend) + (two +1s in Momentum) + (two +1s in Price Action) = 7 bullish signals, negCount = 0.
• Final Zone = “BULLISH.”
• The trader sees that both Trend and Momentum are reinforcing each other under high volatility. They might wait one more candle for confirmation but already have strong evidence to consider a long.
---
• .
---
Disclaimer
This indicator is strictly a technical analysis tool and does not constitute financial advice. All trading involves risk, including potential loss of capital. Past performance is not indicative of future results. Traders should:
• Always backtest the “Market Zone Analyzer ” on their chosen symbols and timeframes before committing real capital.
• Combine this tool with sound risk management, position sizing, and, if possible, fundamental analysis.
• Understand that no indicator is foolproof; always be prepared for unexpected market moves.
Goodluck
-BullByte!
---
Codigo Trading 1.0📌Codigo Trading 1.0
This indicator strategically combines SuperTrend, multiple Exponential Moving Averages (EMAs), the Relative Strength Index (RSI), and the Average True Range (ATR) to offer clear entry and exit signals, as well as an in-depth view of market trends. Ideal for traders looking to optimize their operations with an all-in-one tool.
🔩How the Indicator Works:
This indicator relies on the interaction and confirmation of several key components to generate signals:
SuperTrend: Determines the primary trend direction. An uptrend SuperTrend signal (green line) indicates an upward trend, while a downtrend (red line) signals a downward trend. It also serves as a guide for setting Stop Loss and Take Profit levels.
EMAs: Includes EMAs of 10, 20, 55, 100, 200, and 325 periods. The relationship between the EMA 10 and EMA 20 is fundamental for confirming the strength and direction of movements. An EMA 10 above the EMA 20 suggests an uptrend, and vice versa. Longer EMAs act as dynamic support and resistance levels, offering a broader view of the market structure.
RSI: Used to identify overbought (RSI > 70/80) and oversold (RSI < 30/20) conditions, generating "Take Profit" alerts for potential trade closures.
ATR: Monitors market volatility to help you manage exits. ATR exit signals are triggered when volatility changes direction, indicating a possible exhaustion of the movement.
🗒️Entry and Exit Signals:
I designed specific alerts based on all the indicators I use in conjunction:
Long Entries: When SuperTrend is bullish and EMA 10 crosses above EMA 20.
Short Entries: When SuperTrend is bearish and EMA 10 crosses below EMA 20.
RSI Exits (Take Profit): Indicated by "TP" labels on the chart, when the RSI reaches extreme levels (overbought for longs, oversold for shorts).
EMA 20 Exits: When the price closes below EMA 20 (for longs) or above EMA 20 (for shorts).
ATR Exits: When the ATR changes direction, signaling a possible decrease in momentum.
📌Key Benefits:
Clarity in Trend: Quickly identifies market direction with SuperTrend and EMA alignment.
Strategic Entry and Exit Signals: Receive timely alerts to optimize your entry and exit points.
Assisted Trade Management: RSI and ATR help you consider when to take profits or exit a position.
Intuitive Visualization: Arrows, labels, and colored lines make analysis easy to interpret.
Disclaimer:
Trading in financial markets carries significant risks. This indicator is an analysis tool and should not be considered financial advice. Always conduct your own research and trade at your own risk.
Ergodic Market Divergence (EMD)Ergodic Market Divergence (EMD)
Bridging Statistical Physics and Market Dynamics Through Ensemble Analysis
The Revolutionary Concept: When Physics Meets Trading
After months of research into ergodic theory—a fundamental principle in statistical mechanics—I've developed a trading system that identifies when markets transition between predictable and unpredictable states. This indicator doesn't just follow price; it analyzes whether current market behavior will persist or revert, giving traders a scientific edge in timing entries and exits.
The Core Innovation: Ergodic Theory Applied to Markets
What Makes Markets Ergodic or Non-Ergodic?
In statistical physics, ergodicity determines whether a system's future resembles its past. Applied to trading:
Ergodic Markets (Mean-Reverting)
- Time averages equal ensemble averages
- Historical patterns repeat reliably
- Price oscillates around equilibrium
- Traditional indicators work well
Non-Ergodic Markets (Trending)
- Path dependency dominates
- History doesn't predict future
- Price creates new equilibrium levels
- Momentum strategies excel
The Mathematical Framework
The Ergodic Score combines three critical divergences:
Ergodic Score = (Price Divergence × Market Stress + Return Divergence × 1000 + Volatility Divergence × 50) / 3
Where:
Price Divergence: How far current price deviates from market consensus
Return Divergence: Momentum differential between instrument and market
Volatility Divergence: Volatility regime misalignment
Market Stress: Adaptive multiplier based on current conditions
The Ensemble Analysis Revolution
Beyond Single-Instrument Analysis
Traditional indicators analyze one chart in isolation. EMD monitors multiple correlated markets simultaneously (SPY, QQQ, IWM, DIA) to detect systemic regime changes. This ensemble approach:
Reveals Hidden Divergences: Individual stocks may diverge from market consensus before major moves
Filters False Signals: Requires broader market confirmation
Identifies Regime Shifts: Detects when entire market structure changes
Provides Context: Shows if moves are isolated or systemic
Dynamic Threshold Adaptation
Unlike fixed-threshold systems, EMD's boundaries evolve with market conditions:
Base Threshold = SMA(Ergodic Score, Lookback × 3)
Adaptive Component = StDev(Ergodic Score, Lookback × 2) × Sensitivity
Final Threshold = Smoothed(Base + Adaptive)
This creates context-aware signals that remain effective across different market environments.
The Confidence Engine: Know Your Signal Quality
Multi-Factor Confidence Scoring
Every signal receives a confidence score based on:
Signal Clarity (0-35%): How decisively the ergodic threshold is crossed
Momentum Strength (0-25%): Rate of ergodic change
Volatility Alignment (0-20%): Whether volatility supports the signal
Market Quality (0-20%): Price convergence and path dependency factors
Real-Time Confidence Updates
The Live Confidence metric continuously updates, showing:
- Current opportunity quality
- Market state clarity
- Historical performance influence
- Signal recency boost
- Visual Intelligence System
Adaptive Ergodic Field Bands
Dynamic bands that expand and contract based on market state:
Primary Color: Ergodic state (mean-reverting)
Danger Color: Non-ergodic state (trending)
Band Width: Expected price movement range
Squeeze Indicators: Volatility compression warnings
Quantum Wave Ribbons
Triple EMA system (8, 21, 55) revealing market flow:
Compressed Ribbons: Consolidation imminent
Expanding Ribbons: Directional move developing
Color Coding: Matches current ergodic state
Phase Transition Signals
Clear entry/exit markers at regime changes:
Bull Signals: Ergodic restoration (mean reversion opportunity)
Bear Signals: Ergodic break (trend following opportunity)
Confidence Labels: Percentage showing signal quality
Visual Intensity: Stronger signals = deeper colors
Professional Dashboard Suite
Main Analytics Panel (Top Right)
Market State Monitor
- Current regime (Ergodic/Non-Ergodic)
- Ergodic score with threshold
- Path dependency strength
- Quantum coherence percentage
Divergence Metrics
- Price divergence with severity
- Volatility regime classification
- Strategy mode recommendation
- Signal strength indicator
Live Intelligence
- Real-time confidence score
- Color-coded risk levels
- Dynamic strategy suggestions
Performance Tracking (Left Panel)
Signal Analytics
- Total historical signals
- Win rate with W/L breakdown
- Current streak tracking
- Closed trade counter
Regime Analysis
- Current market behavior
- Bars since last signal
- Recommended actions
- Average confidence trends
Strategy Command Center (Bottom Right)
Adaptive Recommendations
- Active strategy mode
- Primary approach (mean reversion/momentum)
- Suggested indicators ("weapons")
- Entry/exit methodology
- Risk management guidance
- Comprehensive Input Guide
Core Algorithm Parameters
Analysis Period (10-100 bars)
Scalping (10-15): Ultra-responsive, more signals, higher noise
Day Trading (20-30): Balanced sensitivity and stability
Swing Trading (40-100): Smooth signals, major moves only Default: 20 - optimal for most timeframes
Divergence Threshold (0.5-5.0)
Hair Trigger (0.5-1.0): Catches every wiggle, many false signals
Balanced (1.5-2.5): Good signal-to-noise ratio
Conservative (3.0-5.0): Only extreme divergences Default: 1.5 - best risk/reward balance
Path Memory (20-200 bars)
Short Memory (20-50): Recent behavior focus, quick adaptation
Medium Memory (50-100): Balanced historical context
Long Memory (100-200): Emphasizes established patterns Default: 50 - captures sufficient history without lag
Signal Spacing (5-50 bars)
Aggressive (5-10): Allows rapid-fire signals
Normal (15-25): Prevents clustering, maintains flow
Conservative (30-50): Major setups only Default: 15 - optimal trade frequency
Ensemble Configuration
Select markets for consensus analysis:
SPY: Broad market sentiment
QQQ: Technology leadership
IWM: Small-cap risk appetite
DIA: Blue-chip stability
More instruments = stronger consensus but potentially diluted signals
Visual Customization
Color Themes (6 professional options):
Quantum: Cyan/Pink - Modern trading aesthetic
Matrix: Green/Red - Classic terminal look
Heat: Blue/Red - Temperature metaphor
Neon: Cyan/Magenta - High contrast
Ocean: Turquoise/Coral - Calming palette
Sunset: Red-orange/Teal - Warm gradients
Display Controls:
- Toggle each visual component
- Adjust transparency levels
- Scale dashboard text
- Show/hide confidence scores
- Trading Strategies by Market State
- Ergodic State Strategy (Primary Color Bands)
Market Characteristics
- Price oscillates predictably
- Support/resistance hold
- Volume patterns repeat
- Mean reversion dominates
Optimal Approach
Entry: Fade moves at band extremes
Target: Middle band (equilibrium)
Stop: Just beyond outer bands
Size: Full confidence-based position
Recommended Tools
- RSI for oversold/overbought
- Bollinger Bands for extremes
- Volume profile for levels
- Non-Ergodic State Strategy (Danger Color Bands)
Market Characteristics
- Price trends persistently
- Levels break decisively
- Volume confirms direction
- Momentum accelerates
Optimal Approach
Entry: Breakout from bands
Target: Trail with expanding bands
Stop: Inside opposite band
Size: Scale in with trend
Recommended Tools
- Moving average alignment
- ADX for trend strength
- MACD for momentum
- Advanced Features Explained
Quantum Coherence Metric
Measures phase alignment between individual and ensemble behavior:
80-100%: Perfect sync - strong mean reversion setup
50-80%: Moderate alignment - mixed signals
0-50%: Decoherence - trending behavior likely
Path Dependency Analysis
Quantifies how much history influences current price:
Low (<30%): Technical patterns reliable
Medium (30-50%): Mixed influences
High (>50%): Fundamental shift occurring
Volatility Regime Classification
Contextualizes current volatility:
Normal: Standard strategies apply
Elevated: Widen stops, reduce size
Extreme: Defensive mode required
Signal Strength Indicator
Real-time opportunity quality:
- Distance from threshold
- Momentum acceleration
- Cross-validation factors
Risk Management Framework
Position Sizing by Confidence
90%+ confidence = 100% position size
70-90% confidence = 75% position size
50-70% confidence = 50% position size
<50% confidence = 25% or skip
Dynamic Stop Placement
Ergodic State: ATR × 1.0 from entry
Non-Ergodic State: ATR × 2.0 from entry
Volatility Adjustment: Multiply by current regime
Multi-Timeframe Alignment
- Check higher timeframe regime
- Confirm ensemble consensus
- Verify volume participation
- Align with major levels
What Makes EMD Unique
Original Contributions
First Ergodic Theory Trading Application: Transforms abstract physics into practical signals
Ensemble Market Analysis: Revolutionary multi-market divergence system
Adaptive Confidence Engine: Institutional-grade signal quality metrics
Quantum Coherence: Novel market alignment measurement
Smart Signal Management: Prevents clustering while maintaining responsiveness
Technical Innovations
Dynamic Threshold Adaptation: Self-adjusting sensitivity
Path Memory Integration: Historical dependency weighting
Stress-Adjusted Scoring: Market condition normalization
Real-Time Performance Tracking: Built-in strategy analytics
Optimization Guidelines
By Timeframe
Scalping (1-5 min)
Period: 10-15
Threshold: 0.5-1.0
Memory: 20-30
Spacing: 5-10
Day Trading (5-60 min)
Period: 20-30
Threshold: 1.5-2.5
Memory: 40-60
Spacing: 15-20
Swing Trading (1H-1D)
Period: 40-60
Threshold: 2.0-3.0
Memory: 80-120
Spacing: 25-35
Position Trading (1D-1W)
Period: 60-100
Threshold: 3.0-5.0
Memory: 100-200
Spacing: 40-50
By Market Condition
Trending Markets
- Increase threshold
- Extend memory
- Focus on breaks
Ranging Markets
- Decrease threshold
- Shorten memory
- Focus on restores
Volatile Markets
- Increase spacing
- Raise confidence requirement
- Reduce position size
- Integration with Other Analysis
- Complementary Indicators
For Ergodic States
- RSI divergences
- Bollinger Band squeezes
- Volume profile nodes
- Support/resistance levels
For Non-Ergodic States
- Moving average ribbons
- Trend strength indicators
- Momentum oscillators
- Breakout patterns
- Fundamental Alignment
- Check economic calendar
- Monitor sector rotation
- Consider market themes
- Evaluate risk sentiment
Troubleshooting Guide
Too Many Signals:
- Increase threshold
- Extend signal spacing
- Raise confidence minimum
Missing Opportunities
- Decrease threshold
- Reduce signal spacing
- Check ensemble settings
Poor Win Rate
- Verify timeframe alignment
- Confirm volume participation
- Review risk management
Disclaimer
This indicator is for educational and informational purposes only. It does not constitute financial advice. Trading involves substantial risk of loss and is not suitable for all investors. Past performance does not guarantee future results.
The ergodic framework provides unique market insights but cannot predict future price movements with certainty. Always use proper risk management, conduct your own analysis, and never risk more than you can afford to lose.
This tool should complement, not replace, comprehensive trading strategies and sound judgment. Markets remain inherently unpredictable despite advanced analysis techniques.
Transform market chaos into trading clarity with Ergodic Market Divergence.
Created with passion for the TradingView community
Trade with insight. Trade with anticipation.
— Dskyz , for DAFE Trading Systems
ADX and DI - Trader FelipeADX and DI - Trader Felipe
This indicator combines the Average Directional Index (ADX) and the Directional Indicators (DI+ and DI-) to help traders assess market trends and their strength. It is designed to provide a clear view of whether the market is in a trending phase (either bullish or bearish) and helps identify potential entry and exit points.
What is ADX and DI?
DI+ (Green Line):
DI+ measures the strength of upward (bullish) price movements. When DI+ is above DI-, it signals that the market is experiencing upward momentum.
DI- (Red Line):
DI- measures the strength of downward (bearish) price movements. When DI- is above DI+, it suggests that the market is in a bearish phase, with downward momentum.
ADX (Blue Line):
ADX quantifies the strength of the trend, irrespective of whether it is bullish or bearish. The higher the ADX, the stronger the trend:
ADX > 20: Indicates a trending market (either up or down).
ADX < 20: Indicates a weak or sideways market with no clear trend.
Threshold Line (Gray Line):
This horizontal line, typically set at 20, represents the threshold for identifying whether the market is trending or not. If ADX is above 20, the market is considered to be in a trend. If ADX is below 20, it suggests that the market is not trending and is likely in a consolidation phase.
Summary of How to Use the Indicator:
Trend Confirmation: Use ADX > 20 to confirm a trending market. If ADX is below 20, avoid trading.
Long Entry: Enter a long position when DI+ > DI- and ADX > 20.
Short Entry: Enter a short position when DI- > DI+ and ADX > 20.
Avoid Sideways Markets: Do not trade when ADX is below 20. Look for other strategies for consolidation phases.
Exit Strategy: Exit the trade if ADX starts to decline or if the DI lines cross in the opposite direction.
Combine with Other Indicators: Use additional indicators like RSI, moving averages, or support/resistance to filter and confirm signals.
Breadth-Driven Swing StrategyWhat it does
This script trades the S&P 500 purely on market breadth extremes:
• Data source : INDEX:S5TH = % of S&P 500 stocks above their own 200-day SMA (range 0–100).
• Buy when breadth is washed-out.
• Sell when breadth is overheated.
It is long-only by design; shorting and ATR trailing stops have been removed to keep the logic minimal and transparent.
⸻
Signals in plain English
1. Long entry
A. A 200-EMA trough in breadth is printed and the trough value is ≤ 40 %.
or
B. A 5-EMA trough appears, its prominence passes the user threshold, and the lowest breadth reading in the last 20 bars is ≤ 20 %.
(Toggle this secondary trigger on/off with “ Enter also on 5-EMA trough ”.)
2. Exit (close long)
First 200-EMA peak whose breadth value is ≥ 70 %.
3. Risk control
A fixed stop-loss (% of entry price, default 8 %) is attached to every long trade.
⸻
Key parameters (defaults shown)
• Long EMA length 200 • Short EMA length 5
• Peak prominence 0.5 pct-pts • Trough prominence 3 pct-pts
• Peak level 70 % • Trough level 40 % • 5-EMA trough level 20 %
• Fixed stop-loss 8 %
• “Enter also on 5-EMA trough” = true (allows additional entries on extreme momentum reversals)
Feel free to tighten or relax any of these thresholds to match your risk profile or account for different market regimes.
⸻
How to use it
1. Load the script on a daily SPX / SPY chart.
(The price chart drives order execution; the breadth series is pulled internally and does not need to be on the chart.)
2. Verify the breadth feed.
INDEX:S5TH is updated after each session; your broker must provide it.
3. Back-test across several cycles.
Two decades of daily data is recommended to see how the rules behave in bear markets, range markets, and bull trends.
4. Adjust position sizing in the Properties tab.
The default is “100 % of equity”; change it if you prefer smaller allocations or pyramiding caps.
⸻
Why it can help
• Breadth signals often lead price, allowing entries before index-level momentum turns.
• Simple, rule-based exits prevent “waiting for confirmation” paralysis.
• Only one input series—easy to audit, no black-box math.
Trade-offs
• Relies on a single breadth metric; other internals (advance/decline, equal-weight returns, etc.) are ignored.
• May sit in cash during shallow pullbacks that never push breadth ≤ 40 %.
• Signals arrive at the end of the session (breadth is EoD data).
⸻
Disclaimer
This script is provided for educational purposes only and is not financial advice. Markets are risky; test thoroughly and use your own judgment before trading real money.
ストラテジー概要
本スクリプトは S&P500 のマーケットブレッド(内部需給) だけを手がかりに、指数をスイングトレードします。
• ブレッドデータ : INDEX:S5TH
(S&P500 採用銘柄のうち、それぞれの 200 日移動平均線を上回っている銘柄比率。0–100 %)
• 買い : ブレッドが極端に売られたタイミング。
• 売り : ブレッドが過熱状態に達したタイミング。
余計な機能を削り、ロングオンリー & 固定ストップ のシンプル設計にしています。
⸻
シグナルの流れ
1. ロングエントリー
• 条件 A : 200-EMA がトラフを付け、その値が 40 % 以下
• 条件 B : 5-EMA がトラフを付け、
・プロミネンス条件を満たし
・直近 20 本のブレッドス最小値が 20 % 以下
• B 条件は「5-EMA トラフでもエントリー」を ON にすると有効
2. ロング決済
最初に出現した 200-EMA ピーク で、かつ値が 70 % 以上 のバーで手仕舞い。
3. リスク管理
各トレードに 固定ストップ(初期価格から 8 %)を設定。
⸻
主なパラメータ(デフォルト値)
• 長期 EMA 長さ : 200 • 短期 EMA 長さ : 5
• ピーク判定プロミネンス : 0.5 %pt • トラフ判定プロミネンス : 3 %pt
• ピーク水準 : 70 % • トラフ水準 : 40 % • 5-EMA トラフ水準 : 20 %
• 固定ストップ : 8 %
• 「5-EMA トラフでもエントリー」 : ON
相場環境やリスク許容度に合わせて閾値を調整してください。
⸻
使い方
1. 日足の SPX / SPY チャート にスクリプトを適用。
2. ブレッドデータの供給 (INDEX:S5TH) がブローカーで利用可能か確認。
3. 20 年以上の期間でバックテスト し、強気相場・弱気相場・レンジ局面での挙動を確認。
4. 資金配分 は プロパティ → 戦略実行 で調整可能(初期値は「資金の 100 %」)。
⸻
強み
• ブレッドは 価格より先行 することが多く、天底を早期に捉えやすい。
• ルールベースの出口で「もう少し待とう」と迷わずに済む。
• 入力 series は 1 本のみ、ブラックボックス要素なし。
注意点・弱み
• 単一指標に依存。他の内部需給(A/D ライン等)は考慮しない。
• 40 % を割らない浅い押し目では機会損失が起こる。
• ブレッドは終値ベースの更新。ザラ場中の変化は捉えられない。
⸻
免責事項
本スクリプトは 学習目的 で提供しています。投資助言ではありません。
実取引の前に必ず自己責任で十分な検証とリスク管理を行ってください。
Combined EMA/Smiley & DEM System## 🔷 General Overview
This script creates an advanced technical analysis system for TradingView, combining multiple Exponential Moving Averages (EMAs), Simple Moving Averages (SMAs), dynamic Fibonacci levels, and ATR (Average True Range) analysis. It presents the results clearly through interactive, real-time tables directly on the chart.
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## 🔹 Indicator Structure
The script consists of two main parts:
### **1. EMA & SMA Combined System with Fibonacci**
- **Purpose:**
Provides visual insights by comparing multiple EMA/SMA periods and identifying significant dynamic price levels using Fibonacci ratios around a calculated "Golden" line.
- **Components:**
- **Moving Averages (MAs)**:
- 20 EMAs (periods from 20 to 400)
- 20 SMAs (also from 20 to 400)
- **Golden Line:**
Calculated as the average of all EMAs and SMAs.
- **Dynamic Fibonacci Levels:**
Key ratios around the Golden line (0.5, 0.618, 0.786, 1.0, 1.272, 1.414, 1.618, 2.0) dynamically adjust based on market conditions.
- **Fibonacci Labels:**
Labels are shown next to Fibonacci lines, indicating their numeric value clearly on the chart.
- **Table (Top Right Corner):**
- Displays:
- **Input:** EMA/SMA periods sorted by their current average price levels.
- **AVG:** The average of corresponding EMA & SMA pairs.
- **EMA & SMA Values:** Individual EMA/SMA values clearly marked.
- **Dynamic Highlighting:** Highlights the row whose average (EMA+SMA)/2 is closest to the current price, helping identify immediate price action significance.
- **Sorting Logic:**
Each EMA/SMA pair is dynamically sorted based on their average values. Color coding (red/green) is used:
- **Green:** EMA/SMA pairs with shorter periods when their average is lower.
- **Red:** EMA/SMA pairs with longer periods when their average is lower.
- **Star (⭐):** Represents the "Golden" average clearly.
---
### **2. DEM System (Dynamic EMA/ATR Metrics)**
- **Purpose:**
Provides detailed ATR statistics to assess market volatility clearly and quickly.
- **Components:**
- **Moving Averages:**
- SMA lines: 25, 50, 100, 200.
- **Bollinger Bands:**
- Based on 20-period SMA of highs and standard deviation of lows.
- **ATR Analysis:**
- ATR calculations for multiple periods (1-day, 10, 20, 30, 40, 50).
- **ATR Premium:** Average ATR of all calculated periods, providing an overarching volatility indicator.
- **ATR Table (Bottom Right Corner):**
- Displays clearly structured ATR values and percentages relative to the current close price:
- Columns: **ATR Period**, **Value**, and **% of Close**.
- Rows: Each specific ATR (1D, 10, 20, 30, 40, 50), plus ATR premium.
- The ATR premium is highlighted in yellow to signify its importance clearly.
---
## 🔹 Key Features and Logic Explained
- **Dynamic EMA/SMA Sorting:**
The script computes the average of each EMA/SMA pair and sorts them dynamically on each bar, highlighting their relative importance visually. This allows traders to easily interpret the strength of current support/resistance levels based on moving averages.
- **Closest EMA/SMA Pair to Current Price:**
Calculates the absolute difference between the current price and all EMA/SMA averages, highlighting the closest one for quick reference.
- **Fibonacci Ratios:**
- Dynamically calculated Fibonacci levels based on the "Golden" EMA/SMA average give clear visual guidance for potential targets, supports, and resistances.
- Labels are continuously updated and placed next to levels for clarity.
- **ATR Volatility Analysis:**
- Provides immediate insight into market volatility with absolute and relative (percentage-based) ATR values.
- ATR premium summarizes volatility across multiple timeframes clearly.
---
## 🔹 Practical Use Case:
- Traders can quickly identify support/resistance and critical price zones through EMA/SMA and Fibonacci combinations.
- Useful in assessing immediate volatility, guiding stop-loss and take-profit levels through detailed ATR metrics.
- The dynamic highlighting in tables provides intuitive, real-time decision support for active traders.
---
## 🔹 How to Use this Script:
1. **Adjust EMA & SMA Lengths** from indicator settings if different periods are preferred.
2. **Monitor dynamic Fibonacci levels** around the "Golden" average to identify possible reversal or continuation points.
3. **Check EMA/SMA table:** Rows highlighted indicate immediate significance concerning current market price.
4. **ATR table:** Use volatility metrics for better risk management.
---
## 🔷 Conclusion
This advanced Pine Script indicator efficiently combines multiple EMAs, SMAs, dynamic Fibonacci retracement levels, and volatility analysis using ATR into a comprehensive real-time analytical tool, enhancing traders' decision-making capabilities by providing clear and actionable insights directly on the TradingView chart.
ScalpSwing Pro SetupScript Overview
This script is a multi-tool setup designed for both scalping (1m–5m) and swing trading (1H–4H–Daily). It combines the power of trend-following , momentum , and mean-reversion tools:
What’s Included in the Script
1. EMA Indicators (20, 50, 200)
- EMA 20 (blue) : Short-term trend
- EMA 50 (orange) : Medium-term trend
- EMA 200 (red) : Long-term trend
- Use:
- EMA 20 crossing above 50 → bullish trend
- EMA 20 crossing below 50 → bearish trend
- Price above 200 EMA = uptrend bias
2. VWAP (Volume Weighted Average Price)
- Shows the average price weighted by volume
- Best used in intraday (1m to 15m timeframes)
- Use:
- Price bouncing from VWAP = reversion trade
- Price far from VWAP = likely pullback incoming
3. RSI (14) + Key Levels
- Shows momentum and overbought/oversold zones
- Levels:
- 70 = Overbought (potential sell)
- 30 = Oversold (potential buy)
- 50 = Trend confirmation
- Use:
- RSI 30–50 in uptrend = dip buying zone
- RSI 70–50 in downtrend = pullback selling zone
4. MACD Crossovers
- Standard MACD with histogram & cross alerts
- Shows trend momentum shifts
- Green triangle = Bullish MACD crossover
- Red triangle = Bearish MACD crossover
- Use:
- Confirm swing trades with MACD crossover
- Combine with RSI divergence
5. Buy & Sell Signal Logic
BUY SIGNAL triggers when:
- EMA 20 crosses above EMA 50
- RSI is between 50 and 70 (momentum bullish, not overbought)
SELL SIGNAL triggers when:
- EMA 20 crosses below EMA 50
- RSI is between 30 and 50 (bearish momentum, not oversold)
These signals appear as:
- BUY : Green label below the candle
- SELL : Red label above the candle
How to Trade with It
For Scalping (1m–5m) :
- Focus on EMA crosses near VWAP
- Confirm with RSI between 50–70 (buy) or 50–30 (sell)
- Use MACD triangle as added confluence
For Swing (1H–4H–Daily) :
- Look for EMA 20–50 cross + price above EMA 200
- Confirm trend with MACD and RSI
- Trade breakout or pullback depending on structure
Green*DiamondGreen*Diamond (GD1)
Unleash Dynamic Trading Signals with Volatility and Momentum
Overview
GreenDiamond is a versatile overlay indicator designed for traders seeking actionable buy and sell signals across various markets and timeframes. Combining Volatility Bands (VB) bands, Consolidation Detection, MACD, RSI, and a unique Ribbon Wave, it highlights high-probability setups while filtering out noise. With customizable signals like Green-Yellow Buy, Pullback Sell, and Inverse Pullback Buy, plus vibrant candle and volume visuals, GreenDiamond adapts to your trading style—whether you’re scalping, day trading, or swing trading.
Key Features
Volatility Bands (VB): Plots dynamic upper and lower bands to identify breakouts or reversals, with toggleable buy/sell signals outside consolidation zones.
Consolidation Detection: Marks low-range periods to avoid choppy markets, ensuring signals fire during trending conditions.
MACD Signals: Offers flexible buy/sell conditions (e.g., cross above signal, above zero, histogram up) with RSI divergence integration for precision.
RSI Filter: Enhances signals with customizable levels (midline, oversold/overbought) and bullish divergence detection.
Ribbon Wave: Visualizes trend strength using three EMAs, colored by MACD and RSI for intuitive momentum cues.
Custom Signals: Includes Green-Yellow Buy, Pullback Sell, and Inverse Pullback Buy, with limits on consecutive signals to prevent overtrading.
Candle & Volume Styling: Blends MACD/RSI colors on candles and scales volume bars to highlight momentum spikes.
Alerts: Set up alerts for VB signals, MACD crosses, Green*Diamond signals, and custom conditions to stay on top of opportunities.
How It Works
Green*Diamond integrates multiple indicators to generate signals:
Volatility Bands: Calculates bands using a pivot SMA and standard deviation. Buy signals trigger on crossovers above the lower band, sell signals on crossunders below the upper band (if enabled).
Consolidation Filter: Suppresses signals when candle ranges are below a threshold, keeping you out of flat markets.
MACD & RSI: Combines MACD conditions (e.g., cross above signal) with RSI filters (e.g., above midline) and optional volume spikes for robust signals.
Custom Logic: Green-Yellow Buy uses MACD bullishness, Pullback Sell targets retracements, and Inverse Pullback Buy catches reversals after downmoves—all filtered to avoid consolidation.
Visuals: Ribbon Wave shows trend direction, candles blend momentum colors, and volume bars scale dynamically to confirm signals.
Settings
Volatility Bands Settings:
VB Lookback Period (20): Adjust to 10–15 for faster markets (e.g., 1-minute scalping) or 25–30 for daily charts.
Upper/Lower Band Multiplier (1.0): Increase to 1.5–2.0 for wider bands in volatile stocks like AEHL; decrease to 0.5 for calmer markets.
Show Volatility Bands: Toggle off to reduce chart clutter.
Use VB Signals: Enable for breakout-focused trades; disable to focus on Green*Diamond signals.
Consolidation Settings:
Consolidation Lookback (14): Set to 5–10 for small caps (e.g., AEHL) to catch quick consolidations; 20 for higher timeframes.
Range Threshold (0.5): Lower to 0.3 for stricter filtering in choppy markets; raise to 0.7 for looser signals.
MACD Settings:
Fast/Slow Length (12/26): Shorten to 8/21 for scalping; extend to 15/34 for swing trading.
Signal Smoothing (9): Reduce to 5 for faster signals; increase to 12 for smoother trends.
Buy/Sell Signal Options: Choose “Cross Above Signal” for classic MACD; “Histogram Up” for momentum plays.
Use RSI Div + MACD Cross: Enable for high-probability reversal signals.
RSI Settings:
RSI Period (14): Drop to 10 for 1-minute charts; raise to 20 for daily.
Filter Level (50): Set to 55 for stricter buys; 45 for sells.
Overbought/Oversold (70/30): Tighten to 65/35 for small caps; widen to 75/25 for indices.
RSI Buy/Sell Options: Select “Bullish Divergence” for reversals; “Cross Above Oversold” for momentum.
Color Settings:
Adjust bullish/bearish colors for visibility (e.g., brighter green/red for dark themes).
Border Thickness (1): Increase to 2–3 for clearer candle outlines.
Volume Settings:
Volume Average Length (20): Shorten to 10 for scalping; extend to 30 for swing trades.
Volume Multiplier (2.0): Raise to 3.0 for AEHL’s volume surges; lower to 1.5 for steady stocks.
Bar Height (10%): Increase to 15% for prominent bars; decrease to 5% to reduce clutter.
Ribbon Settings:
EMA Periods (10/20/30): Tighten to 5/10/15 for scalping; widen to 20/40/60 for trends.
Color by MACD/RSI: Disable for simpler visuals; enable for dynamic momentum cues.
Gradient Fill: Toggle on for trend clarity; off for minimalism.
Custom Signals:
Enable Green-Yellow Buy: Use for momentum confirmation; limit to 1–2 signals to avoid spam.
Pullback/Inverse Pullback % (50): Set to 30–40% for small caps; 60–70% for indices.
Max Buy Signals (1): Increase to 2–3 for active markets; keep at 1 for discipline.
Tips and Tricks
Scalping Small Caps (e.g., AEHL):
Use 1-minute charts with VB Lookback = 10, Consolidation Lookback = 5, and Volume Multiplier = 3.0 to catch $0.10–$0.20 moves.
Enable Green-Yellow Buy and Inverse Pullback Buy for quick entries; disable VB Signals to focus on Green*Diamond logic.
Pair with SMC+ green boxes (if you use them) for reversal confirmation.
Day Trading:
Try 5-minute charts with MACD Fast/Slow = 8/21 and RSI Period = 10.
Enable RSI Divergence + MACD Cross for high-probability setups; set Max Buy Signals = 2.
Watch for volume bars turning yellow to confirm entries.
Swing Trading:
Use daily charts with VB Lookback = 30, Ribbon EMAs = 20/40/60.
Enable Pullback Sell (60%) to exit after rallies; disable RSI Color for cleaner candles.
Check Ribbon Wave gradient for trend strength—bright green signals strong bulls.
Avoiding Noise:
Increase Consolidation Threshold to 0.7 on volatile days to skip false breakouts.
Disable Ribbon Wave or Volume Bars if the chart feels crowded.
Limit Max Buy Signals to 1 for disciplined trading.
Alert Setup:
In TradingView’s Alerts panel, select:
“GD Buy Signal” for standard entries.
“RSI Div + MACD Cross Buy” for reversals.
“VB Buy Signal” for breakout plays.
Set to “Once Per Bar Close” for confirmed signals; “Once Per Bar” for scalping.
Backtesting:
Replay on small caps ( Float < 5M, Price $0.50–$5) to test signals.
Focus on “GD Buy Signal” with yellow volume bars and green Ribbon Wave.
Avoid signals during gray consolidation squares unless paired with RSI Divergence.
Usage Notes
Markets: Works on stocks, forex, crypto, and indices. Best for volatile assets (e.g., small-cap stocks, BTCUSD).
Timeframes: Scalping (1–5 minutes), day trading (15–60 minutes), or swing trading (daily). Adjust settings per timeframe.
Risk Management: Combine with stop-losses (e.g., 1% risk, $0.05 below AEHL entry) and take-profits (3–5%).
Customization: Tweak inputs to match your strategy—experiment in replay to find your sweet spot.
Disclaimer
Green*Diamond is a technical tool to assist with trade identification, not a guarantee of profits. Trading involves risks, and past performance doesn’t predict future results. Always conduct your own analysis, manage risk, and test settings before live trading.
Feedback
Love Green*Diamond? Found a killer setup?
US 20Y Treasury YieldWhat This Indicator Does
This Pine Script creates a custom indicator for TradingView that displays the US 20-Year Treasury Yield (US20Y) on your chart. Here's what it does step by step:
1. What Is the US 20-Year Treasury Yield?
The US 20-Year Treasury Yield is a financial metric that shows the interest rate (or yield) investors earn when they buy US government bonds that mature in 20 years. It’s an important indicator of the economy and can influence other markets like stocks, bonds, and currencies.
2. How Does the Indicator Work?
The indicator fetches the latest data for the US 20-Year Treasury Yield from TradingView's database.
It then plots this data in a separate pane below your main chart, so you can easily monitor the yield without cluttering your price chart.
3. What Does the Indicator Show?
A blue line is drawn in the separate pane, showing the movement of the US 20-Year Treasury Yield over time.
A gray dashed line is added at the 4.0% level as a reference point. You can use this line to quickly see when the yield is above or below 4.0%.
5. Why Use This Indicator?
Monitor Economic Trends : The US 20-Year Treasury Yield is a key economic indicator. By plotting it on your chart, you can stay informed about changes in interest rates and their potential impact on other markets.
Crypto Scanner v4This guide explains a version 6 Pine Script that scans a user-provided list of cryptocurrency tokens to identify high probability tradable opportunities using several technical indicators. The script combines trend, momentum, and volume-based analyses to generate potential buying or selling signals, and it displays the results in a neatly formatted table with alerts for trading setups. Below is a detailed walkthrough of the script’s design, how traders can interpret its outputs, and recommendations for optimizing indicator inputs across different timeframes.
## Overview and Key Components
The script is designed to help traders assess multiple tokens by calculating several indicators for each one. The key components include:
- **Input Settings:**
- A comma-separated list of symbols to scan.
- Adjustable parameters for technical indicators such as ADX, RSI, MFI, and a custom Wave Trend indicator.
- Options to enable alerts and set update frequencies.
- **Indicator Calculations:**
- **ADX (Average Directional Index):** Measures trend strength. A value above the provided threshold indicates a strong trend, which is essential for validating momentum before entering a trade.
- **RSI (Relative Strength Index):** Helps determine overbought or oversold conditions. When the RSI is below the oversold level, it may present a buying opportunity, while an overbought condition (not explicitly part of this setup) could suggest selling.
- **MFI (Money Flow Index):** Similar in concept to RSI but incorporates volume, thus assessing buying and selling pressure. Values below the designated oversold threshold indicate potential undervaluation.
- **Wave Trend:** A custom indicator that calculates two components (WT1 and WT2); a crossover where WT1 moves from below to above WT2 (particularly near oversold levels) may signal a reversal and a potential entry point.
- **Scanning and Trading Zone:**
- The script identifies a *bullish setup* when the following conditions are met for a token:
- ADX exceeds the threshold (strong trend).
- Both RSI and MFI are below their oversold levels (indicating potential buying opportunities).
- A Wave Trend crossover confirms near-term reversal dynamics.
- A *trading zone* condition is also defined by specific ranges for ADX, RSI, MFI, and a limited difference between WT1 and WT2. This zone suggests that the token might be in a consolidation phase where even small moves may be significant.
- **Alerts and Table Reporting:**
- A table is generated, with each row corresponding to a token. The table contains columns for the symbol, ADX, RSI, MFI, WT1, WT2, and the trading zone status.
- Visual cues—such as different background colors—highlight tokens with a bullish setup or that are within the trading zone.
- Alerts are issued based on the detection of a bullish setup or entry into a trading zone. These alerts are limited per bar to avoid flooding the trader with notifications.
## How to Interpret the Indicator Outputs
Traders should use the indicator values as guidance, verifying them against their own analysis before making any trading decision. Here’s how to assess each output:
- **ADX:**
- **High values (above threshold):** Indicate strong trends. If other indicators confirm an oversold condition, a trader may consider a long position for a corrective reversal.
- **Low values:** Suggest that the market is not trending strongly, and caution should be taken when considering entry.
- **RSI and MFI:**
- **Below oversold levels:** These conditions are traditionally seen as signals that an asset is undervalued, potentially triggering a bounce.
- **Above typical resistance levels (not explicitly used here):** Would normally caution a trader against entering a long position.
- **Wave Trend (WT1 and WT2):**
- A crossover where WT1 moves upward above WT2 in an oversold environment can signal the beginning of a recovery or reversal, thereby reinforcing buy signals.
- **Trading Zone:**
- Being “in zone” means that the asset’s current values for ADX, RSI, MFI, and the closeness of the Wave Trend lines indicate a period of consolidation. This scenario might be suitable for both short-term scalping or as an early exit indicator, depending on further market analysis.
## Timeframe Optimization Input Table
Traders can optimize indicator inputs depending on the timeframe they use. The following table provides a set of recommended input values for various timeframes. These values are suggestions and should be adjusted based on market conditions and individual trading styles.
Timeframe ADX RSI MFI ADX RSI MFI WT Channel WT Average
5-min 10 10 10 20 30 20 7 15
15-min 12 12 12 22 30 20 9 18
1-hour 14 14 14 25 30 20 10 21
4-hour 16 16 16 27 30 20 12 24
1-day 18 18 18 30 30 20 14 28
Adjust these parameters directly in the script’s input settings to match the selected timeframe. For shorter timeframes (e.g., 5-min or 15-min), the shorter lengths help filter high-frequency noise. For longer timeframes (e.g., 1-day), longer input values may reduce false signals and capture more significant trends.
## Best Practices and Usage Tips
- **Token Limit:**
- Limit the number of tokens scanned to 10 per query line. If you need to scan more tokens, initiate a new query line. This helps manage screen real estate and ensures the table remains legible.
- **Confirming Signals:**
- Use this script as a starting point for identifying high potential trades. Each indicator’s output should be used to confirm your trading decision. Always cross-reference with additional technical analysis tools or market context.
- **Regular Review:**
- Since the script updates the table every few bars (as defined by the update frequency), review the table and alerts regularly. Market conditions change rapidly, so timely decisions are crucial.
## Conclusion
This Pine Script provides a comprehensive approach for scanning multiple cryptocurrencies using a combination of trend strength (ADX), momentum (RSI and MFI), and reversal signals (Wave Trend). By using the provided recommendation table for different timeframes and limiting the tokens to 20 per query line (with a maximum of four query lines), traders can streamline their scanning process and more effectively identify high probability tradable tokens. Ultimately, the outputs should be critically evaluated and combined with additional market research before executing any trades.
Accurate Bollinger Bands mcbw_ [True Volatility Distribution]The Bollinger Bands have become a very important technical tool for discretionary and algorithmic traders alike over the last decades. It was designed to give traders an edge on the markets by setting probabilistic values to different levels of volatility. However, some of the assumptions that go into its calculations make it unusable for traders who want to get a correct understanding of the volatility that the bands are trying to be used for. Let's go through what the Bollinger Bands are said to show, how their calculations work, the problems in the calculations, and how the current indicator I am presenting today fixes these.
--> If you just want to know how the settings work then skip straight to the end or click on the little (i) symbol next to the values in the indicator settings window when its on your chart <--
--------------------------- What Are Bollinger Bands ---------------------------
The Bollinger Bands were formed in the 1980's, a time when many retail traders interacted with their symbols via physically printed charts and computer memory for personal computer memory was measured in Kb (about a factor of 1 million smaller than today). Bollinger Bands are designed to help a trader or algorithm see the likelihood of price expanding outside of its typical range, the further the lines are from the current price implies the less often they will get hit. With a hands on understanding many strategies use these levels for designated levels of breakout trades or to assist in defining price ranges.
--------------------------- How Bollinger Bands Work ---------------------------
The calculations that go into Bollinger Bands are rather simple. There is a moving average that centers the indicator and an equidistant top band and bottom band are drawn at a fixed width away. The moving average is just a typical moving average (or common variant) that tracks the price action, while the distance to the top and bottom bands is a direct function of recent price volatility. The way that the distance to the bands is calculated is inspired by formulas from statistics. The standard deviation is taken from the candles that go into the moving average and then this is multiplied by a user defined value to set the bands position, I will call this value 'the multiple'. When discussing Bollinger Bands, that trading community at large normally discusses 'the multiple' as a multiplier of the standard deviation as it applies to a normal distribution (gaußian probability). On a normal distribution the number of standard deviations away (which trades directly use as 'the multiple') you are directly corresponds to how likely/unlikely something is to happen:
1 standard deviation equals 68.3%, meaning that the price should stay inside the 1 standard deviation 68.3% of the time and be outside of it 31.7% of the time;
2 standard deviation equals 95.5%, meaning that the price should stay inside the 2 standard deviation 95.5% of the time and be outside of it 4.5% of the time;
3 standard deviation equals 99.7%, meaning that the price should stay inside the 3 standard deviation 99.7% of the time and be outside of it 0.3% of the time.
Therefore when traders set 'the multiple' to 2, they interpret this as meaning that price will not reach there 95.5% of the time.
---------------- The Problem With The Math of Bollinger Bands ----------------
In and of themselves the Bollinger Bands are a great tool, but they have become misconstrued with some incorrect sense of statistical meaning, when they should really just be taken at face value without any further interpretation or implication.
In order to explain this it is going to get a bit technical so I will give a little math background and try to simplify things. First let's review some statistics topics (distributions, percentiles, standard deviations) and then with that understanding explore the incorrect logic of how Bollinger Bands have been interpreted/employed.
---------------- Quick Stats Review ----------------
.
(If you are comfortable with statistics feel free to skip ahead to the next section)
.
-------- I: Probability distributions --------
When you have a lot of data it is helpful to see how many times different results appear in your dataset. To visualize this people use "histograms", which just shows how many times each element appears in the dataset by stacking each of the same elements on top of each other to form a graph. You may be familiar with the bell curve (also called the "normal distribution", which we will be calling it by). The normal distribution histogram looks like a big hump around zero and then drops off super quickly the further you get from it. This shape (the bell curve) is very nice because it has a lot of very nifty mathematical properties and seems to show up in nature all the time. Since it pops up in so many places, society has developed many different shortcuts related to it that speed up all kinds of calculations, including the shortcut that 1 standard deviation = 68.3%, 2 standard deviations = 95.5%, and 3 standard deviations = 99.7% (these only apply to the normal distribution). Despite how handy the normal distribution is and all the shortcuts we have for it are, and how much it shows up in the natural world, there is nothing that forces your specific dataset to look like it. In fact, your data can actually have any possible shape. As we will explore later, economic and financial datasets *rarely* follow the normal distribution.
-------- II: Percentiles --------
After you have made the histogram of your dataset you have built the "probability distribution" of your own dataset that is specific to all the data you have collected. There is a whole complicated framework for how to accurately calculate percentiles but we will dramatically simplify it for our use. The 'percentile' in our case is just the number of data points we are away from the "middle" of the data set (normally just 0). Lets say I took the difference of the daily close of a symbol for the last two weeks, green candles would be positive and red would be negative. In this example my dataset of day by day closing price difference is:
week 1:
week 2:
sorting all of these value into a single dataset I have:
I can separate the positive and negative returns and explore their distributions separately:
negative return distribution =
positive return distribution =
Taking the 25th% percentile of these would just be taking the value that is 25% towards the end of the end of these returns. Or akin the 100%th percentile would just be taking the vale that is 100% at the end of those:
negative return distribution (50%) = -5
positive return distribution (50%) = +4
negative return distribution (100%) = -10
positive return distribution (100%) = +20
Or instead of separating the positive and negative returns we can also look at all of the differences in the daily close as just pure price movement and not account for the direction, in this case we would pool all of the data together by ignoring the negative signs of the negative reruns
combined return distribution =
In this case the 50%th and 100%th percentile of the combined return distribution would be:
combined return distribution (50%) = 4
combined return distribution (100%) = 10
Sometimes taking the positive and negative distributions separately is better than pooling them into a combined distribution for some purposes. Other times the combined distribution is better.
Most financial data has very different distributions for negative returns and positive returns. This is encapsulated in sayings like "Price takes the stairs up and the elevator down".
-------- III: Standard Deviation --------
The formula for the standard deviation (refereed to here by its shorthand 'STDEV') can be intimidating, but going through each of its elements will illuminate what it does. The formula for STDEV is equal to:
square root ( (sum ) / N )
Going back the the dataset that you might have, the variables in the formula above are:
'mean' is the average of your entire dataset
'x' is just representative of a single point in your dataset (one point at a time)
'N' is the total number of things in your dataset.
Going back to the STDEV formula above we can see how each part of it works. Starting with the '(x - mean)' part. What this does is it takes every single point of the dataset and measure how far away it is from the mean of the entire dataset. Taking this value to the power of two: '(x - mean) ^ 2', means that points that are very far away from the dataset mean get 'penalized' twice as much. Points that are very close to the dataset mean are not impacted as much. In practice, this would mean that if your dataset had a bunch of values that were in a wide range but always stayed in that range, this value ('(x - mean) ^ 2') would end up being small. On the other hand, if your dataset was full of the exact same number, but had a couple outliers very far away, this would have a much larger value since the square par of '(x - mean) ^ 2' make them grow massive. Now including the sum part of 'sum ', this just adds up all the of the squared distanced from the dataset mean. Then this is divided by the number of values in the dataset ('N'), and then the square root of that value is taken.
There is nothing inherently special or definitive about the STDEV formula, it is just a tool with extremely widespread use and adoption. As we saw here, all the STDEV formula is really doing is measuring the intensity of the outliers.
--------------------------- Flaws of Bollinger Bands ---------------------------
The largest problem with Bollinger Bands is the assumption that price has a normal distribution. This is assumption is massively incorrect for many reasons that I will try to encapsulate into two points:
Price return do not follow a normal distribution, every single symbol on every single timeframe has is own unique distribution that is specific to only itself. Therefore all the tools, shortcuts, and ideas that we use for normal distributions do not apply to price returns, and since they do not apply here they should not be used. A more general approach is needed that allows each specific symbol on every specific timeframe to be treated uniquely.
The distributions of price returns on the positive and negative side are almost never the same. A more general approach is needed that allows positive and negative returns to be calculated separately.
In addition to the issues of the normal distribution assumption, the standard deviation formula (as shown above in the quick stats review) is essentially just a tame measurement of outliers (a more aggressive form of outlier measurement might be taking the differences to the power of 3 rather than 2). Despite this being a bit of a philosophical question, does the measurement of outlier intensity as defined by the STDEV formula really measure what we want to know as traders when we're experiencing volatility? Or would adjustments to that formula better reflect what we *experience* as volatility when we are actively trading? This is an open ended question that I will leave here, but I wanted to pose this question because it is a key part of what how the Bollinger Bands work that we all assume as a given.
Circling back on the normal distribution assumption, the standard deviation formula used in the calculation of the bands only encompasses the deviation of the candles that go into the moving average and have no knowledge of the historical price action. Therefore the level of the bands may not really reflect how the price action behaves over a longer period of time.
------------ Delivering Factually Accurate Data That Traders Need------------
In light of the problems identified above, this indicator fixes all of these issue and delivers statistically correct information that discretionary and algorithmic traders can use, with truly accurate probabilities. It takes the price action of the last 2,000 candles and builds a huge dataset of distributions that you can directly select your percentiles from. It also allows you to have the positive and negative distributions calculated separately, or if you would like, you can pool all of them together in a combined distribution. In addition to this, there is a wide selection of moving averages directly available in the indicator to choose from.
Hedge funds, quant shops, algo prop firms, and advanced mechanical groups all employ the true return distributions in their work. Now you have access to the same type of data with this indicator, wherein it's doing all the lifting for you.
------------------------------ Indicator Settings ------------------------------
.
---- Moving average ----
Select the type of moving average you would like and its length
---- Bands ----
The percentiles that you enter here will be pulled directly from the return distribution of the last 2,000 candles. With the typical Bollinger Bands, traders would select 2 standard deviations and incorrectly think that the levels it highlights are the 95.5% levels. Now, if you want the true 95.5% level, you can just enter 95.5 into the percentile value here. Each of the three available bands takes the true percentile you enter here.
---- Separate Positive & Negative Distributions----
If this box is checked the positive and negative distributions are treated indecently, completely separate from each other. You will see that the width of the top and bottom bands will be different for each of the percentiles you enter.
If this box is unchecked then all the negative and positive distributions are pooled together. You will notice that the width of the top and bottom bands will be the exact same.
---- Distribution Size ----
This is the number of candles that the price return is calculated over. EG: to collect the price return over the last 33 candles, the difference of price from now to 33 candles ago is calculated for the last 2,000 candles, to build a return distribution of 2000 points of price differences over 33 candles.
NEGATIVE NUMBERS(<0) == exact number of candles to include;
EG: setting this value to -20 will always collect volatility distributions of 20 candles
POSITIVE NUMBERS(>0) == number of candles to include as a multiple of the Moving Average Length value set above;
EG: if the Moving Average Length value is set to 22, setting this value to 2 will use the last 22*2 = 44 candles for the collection of volatility distributions
MORE candles being include will generally make the bands WIDER and their size will change SLOWER over time.
I wish you focus, dedication, and earnest success on your journey.
Happy trading :)
AI InfinityAI Infinity – Multidimensional Market Analysis
Overview
The AI Infinity indicator combines multiple analysis tools into a single solution. Alongside dynamic candle coloring based on MACD and Stochastic signals, it features Alligator lines, several RSI lines (including glow effects), and optionally enabled EMAs (20/50, 100, and 200). Every module is individually configurable, allowing traders to tailor the indicator to their personal style and strategy.
Important Note (Disclaimer)
This indicator is provided for educational and informational purposes only.
It does not constitute financial or investment advice and offers no guarantee of profit.
Each trader is responsible for their own trading decisions.
Past performance does not guarantee future results.
Please review the settings thoroughly and adjust them to your personal risk profile; consider supplementary analyses or professional guidance where appropriate.
Functionality & Components
1. Candle Coloring (MACD & Stochastic)
Objective: Provide an immediate visual snapshot of the market’s condition.
Details:
MACD Signal: Used to identify bullish and bearish momentum.
Stochastic: Detects overbought and oversold zones.
Color Modes: Offers both a simple (two-color) mode and a gradient mode.
2. Alligator Lines
Objective: Assist with trend analysis and determining the market’s current phase.
Details:
Dynamic SMMA Lines (Jaw, Teeth, Lips) that adjust based on volatility and market conditions.
Multiple Lengths: Each element uses a separate smoothing period (13, 8, 5).
Transparency: You can show or hide each line independently.
3. RSI Lines & Glow Effects
Objective: Display the RSI values directly on the price chart so critical levels (e.g., 20, 50, 80) remain visible at a glance.
Details:
RSI Scaling: The RSI is plotted in the chart window, eliminating the need to switch panels.
Dynamic Transparency: A pulse effect indicates when the RSI is near critical thresholds.
Glow Mode: Choose between “Direct Glow” or “Dynamic Transparency” (based on ATR distance).
Custom RSI Length: Freely adjustable (default is 14).
4. Optional EMAs (20/50, 100, 200)
Objective: Utilize moving averages for trend assessment and identifying potential support/resistance areas.
Details:
20/50 EMA: Select which one to display via a dropdown menu.
100 EMA & 200 EMA: Independently enabled.
Color Logic: Automatically green (price > EMA) or red (price < EMA). Each EMA’s up/down color is customizable.
Configuration Options
Candle Coloring:
Choose between Gradient or Simple mode.
Adjust the color scheme for bullish/bearish candles.
Transparency is dynamically based on candle body size and Stochastic state.
Alligator Lines:
Toggle each line (Jaw/Teeth/Lips) on or off.
Select individual colors for each line.
RSI Section:
RSI Length can be set as desired.
RSI lines (0, 20, 50, 80, 100) with user-defined colors and transparency (pulse effect).
Additional lines (e.g., RSI 40/60) are also available.
Glow Effects:
Switch between “Dynamic Transparency” (ATR-based) and “Direct Glow”.
Independently applied to the RSI 100 and RSI 0 lines.
EMAs (20/50, 100, 200):
Activate each one as needed.
Each EMA’s up/down color can be customized.
Example Use Cases
Trend Identification:
Enable Alligator lines to gauge general trend direction through SMMA signals.
Timing:
Watch the Candle Colors to spot potential overbought or oversold conditions.
Fine-Tuning:
Utilize the RSI lines to closely monitor important thresholds (50 as a trend barometer, 80/20 as possible reversal zones).
Filtering:
Enable a 50 EMA to quickly see if the market is trading above (bullish) or below (bearish) it.
Austin MTF EMA Entry PointsAustin MTF EMA Entry Points
Overview
The Austin MTF EMA Entry Points is a custom TradingView indicator designed to assist traders in identifying high-probability entry points by combining multiple time frame (MTF) analysis. It leverages exponential moving averages (EMAs) from the daily, 1-hour, and 15-minute charts to generate buy and sell signals that align with the overall trend.
This indicator is ideal for traders who:
Want to trade in the direction of the broader daily trend.
Seek precise entry points on lower time frames (1H and 15M).
Prefer using EMAs as their main trend-following tool.
How It Works
Daily Trend Filter:
The indicator calculates the 50 EMA on the daily chart.
The daily EMA acts as the primary trend filter:
If the current price is above the daily 50 EMA, the trend is bullish.
If the current price is below the daily 50 EMA, the trend is bearish.
Lower Time Frame Entry Points:
The indicator calculates the 20 EMA on both the 1-hour (1H) and 15-minute (15M) time frames.
Buy and sell signals are generated when the price aligns with the trend on all three time frames:
Buy Signal: Price is above the daily 50 EMA and also above the 20 EMA on both the 1H and 15M charts.
Sell Signal: Price is below the daily 50 EMA and also below the 20 EMA on both the 1H and 15M charts.
Visual and Alert Features:
Plot Lines:
The daily 50 EMA is plotted in yellow for easy identification of the main trend.
The 20 EMA from the 1H chart is plotted in blue, and the 15M chart's EMA is in purple for comparison.
Buy/Sell Markers:
Green "Up" arrows appear for buy signals.
Red "Down" arrows appear for sell signals.
Alerts:
Alerts notify users when a buy or sell signal is triggered, making it easier to act on trading opportunities in real-time.
How to Use the Indicator
Identify the Main Trend:
Check the relationship between the price and the daily 50 EMA (yellow line):
Only look for buy signals if the price is above the daily 50 EMA.
Only look for sell signals if the price is below the daily 50 EMA.
Wait for Lower Time Frame Alignment:
For a valid signal, ensure that the price is also above or below the 20 EMA (blue and purple lines) on both the 1H and 15M time frames:
This alignment confirms short-term momentum in the same direction as the daily trend.
Act on Signals:
Use the arrows as visual cues for entry points:
Enter long trades on green "Up" arrows.
Enter short trades on red "Down" arrows.
The alerts will notify you of these signals, so you don’t have to monitor the chart constantly.
Exit Strategy:
Use your preferred stop-loss, take-profit, or trailing stop strategy.
You can also exit trades if the price crosses back below/above the daily 50 EMA, signaling a potential reversal.
Use Cases
Swing Traders: Use the daily trend filter to trade in the direction of the dominant trend, while using 1H and 15M signals to fine-tune entries.
Day Traders: Leverage the 1H and 15M time frames to capitalize on short-term momentum while respecting the broader daily trend.
Position Traders: Monitor the indicator to determine potential reversals or significant alignment across time frames.
Customizable Inputs
The indicator includes the following inputs:
Daily EMA Length: Default is 50. Adjust this to change the length of the trend filter EMA.
Lower Time Frame EMA Length: Default is 20. Adjust this to change the short-term EMA for the 1H and 15M charts.
Time Frames: Hardcoded to "D", "60", and "15", but you can modify the script for different time frames if needed.
Example Scenarios
Buy Signal:
Price is above the daily 50 EMA.
Price crosses above the 20 EMA on both the 1H and 15M time frames.
A green "Up" arrow is displayed, and an alert is triggered.
Sell Signal:
Price is below the daily 50 EMA.
Price crosses below the 20 EMA on both the 1H and 15M time frames.
A red "Down" arrow is displayed, and an alert is triggered.
Strengths and Limitations
Strengths:
Aligns trades with the higher time frame trend for increased probability.
Uses multiple time frame analysis to identify precise entry points.
Visual signals and alerts make it easy to use in real-time.
Limitations:
May produce fewer signals in choppy or ranging markets.
Requires discipline to avoid overtrading when conditions are unclear.
Lag in EMAs could result in late entries in fast-moving markets.
Final Notes
The Austin MTF EMA Entry Points indicator is a powerful tool for traders who value multiple time frame alignment and trend-following strategies. While it simplifies decision-making, it is always recommended to backtest and practice proper risk management before using it in live markets.
Try it out and make smarter, trend-aligned trades today! 🚀
3_SMA_Strategy_V-Singhal by ParthibIndicator Name: 3_SMA_Strategy_V-Singhal by Parthib
Description:
The 3_SMA_Strategy_V-Singhal by Parthib is a dynamic trend-following strategy that combines three key simple moving averages (SMA) — SMA 20, SMA 50, and SMA 200 — to generate buy and sell signals. This strategy uses these SMAs to capture and follow market trends, helping traders identify optimal entry (buy) and exit (sell) points. Additionally, the strategy highlights the closing price (CP), which plays a critical role in confirming buy and sell signals.
The strategy also features a Second Buy Signal triggered if the price falls more than 10% after an initial buy signal, providing a re-entry opportunity with a different visual highlight for the second buy signal.
Features:
Three Simple Moving Averages (SMA):
SMA 20: Short-term moving average reflecting immediate market trends.
SMA 50: Medium-term moving average showing the prevailing trend.
SMA 200: Long-term moving average that indicates the overall market trend.
Buy Signal (B1):
Triggered when:
SMA 200 > SMA 50 > SMA 20, indicating a bullish market structure.
The closing price is positioned below all three SMAs, confirming a potential upward reversal.
A green label appears at the low of the bar with the text B1-Price, indicating the price at which the buy signal is generated.
Second Buy Signal (B2):
Triggered if the price falls more than 10% after the first buy signal, providing an opportunity to re-enter the market at a potentially better price.
A blue label appears at the low of the bar with the text B2-Price, showing the price at which the second buy opportunity arises.
Sell Signal (S):
Triggered when:
SMA 20 > SMA 50 > SMA 200, indicating a bearish trend.
The closing price (CP) is positioned above all three SMAs, confirming a potential downward movement.
A red label appears at the high of the bar with the text S-Price, showing the price at which the sell signal is triggered.
How It Works:
Buy Conditions:
SMA 200 > SMA 50 > SMA 20: Indicates a bullish market where the long-term trend (SMA 200) is above the medium-term (SMA 50), and the medium-term trend is above the short-term (SMA 20).
Closing price below all three SMAs: Confirms that the price is in a favorable position for a potential upward reversal.
Sell Conditions:
SMA 20 > SMA 50 > SMA 200: This setup indicates a bearish trend.
Closing price above all three SMAs: Confirms that the price is in a favorable position for a potential downward movement.
Second Buy Signal (B2): If the price falls more than 10% after the first buy signal, the strategy triggers a second buy opportunity (B2) at a potentially better price. This helps traders take advantage of pullbacks or corrections after an initial favorable entry.
Labeling System:
B1-Price: The first buy signal label, appearing when the market is bullish and the closing price is below all three SMAs.
B2-Price: The second buy signal label, triggered if the price falls more than 10% after the initial buy signal.
S-Price: The sell signal label, appearing when the market turns bearish and the closing price is above all three SMAs.
How to Use:
Add the Indicator: Add "3_SMA_Strategy_V-Singhal by Parthib" to your chart on TradingView.
Interpret Buy Signals (B1): Look for green labels with the text "B1-Price" when the closing price (CP) is below all three SMAs and the trend is bullish.
Interpret Second Buy Signals (B2): If the price falls more than 10% after the first buy, look for blue labels with "B2-Price" and a re-entry opportunity.
Interpret Sell Signals (S): Look for red labels with the text "S-Price" when the market turns bearish, and the closing price (CP) is above all three SMAs.
Conclusion:
The 3_SMA_Strategy_V-Singhal by Parthib is an efficient and simple trend-following tool for traders looking to make informed buy and sell decisions. By combining the power of three SMAs and the closing price (CP) confirmation, this strategy helps traders to buy when the market shows a strong bullish setup and sell when the trend turns bearish. Additionally, the second buy signal feature ensures that traders don’t miss out on re-entry opportunities after price corrections, giving them a chance to re-enter the market at a favorable price.
RSI and Bollinger Bands Screener [deepakks444]Indicator Overview
The indicator is designed to help traders identify potential long signals by combining the Relative Strength Index (RSI) and Bollinger Bands across multiple timeframes. This combination allows traders to leverage the strengths of both indicators to make more informed trading decisions.
Understanding RSI
What is RSI?
The Relative Strength Index (RSI) is a momentum oscillator that measures the speed and change of price movements. Developed by J. Welles Wilder Jr. for stocks and forex trading, the RSI is primarily used to identify overbought or oversold conditions in an asset.
How RSI Works:
Calculation: The RSI is calculated using the average gains and losses over a specified period, typically 14 periods.
Range: The RSI oscillates between 0 and 100.
Interpretation:
Key Features of RSI:
Momentum Indicator: RSI helps identify the momentum of price movements.
Divergences: RSI can show divergences, where the price makes a higher high, but the RSI makes a lower high, indicating potential reversals.
Trend Identification: RSI can also help identify trends. In an uptrend, the RSI tends to stay above 50, and in a downtrend, it tends to stay below 50.
Understanding Bollinger Bands
What is Bollinger Bands?
Bollinger Bands are a type of trading band or envelope plotted two standard deviations (positively and negatively) away from a simple moving average (SMA) of a price. Developed by financial analyst John Bollinger, Bollinger Bands consist of three lines:
Upper Band: SMA + (Standard Deviation × Multiplier)
Middle Band (Basis): SMA
Lower Band: SMA - (Standard Deviation × Multiplier)
How Bollinger Bands Work:
Volatility Measure: Bollinger Bands measure the volatility of the market. When the bands are wide, it indicates high volatility, and when the bands are narrow, it indicates low volatility.
Price Movement: The price tends to revert to the mean (middle band) after touching the upper or lower bands.
Support and Resistance: The upper and lower bands can act as dynamic support and resistance levels.
Key Features of Bollinger Bands:
Volatility Indicator: Bollinger Bands help traders understand the volatility of the market.
Mean Reversion: Prices tend to revert to the mean (middle band) after touching the bands.
Squeeze: A Bollinger Band Squeeze occurs when the bands narrow significantly, indicating low volatility and a potential breakout.
Combining RSI and Bollinger Bands
Strategy Overview:
The strategy aims to identify potential long signals by combining RSI and Bollinger Bands across multiple timeframes. The key conditions are:
RSI Crossing Above 60: The RSI should cross above 60 on the 15-minute timeframe.
RSI Above 60 on Higher Timeframes: The RSI should already be above 60 on the hourly and daily timeframes.
Price Above 20MA or Walking on Upper Bollinger Band: The price should be above the 20-period moving average of the Bollinger Bands or walking on the upper Bollinger Band.
Strategy Details:
RSI Calculation:
Calculate the RSI for the 15-minute, 1-hour, and 1-day timeframes.
Check if the RSI crosses above 60 on the 15-minute timeframe.
Ensure the RSI is above 60 on the 1-hour and 1-day timeframes.
Bollinger Bands Calculation:
Calculate the Bollinger Bands using a 20-period moving average and 2 standard deviations.
Check if the price is above the 20-period moving average or walking on the upper Bollinger Band.
Entry and Exit Signals:
Long Signal: When all the above conditions are met, consider a long entry.
Exit: Exit the trade when the price crosses below the 20-period moving average or the stop-loss is hit.
Example Usage
Setup:
Add the indicator to your TradingView chart.
Configure the inputs as per your requirements.
Monitoring:
Look for the long signal on the chart.
Ensure that the RSI is above 60 on the 15-minute, 1-hour, and 1-day timeframes.
Check that the price is above the 20-period moving average or walking on the upper Bollinger Band.
Trading:
Enter a long position when the criteria are met.
Set a stop-loss below the low of the recent 15-minute candle or based on your risk management rules.
Monitor the trade and exit when the RSI returns below 60 on any of the timeframes or when the price crosses below the 20-period moving average.
House Rules Compliance
No Financial Advice: This strategy is for educational purposes only and should not be construed as financial advice.
Risk Management: Always use proper risk management techniques, including stop-loss orders and position sizing.
Past Performance: Past performance is not indicative of future results. Always conduct your own research and analysis.
TradingView Guidelines: Ensure that any shared scripts or strategies comply with TradingView's terms of service and community guidelines.
Conclusion
This strategy combines RSI and Bollinger Bands across multiple timeframes to identify potential long signals. By ensuring that the RSI is above 60 on higher timeframes and that the price is above the 20-period moving average or walking on the upper Bollinger Band, traders can make more informed decisions. Always remember to conduct thorough research and use proper risk management techniques.
simple swing indicator-KTRNSE:NIFTY
1. Pivot High/Low as Lines:
Purpose: Identifies local peaks (pivot highs) and troughs (pivot lows) in price and draws horizontal lines at these levels.
How it Works:
A pivot high occurs when the price is higher than the surrounding bars (based on the pivotLength parameter).
A pivot low occurs when the price is lower than the surrounding bars.
These pivots are drawn as horizontal lines at the price level of the pivot.
Visualization:
Pivot High: A red horizontal line is drawn at the price level of the pivot high.
Pivot Low: A green horizontal line is drawn at the price level of the pivot low.
Example:
Imagine the price is trending up, and at some point, it forms a peak. The script identifies this peak as a pivot high and draws a red line at the price of that peak. Similarly, if the price forms a trough, the script will draw a green line at the low point.
2. Moving Averages (20-day and 50-day):
Purpose: Plots the 20-day and 50-day simple moving averages (SMA) on the chart.
How it Works:
The 20-day SMA smooths the closing price over the last 20 days.
The 50-day SMA smooths the closing price over the last 50 days.
These lines provide an overview of short-term and long-term price trends.
Visualization:
20-day SMA: A blue line showing the 20-day moving average.
50-day SMA: An orange line showing the 50-day moving average.
Example:
When the price is above both moving averages, it indicates an uptrend. If the price crosses below these averages, it might signal a downtrend.
3. Supertrend:
Purpose: The Supertrend is an indicator based on the Average True Range (ATR) and is used to track the market trend.
How it Works:
When the market is in an uptrend, the Supertrend line will be green.
When the market is in a downtrend, the Supertrend line will be red.
Visualization:
Uptrend: The Supertrend line will be plotted in green.
Downtrend: The Supertrend line will be plotted in red.
Example:
If the price is above the Supertrend, the market is considered to be in an uptrend, and if the price is below the Supertrend, the market is in a downtrend.
4. Momentum (Rate of Change):
Purpose: Measures the rate at which the price changes over a set period, showing if the momentum is positive or negative.
How it Works:
The Rate of Change (ROC) measures how much the price has changed over a certain number of periods (e.g., 14).
Positive ROC indicates upward momentum, and negative ROC indicates downward momentum.
Visualization:
Positive ROC: A purple line is plotted above the zero line.
Negative ROC: A purple line is plotted below the zero line.
Example:
If the ROC line is above zero, it means the price is increasing, suggesting bullish momentum. If the ROC is below zero, it indicates bearish momentum.
5. Volume:
Purpose: Displays the volume of traded assets, giving insight into the strength of price movements.
How it Works:
The script will color the volume bars based on whether the price closed higher or lower than the previous bar.
Green bars indicate bullish volume (closing price higher than the previous bar), and red bars indicate bearish volume (closing price lower than the previous bar).
Visualization:
Bullish Volume: Green volume bars when the price closes higher.
Bearish Volume: Red volume bars when the price closes lower.
Example:
If you see a green volume bar, it suggests that the market is participating in an uptrend, and the price has closed higher than the previous period. Red bars indicate a downtrend or selling pressure.
6. MACD (Moving Average Convergence Divergence):
Purpose: The MACD is a trend-following momentum indicator that shows the relationship between two moving averages of the price.
How it Works:
The MACD Line is the difference between the 12-period EMA (Exponential Moving Average) and the 26-period EMA.
The Signal Line is the 9-period EMA of the MACD Line.
The MACD Histogram shows the difference between the MACD line and the Signal line.
Visualization:
MACD Line: A blue line representing the difference between the 12-period and 26-period EMAs.
Signal Line: An orange line representing the 9-period EMA of the MACD line.
MACD Histogram: A red or green histogram that shows the difference between the MACD line and the Signal line.
Example:
When the MACD line crosses above the Signal line, it’s considered a bullish signal. When the MACD line crosses below the Signal line, it’s considered a bearish signal.
Full Chart Example:
Imagine you're looking at a price chart with all the indicators:
Pivot High/Low Lines are drawn as red and green horizontal lines.
20-day and 50-day SMAs are plotted as blue and orange lines, respectively.
Supertrend shows a green or red line indicating the trend.
Momentum (ROC) is shown as a purple line oscillating around zero.
Volume bars are green or red based on whether the close is higher or lower.
MACD appears as a blue line and orange line, with a red or green histogram showing the MACD vs. Signal line difference.
How the Indicators Work Together:
Trend Confirmation: If the price is above the Supertrend line and both SMAs are trending up, it indicates a strong bullish trend.
Momentum: If the ROC is positive and the MACD line is above the Signal line, it further confirms bullish momentum.
Volume: Increasing volume, especially with green bars, suggests that the trend is being supported by active participation.
By using these combined indicators, you can get a comprehensive view of the market's trend, momentum, and potential reversal points (via pivot highs and lows).
Volume HighlightVolume Highlight
Description:
This script helps users analyze trading volume by:
1. Highlighting the highest volume bars:
• Trading sessions with volume equal to or exceeding the highest value over the last 20 periods are displayed in purple.
• Other sessions are displayed in light gray.
2. Displaying the 20-period SMA (Simple Moving Average):
• A 20-period SMA line of the volume is included to track the general trend of trading volume.
Key Features:
• Color-coded Highlights:
• Quickly identify trading sessions with significant volume spikes.
• 20-Period SMA Line:
• Observe the overall trend of trading volume.
• Intuitive Volume Bars:
• Volume bars are clearly displayed for easy interpretation.
How to Use:
1. Add the script to your chart on TradingView.
2. Look at the color of the volume bars:
• Purple: Sessions with the highest trading volume in the past 20 periods.
• Light gray: Other sessions.
3. Use the 20-period SMA line to analyze volume trends.
Purpose:
• Analyze market momentum through trading volume.
• Support trading decisions by identifying significant volume spikes.
Illustration:
• A chart showing color-coded volume bars and the 20-period SMA line.
Options Series - Explode BB⭐ Bullish Zone:
⭐ Bearish Zone:
⭐ Neutral Zone:
The provided script integrates Bollinger Bands with different lengths (20 and 200 periods) and applies customized candle coloring based on certain conditions. Here's a breakdown of its importance and insights:
⭐ 1. Dual Bollinger Bands (BBs):
Bollinger Bands (BB) with 20-period length:
This is the standard setting for Bollinger Bands, with a 20-period simple moving average (SMA) as the central line and upper/lower bands derived from the standard deviation.
These bands are used to identify volatility. Wider bands indicate higher volatility, while narrower bands indicate low volatility.
200-period BB:
This is a longer-term indicator providing insight into the overall trend and long-term volatility.
The 200-period bands filter out noise and offer a "macro" view of price movements compared to the 20-period bands, which focus on short-term price actions.
⭐ 2. Overlay of Bollinger Bands and SMA:
The script plots the Bollinger Bands along with the SMA (Simple Moving Average) of the 200-period BB. This gives traders both a short-term (20-period) and long-term (200-period) perspective, which is valuable for detecting major trend shifts or key support and resistance zones.
Using multiple time frames (20-period for short-term and 200-period for long-term) can help traders spot both immediate opportunities and overarching trends.
⭐ 3. Candle Coloring Based on Key Conditions:
Bullish Signal (GreenFluroscent): When the price closes above the upper 200-period Bollinger Band, the candle turns green, indicating a potential bullish breakout.
Bearish Signal (RedFluroscent): If the price closes below the lower 200-period Bollinger Band, the candle turns red, suggesting a bearish breakout.
Neutral or Uncertain Market: Candles are gray when the price remains between the upper and lower bands, indicating a lack of a strong directional bias.
This color-coded visualization allows traders to quickly assess market sentiment based on the Bollinger Bands' extremes.
⭐ 4. Strategic Importance of the Setup:
Multi-timeframe Analysis: Combining short-term (20-period) and long-term (200-period) Bollinger Bands enables traders to assess the market's overall volatility and trend strength. The longer-term bands act as a reference for broader trend direction, while the shorter-term bands can signal shorter-term pullbacks or entry/exit points.
Breakout Identification: By color-coding the candles when prices cross either the upper or lower 200-period bands, the script makes it easier to spot potential breakouts. This can be particularly helpful in trading strategies that rely on volatility expansions or trend-following tactics.
⭐ 5. Customization and Flexibility:
Custom Colors: The script uses distinct fluorescent green and red colors to highlight key bullish and bearish conditions, providing clear visual cues.
Simplicity with Flexibility: Despite its simplicity, the script leaves room for customization, allowing traders to adjust the Bollinger Band multipliers or apply different conditions to candle coloring for more nuanced setups.
This script enhances standard Bollinger Band usage by introducing multi-timeframe analysis, breakout signals, and visual cues for trend strength, making it a powerful tool for both trend-following and mean-reversion strategies.
🚀 Conclusion:
This script effectively simplifies volatility analysis by visually marking bullish, bearish, and neutral zones, making it a robust tool for identifying trade opportunities across multiple timeframes. Its dual-band approach ensures both trend-following and mean-reversion strategies are supported.
VWAP and MA Crossover SignalsDescription: The VWAP and 20 MA Crossover Indicator is a powerful trading tool designed to capitalize on trend reversals and momentum shifts. This indicator overlays two key technical analysis tools on the price chart: the Volume Weighted Average Price (VWAP) and the 20-period Moving Average (MA).
Functionality:
VWAP: Represents the average price a security has traded at throughout the day, based on volume and price. It is a measure of the market's trend and trading volume.
20 MA: Offers a smoothed average of the closing prices over the last 20 periods, providing a glimpse of the underlying trend.
Signals:
Buy Signal: Generated when the VWAP crosses above the 20-period MA, suggesting an upward momentum and a potential bullish trend reversal.
Sell Signal: This occurs when the VWAP crosses below the 20-period MA, indicating a downward momentum and a potential bearish trend reversal.
Usage: This indicator is ideal for traders focusing on intraday and swing trading strategies, providing clear visual cues for entry and exit points based on the interaction between VWAP and the 20 MA. By identifying key crossover points, traders can make informed decisions about potential bullish or bearish movements in the market.
Application: To use this indicator, simply add it to your TradingView chart setup. The buy and sell signals will be displayed directly on the chart, allowing for easy interpretation and quick action. Adjust the settings to fit your specific trading strategy or market conditions.
Uptrick: EMA Trend Indicator
### Overview
The goal of this script is to visually indicate on a trading chart whether all three Exponential Moving Averages (EMAs) are trending upwards (i.e., their slopes are positive). If all EMAs are trending upwards, the script will color the bars green. If not, the bars will be colored red.
### Key Concepts
1. **Exponential Moving Average (EMA)**: An EMA is a type of moving average that places more weight on recent data, making it more responsive to price changes compared to a simple moving average (SMA). In this script, we use three different EMAs with different lengths (20, 50, and 200 periods).
2. **Slope of an EMA**: The slope of an EMA refers to the direction in which the EMA is moving. If the current value of the EMA is higher than its value in the previous bar, the slope is positive (upward). Conversely, if the current value is lower than its previous value, the slope is negative (downward).
3. **Bar Color Coding**: The script changes the color of the bars on the chart to provide a visual cue:
- **Green Bars**: Indicate that all three EMAs are trending upwards.
- **Red Bars**: Indicate that one or more EMAs are not trending upwards.
### Detailed Breakdown
#### 1. Input Fields
- **EMA Lengths**: The script starts by allowing the user to input the lengths for the three EMAs. These lengths determine how many periods (e.g., days) are used to calculate each EMA.
- `ema20_length` is set to 20, meaning the first EMA uses the last 20 bars of data.
- `ema50_length` is set to 50, meaning the second EMA uses the last 50 bars of data.
- `ema200_length` is set to 200, meaning the third EMA uses the last 200 bars of data.
#### 2. EMA Calculation
- The script calculates the values of the three EMAs:
- **EMA 20**: This is calculated using the last 20 bars of closing prices.
- **EMA 50**: This is calculated using the last 50 bars of closing prices.
- **EMA 200**: This is calculated using the last 200 bars of closing prices.
These calculations result in three values for each bar on the chart, each representing the EMA value at that point in time.
#### 3. Determining EMA Slopes
- **EMA Slopes**: To understand the trend of each EMA, the script compares the current value of each EMA to its value in the previous bar:
- For the 20-period EMA, the script checks if today’s EMA value is higher than yesterday’s EMA value.
- This process is repeated for the 50-period and 200-period EMAs.
- If today’s EMA value is greater than yesterday’s value, the slope is positive (upward).
- If today’s EMA value is not greater (it is either equal to or less than yesterday’s value), the slope is not positive.
#### 4. Evaluating All Slopes
- **All Slopes Positive Condition**: The script combines the results of the individual slope checks into a single condition. It uses a logical "AND" operation:
- The condition will be `true` only if all three EMAs (20, 50, and 200) have positive slopes.
- If any one of the EMAs does not have a positive slope, the condition will be `false`.
#### 5. Coloring the Bars
- **Bar Coloring Logic**: Based on the above condition, the script decides the color of each bar on the chart:
- If all slopes are positive (condition is `true`), the bar is colored green.
- If any slope is not positive (condition is `false`), the bar is colored red.
- **Visual Cue**: This provides a quick, visual indication to traders:
- Green bars suggest that the market is in an upward trend across all three EMAs, which might indicate a strong bullish trend.
- Red bars suggest that the trend is not uniformly upward, which could be a sign of weakening momentum or a potential reversal.
#### 6. Alerts
- **Alert Conditions**: The script also allows for alert conditions to be set based on the slope analysis:
- An alert can be triggered when all EMA slopes are positive. This might be useful for traders who want to be notified when the market shows strong upward momentum.
### Summary
- The script essentially takes the market data and applies three different EMAs to it, each with a different time frame.
- It then checks the direction (slope) of each of these EMAs to determine if they are all trending upwards.
- If they are, the script colors the bar green, signaling a potentially strong bullish trend.
- If any of the EMAs is not trending upwards, it colors the bar red, indicating a potential issue with the strength of the trend.
This approach helps traders quickly assess market conditions based on multiple EMAs, providing a clearer picture of the overall trend across different time frames.
Trading Made Easy ATR BandsAs always, this is not financial advice and use at your own risk. Trading is risky and can cost you significant sums of money if you are not careful. Make sure you always have a proper entry and exit plan that includes defining your risk before you enter a trade.
Background:
This is my take on two relatively famous indicators that paint the colour of your candles in order to help identify trend direction and smooth out market noise. The Elder Impulse System was designed by Dr . Alexander Elder in his book Come Into My Trading Room and attempts to identify the change of trends and when these trends speed up and slow down (school.stockcharts.com). The system used a 13 period EMA and a MACD histogram, and compared each of these indicators to the previous period. In short, when both the histogram and the EMA were rising, the trend was accelerating to the upside and when both were falling, accelerating to the downside. Conversely, when the indicators were not in alignment, say the MACD falling but the EMA rising, it signaled a slowing down of momentum. The downside of this indicator is that it be can rather jumpy, focusing on a short period EMA for 50% of its calculation, leaving a trader to potentially sit on the sidelines during opportune pull backs to enter winning positions, or exit early when there is still a lot of gas left in the tank.
A similar concept has been employed by John Carter and his organization, SimplerTrading, with the 10X bars indicator. However, here they use the famous Directional Movement Index (DMI) created by J. Welles Wilder as the basis for their bars (www.simplertrading.com). John Carter states that the use of this indicator can lead to getting in earlier on more, bigger, and faster setups. The downside of this indicator is the reliance on the ADX calculations to keep you out of rangebound trades. Anyone who is familiar with the DMI system understands it has unparalleled ability to identify longer term trends, but it is also quite slow, leaving the trader to miss a good portion of the initial runup due to this ADX portion that is very slow to get moving and also slow to signal exits.
In short, both of these systems are designed with one thing in mind: keeping the trader on the right side of the move --- but both suffer from the same issue but on opposite sides of the spectrum. One is too fast and the other is too slow. Ultimately, leaving profits on the table for the trader when such a situation could be avoided.
Here I present my own take on these and have made the “Trading Made Easy ATR Bands”. I name it this because trading is much easier when you trade with the prevailing trend, and this system identifies these periods quite effectively while doing a better job of handling the speed flux of most markets. The base formula uses the DMI as its main calculation and the relationship between the DMI+ and DMI- lines, respectively, like the 10X bars. While the trader can investigate these on their own to understand these more intimately, essentially the DMI+ and DMI- lines are calculating the highs and lows respectively of each bar compared to a period in the past and smoothed with the true range, a measurement of volatility . What this ultimately presents is a picture of uptrends and downtrends, where price is making consistently more highs or more lows over a period of time. Where I have modified this relative to the 10X bars is I have ignored the ADX calculations. Further, values over 25 have been discussed as “strong” momentum, in my calculations, I have sped this up to 20 to get a trader into the move earlier. Second, I have added an additional calculation based around the 21-period exponential moving average calculated against its previous output. This then, like the Elder Impulse System, has two forms of market momentum as its calculation to smooth out noise, but has the benefit of being less jumpy, like the original 10X bar system. I have added a series of exponential moving averages following the Fibonacci sequence from 8-144 as a system of dynamic support and resistance showing the sentiment of both the shorter and longer term market participants. Last, I have added a series of Keltner Channels , from 1X-4X, that encompass the 21 period EMA as a base line. The 21 EMA is a stable in all of John Carter’s work and I do believe he is correct that the market is mostly structured around this line, since it roughly approximates one month of trading data. It is not uncommon to see price expand and contract back to this line over and over again.
Trade Signals:
Strong Bullish Momentum – The system will generate a green bar when the DMI+ line is over the DMI- line, the DMI+ line is equal or greater than 20 and the 21 EMA has increased relative to its last close.
Weak Bullish Momentum – The system will generate a blue bar in several scenarios. First, when the DMI+ line is over the DMI- line but the DMI+ line is not over 20 and the EMA is equal or less than the previous close. It will also print a blue bar if either the DMI or the EMA are not aligned, such as the DMI+ is over the DMI- but not over 20 but the EMA has risen compared to the last bar. Last, it will also print a blue bar if the DMI- is over the DMI+ but the EMA is rising.
Strong Bearish Momentum – The system will generate a red bar when the DMI- line is over the DMI+ line, the DMI- line is equal or greater than 20, and the 21 EMA has fallen relative to its last close.
Weak Bearish Momentum – The system will generate an orange bar in several scenarios. First when the DMI- line is over the DMI+ line but the DMI- line is not over 20 and the EMA is equal or greater than the last bar. It will also print an orange bar if either the DMI or the EMA are not aligned, such as the DMI- is over the DMI+ but not over 20 but the EMA has fallen. Lastly, it will also print an orange bar if the DMI+ line is over the DMI- and the EMA has fallen relative to the last bar.
Uses:
1) Like the Elder Impulse System and 10X Bar systems, these should be used as trade filters only.. It is in the trader’s best interest to trade with the trends and these bars identify these periods but may not always generate the most opportune time to enter a market. For instance, trying to short a market when the market is in a phase of Strong Bullish Momentum would not be wise, and vice versa with trying to open long positions when the market is exhibiting Strong Bearish Momentum. Use multiple forms of evidence to confirm the signals shown before entering any trade and to not take these signals on their without confluence of ideas. A viable system could use the Elder Triple Screen System (for reference, see this decent write up --- www.dailyforex.com) with the Trading Made Easy Bands as your “Tide” or longer term filter, and a further trading plan to establish an entry on a short time frame pull back.
2) Interim Trend Exhaustion – Keltner channels work as moving standard deviations from the 21 EMA . 3X multipliers will encompass 99.7% of price and 4X will encompass 99.9% of price away from the 21 EMA . During a trend it would be a good idea to lock in partial profits when price reaches these outer extrema as it is very highly probable that a retracement back to the mean is approaching. While not part of the system, and not recommended to be used by this system, a mean reversion trader could in theory look for reversals at these extrema points and trade a mean reversion strategy back to the 21EMA, but is a much riskier trade with lower probability of success. A trend trader should look to enter trades when a signal is given within the 1ATR or 2ATR zone as this is when price has not really started accelerating yet and is likely to see continued momentum in that direction.
FARAZ.MATI20vA personal indicator.
This indicator has the following features :
Thanks to the managers and administrators of TradingView site for the appropriate space with wide facilities for optimal use. All (indicators) were available on the site and I only defined certain settings for them.
FARAZ.MATI20v
EMA: 5
SMA : 20
SMA : 50
Collision and interruption of Moving 20 by Moving 5 can be the beginning of an upward trend. Provided that the Moving 5 is placed under the candles. (The best signal for the Moving 5 is to collide with the Moving 20 under the candles). Also, the collision of the Moing 5 with the Moing 20 on top of the candles can be a sign of falling. Especially if this collision occurs above the candles.The cut of the Moving 20 and the Moving 50 indicate the intensity of the wave. If Moving 20 is above Moving 50 in this collision, it shows the intensity of the uptrend and if it is below Moving 50, it shows the intensity of the downtrend.
SMA : 100
SMA : 200
Both (resistance and support) are very strong, which is very effective in larger timeframes (such as 1 day).
HMA : 20
To determine the entry point. In such a way that whenever the seeds (HMA) are below the candlesticks. 3 seeds are in ascending position. The body of the candle and the shadow should not touch them. It can be a good signal to enter. Also if the seeds are placed on top of the candlesticks. Show the descending direction of 3 seeds. Provided that the body of the candle and the shadow have not hit them. It is a signal for the short position.
SAR : With the applied settings, it is a kind (trending view) that can evaluate the volume of input to any currency much sooner and determine the probability of rising or falling. If our wave lines (stairs) are at the bottom of the candles, it means an upward trend, and if they are at the top of the candles, it means a downward trend. As the volume of inputs increases, the trend increases, and as the volume of inputs decreases, the trend will also decrease.
Ichimoku Cloud : To determine the lines (support and resistance) the peaks formed by the cloud can represent a resistance area. Price To cross the area marked by the Ichimoku cloud must have a strong candle. This can be very effective in determining the point of entry and purchase.
zig zag : For better diagnosis of the process. Using it to determine areas of support and resistance can be useful. Determining the points of the Fibonacci table is also very effective.