Abz US Real ratesThis indicator shows Fed Funds Rate vs US inflation. It also shows the US 10 year bond yield and provides a color indication that aims to indicate if this is a period where owning TLT is a good idea or not. It is not investment advice and it is only aiming to indicate whether the trend is supportive or not for long dated US bonds in comparison with short dated treasury bills and versus inflation.
Recessions: Recessions are indicated by a grey background.
Yield inversion: Periods where the Fed Funds Rate is above the US 10 year bond yield are shown as a maroon background and frequently are macro indicators of an upcoming recession. Like other macro signals, this can't be relied upon as a timing tool.
This is intended to be used as an indictor on a long term chart. Minimum would be weekly but could be even more valid to focus on a chart with monthly candles.
Recherche dans les scripts pour "10年期国债+交易单位+价格"
Median of Means Estimator Median of Means (MoM) is a measure of central tendency like mean (average) and median. However, it could be a better and robust estimator of central tendency when the data is not normal, asymmetric, have fat tails (like stock price data) and have outliers. The MoM can be used as a robust trend following tool and in other derived indicators.
Median of means (MoM) is calculated as follows, the MoM estimator shuffles the "n" data points and then splits them into k groups of m data points (n= k*m). It then computes the Arithmetic Mean of each group (k). Finally, it calculate the median over the resulting k Arithmetic Means. This technique diminishes the effect that outliers have on the final estimation by splitting the data and only considering the median of the resulting sub-estimations. This preserves the overall trend despite the data shuffle.
Below is an example to illustrate the advantages of MoM
Set A Set B Set C
3 4 4
3 4 4
3 5 5
3 5 5
4 5 5
4 5 5
5 5 5
5 5 5
6 6 8
6 6 8
7 7 10
7 7 15
8 8 40
9 9 50
10 100 100
Median 5 5 5
Mean 5.5 12.1 17.9
MoM 5.7 6.0 17.3
For all three sets the median is the same, though set A and B are the same except for one outlier in set B (100) it skews the mean but the median is resilient. However, in set C the group has several high values despite that the median is not responsive and still give 5 as the central tendency of the group, but the median of means is a value of 17.3 which is very close to the group mean 17.9. In all three cases (set A, B and C) the MoM provides a better snapshot of the central tendency of the group. Note: The MoM is dependent on the way we split the data initially and the value might slightly vary when the randomization is done sevral time and the resulting value can give the confidence interval of the MoM estimator.
Tops & Bottoms by Volume [SS]Hey everyone,
Releasing this indicator that helps you time entries by alerting to potential tops and bottoms in the market.
Background to the indicator:
I was playing around with things that signalled reversals / tops and bottoms in SPSS and R using Pivot Points to mark tops and bottoms. Happened to come across a generally statistically significant relationship between sell to buy volume that was tracked over 10 to 50 candles back and pivot highs and pivot lows.
So I put it into a beta version of an indicator to see how it looked and was a bit surprised.
Since then, I have went back and narrowed down the details of what works/what doesn't work and this is the tentative result!
What it does / How to Use:
It tracks the cumulative buy vs sell volume. Buy volume is cumulated as close > open (or green candles) and sell is open > close (or red candles).
It then cumulates this over a user-defined period (defaulted to 14). It then looks back to see the highest vs lowest areas of sell and buy volume and makes determinations based on this relationship.
The relationship was determined by me using my own analysis and programmed into the indicators algorithm (using highest vs lowest function in pine).
It will plot areas of potential reversal to the upside as green on the histogram or red for a downside reversal. Once this becomes significant enough to signal an actual bottom or top, it will then change the SMA colour from white to green (for bottom) or red (for top).
Your entries generally should be once the SMA turns back to white. So from green to white, you would enter long or inverse for red to white (enter short).
Settings and Customizability:
Here are the key points to keep in mind if you are using this indicator:
Your lookback length should be between 10 to 50. I have left it open for you to modify it below and above this lookback period; however, this is the major periods deemed to be significant in identifying tops and bottoms. Thus, I advise against operating outside of those parameters.
You can toggle between smoothed look or historgram with SMA. The strength in this indicator comes from using the SMA and watching the SMA for signals of reversals, so if you want to filter out the background noise, you can simply look at the plotted SMA. If you want a more responsive indication of impending reversals, leave the smoothed option off and view the histogram in conjunction with the SMA.
The indicator will change the candle colour to red for bearish reversal and green to bullish reversal. This is based on the SMA. You can toggle this off and/or on as desired.
It is recommended to leave ETH (extended trading hours) turned off and RTH turned on.
Please read the instructions carefully.
If you require further assistance, I have posted a tutorial video.
Please be sure you are reading and/or watching carefully.
If you have questions, please feel free to post them below. But bear in mind I likely will not respond if it is already addressed in the description above (this happens often).
Also, feel free to leave your comments or suggestions below as well.
Thanks for checking this out. If you are interested in volume based trading, I suggest also checking out my Buyer to Seller volume indicator which cumulates total buying vs selling volume over a designated lookback period. Both of these used in conjunction are very powerful tools for volume based traders! ( Available here )
NOTE:
The boxes drawn in the chart are my own for demonstration purposes. I unfortunately cannot get the indicator to overlay the boxes on the chart in a separate viewing pane. That is why I opted to use the barcolor function to change the candle color instead :-).
Thanks again everyone and safe trades!
Cross Correlation [Kioseff Trading]Hello!
This script "Cross Correlation" calculates up to ~10,000 lag-symbol pair cross correlation values simultaneously!
Cross correlation calculation for 20 symbols simultaneously
+/- Lag Range is theoretically infinite (configurable min/max)
Practically, calculate up to 10000 lag-symbol pairs
Results can be sorted by greatest absolute difference or greatest sum
Ability to "isolate" the symbol on your chart and check for cross correlation against a list of symbols
Script defaults to stock pairs when on a stock, Forex pairs when on a Forex pair, crypto when on a crypto coin, futures when on a futures contract.
A custom symbol list can be used for cross correlation checking
Can check any number of available historical data points for cross correlation
Practical Assessment
Ideally, we can calculate cross correlation to determine if, in a list of assets, any of the assets frequently lead or lag one another.
Example
Say we are comparing the log returns for the previous 10 days for SPY and XLU.
*A single time-interval corresponds to the timeframe of your chart i.e. 1-minute chart = 1-minute time interval. We're using days for this example.
(Example Results)
A lag value (k) +/-3 is used.
The cross correlation (normalized) for k = +3 is -0.787
The cross correlation (normalized) for k = -3 is 0.216
A positive "k" value indicates the correlation when Asset A (SPY) leads Asset B (XLU)
A negative "k" value indicates the correlation when Asset B (XLU) leads Asset A (SPY)
A normalized cross correlation of -0.787 for k = +3 indicates an "adequately strong" negative relationship when SPY leads XLU by 3 days.
When SPY increases or decreases - XLU frequently moves in the opposite direction 3 days later.
A cross correlation value of 0.216 at k = −3 indicates a "weak" positive correlation when XLU leads SPY by 3 days.
There's a slight tendency for SPY to move in the same direction as XLU 3 days later.
After the cross-correlation score is normalized it will fall between -1 and 1.
A cross-correlation score of 1 indicates a perfect directional relationship between asset A and asset B at the corresponding lag (k).
A cross correlation of -1 indicates a perfect inverse relationship between asset A and asset B at the corresponding lag (k).
A cross correlation of 0 indicates no correlation at the corresponding lag (k).
The image above shows the primary usage for the script!
The image above further explains the data points located in the table!
The image above shows the script "isolating" the symbol on my chart and checking the cross correlation between the symbol and a list of symbols!
Wrapping Up
With this information, hopefully you can find some meaningful lead-lag relationships amongst assets!
Thank you for checking this out (:
JK - Q SuiteThis indicator is primarily for identifying pauses in Stage 2 uptrends, modelled on Qullamaggie's style of trading, but fits well with many traders including William O' Neil. or Mark Minervini.
I built this for my own purposes, and have gradually added range of tools into a single suite. My goal has also to be as clean as possible, while providing clear, actionable information.
This suite includes all of the following:
Moving averages (10, 20, 50, 200)
Coloured bars showing tightening price (blue under 75% of ADR, orange under 50% of ADR)
A 'markets' dashboard (top-right), showing the major indexes. Red if 10<20MA, or price <20MA
A 'sectors' dashboard (top-right, below markets). Red if 5<10MA, or price <10MA - see note below
Strength / Weakness information - two cells at the top, bottom-right. See below
Stock information - glanceable stock info as quick filters. The thresholds for ADR, Average volume, and Dollar Volume can be customised.
NOTE - if the 'tightening coloured candles' are not showing, the indicator needs to be at the top of the stack. Click the triple squares at the very bottom-right of the TradingView interface, and drag the indicator to the top, should work then!
=============
Sectors
These are based on the 11 official Sectors, tracked using index funds (XLY, XLK etc). HOWEVER, TradingView does NOT use the official 11 sectors - therefore I've done my best to match TradingViews ones to the official ones, but doesn't always work... e.g. 'Electronic Technology' is typically semiconductors, which are classes as 'Industrials', but Apple is the same sector in TV, but classed as 'Technology' using the official 11 Sectors.
If TradingView move to use the official 11 I'll update this, but for now it's a best guess and will sometimes be wrong, sorry!
Strength / Weakness information
This was an experiment in trying not to give too much back to the market! Typically the strategy would be to sell if price closes below 10MA (Weakness), however there may be large pops that can be advantageous to sell into.
The 'Strength' information (top cell, bottom-right), checks how far the price is extended above 10MA - this is customisable as a multiple of ADR. You may find that in weak markets (like now), it can be best to take profits quickly - in good markets, you could increase this as stocks make bigger or more sustained moves.
=============
While I'm not the best coder - and I've hacked and tried and changed different things - this has been a labour of love and essential for me.
If you have any suggestions, while I may or may not be able to implement them, I'm certainly open to ideas!
Strategy:Reversal-CatcherWhat
This is a plain and vanilla reversal based strategy for intraday (15m) timeframe on Futures prices of the assets.
Now what all it comprises of?
It finds out the dynamic support & resistance from Bollinger Band (20 period, 1.5 std dev).
It finds out the potential divergence of price deviation from 5 period exponential moving average (EMA).
If the previous candle (N-1) shows a divergence it confirms the reversal by checking the present candle (N) to be closed inside the Bollinger Band.
It confirms the momentum by checking RSI shows a crossover/crossunder to oversold (30) / overbought (70) region.
It also confirms whether the trend is up (then only reversal trade to short) or down (then only reversal trade to long). The trend is checked with EMA-21 and EMA-50.
Re-affirmation Condition : It re-affirms the position of two successive candles called as `hhLLong` and `hhLLShort` in the script.
Why
In Indian context, retail participants are pre-dominantly (yes- 80% of Indian daily volume) Options buyers mainly in weekly indices (Nifty, BankNifty, FinNifty, CNXMidcap, Sensex, Bankx .. well everyday is expiry now in India, except -- Thank God -- Saturday & Sunday).
And in Index Options the momentum plays a big role.
If one can catch a good reversal point the potential of high Risk-to-Reward trade (hence earn handsomely) is very likely (please note: there is no holy grail in trading. Nothing works 100%).
So this is the attempt to catch a reversal.
Re-affirmation of Reversal
hhLLong : It's a reversal point after an uptrend. It checks the relative positioning of current candle compared to that of previous candle. [The details are in the script. Check for variable hhLLong in script.
hhLLShort : It's a reversal point after a downtrend. It checks the relative positioning of current candle compared to that of previous candle. [The details are in the script. Check for variable hhLLShort in script.
Unique-ness
What's unique in it? Why we decided to publicly share this:
Already given the context of The Great Indian Options Buyers community. It should be helpful to them, we believe.
It takes Very Less Number of Trades with High Accuracy . Please check the result in NSE:NIFTY1! in 15m timeframe. 71% accuracy with roughly a trade in a month.
There is no point giving brokers' the brokerages taking 10 trades a day and ending not-so-good EoD. Better lets take less trades with better result possibility. .
Mention
There are many people uses this variation of Bolling Band, 5EMA
Many people use RSI, trends and relative positioning of candles.
--> We are grateful to all of them. It's really difficult to mention everyone's name. But all people somehow influence the thought process. Thanks for all of them.
Statutory Disclaimer
There is no silver bullet / holy grail in trading. Nothing works 100% time. One has to be careful about the loss (s)he can bear in case of the trade goes against.
We, as the author of this script, is not responsible for any trading or position decision one is taken based on the outcome of this.
It is our sole discretion to change, add, delete the portion or withdraw the whole script without any prior notice or intimation.
In Indian Context : We are not SEBI registered, will never be SEBI registered.
Dynamic Liquidity Map [Kioseff Trading]Hello!
Just a quick/fun project here: "Dynamic Heatmap".
This script draws a volume delta or open interest delta heatmap for the asset on your chart.
The adjective "Dynamic" is used for two reasons (:
1: Self-Adjusting Lower Timeframe Data
The script requests ~10 lower timeframe volume and open interest data sets.
When using the fixed range feature the script will, beginning at the start time, check the ~10 requested lower timeframes to see which of the lower timeframes has available data.
The script will always use the lowest timeframe available during the calculation period. As time continues, the script will continue to check if new lower timeframe data (lower than the currently used lowest timeframe) is available. This process repeats until bar time is close enough to the current time that 1-minute data can be retrieved.
The image above exemplifies the process.
Incrementally lower timeframe data will be used as it becomes available.
1: Fixed range capabilities
The script features a "fixed range" tool, where you can manually set a start time (or drag & drop a bar on the chart) to determine the interval the heatmap covers.
From the start date, the script will calculate the calculate the sub-intervals necessary to draw a rows x columns heatmap. Consequently, setting the start time further back will draw a heat map with larger rows x columns, whereas, a start time closer to the current bar time will draw a more "precise" heatmap with smaller rows x columns.
Additionally, the heatmap can be calculated using open interest data.
The image above shows the heatmap displaying open interest delta.
The image above shows alternative settings for the heatmap.
Delta values have been hidden alongside grid border colors. These settings can be replicated to achieve a more "traditional" feel for the heatmap.
Thanks for checking this out!
[OKX Signal Bot] Indicator Script Set Up TemplateDiscover the power of the Turtle Trade Channels Indicator (TUTCI), an innovative tool that integrates the time-tested principles of the legendary Turtle Trade system. This groundbreaking system shattered the belief that successful traders are born, not made, by transforming ordinary individuals into profitable traders.
The Turtle Trade Experiment, which achieved a remarkable 80% annual return over four years and amassed a staggering $150 million, showcased the immense potential of this trend-following strategy. Unlike the conventional "buy low and sell high" approach, the Turtle Trade system embraces a different philosophy—one of capturing substantial profits by following prevailing trends.
At the heart of the Turtle Trade Channels Indicator lies the concept of Donchian Channels, a powerful technical indicator developed by Richard Donchian. Building upon this foundation, the main rule of TUTCI is to identify 20-day breakouts and capitalize on them, while simultaneously utilizing a profit-taking strategy based on breaching 10-day highs or lows.
For long trades, the indicator signals a buying opportunity when the price breaks above the 20-day high. Conversely, for short trades, a selling opportunity arises when the price falls below the 20-day low. This systematic approach allows traders to align themselves with the prevailing momentum, capturing significant price movements.
To further enhance trading precision, TUTCI incorporates two key lines. The red line represents the trading line, indicating the direction of the trend. Price bars above the trend line suggest an uptrend, while those below indicate a downtrend. The dotted blue line serves as the exit line, guiding traders to close their positions when price action breaches the 10-day high or low. This rule safeguards profits and helps traders avoid potential trend reversals.
The Turtle Trade Channels Indicator (TUTCI) is a versatile tool applicable to various financial markets, including stocks, commodities, and forex. By harnessing the power of breakouts and integrating profit-taking rules, this indicator empowers traders to capitalize on favorable trading opportunities while managing risk effectively.
As with any trading strategy, it is crucial to conduct thorough backtesting and evaluation of the TUTCI system before implementing it in live trading. Traders can customize the indicator's parameters to align with their trading preferences and adapt to changing market conditions. Employing sound risk management techniques, such as position sizing and stop-loss orders, is paramount to protect capital and minimize potential losses.
Experience the transformational potential of the Turtle Trade Channels Indicator (TUTCI) and embark on a journey of trend following, capturing significant profits, and achieving trading success.
These scripts are only functioning as sample script templates to support okx alert standards. It is not intended to provide any investment, tax, or legal advice, nor should it be considered an offer to purchase, sell, hold or offer any services relating to digital assets. Digital assets, including stablecoins, involve a high degree of risk, can fluctuate greatly, and can even become worthless. You should carefully consider whether trading or holding digital assets is suitable for you in light of your financial condition and risk tolerance. OKX does not provide investment or asset recommendations. You are solely responsible for your investment decisions, and OKX is not responsible for any potential losses. Past performance is not indicative of future results. Please consult your legal/tax/investment professional for questions about your specific circumstances.
Volume Delta Compare [Ticks ~ LTF data]
The "Volume Delta Compare " publication shows 2 different techniques to show into-depth details of Volume, using Tick and Lower-Time-Frame (LTF) data.
🔶 USAGE
Check for divergences between price and volume movement
Check details (why and when a ΔV developed)
Or if you want to see a lot of data stacked on each other )
🔶 CONCEPTS
🔹 Tick vs. LTF data
a Tick is an measure of (upward or downward) movement in price OR volume.
We can use this data by using varip in the code.
Advantage:
• Detail, detail, detail
• Accurate, per tick
Disadvantage:
• Only realtime
• Can reset 'easily' -> loss of data
• Will reset when settings are changed
LTF data, through the request.security_lower_tf() function, measures the OHLCV data per LTF bar
Advantage:
• Access to history when loading a chart
• No 'loss' of data when chart resets
Disadvantage:
• Less detailed
• Less accurate
This script makes it possible to compare the 2 techniques and enables you to show different values.
🔹 Values
There are mainly 3 important values:
• UP volume (uV): volume when price rises
• DOWN volume (dV): volume when price falls
• NEUTRAL volume (nV): volume when price stays the same
From this, additional data is calculated:
• Volume Delta (ΔV): uV minus dV
• Cumulative Delta Volume (cΔV): sum of ΔV
One typical nV is at open: at that moment there isn't a base price to compare with,
so when the first trade doesn't fully fill the first supply (up or down), volume will rise, but price just is 'open', no movement -> no uV or dV.
• Tick data: every volume changement per tick will be added to the concerning variable (uV, dV or nV)
• LTF data: every volume changement of each bar will be added to the concerning variable (uV, dV or nV)
-> this can easily give a difference, for example (Tick vs. 1 minute LTF), when most of the ticks caused a rise of price, but at the last few seconds, a few ticks causes the close to come below open, with Tick data this could give more UP Volume, while LTF data will show 1 value of DOWN Volume.
🔶 EXAMPLES
🔹 Details
In these examples you can see:
• grey line: Total volume (higher precision)
• UP/DOWN/NEUTRAL Volume
• green columns: uV
• orange columns: dV
• blue pillars: nV
• coloured stepline: reflects ΔV
• close > open and positive ΔV -> green
• close > open but negative ΔV -> fuchsia
• close < open and negative ΔV -> orange
• close < open but positive ΔV -> bright lime green
• Right side -> indication of used data (Tick/LTF data) + last ΔV
• labels (can be disabled)
Above 0 (only with Tick data): data from EVERY tick (ΔV ):
• first the amount of Volume (0 when the amount is very minimal)
• between brackets: price movement
Below 0:
• Σ V: sum of uV, dV and nV, for that bar
• Σ up: sum of uV for that bar
• Σ dn: sum of dV for that bar
• Σ nt: sum of nV for that bar
• Σ P: sum of price movement, for that bar (only at Tick data)
(At the right you'll see a new bar just started)
Here is a detail of the first second at opening:
🔹 Cumulative Volume Delta (CVD)
Difference CVD based on Tick vs. LTF data :
(horizontal lines added for reference)
🔶 FEATURES
🔹 Minimal plotting of na values
Data window and status line only show what is applicable (tick or LTF data) to diminish clutter of data values:
The Tick option has a label above 0 which includes details of every Tick.
If data is added every tick, that label on a 10 minute chart will be filled beyond limitations pretty quickly (string max_length = 4096 limit).
To prevent the script stopping to execute, at a certain limit, this label will stop updating and show the message "Too much data".
The label below the 0-line won't reach that limit, so it will keep on updating.
Timeframes closer to 1 second will have less risk to reach that 4096 limit. Details will remain to show in this case.
🔹 Automatic label colour adaption when changing between dark/light mode values
Label background/text-colour will adapt according to the dark/light-mode by using chart.fg_color / chart.bg_color
🔶 SETTINGS
🔹 Data from: Ticks vs. LTF data
🔹 LTF: Lower Time-Frame for when LTF option is chosen: 1, 5, 10, 15, 30 Seconds or 1 minute
🔹 Also start when bar already has data: only for tick data -> when disabled calculations only start on a new bar.
🔹 CVD, Only show Cumulative Delta Volume: enable to just display CVD
🔹 Colours: colour at the right is for price/volume direction divergences
🔹 Label: choose what you want to display + size labels
🔹 0-line: The label under the 0-line sometimes goes below the chart. this can be adjusted with this setting.
TrendGuard Flag Finder - Strategy [presentTrading]
Introduction and How It Is Different
In the vast world of trading strategies, the TrendGuard Flag Finder stands out as a unique blend of traditional flag pattern detection and the renowned SuperTrend indicator.
- A significant portion of the Flag Pattern detection is inspired by the "Flag Finder" code by @Amphibiantrading, which serves as one of foundational element of this strategy.
- While many strategies focus on either trend-following or pattern recognition, this strategy harmoniously combines both, offering traders a more holistic view of the market.
- The integration of the SuperTrend indicator not only provides a clear direction of the prevailing trend but also offers potential stop-loss levels, enhancing the strategy's risk management capabilities.
AAPL 1D chart
ETHBTC 6hr chart
Strategy: How It Works
The TrendGuard Flag Finder is primarily built on two pillars:
1. Flag Pattern Detection : At its core, the strategy identifies flag patterns, which are continuation patterns suggesting that the prevailing trend will resume after a brief consolidation. The strategy meticulously detects both bullish and bearish flags, ensuring traders can capitalize on opportunities in both rising and falling markets.
What is a Flag Pattern? A flag pattern consists of two main components:
1.1 The Pole : This is the initial strong price move, which can be either upwards (for bullish flags) or downwards (for bearish flags). The pole represents a strong surge in price in a particular direction, driven by significant buying or selling momentum.
1.2 The Flag : Following the pole, the price starts consolidating, moving against the initial trend. This consolidation forms a rectangular shape and is characterized by parallel trendlines. In a bullish flag, the consolidation will have a slight downward tilt, while in a bearish flag, it will have a slight upward tilt.
How the Strategy Detects Flags:
Identifying the Pole: The strategy first identifies a strong price movement over a user-defined number of bars. This movement should meet a certain percentage change to qualify as a pole.
Spotting the Flag: After the pole is identified, the strategy looks for a consolidation phase. The consolidation should be counter to the prevailing trend and should be contained within parallel lines. The depth (for bullish flags) or rally (for bearish flags) of this consolidation is calculated to ensure it meets user-defined criteria.
2. SuperTrend Integration : The SuperTrend indicator, known for its simplicity and effectiveness, is integrated into the strategy. It provides a dynamic line on the chart, signaling the prevailing trend. When prices are above the SuperTrend line, it's an indication of an uptrend, and vice versa. This not only confirms the flag pattern's direction but also offers a potential stop-loss level for trades.
When combined, these components allow traders to identify potential breakout (for bullish flags) or breakdown (for bearish flags) scenarios, backed by the momentum indicated by the SuperTrend.
Usage
To use the SuperTrend Enhanced Flag Finder:
- Inputs : Begin by setting the desired parameters. The strategy offers a range of user-controlled settings, allowing for customization based on individual trading preferences and risk tolerance.
- Visualization : Once the parameters are set, the strategy will identify and visually represent flag patterns on the chart. Bullish flags are represented in green, while bearish flags are in red.
- Trade Execution : When a breakout or breakdown is identified, the strategy provides entry signals. It also offers exit signals based on the SuperTrend, ensuring that traders can capitalize on the momentum while managing risk.
Default Settings
The strategy comes with a set of default settings optimized for general use:
- SuperTrend Parameters: Length set to 10 and Factor set to 5.0.
- Bull Flag Criteria: Max Flag Depth at 7, Max Flag Length at 10 bars, Min Flag Length at 3 bars, Prior Uptrend Minimum at 9%, and Flag Pole Length between 7 to 13 bars.
- Bear Flag Criteria: Similar settings adjusted for bearish patterns.
- Display Options: By default, both bullish and bearish flags are displayed, with breakout and breakdown points highlighted.
Liquidity Breakout - Strategy [presentTrading]- Introduction and How It Is Different
The Liquidity Breakout Strategy is a unique trading strategy that focuses on identifying and leveraging patterns in market price data. This strategy, mainly inspired by the script "Master Pattern" by LuxAlgo, takes a different approach from many traditional strategies that rely on technical indicators or fundamental analysis. Instead, the Liquidity Breakout is based on the concept of contraction detection and liquidity levels. This approach allows traders to identify potential trading opportunities that other strategies might miss.
BTCUSDT 6h
The strategy is different from other trading strategies because it uses a unique combination of pattern detection, liquidity levels, and user-defined trading direction. This combination allows the strategy to adapt to various market conditions and trading styles, making it a versatile tool for traders.
- Strategy: How It Works
1. Contraction Detection: The strategy uses a lookback period defined by the user (default is 10 bars) to identify contractions in the market. A contraction is a period where the market is consolidating, often followed by a significant price movement. The strategy identifies contractions by finding pivot highs and pivot lows within the lookback period. If a pivot high is lower than the previous pivot high and a pivot low is higher than the previous pivot low, a contraction is detected.
2. liquidity Levels:
What are Liquidity levels? Liquidity levels, also known as liquidity pools or zones, are price levels at which there is a significant amount of trading activity. They are often areas where large institutional traders (like banks or hedge funds) have placed orders. These levels are important because they can act as support or resistance levels, and price often reacts at these levels.
In the context of this strategy, liquidity levels are used to identify potential entry and exit points for trades. When the price reaches a liquidity level, it could indicate a potential trading opportunity. For example, if the price breaks through a liquidity level, it could signal the start of a new trend. On the other hand, if the price approaches a liquidity level and then reverses, it could signal a potential reversal.
The strategy uses these two elements to identify potential trading opportunities. When a contraction is detected, the strategy will look for a breakout in the direction of the trend. If the breakout occurs at a liquidity level, the strategy will execute a trade.
The strategy also allows traders to set their stop loss based on either the Average True Range (ATR) or a fixed percentage. This flexibility allows traders to manage their risk according to their personal risk tolerance and trading style.
- Trade Direction
One of the unique features of the Master Pattern Strategy is the ability to choose the trading direction. Traders can choose to trade in the "Long" direction, the "Short" direction, or "Both". This feature allows traders to adapt the strategy to their personal trading style and market outlook.
For example, if a trader believes that the market is in an uptrend, they can choose to trade only in the "Long" direction. Conversely, if the market is in a downtrend, they can choose to trade only in the "Short" direction. If the trader believes that the market is volatile and there are opportunities in both directions, they can choose to trade in "Both" directions.
- Usage
To use the strategy, traders need to input their preferred settings, including the contraction detection lookback period, liquidity levels, stop loss type, and trading direction. Once these settings are input, the strategy will automatically detect potential trading opportunities and execute trades according to the defined parameters.
- Default Settings
The default settings for the Master Pattern Strategy are as follows:
Contraction Detection Lookback: 10
Liquidity Levels: 20
Stop Loss Type: ATR
ATR Length: 20
ATR Multiplier: 3.0
Fixed Percentage: 0.01
Trading Direction: Both
These settings can be adjusted according to the trader's personal preferences and market conditions. It's recommended that traders experiment with different settings to find the ones that work best for their trading style and goals.
Volume [Entoryx]
Certainly! Here's a more concise description for the "Entoryx Volume" indicator, with less focus on the specifics of the order block bar detection:
The "Entoryx Volume" is a versatile technical indicator that analyzes the relationship between price ranges and volume over a user-defined number of bars. By calculating a delta between the highest high and lowest low, it offers insights into market momentum and direction.
Key features of this indicator include:
1) Current Value Plotting: A dynamic line plotted on the chart represents the current value, which reflects market trends. The color of the line changes to green for bullish conditions and red for bearish conditions, depending on its relationship with the Exponential Moving Average (EMA) of the close.
2) Color-Coded Regions: The area between the current value plot and a baseline zero line is filled with a corresponding color, providing a visual representation of market sentiment.
3) Boundary Lines: Horizontal lines at +10 and -10 serve as reference points to highlight significant market movements.
4) Order Block Bar Detection (Optional): An optional feature that places visual markers on the chart to signal potential reversals. This can be enabled or disabled by the user, according to preference.
The "Entoryx Volume" indicator is tailored for traders aiming to understand market momentum with a clear and visually intuitive display. It is suitable across various trading strategies and market conditions, with customization options to fit individual needs.
The source code for this indicator is subject to the terms of the Mozilla Public License 2.0.
Custom EMAsNow the indicator includes 10 different types of EMAs, each with a changeable length and selectable type. You can use the input settings to adjust the type and length for each EMA. The plot shows all 10 EMAs on the chart.
Expected Move from RSI [SS]Publishing this experimental indicator.
What it does:
The indicator uses a user-defined lookback period on a user-defined timeframe to lookback at all instances of RSI. It breaks RSI down as follows:
RSI between
0 - 10
10 - 20
20 - 30
30 - 40
40 - 50
50 - 60
60 - 70
70 - 80
80 - 90
90 - 100
From there, it stores the ticker's move from open to high and open to low. It will then use this data to look at the current RSI based on the specified timeframe and plot the expected move based on the average move the ticker does with a similar RSI reading.
It will plot the expected range, with the high range being plotted in green and the low range being plotted in red.
It will also display an infographic that dictates the current RSI based on the selected time frame, the anticipated up move and the anticipated down move. This infographic will also tell you the strength of the relationship (correlation) RSI has with the ticker's high or low price:
From there the user can determine whether this RSI reading is traditionally bullish or bearish for the ticker. A greater down move indicates that the RSI traditionally elicits a bearish response. A greater up move indicates the inverse.
The user can also view a chart of a breakdown of the anticipated moves based on RSI. If the option to "Show Expected Move Table" is select in the settings menu, the following table will appear:
From here you can see the average up move and down move a ticker does based on its corresponding RSI reading.
NOTE: When using the table, please adjust your chart timeframe to the selected timeframe on the indicator. Thus, if you are looking at the 1 hour levels, please adjust your chart to the 1 hour timeframe to use the chart.
Additional Note: When using the table, an "NaN" means that there are no instances of the ticker being at that RSI level within the designated timeframe period. You can extend your lookback period to up to 500 candles to see if it finds additional instances of similar RSI. Otherwise, you can adjust the selected timeframe.
Uses:
The indicator can be used on all timeframes. It can help give you an idea as to whether the RSI indicates a bearish or bullish sentiment.
It can signal a potential reversal or continuation. It can also help you with determining target prices for day trades and scalp trades.
And that is the indicator. Its pretty straight forward. It is experimental and new, so feel free to play around with it and let me know your thoughts.
Safe trades everyone and thank you for reading!
CCI+EMA Strategy with Percentage or ATR TP/SL [Alifer]This is a momentum strategy based on the Commodity Channel Index (CCI), with the aim of entering long trades in oversold conditions and short trades in overbought conditions.
Optionally, you can enable an Exponential Moving Average (EMA) to only allow trading in the direction of the larger trend. Please note that the strategy will not plot the EMA. If you want, for visual confirmation, you can add to the chart an Exponential Moving Average as a second indicator, with the same settings used in the strategy’s built-in EMA.
The strategy also allows you to set internal Stop Loss and Take Profit levels, with the option to choose between Percentage-based TP/SL or ATR-based TP/SL.
The strategy can be adapted to multiple assets and timeframes:
Pick an asset and a timeframe
Zoom back as far as possible to identify meaningful positive and negative peaks of the CCI
Set Overbought and Oversold at a rough average of the peaks you identified
Adjust TP/SL according to your risk management strategy
Like the strategy? Give it a boost!
Have any questions? Leave a comment or drop me a message.
CAUTIONARY WARNING
Please note that this is a complex trading strategy that involves several inputs and conditions. Before using it in live trading, it is highly recommended to thoroughly test it on historical data and use risk management techniques to safeguard your capital. After backtesting, it's also highly recommended to perform a first live test with a small amount. Additionally, it's essential to have a good understanding of the strategy's behavior and potential risks. Only risk what you can afford to lose .
USED INDICATORS
1 — COMMODITY CHANNEL INDEX (CCI)
The Commodity Channel Index (CCI) is a technical analysis indicator used to measure the momentum of an asset. It was developed by Donald Lambert and first published in Commodities magazine (now Futures) in 1980. Despite its name, the CCI can be used in any market and is not just for commodities. The CCI compares current price to average price over a specific time period. The indicator fluctuates above or below zero, moving into positive or negative territory. While most values, approximately 75%, fall between -100 and +100, about 25% of the values fall outside this range, indicating a lot of weakness or strength in the price movement.
The CCI was originally developed to spot long-term trend changes but has been adapted by traders for use on all markets or timeframes. Trading with multiple timeframes provides more buy or sell signals for active traders. Traders often use the CCI on the longer-term chart to establish the dominant trend and on the shorter-term chart to isolate pullbacks and generate trade signals.
CCI is calculated with the following formula:
(Typical Price - Simple Moving Average) / (0.015 x Mean Deviation)
Some trading strategies based on CCI can produce multiple false signals or losing trades when conditions turn choppy. Implementing a stop-loss strategy can help cap risk, and testing the CCI strategy for profitability on your market and timeframe is a worthy first step before initiating trades.
2 — AVERAGE TRUE RANGE (ATR)
The Average True Range (ATR) is a technical analysis indicator that measures market volatility by calculating the average range of price movements in a financial asset over a specific period of time. The ATR was developed by J. Welles Wilder Jr. and introduced in his book “New Concepts in Technical Trading Systems” in 1978.
The ATR is calculated by taking the average of the true range over a specified period. The true range is the greatest of the following:
The difference between the current high and the current low.
The difference between the previous close and the current high.
The difference between the previous close and the current low.
The ATR can be used to set stop-loss orders. One way to use ATR for stop-loss orders is to multiply the ATR by a factor (such as 2 or 3) and subtract it from the entry price for long positions or add it to the entry price for short positions. This can help traders set stop-loss orders that are more adaptive to market volatility.
3 — EXPONENTIAL MOVING AVERAGE (EMA)
The Exponential Moving Average (EMA) is a type of moving average (MA) that places a greater weight and significance on the most recent data points.
The EMA is calculated by taking the average of the true range over a specified period. The true range is the greatest of the following:
The difference between the current high and the current low.
The difference between the previous close and the current high.
The difference between the previous close and the current low.
The EMA can be used by traders to produce buy and sell signals based on crossovers and divergences from the historical average. Traders often use several different EMA lengths, such as 10-day, 50-day, and 200-day moving averages.
The formula for calculating EMA is as follows:
Compute the Simple Moving Average (SMA).
Calculate the multiplier for weighting the EMA.
Calculate the current EMA using the following formula:
EMA = Closing price x multiplier + EMA (previous day) x (1-multiplier)
STRATEGY EXPLANATION
1 — INPUTS AND PARAMETERS
The strategy uses the Commodity Channel Index (CCI) with additional options for an Exponential Moving Average (EMA), Take Profit (TP) and Stop Loss (SL).
length : The period length for the CCI calculation.
overbought : The overbought level for the CCI. When CCI crosses above this level, it may signal a potential short entry.
oversold : The oversold level for the CCI. When CCI crosses below this level, it may signal a potential long entry.
useEMA : A boolean input to enable or disable the use of Exponential Moving Average (EMA) as a filter for long and short entries.
emaLength : The period length for the EMA if it is used.
2 — CCI CALCULATION
The CCI indicator is calculated using the following formula:
(src - ma) / (0.015 * ta.dev(src, length))
src is the typical price (average of high, low, and close) and ma is the Simple Moving Average (SMA) of src over the specified length.
3 — EMA CALCULATION
If the useEMA option is enabled, an EMA is calculated with the given emaLength .
4 — TAKE PROFIT AND STOP LOSS METHODS
The strategy offers two methods for TP and SL calculations: percentage-based and ATR-based.
tpSlMethod_percentage : A boolean input to choose the percentage-based method.
tpSlMethod_atr : A boolean input to choose the ATR-based method.
5 — PERCENTAGE-BASED TP AND SL
If tpSlMethod_percentage is chosen, the strategy calculates the TP and SL levels based on a percentage of the average entry price.
tp_percentage : The percentage value for Take Profit.
sl_percentage : The percentage value for Stop Loss.
6 — ATR-BASED TP AND SL
If tpSlMethod_atr is chosen, the strategy calculates the TP and SL levels based on Average True Range (ATR).
atrLength : The period length for the ATR calculation.
atrMultiplier : A multiplier applied to the ATR to set the SL level.
riskRewardRatio : The risk-reward ratio used to calculate the TP level.
7 — ENTRY CONDITIONS
The strategy defines two conditions for entering long and short positions based on CCI and, optionally, EMA.
Long Entry: CCI crosses below the oversold level, and if useEMA is enabled, the closing price should be above the EMA.
Short Entry: CCI crosses above the overbought level, and if useEMA is enabled, the closing price should be below the EMA.
8 — TP AND SL LEVELS
The strategy calculates the TP and SL levels based on the chosen method and updates them dynamically.
For the percentage-based method, the TP and SL levels are calculated as a percentage of the average entry price.
For the ATR-based method, the TP and SL levels are calculated using the ATR value and the specified multipliers.
9 — EXIT CONDITIONS
The strategy defines exit conditions for both long and short positions.
If there is a long position, it will be closed either at TP or SL levels based on the chosen method.
If there is a short position, it will be closed either at TP or SL levels based on the chosen method.
Additionally, positions will be closed if CCI crosses back above oversold in long positions or below overbought in short positions.
10 — PLOTTING
The script plots the CCI line along with overbought and oversold levels as horizontal lines.
The CCI line is colored red when above the overbought level, green when below the oversold level, and white otherwise.
The shaded region between the overbought and oversold levels is plotted as well.
Indian Market Sessions for BacktestingThis indicator is designed to increase the quality of your backtesting in the Indian Market.
NSE & BSE run from 9:15 am IST to 3:30 pm IST.
Naturally different times have different kinds of volatility.
On your chart you will find premarked -
Saffron - 9:15 am to 10:30 am - Opening Session - High Volatility Observed Historically
White - 10:35 am to 2:25 pm - Middle Session - Lower Volatility Observed Historically
Green - 2:30 pm to 3:30 pm - Closing Session - Medium to High Volatility Observed Historically
You will also find the start of each session marked with an arrow.
Feel free to change the times from the input settings and the color and visibility from the style settings.
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Usage:
When you backtest any strategies, say moving average crossovers, also mark the sessions in your sheet which will help you further increase accuracy.
Feel free to drop your doubts in the comments.
