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Time█   OVERVIEW This library is a Pine Script™ programmer’s tool containing a variety of time related functions to calculate or measure time, or format time into string variables. █   CONCEPTS `formattedTime()`, `formattedDate()` and `formattedDay()` Pine Script™, like many other programming languages, uses timestamps in UNIX format, expressed as the number of milliseconds elapsed since 00:00:00 UTC, 1 January 1970. These three functions convert a UNIX timestamp to a formatted string for human consumption. These are examples of ways you can call the functions, and the ensuing results: CODE RESULT formattedTime(timenow) >>> "00:40:35" formattedTime(timenow, "short") >>> "12:40 AM" formattedTime(timenow, "full") >>> "12:40:35 AM ​UTC​" formattedTime(1000 * 60 * 60 * 3.5, "HH:mm") >>> "03:30" formattedDate(timenow, "short") >>> "4/30/22" formattedDate(timenow, "medium") >>> ​"Apr​ 30, 2022" formattedDate(timenow, "full") >>> "Saturday, April 30, 2022" formattedDay(timenow, "E") >>> "Sat" formattedDay(timenow, "dd.MM.yy") >>> "30.04.22" formattedDay(timenow, "yyyy.MM.dd G 'at' hh:mm:ss z") >>> "2022.04.30 AD at 12:40:35 UTC" These functions use str.format() and some of the special formatting codes it allows for. Pine Script™ documentation does not yet contain complete specifications on these codes, but in the meantime you can find some information in the The Java™ Tutorials and in Java documentation of its MessageFormat class . Note that str.format() implements only a subset of the MessageFormat features in Java. `secondsSince()` The introduction of varip variables in Pine Script™ has made it possible to track the time for which a condition is true when a script is executing on a realtime bar. One obvious use case that comes to mind is to enable trades to exit only when the exit condition has been true for a period of time, whether that period is shorter that the chart's timeframe, or spans across multiple realtime bars. For more information on this function and varip please see our Using `varip` variables publication. `timeFrom( )` When plotting lines , boxes , and labels one often needs to calculate an offset for past or future end points relative to the time a condition or point occurs in history. Using xloc.bar_index is often the easiest solution, but some situations require the use of xloc.bar_time . We introduce `timeFrom()` to assist in calculating time-based offsets. The function calculates a timestamp using a negative (into the past) or positive (into the future) offset from the current bar's starting or closing time, or from the current time of day. The offset can be expressed in units of chart timeframe, or in seconds, minutes, hours, days, months or years. This function was ported from our Time Offset Calculation Framework . `formattedNoOfPeriods()` and `secondsToTfString()` Our final two offerings aim to confront two remaining issues: How much time is represented in a given timestamp? How can I produce a "simple string" timeframe usable with request.security() from a timeframe expressed in seconds? `formattedNoOfPeriods()` converts a time value in ​ms to a quantity of time units. This is useful for calculating a difference in time between 2 points and converting to a desired number of units of time. If no unit is supplied, the function automatically chooses a unit based on a predetermined time step. `secondsToTfString()` converts an input time in seconds to a target timeframe string in timeframe.period string format. This is useful for implementing stepped timeframes relative to the chart time, or calculating multiples of a given chart timeframe. Results from this function are in simple form, which means they are useable as `timeframe` arguments in functions like request.security() . █   NOTES Although the example code is commented in detail, the size of the library justifies some further explanation as many concepts are demonstrated. Key points are as follows:  • ​Pivot points are used to draw lines from. `timeFrom( )` calculates the length of the lines in the specified unit of time.   By default the script uses 20 units of the charts timeframe. Example: a 1hr chart has arrows 20 hours in length.  • At the point of the arrows `formattedNoOfPeriods()` calculates the line length in the specified unit of time from the input menu.   If “Use Input Time” is disabled, a unit of time is automatically assigned.  • At each ​pivot point a label with a formatted date or time is placed with one of the three formatting helper functions to display the time or date the ​pivot occurred.  • A label on the last bar showcases `secondsSince()` . The label goes through three stages of detection for a timed alert.   If the difference between the high and the open in ticks exceeds the input value, a timer starts and will turn the label red once the input time is exceeded to simulate a time-delayed alert.  • In the bottom right of the screen `secondsToTfString()` posts the chart timeframe in a table. This can be multiplied from the input menu. Look first. Then leap. █   FUNCTIONS formattedTime(timeInMs, format)   Converts a UNIX timestamp (in milliseconds) to a formatted time string.   Parameters:      timeInMs : (series float) Timestamp to be formatted.      format : (series string) Format for the time. Optional. The default value is "HH:mm:ss".   Returns: (string) A string containing the formatted time. formattedDate(timeInMs, format)   Converts a UNIX timestamp (in milliseconds) to a formatted date string.   Parameters:      timeInMs : (series float) Timestamp to be formatted.      format : (series string) Format for the date. Optional. The default value is "yyyy-MM-dd".   Returns: (string) A string containing the formatted date. formattedDay(timeInMs, format)   Converts a UNIX timestamp (in milliseconds) to the name of the day of the week.   Parameters:      timeInMs : (series float) Timestamp to be formatted.      format : (series string) Format for the day of the week. Optional. The default value is "EEEE" (complete day name).   Returns: (string) A string containing the day of the week. secondsSince(cond, resetCond)   The duration in milliseconds that a condition has been true.   Parameters:      cond : (series bool) Condition to time.      resetCond : (series bool) When `true`, the duration resets.   Returns: The duration in seconds for which `cond` is continuously true. timeFrom(from, qty, units)   Calculates a +/- time offset in variable units from the current bar's time or from the current time.   Parameters:      from : (series string) Starting time from where the offset is calculated: "bar" to start from the bar's starting time, "close" to start from the bar's closing time, "now" to start from the current time.      qty : (series int) The +/- qty of units of offset required. A "series float" can be used but it will be cast to a "series int".      units : (series string) String containing one of the seven allowed time units: "chart" (chart's timeframe), "seconds", "minutes", "hours", "days", "months", "years".   Returns: (int) The resultant time offset `from` the `qty` of time in the specified `units`. formattedNoOfPeriods(​ms, unit)   Converts a time value in ​ms to a quantity of time units.   Parameters:      ms : (series int) Value of time to be formatted.      unit : (series string) The target unit of time measurement. Options are "seconds", "minutes", "hours", "days", "weeks", "months". If not used one will be automatically assigned.   Returns: (string) A formatted string from the number of `ms` in the specified `unit` of time measurement secondsToTfString(tfInSeconds, mult)   Convert an input time in seconds to target string TF in `timeframe.period` string format.   Parameters:      tfInSeconds : (simple int) a timeframe in seconds to convert to a string.      mult : (simple float) Multiple of `tfInSeconds` to be calculated. Optional. 1 (no multiplier) is default.   Returns: (string) The `tfInSeconds` in `timeframe.period` format usable with `request.security()`.
Bibliothèque Pine Script®
par PineCoders
35
Runners & Laggers (scanner)Firstly, seems to me this may only work with crypto but I know nothing about the other sectors so i could be wrong. I was trying to think up a good way to find moving coins(other than by volume bc theres holes in the results when using it this way). Thought this was an interesting concept so decided to publish it as I've seen no others like it (though i did not extensively search for it. We need to start with a little Tradingview(TV) common knowledge. When there is no update of trades/volume in a candle TV does not print the candle. So when looking at (let's say) a 1 second chart, if the coin being observed by the user has no update from a trade in the time of that 1 sec candle it is skipped over. This means that a coin with a ton of volume might fill an entire 60 seconds with 60 candles and conversely with a low volume coin there could be as little as 0 1-second candles. BUT even for normally low volume coins, when a pump is beginning with the coin it could literally go from 0 1-second candles within a minute to 60 1-second candles within the next minute. ***NOTE: This DOES NOT show ANY information if the coin is going up or down but rather that a LOT more trading volume is occurring than normal.*** What this script does is scans (via request.security feature) up to 40 coins at a time and counts how many candles are printed within a user set timespan calculated in minute. 1 candle print per incremented timeframe that the chart is on. ie. if the chart is a 1 min chart it counts how many 1 min candles are printed. So, (as is in the captured image for the script) if you wanted to count how many 5 second candles are printed for each coin in 1 min then you would have to put the charts timeframe on 5sec and the setting titled 'Window of TIME(in minutes) to count bars' as 1.0 (which bc it's in minutes 1.0m = 60sec and bc 60s / 5s = 12 there would be 12 possible values that each coin can be at depending on how many bars are counted within that 1min/60sec. *** I will update to show an image of what I'm talking about here. Now, the exchange I'm scanning here is Kucoin's Margin Coins. There are 170 something coins total but I removed a few i didn't care for to make it a round 40 coins per set (there being 4 sets of 40 coins total=160 coins being scanned). To scan all 4 sets the indicator must be added 4 times to the chart and a different 'set' selected for each iteration of the script on the chart. Free users can only scan 3 at the most. All others can scan all 4 sets. In the script you can change the exchange and coins as necessary. If there done so and there are not 40 coins total just put '' '' in the extra coins spots that are not filled and the script will skip over these blankly filled spots. The suffix (traded pair) for the tickerID on all Kucoin's Margin Coin's is USDT so that's what i have inputted in the main function on line 46 (will need to be changed if that differs from the coins you want to scan. Next in the line of settings is 'Window of TIME(in minutes) to count bars' which has already been discussed. Following that is the setting "Table Shows" which the results are all in a table and the table will present the coins that have either "Passed" or "Failed" depending on which you choose. The next setting determines what passes or fails. If there are 12 possible rows for the coins to be in (as described above) then this setting is the "Pass/Fail Cutoff" level. So if you want to show all the coins that are in rows 11 and 12 (as in the image at top) then 11 should be selected here. At this point you will see all the coins that have a lot of volume in them. Finding coin names in the table that are usually not with a ton of volume will present your present movers. NOTE: coins like BTC and ETH will almost always be in these levels so it does not indicate anything different from the norm of these coins. Last setting is the ability to show the table on the main window or not. Hope you enjoy and find use in it. BTW this screener format is the same as the others I have published. If you like, check those out too. If you find difficulty using then refer to those as well as they have additional info in them on how to use the scanner and its format. Lastly, in the script is the ability to print the plots and labels but I commented them out bc its really just a jumbled mess. In the commented out sections there is a Random Color Function (provided by @hewhomustnotbenamed which was developed on the basis of Function-HSL-color by @RicardoSantos. All right, peace brothers....and sisters. **** Also, I see how the "levels" could be confusing so I will put them into a % format soon (probably not today) so that the "Pass/Fail Cutoff" can be in % format so that if "passed" is chosen and 50% is chosen (in the new setting that will be changed) then it'll show you all the coins that have more than 50% of the bars printed within the time window chosen. Goodluck in all your trading adventures. ChasinAlts out.
Indicateur Pine Script®
par A_Traders_Edge
3
[kai]Futility RatioAn indicator that measures movement inefficiency Inefficient movement, that is, the range market becomes a high number, the limit is reached at about 60 and a trend occurs When the range breaks and a trend occurs, the inefficiency drops to about 40 and many trends end. The full-scale trend goes down further and goes down to about 25, which is evaluated as an efficient movement, the limit is reached and the trend ends. As for how to use this Inge, the direction of the trend needs to be considered in other ways. Create a position when you reach 60 Position closed or contrarian at 40 or 25 I assume the usage 動きの非効率性を測定するインジケーターです 非効率な動きをするつまりレンジ相場は高い数字になって、60程度で限界が訪れてトレンドが発生します レンジがブレイクしトレンドが発生すると40程度まで非効率性は下がりって多くのトレンドは終了します 本格的なトレンドはさらに下がっていって効率的な動きと評価される25程度まで下がって限界が訪れてトレンドが終了します このインジの使い方はトレンドの方向は他の方法で考える必要がありますが 60まで上がったときにポジション作成 40又は25でポジションクローズ又は逆張り という使い方を想定しています
Indicateur Pine Script®
par xinolia
1
Multiple Screeners with AlertsI already published few version of my custom screeners. Unfortunately, because of TradingView's security function call limit you can't use more than 40 stocks in 1 screener. Fortunately, you can compute multiple values in your function and screen few indicators at once. In this script I show how you can compute 5 indicators at the same time for 40 instruments. I display then in different labels. Every label consist of list of instruments satisfying current indicator conditions and a value for it. It can be absolute value as for RSI or -1/1 representing Bullish/Bearish event. Also you can create 1 alert with result of all screeners inside. In this example I took 5 indicators with following conditions: RSI - "RSI < 30" or "RSI > 70" TSI - "TSI < -30" or "RSI >30" ADX - "ADX > 40" MACD - "MACD Bullish Cross" or "MACD Bearish Cross" (1 and -1 in screener) AO - "AO Crosses 0 UP" or "AO Crosses 0 DOWN" (1 and -1 in screener) Params - bars_apart - this parameter define how may bars apart you labels are on your chart. If you see labels overlapping, increase this number. - Parameters for all used indicators - 40 symbol inputs for instruments you want to use in this screener Alerts You can create an alert from it easily by selecting screener name from the list and then selecting "Any alert() function call". No additional configuration is required, message and alert on close is generated in the code. You should better change default name for your alert. Sometimes because of big amount of inputs you might receive an error. Disclaimer Please remember that past performance may not be indicative of future results. Due to various factors, including changing market conditions, the strategy may no longer perform as good as in historical backtesting. This post and the script don’t provide any financial advice.
Indicateur Pine Script®
par QuantNomad
53
RSI_SpeedUp_Volume measures the speed of purchases.If the RSI indicator shows the dominance of purchases over sales, it is interesting to know the speed of purchases. We calculate the speed using the wt indicator. We compute WT (RSI,len). Setting and designation of indicator RSI_SpeedUP. The RSI lines you are looking for are shown in smooth lines. The speed is shown by stepped lines. In the indicator RSI and speed are calculated in two ways. The first method-calculations are made from the closing price. The second way is from the volume price. Volume price is the closing price multiplied by volume. Basic settings of the RSI_SpeedUp-V indicator (1,24,9,40,14). What they mean? RSI is calculated for two periods 24 and 9. The first parameter in the setting is "1", that the display of lines will be from the first period = 24. If the parameter is "2", the lines will be displayed from the second period = 9. If the parameter is "3", the display will be simultaneously from both periods. The fourth parameter " 40 " shows the width of the green and pink areas. The fifth parameter " 14 " is the period with which the wt rate is calculated(rsi,14). By default, the indicator window displays only the rates from the simple price and the volume price. In order to enable the display of RSI lines, press the "vkl RSI"button. The blue line is RSI (close). Blue line-RSI (close*volume). Stepped green-speed from simple price wt(rsi (close)). Step brown line-speed from the volume price wt(rsi (close*volume)). How to use. The volume price starts to react to the trend change earlier. Long before the reversal, it changes its direction. Comparison with the simple price speed line gives additional information about the market mood. Good luck with your trading. -------------------------- Если индикатор RSI показывает доминирование покупок над продажами, то интересно знать скорость покупок. Скорость мы вычисляем с помощью индикатора WT. Мы вычисляем WT ( RSI,len). Настройки и обозначения индикатора RSI_SpeedUP. Искомые линии RSI показаны гладкими линиями. Скорость показана ступенчатыми линиями. В индикаторе RSI и скорость вычисляются двумя способами. Первый способ - вычисления производятся от цены закрытия. Второй способ от объемной цены. Объемная цена это цена закрытия умноженная на объем. Базовые настройки индикатора RSI_SpeedUp-V (1,24,9,40,14). Что они означают? RSI вычисляется для двух периодов 24 и 9. Первый параметр в настройке "1" , что отображение линий будет от первого периода = 24. Если параметр "2", то отображение линий будет от второго периода = 9. Если параметр "3", то отображение будет одновременно от обоих периодов. Четвертый параметр "40" показывает ширину области зеленой и розовой. Пятый параметр "14" это период с которым вычисляется скорость wt(rsi,14). По умолчанию в окне индикатора отображаются только скорости от простой цены и от объемной цены. Для того чтобы включить отображение линий RSI надо нажать кнопочку "vkl RSI". Синяя линия - RSI (close). Голубая линия - RSI (close*volume). Ступенчатая зеленая - скорость от простой цены wt(rsi(close)). Ступенчатая коричневая линия - скорость от объемной цены wt(rsi(close*volume)). Как пользоваться. Объемная цена раньше начинает реагировать на изменение тенденции. Задолго до разворота она изменяет своё направление. Сравнение с линией скорости простой цены дает дополнительную информацию о настроении рынка. Успехов Вам в торговле.
Indicateur Pine Script®
par wozdux
2
Aroon Single Line This indicator converts double lined Aroon indicator into a single line oscillator. It is simply obtained by subtracting Aroon down from Aroon Up. *If Oscillator points 100 value, it means there is a Strong Uptrend. *If Oscillator points values between 100 and 40, it means there is an uptrend. *If Oscillator points values between 20 and -20, it means no trend, it is sideways.But, when it is sideways; generally, oscillator makes FLAT LINES between 20 and -20 values. 0 value is pointed out when the trend is downward as well, which means aroon up=aroon down. *If Oscillator points values between -40 and -100, it means there is a downtrend. *If Oscillator points -100 value, it means there is a Strong downtrend. (20, 40) and (-20, -40) intervals are not mentioned, because; generally these are transition values and hard to comment, it will be more certain to wait till values are between or at the reference values given.
Indicateur Pine Script®
par gknpytr22
4
Confluence Engine Confluence Engine is a practical, non-repainting decision aid that scores market conditions from −100…+100 by combining six proven modules: Trend, Momentum, Volatility, Volume, Structure, and an HTF confirmation. It’s designed for crypto, forex, indices, and stocks, and it fires entries only on confirmed bar closes. What’s inside Trend: EMA 20/50/200 alignment plus a Supertrend/KAMA toggle (you choose the baseline). Momentum: RSI + MACD with confirmed-pivot divergence detection. Volatility: ATR% and Bollinger Band width vs its average to favor expansion over chop. Volume: OBV-style cumulative flow slope + volume surge vs SMA×multiplier. Market Structure: Confirmed pivots, BOS (break of structure) and CHOCH (change of character). HTF Filter: Closed higher-timeframe context via request.security(..., barmerge.gaps_on, barmerge.lookahead_off). Why it does not repaint Signals are computed and plotted on closed bars only. Pivots/divergences use confirmed pivot points (no forward look). HTF series are fetched with lookahead_off and use the last closed HTF bar in realtime. No future bar references are used for entries or alerts. How to use (3 steps) Pick a timeframe pair: use a 4–6× HTF multiplier (5m→30m, 15m→1h, 1h→4h, 4h→1D, 1D→1W). Trade with the HTF: take longs only when the HTF filter is bullish; shorts only when bearish. Prefer expansion: act when BB width > its average and ATR% is elevated; skip most signals in compression. Suggested presets (start here) Crypto (BTC/ETH): 15m→1h, 1h→4h. stLen=10, stMult=3.0, bbLen=20, surgeMul=1.8–2.2, thresholds +40 / −40 (intraday can try +35 / −35). Forex majors: 15m→1h, 1h→4h. stLen=10–14, stMult=2.5–3.0, surgeMul=1.5–1.8, thresholds +35 / −35 (swing: +45 / −45). US equities (liquid): 5m→30m/1h, 15m→1h/2h. stMult=3.0–3.5, surgeMul=1.6–2.0, thresholds +45 / −45 to reduce chop. Indices (ES/NQ): 5m→30m, 15m→1h. Defaults are fine; start at +40 / −40. Gold/Oil: 15m→1h, 1h→4h. Thresholds +35 / −35, surgeMul=1.6–1.9. Inputs (plain English) Use Supertrend (off = KAMA): choose the trend baseline. EMA Fast/Mid/Slow: 20/50/200 by default for classic stack. RSI/MACD + divergence pivots: momentum and exhaustion context. ATR Length & BB Length: volatility regime detection. Volume SMA & Surge Multiplier: defines “meaningful” volume spikes. Pivot left/right & “Confirm BOS/CHOCH on Close”: structure strictness. Enable HTF & Higher Timeframe: confirms the lower timeframe direction. Thresholds (+long / −short): when the score crosses these, you get signals. Signals & alerts (IDs preserved) Entry shapes plot at bar close when the score crosses thresholds. Alerts you can enable: CONFLUENCE LONG — long entry signal CONFLUENCE SHORT — short entry signal BULLISH BIAS — score turned positive BEARISH BIAS — score turned negative Best practices Focus on signals with HTF agreement and volatility expansion; require volume participation (surge or rising OBV slope) for higher quality. Raise thresholds (+45/−45 or +50/−50) to reduce whipsaws in choppy sessions. Lower thresholds (+35/−35) only if you also require volatility/volume filters. Performance & scope Works across crypto/FX/equities/indices; no broker data or special feeds required. No repainting by design; signals/alerts are computed on closed bars. As with any tool, results vary by regime; always combine with risk management. Disclosure This script is for educational purposes only and is not financial advice. Trading involves risk. Test on historical data and paper trade before using live.
Indicateur Pine Script®
par Finntech1
1
ADX MTF mura visionOverview ADX MTF — mura vision measures trend strength and visualizes a higher-timeframe (HTF) ADX on any chart. The current-TF ADX is drawn as a line; the HTF ADX is rendered as “step” segments to reflect closed HTF bars without repainting. Optional soft fills highlight the 20–25 (trend forming) and 40–50 (strong trend) zones. How it works ADX (current TF) : Classic Wilder formulation using DI components and RMA smoothing. HTF ADX : Requested via request.security(..., lookahead_off, gaps_off). When a new HTF bar opens, the previous value is frozen as a horizontal segment. The current HTF bar is shown as a live moving segment. This staircase look is expected on lower timeframes. Auto timeframe mapping If “Auto” is selected, the HTF is derived from the chart TF: <30m → 60m, 30–<240m → 240m, 240m–<1D → 1D, 1D → 1W, 1W/2W → 1M, ≥1M → same. Inputs DI Length and ADX Smoothing — core ADX parameters. Higher Time Frame — Auto or a fixed TF. Line colors/widths for current ADX and HTF ADX. Fill zone 20–25 and Fill zone 40–50 — optional light background fills. Number of HTF ADX Bars — limits stored HTF segments to control chart load. Reading the indicator ADX < 20: typically range-bound conditions; trend setups require extra caution. 20–25: trend emergence; breakouts and continuation structures gain validity. 40–50: strong trend; favor continuation and manage with trailing stops. >60 and turning down: possible trend exhaustion or transition toward range. Note: ADX measures strength, not direction. Combine with your directional filter (e.g., price vs. MA, +DI/−DI, structure/levels). Non-repainting behavior HTF values use lookahead_off; closed HTF bars are never revised. The only moving piece is the live segment for the current HTF bar. Best practices Use HTF ADX as a regime filter; time entries with the current-TF ADX rising through your threshold. Pair with ATR-based stops and a MA/structure filter for direction. Consider higher thresholds on highly volatile altcoins. Performance notes The script draws line segments for HTF bars. If your chart becomes heavy, reduce “Number of HTF ADX Bars.” Disclaimer This script is for educational purposes only and does not constitute financial advice. Trading involves risk.
Indicateur Pine Script®
par trading_mura
Martingale Strategy Simulator [BackQuant]Martingale Strategy Simulator Purpose This indicator lets you study how a martingale-style position sizing rule interacts with a simple long or short trading signal. It computes an equity curve from bar-to-bar returns, adapts position size after losing streaks, caps exposure at a user limit, and summarizes risk with portfolio metrics. An optional Monte Carlo module projects possible future equity paths from your realized daily returns. What a martingale is A martingale sizing rule increases stake after losses and resets after a win. In its classical form from gambling, you double the bet after each loss so that a single win recovers all prior losses plus one unit of profit. In markets there is no fixed “even-money” payout and returns are multiplicative, so an exact recovery guarantee does not exist. The core idea is unchanged: Lose one leg → increase next position size Lose again → increase again Win → reset to the base size The expectation of your strategy still depends on the signal’s edge. Sizing does not create positive expectancy on its own. A martingale raises variance and tail risk by concentrating more capital as a losing streak develops. What it plots Equity – simulated portfolio equity including compounding Buy & Hold – equity from holding the chart symbol for context Optional helpers – last trade outcome, current streak length, current allocation fraction Optional diagnostics – daily portfolio return, rolling drawdown, metrics table Optional Monte Carlo probability cone – p5, p16, p50, p84, p95 aggregate bands Model assumptions Bar-close execution with no slippage or commissions Shorting allowed and frictionless No margin interest, borrow fees, or position limits No intrabar moves or gaps within a bar (returns are close-to-close) Sizing applies to equity fraction only and is capped by your setting All results are hypothetical and for education only. How the simulator applies it 1) Directional signal You pick a simple directional rule that produces +1 for long or −1 for short each bar. Options include 100 HMA slope, RSI above or below 50, EMA or SMA crosses, CCI and other oscillators, ATR move, BB basis, and more. The stance is evaluated bar by bar. When the stance flips, the current trade ends and the next one starts. 2) Sizing after losses and wins Position size is a fraction of equity: Initial allocation – the starting fraction, for example 0.15 means 15 percent of equity Increase after loss – multiply the next allocation by your factor after a losing leg, for example 2.00 to double Reset after win – return to the initial allocation Max allocation cap – hard ceiling to prevent runaway growth At a high level the size after k consecutive losses is alloc(k) = min( cap , base × factor^k ) . In practice the simulator changes size only when a leg ends and its PnL is known. 3) Equity update Let r_t = close_t / close_{t-1} − 1 be the symbol’s bar return, d_{t−1} ∈ {+1, −1} the prior bar stance, and a_{t−1} the prior bar allocation fraction. The simulator compounds: eq_t = eq_{t−1} × (1 + a_{t−1} × d_{t−1} × r_t) . This is bar-based and avoids intrabar lookahead. Costs, slippage, and borrowing costs are not modeled. Why traders experiment with martingale sizing Mean-reversion contexts – if the signal often snaps back after a string of losses, adding size near the tail of a move can pull the average entry closer to the turn Behavioral or microstructure edges – some rules have modest edge but frequent small whipsaws; size escalation may shorten time-to-recovery when the edge manifests Exploration and stress testing – studying the relationship between streaks, caps, and drawdowns is instructive even if you do not deploy martingale sizing live Why martingale is dangerous Martingale concentrates capital when the strategy is performing worst. The main risks are structural, not cosmetic: Loss streaks are inevitable – even with a 55 percent win rate you should expect multi-loss runs. The probability of at least one k-loss streak in N trades rises quickly with N. Size explodes geometrically – with factor 2.0 and base 10 percent, the sequence is 10, 20, 40, 80, 100 (capped) after five losses. Without a strict cap, required size becomes infeasible. No fixed payout – in gambling, one win at even odds resets PnL. In markets, there is no guaranteed bounce nor fixed profit multiple. Trends can extend and gaps can skip levels. Correlation of losses – losses cluster in trends and in volatility bursts. A martingale tends to be largest just when volatility is highest. Margin and liquidity constraints – leverage limits, margin calls, position limits, and widening spreads can force liquidation before a mean reversion occurs. Fat tails and regime shifts – assumptions of independent, Gaussian returns can understate tail risk. Structural breaks can keep the signal wrong for much longer than expected. The simulator exposes these dynamics in the equity curve, Max Drawdown, VaR and CVaR, and via Monte Carlo sketches of forward uncertainty. Interpreting losing streaks with numbers A rough intuition: if your per-trade win probability is p and loss probability is q=1−p , the chance of a specific run of k consecutive losses is q^k . Over many trades, the chance that at least one k-loss run occurs grows with the number of opportunities. As a sanity check: If p=0.55 , then q=0.45 . A 6-loss run has probability q^6 ≈ 0.008 on any six-trade window. Across hundreds of trades, a 6 to 8-loss run is not rare. If your size factor is 1.5 and your base is 10 percent, after 8 losses the requested size is 10% × 1.5^8 ≈ 25.6% . With factor 2.0 it would try to be 10% × 2^8 = 256% but your cap will stop it. The equity curve will still wear the compounded drawdown from the sequence that led to the cap. This is why the cap setting is central. It does not remove tail risk, but it prevents the sizing rule from demanding impossible positions Note: The p and q math is illustrative. In live data the win rate and distribution can drift over time, so real streaks can be longer or shorter than the simple q^k intuition suggests.. Using the simulator productively Parameter studies Start with conservative settings. Increase one element at a time and watch how the equity, Max Drawdown, and CVaR respond. Initial allocation – lower base reduces volatility and drawdowns across the board Increase factor – set modestly above 1.0 if you want the effect at all; doubling is aggressive Max cap – the most important brake; many users keep it between 20 and 50 percent Signal selection Keep sizing fixed and rotate signals to see how streak patterns differ. Trend-following signals tend to produce long wrong-way streaks in choppy ranges. Mean-reversion signals do the opposite. Martingale sizing interacts very differently with each. Diagnostics to watch Use the built-in metrics to quantify risk: Max Drawdown – worst peak-to-trough equity loss Sharpe and Sortino – volatility and downside-adjusted return VaR 95 percent and CVaR – tail risk measures from the realized distribution Alpha and Beta – relationship to your chosen benchmark If you would like to check out the original performance metrics script with multiple assets with a better explanation on all metrics please see Monte Carlo exploration When enabled, the forecast draws many synthetic paths from your realized daily returns: Choose a horizon and a number of runs Review the bands: p5 to p95 for a wide risk envelope; p16 to p84 for a narrower range; p50 as the median path Use the table to read the expected return over the horizon and the tail outcomes Remember it is a sketch based on your recent distribution, not a predictor Concrete examples Example A: Modest martingale Base 10 percent, factor 1.25, cap 40 percent, RSI>50 signal. You will see small escalations on 2 to 4 loss runs and frequent resets. The equity curve usually remains smooth unless the signal enters a prolonged wrong-way regime. Max DD may rise moderately versus fixed sizing. Example B: Aggressive martingale Base 15 percent, factor 2.0, cap 60 percent, EMA cross signal. The curve can look stellar during favorable regimes, then a single extended streak pushes allocation to the cap, and a few more losses drive deep drawdown. CVaR and Max DD jump sharply. This is a textbook case of high tail risk. Strengths Bar-by-bar, transparent computation of equity from stance and size Explicit handling of wins, losses, streaks, and caps Portable signal inputs so you can A–B test ideas quickly Risk diagnostics and forward uncertainty visualization in one place Example, Rolling Max Drawdown Limitations and important notes Martingale sizing can escalate drawdowns rapidly. The cap limits position size but not the possibility of extended adverse runs. No commissions, slippage, margin interest, borrow costs, or liquidity limits are modeled. Signals are evaluated on closes. Real execution and fills will differ. Monte Carlo assumes independent draws from your recent return distribution. Markets often have serial correlation, fat tails, and regime changes. All results are hypothetical. Use this as an educational tool, not a production risk engine. Practical tips Prefer gentle factors such as 1.1 to 1.3. Doubling is usually excessive outside of toy examples. Keep a strict cap. Many users cap between 20 and 40 percent of equity per leg. Stress test with different start dates and subperiods. Long flat or trending regimes are where martingale weaknesses appear. Compare to an anti-martingale (increase after wins, cut after losses) to understand the other side of the trade-off. If you deploy sizing live, add external guardrails such as a daily loss cut, volatility filters, and a global max drawdown stop. Settings recap Backtest start date and initial capital Initial allocation, increase-after-loss factor, max allocation cap Signal source selector Trading days per year and risk-free rate Benchmark symbol for Alpha and Beta UI toggles for equity, buy and hold, labels, metrics, PnL, and drawdown Monte Carlo controls for enable, runs, horizon, and result table Final thoughts A martingale is not a free lunch. It is a way to tilt capital allocation toward losing streaks. If the signal has a real edge and mean reversion is common, careful and capped escalation can reduce time-to-recovery. If the signal lacks edge or regimes shift, the same rule can magnify losses at the worst possible moment. This simulator makes those trade-offs visible so you can calibrate parameters, understand tail risk, and decide whether the approach belongs anywhere in your research workflow.
Indicateur Pine Script®
par BackQuant
Top Crypto Above 28-Day AverageDescription The “Top Crypto Above 28-Day Average” (CRYPTOTW) script scans a selectable universe of up to 120 top-capitalization cryptocurrencies (divided into customizable 40-symbol batches), then plots the count of those trading above their own 28-period simple moving average. It helps you gauge broad market strength and identify which tokens are showing momentum relative to their recent trend. Key Features • Batch Selection: Choose among “Top40,” “Mid40,” or “Low40” market-cap groups, or set a custom batch size (up to 40 symbols) to keep within the API limit. • Dynamic Plot: Displays a live line chart of how many cryptos are above their 28-day MA on each bar. • Reference Lines: Automatic horizontal lines at 25%, 50%, and 75% of your batch to provide quick visual thresholds. • Background Coloration: The chart background shifts green/yellow/red based on whether more than 70%, 50–70%, or under 50% of the batch is above the MA. • Optional Table: On the final bar, show a sortable table of up to 28 tickers currently above their 28-day MA, including current price, percent above MA, and “Above” status color-coding. • Alerts: • Strong Batch Performance: Fires when >70% of the batch is above the MA. • Weak Batch Performance: Fires when <10 cryptos (i.e. <25%) are above the MA. Inputs • Show Results Table (show_table): Toggle the detailed table on/off. • Table Position (table_position): Select one of the four corners for your table overlay. • Max Cryptos to Display (max_display): Limit the number of rows in the results table. • Current Batch (current_batch): Pick “Top40,” “Mid40,” or “Low40.” • Batch Size (batch_size): Define the number of symbols (1–40) you want to include from the chosen batch. How to Use 1. Add the CRYPTOTW indicator to any chart. 2. Select your batch and size to focus on the segment of the crypto market you follow. 3. Watch the plotted line to see the proportion of tokens with bullish momentum. 4. (Optional) Enable the results table to see exactly which tokens are outperforming their 28-day average. 5. Set alerts to be notified when the batch either overheats (strong performance) or cools off significantly. Why It Matters By tracking the share of assets riding their 28-day trend, you gain a macro-level view of market breadth—crucial for spotting emerging rallies or early signs of broad weakness. Whether you’re swing-trading individual altcoins or assessing overall market mood, this tool distills complex data into an intuitive, actionable signal.
Indicateur Pine Script®
par Tin2100
Momentum Trail Oscillator [AlgoAlpha]🟠 OVERVIEW This script builds a Momentum Trail Oscillator designed to measure directional momentum strength and dynamically track shifts in trend bias using a combination of smoothed price change calculations and adaptive trailing bands. The oscillator aims to help traders visualize when momentum is expanding or contracting and to identify transitions between bullish and bearish conditions. 🟠 CONCEPTS The core idea combines two methods. First, the script calculates a normalized momentum measure by smoothing price changes relative to their absolute values, which creates a bounded oscillator that highlights whether moves are directional or choppy. Second, it uses a trailing band mechanism inspired by volatility stops, where bands adapt to the oscillator’s volatility, adjusting the thresholds that define a shift in directional bias. This dual approach seeks to address both the magnitude and persistence of momentum, reducing false signals in ranging markets. 🟠 FEATURES The momentum calculation applies Hull Moving Averages and double EMA smoothing to price changes, producing a smooth, responsive oscillator. The trailing bands are derived by offsetting a weighted moving average of the oscillator by a multiple of recent momentum volatility. A directional state variable tracks whether the oscillator is above or below the bands, updating when the momentum crosses these dynamic thresholds. Overbought and oversold zones are visually marked between fixed levels (+30/+40 and -30/-40), with color fills to highlight when momentum is in extreme areas. The script plots signals on both the oscillator pane and optionally overlays markers on the main price chart for clarity. 🟠 USAGE To use the indicator, apply it to any symbol and timeframe. The “Oscillator Length” controls how sensitive the momentum line is to recent price changes—lower values react faster, higher values smooth out noise. The “Trail Multiplier” sets how far the adaptive bands sit from the oscillator mid-line, which affects how often trend state changes occur. When the momentum line rises into the upper filled area and then crosses back below +40, it signals potential overbought exhaustion. The opposite applies for the oversold zone below -40. The plotted trailing bands switch visibility depending on the current directional state: when momentum is trending up, the lower band acts as the active trailing stop, and when trending down, the upper band becomes active. Trend changes are marked with circular symbols when the direction variable flips, and optional overlay arrows appear on the price chart to highlight overbought or oversold reversals. Traders can combine these signals with their own price action or volume analysis to confirm entries or exits.
Indicateur Pine Script®
par AlgoAlpha
9
Market Matrix ViewThis technical indicator is designed to provide traders with a quick and integrated view of market dynamics by combining several popular indicators into a single tool. It's not a magic bullet, but a practical aid for analyzing buying/selling pressure, trends, volume, and divergences, saving you time in the decision-making process. Built for flexibility, the indicator adapts to various trading styles (scalping, swing, or long-term) and offers customizable settings to suit your needs. 🟡 Multi-Timeframe Trends ➤ This section displays the trend direction (bullish, bearish, or neutral) across 15-minute, 1-hour, 4-hour, and Daily timeframes, providing multi-timeframe market context. Timeframes lower than the one currently selected will show "N/A." ➤It utilizes fast and slow Exponential Moving Averages (EMAs) for each timeframe: 15m: Fast EMA 42, Slow EMA 170 1h: Fast EMA 40, Slow EMA 100 4h: Fast EMA 36, Slow EMA 107 Daily: Fast EMA 20, Slow EMA 60 🟡 Smart Flow & RVOL ➤ This section displays "Buying Pressure" or "Selling Pressure" signals based on indicator confluence, alongside volume activity ("High Activity," "Normal Activity," or "Low Activity"). ➤ Smart Flow combines Chaikin Money Flow (CMF) and Money Flow Index (MFI) to detect buying/selling pressure. CMF measures money flow based on price position within the high-low range, while MFI analyzes money flow considering typical price and volume. A signal is generated only when both indicators simultaneously increase/decrease beyond an adjustable threshold ("Buy/Sell Sensitivity") and volume exceeds a Simple Moving Average (SMA) scaled by the "Volume Multiplier." ➤ RVOL (Relative Volume) calculates relative volume separately for bullish and bearish candles, comparing recent volume (fast SMA) with a reference volume (slow SMA). Thresholds are adjusted based on the selected mode. 🟡 ADX & RSI This section displays trend strength ("Strong," "Moderate," or "Weak"), its direction ("Bullish" or "Bearish"), and the RSI momentum status ("Overbought," "Oversold," "Buy/Sell Momentum," or "Neutral"). ➤ ADX (Average Directional Index) measures trend strength (above 40 = "Strong," 20–40 = "Moderate," below 20 = "Weak"). Direction is determined by comparing +DI (upward movement) with -DI (downward movement). Additionally, an arrow indicates whether the trend's strength is decreasing or increasing. ➤RSI (Relative Strength Index) evaluates price momentum. Extreme levels (above 80/85 = "Overbought," below 15/20 = "Oversold") and intermediate zones (47–53 = "Neutral," above 53 = "Buy Momentum," below 47 = "Sell Momentum") are adjusted based on the selected mode. 🟡 When these signals are active for a potential trade setup, the table's background lights up green or red, respectively. 🟡 Volume Spikes ➤This feature highlights bars with significantly higher volume than the recent average, coloring them yellow on the chart to draw attention to intense market activity. ➤It uses the Z-Score method to detect volume anomalies. Current volume is compared to a 10-bar Simple Moving Average (SMA) and the standard deviation of volume over the same period. If the Z-Score exceeds a certain threshold, the bar is marked as a volume spike. 🟡 Divergences (Volume Divergence Detection) ➤ This feature marks divergences between price and technical indicators on the chart, using diamond-shaped labels (green for bullish divergences, red for bearish divergences) to signal potential trend reversals. ➤ It compares price deviations from a Simple Moving Average (SMA) with deviations of three indicators: Chaikin Money Flow (CMF), Money Flow Index (MFI), and On-Balance Volume (OBV). A bullish divergence occurs when price falls below its average, but CMF, MFI, and OBV rise above their averages, indicating hidden accumulation. A bearish divergence occurs when price rises above its average, but CMF, MFI, and OBV fall, suggesting distribution. The length of the moving averages is adjustable (default 13/10/5 bars for Scalping/Balanced/Swing), and detection thresholds are scaled by "Divergence Sensitivity" (default 1.0). 🟡 Adaptive Stop-Loss (ATR) ➤Draws dynamic stop-loss lines (red, dashed) on the chart for buy or sell signals, helping traders manage risk.Uses the Average True Range (ATR) to calculate stop-loss levels, set at low/high ± ATR × multiplier 🟡 Alerts for trend direction changes in the Info Panel: ➤ Triggers notifications when the trend shifts to Bullish (when +DI crosses above -DI) or Bearish (when +DI crosses below -DI), helping you stay informed about key market shifts. How to use: Set alerts in Trading View for “Trend Changed to Bullish” or “Trend Changed to Bearish” with “Once Per Bar Close” for reliable signals. 🟡 Settings (Inputs) ➤ The indicator offers customizable settings to fit your trading style, but it's already optimized for Scalping (1m–15m), Balanced (16m–3h59m), and Swing (4h–Daily) modes, which automatically adjust based on the selected timeframe. The visible inputs allow you to adjust the following parameters: Show Info Panel: Enables/disables the information panel (default: enabled). Show Volume Spikes: Turns on/off coloring for volume spike bars (default: enabled). Spike Sensitivity: Controls the Z-Score threshold for detecting volume spikes (default: 2.0; lower values increase signal frequency). Show Divergence: Enables/disables the display of divergence labels (default: enabled). Divergence Sensitivity: Adjusts the thresholds for divergence detection (default: 1.0; higher values reduce sensitivity). Divergence Lookback Length: Sets the length of the moving averages used for divergences (default: 5, automatically adjusted to 13/10/5 for Scalping/Balanced/Swing). RVOL Reference Period: Defines the reference period for relative volume (default: 20, automatically adjusted to 7/15/20). RSI Length: Sets the RSI length (default: 14, automatically adjusted to 5/10/14). Buy Sensitivity: Controls the increase threshold for Buying Pressure signals (default: 0.007; higher values reduce frequency). Sell Sensitivity: Controls the decrease threshold for Selling Pressure signals (default: 0.007; higher values reduce frequency). Volume Multiplier (B/S Pressure): Adjusts the volume threshold for Smart Flow signals (default: 0.6; higher values require greater volume). 🟡 This indicator is created to simplify market analysis, but I am not a professional in Pine Script or technical indicators. This indicator is not a standalone solution. For optimal results, it must be integrated into a well-defined trading strategy that includes risk management and other confirmations.
Indicateur Pine Script®
par ToCoMi
Langlands-Operadic Möbius Vortex (LOMV)Langlands-Operadic Möbius Vortex (LOMV) Where Pure Mathematics Meets Market Reality A Revolutionary Synthesis of Number Theory, Category Theory, and Market Dynamics 🎓 THEORETICAL FOUNDATION The Langlands-Operadic Möbius Vortex represents a groundbreaking fusion of three profound mathematical frameworks that have never before been combined for market analysis: The Langlands Program: Harmonic Analysis in Markets Developed by Robert Langlands (Fields Medal recipient), the Langlands Program creates bridges between number theory, algebraic geometry, and harmonic analysis. In our indicator: L-Function Implementation: - Utilizes the Möbius function μ(n) for weighted price analysis - Applies Riemann zeta function convergence principles - Calculates quantum harmonic resonance between -2 and +2 - Measures deep mathematical patterns invisible to traditional analysis The L-Function core calculation employs: L_sum = Σ(return_val × μ(n) × n^(-s)) Where s is the critical strip parameter (0.5-2.5), controlling mathematical precision and signal smoothness. Operadic Composition Theory: Multi-Strategy Democracy Category theory and operads provide the mathematical framework for composing multiple trading strategies into a unified signal. This isn't simple averaging - it's mathematical composition using: Strategy Composition Arity (2-5 strategies): - Momentum analysis via RSI transformation - Mean reversion through Bollinger Band mathematics - Order Flow Polarity Index (revolutionary T3-smoothed volume analysis) - Trend detection using Directional Movement - Higher timeframe momentum confirmation Agreement Threshold System: Democratic voting where strategies must reach consensus before signal generation. This prevents false signals during market uncertainty. Möbius Function: Number Theory in Action The Möbius function μ(n) forms the mathematical backbone: - μ(n) = 1 if n is a square-free positive integer with even number of prime factors - μ(n) = -1 if n is a square-free positive integer with odd number of prime factors - μ(n) = 0 if n has a squared prime factor This creates oscillating weights that reveal hidden market periodicities and harmonic structures. 🔧 COMPREHENSIVE INPUT SYSTEM Langlands Program Parameters Modular Level N (5-50, default 30): Primary lookback for quantum harmonic analysis. Optimized by timeframe: - Scalping (1-5min): 15-25 - Day Trading (15min-1H): 25-35 - Swing Trading (4H-1D): 35-50 - Asset-specific: Crypto 15-25, Stocks 30-40, Forex 35-45 L-Function Critical Strip (0.5-2.5, default 1.5): Controls Riemann zeta convergence precision: - Higher values: More stable, smoother signals - Lower values: More reactive, catches quick moves - High frequency: 0.8-1.2, Medium: 1.3-1.7, Low: 1.8-2.3 Frobenius Trace Period (5-50, default 21): Galois representation lookback for price-volume correlation: - Measures harmonic relationships in market flows - Scalping: 8-15, Day Trading: 18-25, Swing: 25-40 HTF Multi-Scale Analysis: Higher timeframe context prevents trading against major trends: - Provides market bias and filters signals - Improves win rates by 15-25% through trend alignment Operadic Composition Parameters Strategy Composition Arity (2-5, default 4): Number of algorithms composed for final signal: - Conservative: 4-5 strategies (higher confidence) - Moderate: 3-4 strategies (balanced approach) - Aggressive: 2-3 strategies (more frequent signals) Category Agreement Threshold (2-5, default 3): Democratic voting minimum for signal generation: - Higher agreement: Fewer but higher quality signals - Lower agreement: More signals, potential false positives Swiss-Cheese Mixing (0.1-0.5, default 0.382): Golden ratio φ⁻¹ based blending of trend factors: - 0.382 is φ⁻¹, optimal for natural market fractals - Higher values: Stronger trend following - Lower values: More contrarian signals OFPI Configuration: - OFPI Length (5-30, default 14): Order Flow calculation period - T3 Smoothing (3-10, default 5): Advanced exponential smoothing - T3 Volume Factor (0.5-1.0, default 0.7): Smoothing aggressiveness control Unified Scoring System Component Weights (sum ≈ 1.0): - L-Function Weight (0.1-0.5, default 0.3): Mathematical harmony emphasis - Galois Rank Weight (0.1-0.5, default 0.2): Market structure complexity - Operadic Weight (0.1-0.5, default 0.3): Multi-strategy consensus - Correspondence Weight (0.1-0.5, default 0.2): Theory-practice alignment Signal Threshold (0.5-10.0, default 5.0): Quality filter producing: - 8.0+: EXCEPTIONAL signals only - 6.0-7.9: STRONG signals - 4.0-5.9: MODERATE signals - 2.0-3.9: WEAK signals 🎨 ADVANCED VISUAL SYSTEM Multi-Dimensional Quantum Aura Bands Five-layer resonance field showing market energy: - Colors: Theme-matched gradients (Quantum purple, Holographic cyan, etc.) - Expansion: Dynamic based on score intensity and volatility - Function: Multi-timeframe support/resistance zones Morphism Flow Portals Category theory visualization showing market topology: - Green/Cyan Portals: Bullish mathematical flow - Red/Orange Portals: Bearish mathematical flow - Size/Intensity: Proportional to signal strength - Recursion Depth (1-8): Nested patterns for flow evolution Fractal Grid System Dynamic support/resistance with projected L-Scores: - Multiple Timeframes: 10, 20, 30, 40, 50-period highs/lows - Smart Spacing: Prevents level overlap using ATR-based minimum distance - Projections: Estimated signal scores when price reaches levels - Usage: Precise entry/exit timing with mathematical confirmation Wick Pressure Analysis Rejection level prediction using candle mathematics: - Upper Wicks: Selling pressure zones (purple/red lines) - Lower Wicks: Buying pressure zones (purple/green lines) - Glow Intensity (1-8): Visual emphasis and line reach - Application: Confluence with fractal grid creates high-probability zones Regime Intensity Heatmap Background coloring showing market energy: - Black/Dark: Low activity, range-bound markets - Purple Glow: Building momentum and trend development - Bright Purple: High activity, strong directional moves - Calculation: Combines trend, momentum, volatility, and score intensity Six Professional Themes - Quantum: Purple/violet for general trading and mathematical focus - Holographic: Cyan/magenta optimized for cryptocurrency markets - Crystalline: Blue/turquoise for conservative, stability-focused trading - Plasma: Gold/magenta for high-energy volatility trading - Cosmic Neon: Bright neon colors for maximum visibility and aggressive trading 📊 INSTITUTIONAL-GRADE DASHBOARD Unified AI Score Section - Total Score (-10 to +10): Primary decision metric - >5: Strong bullish signals - <-5: Strong bearish signals - Quality ratings: EXCEPTIONAL > STRONG > MODERATE > WEAK - Component Analysis: Individual L-Function, Galois, Operadic, and Correspondence contributions Order Flow Analysis Revolutionary OFPI integration: - OFPI Value (-100% to +100%): Real buying vs selling pressure - Visual Gauge: Horizontal bar chart showing flow intensity - Momentum Status: SHIFTING, ACCELERATING, STRONG, MODERATE, or WEAK - Trading Application: Flow shifts often precede major moves Signal Performance Tracking - Win Rate Monitoring: Real-time success percentage with emoji indicators - Signal Count: Total signals generated for frequency analysis - Current Position: LONG, SHORT, or NONE with P&L tracking - Volatility Regime: HIGH, MEDIUM, or LOW classification Market Structure Analysis - Möbius Field Strength: Mathematical field oscillation intensity - CHAOTIC: High complexity, use wider stops - STRONG: Active field, normal position sizing - MODERATE: Balanced conditions - WEAK: Low activity, consider smaller positions - HTF Trend: Higher timeframe bias (BULL/BEAR/NEUTRAL) - Strategy Agreement: Multi-algorithm consensus level Position Management When in trades, displays: - Entry Price: Original signal price - Current P&L: Real-time percentage with risk level assessment - Duration: Bars in trade for timing analysis - Risk Level: HIGH/MEDIUM/LOW based on current exposure 🚀 SIGNAL GENERATION LOGIC Balanced Long/Short Architecture The indicator generates signals through multiple convergent pathways: Long Entry Conditions: - Score threshold breach with algorithmic agreement - Strong bullish order flow (OFPI > 0.15) with positive composite signal - Bullish pattern recognition with mathematical confirmation - HTF trend alignment with momentum shifting - Extreme bullish OFPI (>0.3) with any positive score Short Entry Conditions: - Score threshold breach with bearish agreement - Strong bearish order flow (OFPI < -0.15) with negative composite signal - Bearish pattern recognition with mathematical confirmation - HTF trend alignment with momentum shifting - Extreme bearish OFPI (<-0.3) with any negative score Exit Logic: - Score deterioration below continuation threshold - Signal quality degradation - Opposing order flow acceleration - 10-bar minimum between signals prevents overtrading ⚙️ OPTIMIZATION GUIDELINES Asset-Specific Settings Cryptocurrency Trading: - Modular Level: 15-25 (capture volatility) - L-Function Precision: 0.8-1.3 (reactive to price swings) - OFPI Length: 10-20 (fast correlation shifts) - Cascade Levels: 5-7, Theme: Holographic Stock Index Trading: - Modular Level: 25-35 (balanced trending) - L-Function Precision: 1.5-1.8 (stable patterns) - OFPI Length: 14-20 (standard correlation) - Cascade Levels: 4-5, Theme: Quantum Forex Trading: - Modular Level: 35-45 (smooth trends) - L-Function Precision: 1.6-2.1 (high smoothing) - OFPI Length: 18-25 (disable volume amplification) - Cascade Levels: 3-4, Theme: Crystalline Timeframe Optimization Scalping (1-5 minute charts): - Reduce all lookback parameters by 30-40% - Increase L-Function precision for noise reduction - Enable all visual elements for maximum information - Use Small dashboard to save screen space Day Trading (15 minute - 1 hour): - Use default parameters as starting point - Adjust based on market volatility - Normal dashboard provides optimal information density - Focus on OFPI momentum shifts for entries Swing Trading (4 hour - Daily): - Increase lookback parameters by 30-50% - Higher L-Function precision for stability - Large dashboard for comprehensive analysis - Emphasize HTF trend alignment 🏆 ADVANCED TRADING STRATEGIES The Mathematical Confluence Method 1. Wait for Fractal Grid level approach 2. Confirm with projected L-Score > threshold 3. Verify OFPI alignment with direction 4. Enter on portal signal with quality ≥ STRONG 5. Exit on score deterioration or opposing flow The Regime Trading System 1. Monitor Aether Flow background intensity 2. Trade aggressively during bright purple periods 3. Reduce position size during dark periods 4. Use Möbius Field strength for stop placement 5. Align with HTF trend for maximum probability The OFPI Momentum Strategy 1. Watch for momentum shifting detection 2. Confirm with accelerating flow in direction 3. Enter on immediate portal signal 4. Scale out at Fibonacci levels 5. Exit on flow deceleration or reversal ⚠️ RISK MANAGEMENT INTEGRATION Mathematical Position Sizing - Use Galois Rank for volatility-adjusted sizing - Möbius Field strength determines stop width - Fractal Dimension guides maximum exposure - OFPI momentum affects entry timing Signal Quality Filtering - Trade only STRONG or EXCEPTIONAL quality signals - Increase position size with higher agreement levels - Reduce risk during CHAOTIC Möbius field periods - Respect HTF trend alignment for directional bias 🔬 DEVELOPMENT JOURNEY Creating the LOMV was an extraordinary mathematical undertaking that pushed the boundaries of what's possible in technical analysis. This indicator almost didn't happen. The theoretical complexity nearly proved insurmountable. The Mathematical Challenge Implementing the Langlands Program required deep research into: - Number theory and the Möbius function - Riemann zeta function convergence properties - L-function analytical continuation - Galois representations in finite fields The mathematical literature spans decades of pure mathematics research, requiring translation from abstract theory to practical market application. The Computational Complexity Operadic composition theory demanded: - Category theory implementation in Pine Script - Multi-dimensional array management for strategy composition - Real-time democratic voting algorithms - Performance optimization for complex calculations The Integration Breakthrough Bringing together three disparate mathematical frameworks required: - Novel approaches to signal weighting and combination - Revolutionary Order Flow Polarity Index development - Advanced T3 smoothing implementation - Balanced signal generation preventing directional bias Months of intensive research culminated in breakthrough moments when the mathematics finally aligned with market reality. The result is an indicator that reveals market structure invisible to conventional analysis while maintaining practical trading utility. 🎯 PRACTICAL IMPLEMENTATION Getting Started 1. Apply indicator with default settings 2. Select appropriate theme for your markets 3. Observe dashboard metrics during different market conditions 4. Practice signal identification without trading 5. Gradually adjust parameters based on observations Signal Confirmation Process - Never trade on score alone - verify quality rating - Confirm OFPI alignment with intended direction - Check fractal grid level proximity for timing - Ensure Möbius field strength supports position size - Validate against HTF trend for bias confirmation Performance Monitoring - Track win rate in dashboard for strategy assessment - Monitor component contributions for optimization - Adjust threshold based on desired signal frequency - Document performance across different market regimes 🌟 UNIQUE INNOVATIONS 1. First Integration of Langlands Program mathematics with practical trading 2. Revolutionary OFPI with T3 smoothing and momentum detection 3. Operadic Composition using category theory for signal democracy 4. Dynamic Fractal Grid with projected L-Score calculations 5. Multi-Dimensional Visualization through morphism flow portals 6. Regime-Adaptive Background showing market energy intensity 7. Balanced Signal Generation preventing directional bias 8. Professional Dashboard with institutional-grade metrics 📚 EDUCATIONAL VALUE The LOMV serves as both a practical trading tool and an educational gateway to advanced mathematics. Traders gain exposure to: - Pure mathematics applications in markets - Category theory and operadic composition - Number theory through Möbius function implementation - Harmonic analysis via L-function calculations - Advanced signal processing through T3 smoothing ⚖️ RESPONSIBLE USAGE This indicator represents advanced mathematical research applied to market analysis. While the underlying mathematics are rigorously implemented, markets remain inherently unpredictable. Key Principles: - Use as part of comprehensive trading strategy - Implement proper risk management at all times - Backtest thoroughly before live implementation - Understand that past performance does not guarantee future results - Never risk more than you can afford to lose The mathematics reveal deep market structure, but successful trading requires discipline, patience, and sound risk management beyond any indicator. 🔮 CONCLUSION The Langlands-Operadic Möbius Vortex represents a quantum leap forward in technical analysis, bringing PhD-level pure mathematics to practical trading while maintaining visual elegance and usability. From the harmonic analysis of the Langlands Program to the democratic composition of operadic theory, from the number-theoretic precision of the Möbius function to the revolutionary Order Flow Polarity Index, every component works in mathematical harmony to reveal the hidden order within market chaos. This is more than an indicator - it's a mathematical lens that transforms how you see and understand market structure. Trade with mathematical precision. Trade with the LOMV. *"Mathematics is the language with which God has written the universe." - Galileo Galilei* *In markets, as in nature, profound mathematical beauty underlies apparent chaos. The LOMV reveals this hidden order.* — Dskyz, Trade with insight. Trade with anticipation.
Indicateur Pine Script®
par DskyzInvestments
27
Multi-EMA Crossover StrategyMulti-EMA Crossover Strategy This strategy uses multiple exponential moving average (EMA) crossovers to identify bullish trends and execute long trades. The approach involves progressively stronger signals as different EMA pairs cross, indicating increasing bullish momentum. Each crossover triggers a long entry, and the intensity of bullish sentiment is reflected in the color of the bars on the chart. Conversely, bearish trends are represented by red bars. Strategy Logic: First Long Entry: When the 1-day EMA crosses above the 5-day EMA, it signals initial bullish momentum. Second Long Entry: When the 3-day EMA crosses above the 10-day EMA, it confirms stronger bullish sentiment. Third Long Entry: When the 5-day EMA crosses above the 20-day EMA, it indicates further trend strength. Fourth Long Entry: When the 10-day EMA crosses above the 40-day EMA, it suggests robust long-term bullish momentum. The bar colors reflect these conditions: More blue bars indicate stronger bullish sentiment as more short-term EMAs are above their longer-term counterparts. Red bars represent bearish conditions when short-term EMAs are below longer-term ones. Example: Bitcoin Trading on a Daily Timeframe Bullish Scenario: Imagine Bitcoin is trading at $30,000 on March 31, 2025: First Signal: The 1-day EMA crosses above the 5-day EMA at $30,000. This suggests initial upward momentum, prompting a small long entry. Second Signal: A few days later, the 3-day EMA crosses above the 10-day EMA at $31,000. This confirms strengthening bullish sentiment; another long position is added. Third Signal: The 5-day EMA crosses above the 20-day EMA at $32,500, indicating further upward trend development; a third long entry is executed. Fourth Signal: Finally, the 10-day EMA crosses above the 40-day EMA at $34,000. This signals robust long-term bullish momentum; a fourth long position is entered. Bearish Scenario: Suppose Bitcoin reverses from $34,000 to $28,000: The 1-day EMA crosses below the 5-day EMA at $33,500. The 3-day EMA dips below the 10-day EMA at $32,000. The 5-day EMA falls below the 20-day EMA at $30,000. The final bearish signal occurs when the 10-day EMA drops below the 40-day EMA at $28,000. The bars turn increasingly red as bearish conditions strengthen. Advantages of This Strategy: Progressive Confirmation: Multiple crossovers provide layered confirmation of trend strength. Visual Feedback: Bar colors help traders quickly assess market sentiment and adjust positions accordingly. Flexibility: Suitable for trending markets like Bitcoin during strong rallies or downturns. Limitations: Lagging Signals: EMAs are lagging indicators and may react slowly to sudden price changes. False Breakouts: Crossovers in choppy markets can lead to whipsaws or false signals. This strategy works best in trending markets and should be combined with additional risk management techniques, e.g., stop loss or optimal position sizes (Kelly Criterion).
Stratégie Pine Script®
par joll3d
Ensemble Alerts█ OVERVIEW This indicator creates highly customizable alert conditions and messages by combining several technical conditions into groups , which users can specify directly from the "Settings/Inputs" tab. It offers a flexible framework for building and testing complex alert conditions without requiring code modifications for each adjustment. █ CONCEPTS Ensemble analysis Ensemble analysis is a form of data analysis that combines several "weaker" models to produce a potentially more robust model. In a trading context, one of the most prevalent forms of ensemble analysis is the aggregation (grouping) of several indicators to derive market insights and reinforce trading decisions. With this analysis, traders typically inspect multiple indicators, signaling trade actions when specific conditions or groups of conditions align. Simplifying ensemble creation Combining indicators into one or more ensembles can be challenging, especially for users without programming knowledge. It usually involves writing custom scripts to aggregate the indicators and trigger trading alerts based on the confluence of specific conditions. Making such scripts customizable via inputs poses an additional challenge, as it often involves complicated input menus and conditional logic. This indicator addresses these challenges by providing a simple, flexible input menu where users can easily define alert criteria by listing groups of conditions from various technical indicators in simple text boxes . With this script, you can create complex alert conditions intuitively from the "Settings/Inputs" tab without ever writing or modifying a single line of code. This framework makes advanced alert setups more accessible to non-coders. Additionally, it can help Pine programmers save time and effort when testing various condition combinations. █ FEATURES Configurable alert direction The "Direction" dropdown at the top of the "Settings/Inputs" tab specifies the allowed direction for the alert conditions. There are four possible options:  • Up only : The indicator only evaluates upward conditions.  • Down only : The indicator only evaluates downward conditions.  • Up and down (default): The indicator evaluates upward and downward conditions, creating alert triggers for both.  • Alternating : The indicator prevents alert triggers for consecutive conditions in the same direction. An upward condition must be the first occurrence after a downward condition to trigger an alert, and vice versa for downward conditions. Flexible condition groups This script features six text inputs where users can define distinct condition groups (ensembles) for their alerts. An alert trigger occurs if all the conditions in at least one group occur. Each input accepts a comma-separated list of numbers with optional spaces (e.g., "1, 4, 8"). Each listed number, from 1 to 35, corresponds to a specific individual condition. Below are the conditions that the numbers represent:  1 — RSI above/below threshold  2 — RSI below/above threshold  3 — Stoch above/below threshold  4 — Stoch below/above threshold  5 — Stoch K over/under D  6 — Stoch K under/over D  7 — AO above/below threshold  8 — AO below/above threshold  9 — AO rising/falling  10 — AO falling/rising  11 — Supertrend up/down  12 — Supertrend down/up  13 — Close above/below MA  14 — Close below/above MA  15 — Close above/below open  16 — Close below/above open  17 — Close increase/decrease  18 — Close decrease/increase  19 — Close near Donchian top/bottom (Close > (Mid + HH) / 2)  20 — Close near Donchian bottom/top (Close < (Mid + LL) / 2)  21 — New Donchian high/low  22 — New Donchian low/high  23 — Rising volume  24 — Falling volume  25 — Volume above average (Volume > SMA(Volume, 20))  26 — Volume below average (Volume < SMA(Volume, 20))  27 — High body to range ratio (Abs(Close - Open) / (High - Low) > 0.5)  28 — Low body to range ratio (Abs(Close - Open) / (High - Low) < 0.5)  29 — High relative volatility (ATR(7) > ATR(40))  30 — Low relative volatility (ATR(7) < ATR(40))  31 — External condition 1  32 — External condition 2  33 — External condition 3  34 — External condition 4  35 — External condition 5 These constituent conditions fall into three distinct categories:  •  Directional pairs : The numbers 1-22 correspond to pairs of opposing upward and downward conditions. For example, if one of the inputs includes "1" in the comma-separated list, that group uses the "RSI above/below threshold" condition pair. In this case, the RSI must be above a high threshold for the group to trigger an upward alert, and the RSI must be below a defined low threshold to trigger a downward alert.  •  Non-directional filters : The numbers 23-30 correspond to conditions that do not represent directional information. These conditions act as filters for both upward and downward alerts. Traders often use non-directional conditions to refine trending or mean reversion signals. For instance, if one of the input lists includes "30", that group uses the "Low relative volatility" condition. The group can trigger an upward or downward alert only if the 7-period Average True Range (ATR) is below the 40-period ATR.  •  External conditions : The numbers 31-35 correspond to external conditions based on the plots from other indicators on the chart. To set these conditions, use the source inputs in the "External conditions" section near the bottom of the "Settings/Inputs" tab. The external value can represent an upward, downward, or non-directional condition based on the following logic:  ▫ Any value above 0 represents an upward condition.  ▫ Any value below 0 represents a downward condition.  ▫ If the checkbox next to the source input is selected, the condition becomes non-directional . Any group that uses the condition can trigger upward or downward alerts only if the source value is not 0. To learn more about using plotted values from other indicators, see this article in our Help Center and the Source input section of our Pine Script™ User Manual. Group markers Each comma-separated list represents a distinct group , where all the listed conditions must occur to trigger an alert. This script assigns preset markers (names) to each condition group to make the active ensembles easily identifiable in the generated alert messages and labels. The markers assigned to each group use the format "M", where "M" is short for "Marker" and "x" is the group number. The titles of the inputs at the top of the "Settings/Inputs" tab show these markers for convenience. For upward conditions, the labels and alert messages show group markers with upward triangles (e.g., "M1▲"). For downward conditions, they show markers with downward triangles (e.g., "M1▼"). NOTE: By default, this script populates the "M1" field with a pre-configured list for a mean reversion group ("2,18,24,28"). The other fields are empty. If any "M*" input does not contain a value, the indicator ignores it in the alert calculations. Custom alert messages By default, the indicator's alert message text contains the activated markers and their direction as a comma-separated list. Users can override this message for upward or downward alerts with the two text fields at the bottom of the "Settings/Inputs" tab. When the fields are not empty , the alerts use that text instead of the default marker list. NOTE: This script generates alert triggers, not the alerts themselves. To set up an alert based on this script's conditions, open the "Create Alert" dialog box, then select the "Ensemble Alerts" and "Any alert() function call" options in the "Condition" tabs. See the Alerts FAQ in our Pine Script™ User Manual for more information. Condition visualization This script offers organized visualizations of its conditions, allowing users to inspect the behaviors of each condition alongside the specified groups. The key visual features include:   1) Conditional plots  • The indicator plots the history of each individual condition, excluding the external conditions, as circles at different levels. Opposite conditions appear at positive and negative levels with the same absolute value. The plots for each condition show values only on the bars where they occur.  • Each condition's plot is color-coded based on its type. Aqua and orange plots represent opposing directional conditions, and purple plots represent non-directional conditions. The titles of the plots also contain the condition numbers to which they apply.  • The plots in the separate pane can be turned on or off with the "Show plots in pane" checkbox near the top of the "Settings/Inputs" tab. This input only toggles the color-coded circles, which reduces the graphical load. If you deactivate these visuals, you can still inspect each condition from the script's status line and the Data Window.  • As a bonus, the indicator includes "Up alert" and "Down alert" plots in the Data Window, representing the combined upward and downward ensemble alert conditions. These plots are also usable in additional indicator-on-indicator calculations.   2) Dynamic labels  • The indicator draws a label on the main chart pane displaying the activated group markers (e.g., "M1▲") each time an alert condition occurs.  • The labels for upward alerts appear below chart bars. The labels for downward alerts appear above the bars.  NOTE: This indicator can display up to 500 labels because that is the maximum allowed for a single Pine script.   3) Background highlighting  • The indicator can highlight the main chart's background on bars where upward or downward condition groups activate. Use the "Highlight background" inputs in the "Settings/Inputs" tab to enable these highlights and customize their colors.  • Unlike the dynamic labels, these background highlights are available for all chart bars, irrespective of the number of condition occurrences. █ NOTES • This script uses Pine Script™ v6, the latest version of TradingView's programming language. See the Release notes and Migration guide to learn what's new in v6 and how to convert your scripts to this version. • This script imports our new Alerts library, which features functions that provide high-level simplicity for working with complex compound conditions and alerts. We used the library's `compoundAlertMessage()` function in this indicator. It evaluates items from "bool" arrays in groups specified by an array of strings containing comma-separated index lists , returning a tuple of "string" values containing the marker of each activated group. • The script imports the latest version of the ta library to calculate several technical indicators not included in the built-in `ta.*` namespace, including Double Exponential Moving Average (DEMA), Triple Exponential Moving Average (TEMA), Fractal Adaptive Moving Average (FRAMA), Tilson T3, Awesome Oscillator (AO), Full Stochastic (%K and %D), SuperTrend, and Donchian Channels. • The script uses the `force_overlay` parameter in the label.new() and bgcolor() calls to display the drawings and background colors in the main chart pane. • The plots and hlines use the available `display.*` constants to determine whether the visuals appear in the separate pane. Look first. Then leap.
Indicateur Pine Script®
par PineCoders
3
Linear Regression Channel Screener [Daveatt]Hello traders First and foremost, I want to extend a huge thank you to @LonesomeTheBlue for his exceptional Linear Regression Channel indicator that served as the foundation for this screener. Original work can be found here: Overview This project demonstrates how to transform any open-source indicator into a powerful multi-asset screener. The principles shown here can be applied to virtually any indicator you find interesting. How to Transform an Indicator into a Screener Step 1: Identify the Core Logic First, identify the main calculations of the indicator. In our case, it's the Linear Regression Channel calculation: get_channel(src, len) => mid = math.sum(src, len) / len slope = ta.linreg(src, len, 0) - ta.linreg(src, len, 1) intercept = mid - slope * math.floor(len / 2) + (1 - len % 2) / 2 * slope endy = intercept + slope * (len - 1) dev = 0.0 for x = 0 to len - 1 by 1 dev := dev + math.pow(src - (slope * (len - x) + intercept), 2) dev dev := math.sqrt(dev / len) Step 2: Use request.security() Pass the function to request.security() to analyze multiple assets: = request.security(sym, timeframe.period, get_channel(src, len)) Step 3: Scale to Multiple Assets PineScript allows up to 40 request.security() calls, letting you monitor up to 40 assets simultaneously. Features of This Screener The screener provides real-time trend detection for each monitored asset, giving you instant insights into market movements. It displays each asset's position relative to its middle regression line, helping you understand price momentum. The data is presented in a clean, organized table with color-coded trends for easy interpretation. At its core, the screener performs trend detection based on regression slope calculations, clearly indicating whether an asset is in a bullish or bearish trend. Each asset's price is tracked relative to its middle regression line, providing additional context about trend strength. The color-coded visual feedback makes it easy to spot changes at a glance. Built-in alerts notify you instantly when any asset experiences a trend change, ensuring you never miss important market moves. Customization Tips You can easily expand the screener by adding more symbols to the symbols array, adapting it to your watchlist. The regression parameters can be adjusted to match your preferred trading timeframes and sensitivity. The alert system is already configured to notify you of trend changes, but you can customize the alert messages and conditions to your needs. Limitations While powerful, the screener is bound by PineScript's limitation of 40 security calls, capping the maximum number of monitored assets. Using AI to Help With Conversion An interesting tip: You can use AI tools to help convert single-asset indicators to screeners. Simply provide the original code and ask for assistance in transforming it into a screener format. While the AI output might need some syntax adjustments, it can handle much of the heavy lifting in the conversion process. Prompt (example) : " Please make a pinescript version 5 screener out of this indicator below or in attachment to scan 20 instruments " I prefer Claude AI (Opus model) over ChatGPT for pinescript. Conclusion This screener transformation technique opens up endless possibilities for market analysis. By following these steps, you can convert any indicator into a powerful multi-asset scanner, enhancing your trading toolkit significantly. Remember: The power of a screener lies not just in monitoring multiple assets, but in applying consistent analysis across your entire watchlist in real-time. Feel free to fork and modify this screener for your own needs. Happy trading! 🚀📈 Daveatt
Indicateur Pine Script®
par Daveatt
4
Industry Group Strength - IndiaPresenting the Industry Group Strength Indicator for India market, designed to help traders identify top-performing stocks within specific industry groups that are predefined. ⦿ Identifies Leading Stocks in Industry Groups ⦿ Analyses the following metrics YTD Return : Measures stock performance from the start of the year. RS Rating : Relative Strength rating for user-selected periods. % Return : Percentage return over a user-selected lookback period. Features This indicator dynamically recognises the industry group of the current stock on the chart and ranks stocks within that group based on predefined data points. Traders can add this indicator to focus on top-performing stocks relative to their industry. ⦿ Color-coded for Easy Visualisation You can choose from the following key metrics to rank stocks: YTD Return RS Rating % Return ⦿ Table Format with Performance Metrics Compact mode Vertical View Horizontal View All of the three metrics are shown in the compact mode and the current stock that is viewed is highlighted! Vertical view Horizontal view Stock Ranking Stocks are ranked based on their performance within industry groups, enabling traders to easily spot leaders and laggards in each sector. Color-coded gradients visually represent the stocks’ performance rankings, with higher percentile rankings indicating better performance. Relative Strength (RS) Relative Strength (RS) compares a stock’s performance against the benchmark index. The RS value is normalized from 1 to 99, making it easier to compare across different stocks. A rising RS value indicates that the stock is outperforming the market, helping traders quickly gauge relative performance within industry groups. Limitations At the time of developing this indicator, Pine requests are limited to 40 per script so the predefined symbols had to be filtered to 40 per Industry group Stocks Filters Filters that are used to filter the stocks in an Industry group to have maximum of 40 stocks ⦿ Auto, Chemical, Engineering, Finance, Pharma Market Cap >= 1000 Crores and Market Cap <= 60000 Crores Price >= 30 and Price <= 6000 50 Days Average ( Price * Volume ) >= 6 Crores ⦿ For rest of the Industry groups Market Cap >= 1000 Crores and Market Cap <= 100000 Crores Price >= 20 and Price <= 10000 50 Days Average ( Price * Volume ) >= 3 Crores Credits This indicator is forked from the Script for US market by @Amphibiantrading Thanks Brandon for the beginning of this indicator. This indicator is built on TradingView’s new dynamic requests feature, thanks to @PineCoders for making this possible!
Indicateur Pine Script®
par EquityCraze
23
ICT IPDA Liquidity Matrix By AlgoCadosThe ICT IPDA Liquidity Matrix by AlgoCados is a sophisticated trading tool that integrates the principles of the Interbank Price Delivery Algorithm (IPDA), as taught by The Inner Circle Trader (ICT). This indicator is meticulously designed to support traders in identifying key institutional levels and liquidity zones, enhancing their trading strategies with data-driven insights. Suitable for both day traders and swing traders, the tool is optimized for high-frequency and positional trading, providing a robust framework for analyzing market dynamics across multiple time horizons. # Key Features Multi-Time Frame Analysis High Time Frame (HTF) Levels : The indicator tracks critical trading levels over multiple days, specifically at 20, 40, and 60-day intervals. This functionality is essential for identifying long-term trends and significant support and resistance levels that aid in strategic decision-making for swing traders and positional traders. Low Time Frame (LTF) Levels : It monitors price movements within 20, 40, and 60-hour intervals on lower time frames. This granularity provides a detailed view of intraday price actions, which is crucial for scalping and short-term trading strategies favored by day traders. Daily Open Integration : The indicator includes the daily opening price, providing a crucial reference point that reflects the market's initial sentiment. This feature helps traders assess the market's direction and volatility, enabling them to make informed decisions based on the day's early movements, which is particularly useful for day trading strategies. IPDA Reference Points : By leveraging IPDA's 20, 40, and 60-period lookbacks, the tool identifies Key Highs and Lows, which are used by IPDA as Draw On Liquidity. IPDA is an electronic and algorithmic system engineered for achieving price delivery efficiency, as taught by ICT. These reference points serve as benchmarks for understanding institutional trading behavior, allowing traders to align their strategies with the dominant market forces and recognize institutional key levels. Dynamic Updates and Overlap Management : The indicator is updated daily at the beginning of a new daily candle with the latest market data, ensuring that traders operate with the most current information. It also features intelligent overlap management that prioritizes the most relevant levels based on the timeframe hierarchy, reducing visual clutter and enhancing chart readability. Comprehensive Customization Options : Traders can tailor the indicator to their specific needs through an extensive input menu. This includes toggles for visibility, line styles, color selections, and label display preferences. These customization options ensure that the tool can adapt to various trading styles and preferences, enhancing user experience and analytical capabilities. User-Friendly Interface : The tool is designed with a user-friendly interface that includes clear, concise labels for all significant levels. It supports various font families and sizes, making it easier to interpret and act upon the displayed data, ensuring that traders can focus on making informed trading decisions without being overwhelmed by unnecessary information. # Usage Note The indicator is segmented into two key functionalities: LTF Displays : The Low Time Frame (LTF) settings are exclusive to timeframes up to 1 hour, providing detailed analysis for intraday traders. This is crucial for traders who need precise and timely data to make quick decisions within the trading day. HTF Displays : The High Time Frame (HTF) settings apply to the daily timeframe and any shorter intervals, allowing for comprehensive analysis over extended periods. This is beneficial for swing traders looking to identify broader trends and market directions. # Inputs and Configurations BINANCE:BTCUSDT Offset: Adjustable setting to shift displayed data horizontally for better visibility, allowing traders to view past levels and make informed decisions based on historical data. Label Styles: Choose between compact or verbose label formats for different levels, offering flexibility in how much detail is displayed on the chart. Daily Open Line: Customizable line style and color for the daily opening price, providing a clear visual reference for the start of the trading day. HTF Levels: Configurable high and low lines for HTF with options for style and color customization, allowing traders to highlight significant levels in a way that suits their trading style. LTF Levels: Similar customization options for LTF levels, ensuring flexibility in how data is presented, making it easier for traders to focus on the most relevant intraday levels. Text Utils: Settings for font family, size, and text color, allowing for personalized display preferences and ensuring that the chart is both informative and aesthetically pleasing. # Advanced Features Overlap Management : The script intelligently handles overlapping levels, particularly where multiple timeframes intersect, by prioritizing the more significant levels and removing redundant ones. This ensures that the charts remain clear and focused on the most critical data points, allowing traders to concentrate on the most relevant market information. Real-Time Updates : The indicator updates its calculations at the start of each new daily bar, incorporating the latest market data to provide timely and accurate trading signals. This real-time updating is crucial for traders who rely on up-to-date information to execute their strategies effectively and make informed trading decisions. # Example Use Cases Scalpers/Day traders: Can utilize the LTF features to make rapid decisions based on hourly market movements, identifying short-term trading opportunities with precision. Swing Traders: Will benefit from the HTF analysis to identify broader trends and key levels that influence longer-term market movements, enabling them to capture significant market swings. By providing a clear, detailed view of key market dynamics, the ICT IPDA Liquidity Matrix by AlgoCados empowers traders to make more informed and effective trading decisions, aligning with institutional trading methodologies and enhancing their market understanding. # Usage Disclaimer This tool is designed to assist in trading decisions, but it should be used in conjunction with other analysis methods and risk management strategies. Trading involves significant risk, and it is essential to understand the market conditions thoroughly before making trading decisions.
Indicateur Pine Script®
par AlgoCados
18
Moving Average Momentum SignalsBest for trade execution in lower timeframe (1m,5m,15m) with momentum confirmation in higher timeframes (2h,4h,1d) This indicator relies on three key conditions to determine buy and sell signals: the price's deviation from a short-term moving average, the change in the moving average over time (past 10 candles), and the price's deviation from a historical price (40 candles). The strategy aims to target moments where the asset's price is likely to experience a reversal or momentum shift. Conditions Price deviation from short-term Moving Average (MA): Current candle close minus the 10-period MA (price action past 10 candles) Change in Moving Average over time: Current 10-period MA minus the 10-period MA from 10 candles ago (price action past 20 candles) Price deviation from historical price: Current close minus the close from 40 candles ago (price action past 40 candles) Signal Generation Logic Buy Signal: Triggered when all three conditions are positive. Confirmed if the previous signal was a sell or if there were no previous signals Sell Signal: Triggered when all three conditions are negative. Confirmed if the previous signal was a buy or if there were no previous signals Usage and Strategy After back testing, I observed the higher timeframes were a good indication of momentum/sentiment that you can take note of while trading intraday on the lower time frames (time intervals stated above). Background highlights are also displayed for easier visualization of bullish/bearish skew in terms of the volume of signals generated.
Indicateur Pine Script®
par CPSiphon8
Triple EMA + QQE Trend Following Strategy [TradeDots]The "Triple EMA + QQE Trend Following Strategy" harnesses the power of two sophisticated technical indicators, the Triple Exponential Moving Average (TEMA) and the Qualitative Quantitative Estimation (QQE), to generate precise buy and sell signals. This strategy excels in capturing shifts in trends by identifying short-term price momentum and dynamic overbought or oversold conditions. HOW IT WORKS This strategy integrates two pivotal indicators: Triple Exponential Moving Average (TEMA): TEMA enhances traditional moving averages by reducing lag and smoothing the data more effectively. It achieves this by applying the EMA formula three times onto the price, as follows: tema(src, length) => ema1 = ta.ema(src, length) ema2 = ta.ema(ema1, length) ema3 = ta.ema(ema2, length) tema = 3*ema1 - 3*ema2 + ema3 This computation helps to sharpen the sensitivity to price movements. Qualitative Quantitative Estimation (QQE): The QQE indicator improves upon the standard RSI by incorporating a smoothing mechanism. It starts with the standard RSI, overlays a 5-period EMA on this RSI, and then enhances the result using a double application of a 27-period EMA. A slow trailing line is then derived by multiplying the result with a factor number. This approach establishes a more refined and less jittery trend-following signal, complementing the TEMA to enhance overall market timing during fluctuating conditions. APPLICATION Referenced from insights on "Trading Tact," the strategy implementation follows: First of all, we utilize two TEMA lines: one set at a 20-period and the other at a 40-period. Then following the rules below: 40-period TEMA is rising 20-period TEMA is above 40-period TEMA Price closes above 20-period TEMA Today is not Monday RSI MA crosses the Slow trailing line This strategy does not employ an active take profit mechanism; instead, it utilizes a trailing stop loss to allow the price to reach the stop loss naturally, thereby maximizing potential profit margins. DEFAULT SETUP Commission: 0.01% Initial Capital: $10,000 Equity per Trade: 80% Users are advised to adjust and personalize this trading strategy to better match their individual trading preferences and style. RISK DISCLAIMER Trading entails substantial risk, and most day traders incur losses. All content, tools, scripts, articles, and education provided by TradeDots serve purely informational and educational purposes. Past performances are not definitive predictors of future results. Reference: Trading Tact. What Is the QQE Indicator? Retrieved from: tradingtact.com
Stratégie Pine Script®
par tradedots
Hurst Future Lines of Demarcation StrategyJ. M. Hurst introduced a concept in technical analysis known as the Future Line of Demarcation (FLD), which serves as a forward-looking tool by incorporating a simple yet profound line into future projections on a financial chart. Specifically, the FLD is constructed by offsetting the price half a cycle ahead into the future on the time axis, relative to the Hurst Cycle of interest. For instance, in the context of a 40 Day Cycle, the FLD would be represented by shifting the current price data 20 days forward on the chart, offering an idea of future price movement anticipations. The utility of FLDs extends into three critical areas of insight, which form the backbone of the FLD Trading Strategy: A price crossing the FLD signifies the confirmation of either a peak or trough formation, indicating pivotal moments in price action. Such crossings also help determine precise price targets for the upcoming peak or trough, aligned with the cycle of examination. Additionally, the occurrence of a peak in the FLD itself signals a probable zone where the price might experience a trough, helping to anticipate of future price movements. These insights by Hurst in his "Cycles Trading Course" during the 1970s, are instrumental for traders aiming to determine entry and exit points, and to forecast potential price movements within the market. To use the FLD Trading Strategy, for example when focusing on the 40 Day Cycle, a trader should primarily concentrate on the interplay between three Hurst Cycles: The 20 Day FLD (Signal) - Half the length of the Trade Cycle The 40 Day FLD (Trade) - The Cycle you want to trade The 80 Day FLD (Trend) - Twice the length of the Trade Cycle Traders can gauge trend or consolidation by watching for two critical patterns: Cascading patterns, characterized by several FLDs running parallel with a consistent separation, typically emerge during pronounced market trends, indicating strong directional momentum. Consolidation patterns, on the other hand, occur when multiple FLDs intersect and navigate within the same price bandwidth, often reversing direction to traverse this range multiple times. This tangled scenario results in the formation of Pause Zones, areas where price momentum is likely to temporarily stall or where the emergence of a significant trend might be delayed. This simple FLD indicator provides 3 FLDs with optional source input and smoothing, A-through-H FLD interaction background, adjustable “Close the Trade” triggers, and a simple strategy for backtesting it all. The A-through-H FLD interactions are a framework designed to classify the different types of price movements as they intersect with or diverge from the Future Line of Demarcation (FLD). Each interaction (designated A through H by color) represents a specific phase or characteristic within the cycle, and understanding these can help traders anticipate future price movements and make informed decisions. The adjustable “Close the Trade” triggers are for setting the crossover/under that determines the trade exits. The options include: Price, Signal FLD, Trade FLD, or Trend FLD. For example, a trader may want to exit trades only when price finally crosses the Trade FLD line. Shoutouts & Credits for all the raw code, helpful information, ideas & collaboration, conversations together, introductions, indicator feedback, and genuine/selfless help: 🏆 @TerryPascoe 🏅 @Hpotter 👏 @parisboy
Stratégie Pine Script®
par BarefootJoey
4
Rate of Change RSIIndicator Name: Rate of Change RSI Description: The Rate of Change (ROC) of the Relative Strength Index (RSI) is a technical indicator designed to provide insights into the momentum of an asset's price movement. It combines the Relative Strength Index (RSI), a popular momentum oscillator, with the Rate of Change (ROC) concept to assess the speed at which RSI values are changing. How It Works: Relative Strength Index (RSI): The RSI measures the magnitude of recent price changes to evaluate overbought or oversold conditions in an asset. It oscillates between 0 and 100, with readings above 70 typically indicating overbought conditions and readings below 30 indicating oversold conditions. Rate of Change (ROC): The ROC calculates the percentage change in a given indicator over a specified period. In this indicator, we apply the ROC to the RSI values to determine how quickly the RSI is changing over time. Key Features: Acceleration and Deceleration: The ROC of RSI helps traders identify whether the momentum of the RSI is accelerating or decelerating. Positive values suggest increasing momentum, while negative values indicate decreasing momentum. Dynamic Color Change: The color of the ROC RSI line changes dynamically based on the RSI level. When the RSI is between 0 and 40, the line color is blue, indicating potential oversold conditions. When the RSI is between 40 and 60, the line color is yellow, suggesting neutral conditions. When the RSI is above 60, the line color changes to green, indicating potential overbought conditions. How to Use: Acceleration: When the ROC RSI is positive and increasing while the RSI is above 60 (green), it may signal strong upward momentum. Deceleration: Conversely, if the ROC RSI is negative and decreasing while the RSI is below 40 (blue), it may indicate weakening downward momentum. Originality and Usefulness: This indicator combines the RSI, a well-known momentum oscillator, with the ROC concept to provide a unique perspective on momentum dynamics. By dynamically adjusting the color of the ROC RSI line based on RSI levels, traders can quickly assess potential overbought or oversold conditions in the market. Chart: The chart displayed alongside this script provides a clean and easy-to-understand visualization of the ROC RSI indicator. The ROC RSI line color changes dynamically based on RSI levels, allowing traders to visually identify potential market conditions at a glance.
Indicateur Pine Script®
par Tradernawab
Cycles 90mThe cycles are separated by vertical lines. The first cycle (Q1) is marked with a red line because it is a manipulative cycle where you should not open positions. Other cycles are green (Q2, Q3, Q4). You can add the time of the current candle, its size and position on the chart in the settings The time is highlighted in red in the timeframes 9:30-9:40, 10:00-10:10, 11:00-11:30, 15:30-15:40, 16:00-16:10, 17:00-17:10, 17:30-17:40, as price movements are most often expected during these timeframes. The cycle lines automatically disappear if you open a timeframe above M15
Indicateur Pine Script®
par yerav