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Fib,Guppy Multiple MA(FGMMA)(A/D & Volume Weight,SMA,EMA)[cI8DH]Features: - 3 + 12 MAs (12 is chosen because Guppy has 12 MAs) - MA types can be set to Simple, Exponential, Weighted, and Smoothed - Volume weight can be applied to all available MAs (the built-in VWMA uses Simple MA) - It is possible to count in only effective portions of the volume in the equation by using Accum/Dist Volume Weight - Secondary smoothing (useful when volume weight is enabled) - Predefined MA sets based on Fibonacci sequence (2,3,5,8,.., 377), Guppy (3,5,8,10,12,15 &30,35,40,45,50,60), and cI8DH (2,3,5,8,12,17 & 30,34,39,45,52,60) Recommended settings: - hlc3 as input source captures all the essential information encapsulated in a candle. I'd use hlc3 as the default option. In uptrend, "low" and in downtrend, "high" might give more relevant results when using MAs for structural analysis of a market. For commonly used MAs (EMA20, SMA50,100,200), "close" should be used due to their self-fulfilling prophecy effect. - When you have volume weight above 0, you may want to use secondary smoothing. - Try not to use Simple MA for smaller lengths (below 20). Sharp changes in the past (right before the period specified by the length) will affect the current value of MA dramatically leading to confusion. - I am using the first 3 MAs for SMA 50,100,200. You can disable them from the MA type selector all at once when using Fib or Guppy ribbons. MA-based analysis: There are different ways of structuring a market. Geometrical (trend lines, channels, fans, patterns, etc) and Fib retracement-based structuring is very common among traders. MAs give an alternative way of analyzing markets. MA ribbons such as Guppy (6 slow and 6 fast-moving MAs) are popular for analyzing market flow. IMO default Guppy sets are a bit random as the numbers do not have an elegant sequence. So I proposed my sets based on increasing sequene spacing (+1). These two MA ribbons are good for market flow analysis but the spacing of the MAs are not ideal for structuring a market. Ribbons based on the Fib sequence is a better choice for structuring a market. This is the equivalent of Fib channels but in a more dynamic form. Among other things, MA Fib ribbon can be used to assess market momentum and to compare different stages of a market. Here are two "educational-only" examples: Notes: - Smoothed MA with length L = Exponential MA with length 2*L-1 - Read the background section in my ADP indicator to understand how A/D Volume is calculated
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cI8DH tarafından
11
Better RSI with bullish / bearish market cycle indicator This script improves the default RSI. First. it identifies regions of the RSI which are oversold and overbought by changing the color of RSI from white to red. Second, it adds additional reference lines at 20,40,50,60, and 80 to better gauge the RSI value. Finally, the coolest feature, the middle 50 line is used to indicate which cycle the price is currently at. A green color at the 50 line indicates a bullish cycle, a red color indicators a bearish cycle, and a white color indicates a neutral cycle. The cycles are determined using the RSI as follows: if RSI is overbought, cycle switches to bullish until RSI falls below 40, at which point it becomes neutral if RSI is oversold, cycle switches bearish until RSI rises above 60, at which point it becomes neutral a neutral cycle is exited at either overbought or oversold conditions Very useful, please give it a try and let me know what you think
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TradeCalmly tarafından
18
MG - Multiple time frame Stochastic RSIAllows user to view stochastic RSI from two different time frames. Each stochastic RSI indicator is fully customizable, offering the following options: - Timeframe - RSI source - RSI length - Stochastic length - Stochastic average length - Stochastic smoothing length Usage: Comparing stochastic RSI across two different time frames can sharpen trades. For example, if you configure a 60 min and 5/15 min stochastic RSI pair, you might enter a long trade when the 60 min stoch RSI crosses up and exit / take profit when the 5 min stock RSI crosses down.
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mgibson91 tarafından
1
NG [Simple Harmonic Oscillator]The SHO is a bounded oscillator for the simple harmonic index that calculates the period of the market’s cycle. The oscillator is used for short and intermediate terms and moves within a range of -100 to 100 percent. The SHO has overbought and oversold levels at +40 and -40, respectively. At extreme periods, the oscillator may reach the levels of +60 and -60. The zero level demonstrates an equilibrium between the periods of bulls and bears. The SHO oscillates between +40 and -40. The crossover at those levels creates buy and sell signals. In an uptrend, the SHO fluctuates between 0 and +40 where the bulls are controlling the market. On the contrary, the SHO fluctuates between 0 and -40 during downtrends where the bears controlthe market. Reaching the extreme level -60 in an uptrend is a sign of weakness.
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NGBaltic tarafından
2
DEMA Double Exponential Moving Average Strategy@Moneros 2017 Based on The DEMA is a fast-acting moving average that is more responsive to market changes than a traditional moving average en.wikipedia.org !!!! IN ORDER TO AVOID REPAITING ISSUES !!!! !!!! DO NOT VIEW IN LOWER RESOLUTIONS THAN res/2 PARAMETER !!!! for example res = 120 view >= 60m res = 60 view >= 30m the length of the DEMA sampling shouldn't be longer than a candle Best profits tested on BTCUSD res = 105 slowPeriod = 2 fastPeriod = 32 res = 125 slowPeriod = 3 fastPeriod = 21 res = 120 slowPeriod = 2 fastPeriod = 32 res = 130 slowPeriod = 1 fastPeriod = 24 res = 40 slowPeriod = 4 fastPeriod = 93 res = 60 slowPeriod = 1 fastPeriod = 67 BTCUSD
Pine Script® stratejisi
moneros tarafından
28
Hersheys CoCo VolumeCoCo Volume shows you volume movement of your symbol after subtracting the movement from another symbol, preferrably the sector or market the stock belongs to. My latest update to my CoCoVolume Indicator. It calculates today's volume percent over the 60 period average for both your symbol and index, and displays that difference. If the percent is over the max it highlights the color, showing BIG action for that stock. The last version was calculating the percent volume difference from yesterday to today for the stock and index and displaying the difference. The prior method had large swings on low volume stocks... this one shows the independent volume action much better. The default values will suit most stocks. You can set three variables... - the index symbol, default is SPY - the period for averaging, default is 60 - the max volume percent, default is 500 Good trading! Brian Hershey
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bnh tarafından
1
close-hl2 Price actionStill not tested, but looks very good ; it is the difference between EMA median price and EMA close in different time frame, I used 240, 60, and the current Time frame ,plus one more customed period ; can forcast the price movement , but it s not in scale, so it can not show how much higher or lower the price can goes but just the next direction. I think intraday on 5 ,15 ,60 better then high frame.If you need to try on Daily frame have to change the period to higher then Daily
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MarcoValente tarafından
3
Everyday 0002 _ MAC 1st Trading Hour WalkoverThis is the second strategy for my Everyday project. Like I wrote the last time - my goal is to create a new strategy everyday for the rest of 2016 and post it here on TradingView. I'm a complete beginner so this is my way of learning about coding strategies. I'll give myself between 15 minutes and 2 hours to complete each creation. This is basically a repetition of the first strategy I wrote - a Moving Average Crossover, but I added a tiny thing. I read that "Statistics have proven that the daily high or low is established within the first hour of trading on more than 70% of the time." (source: ) My first Moving Average Crossover strategy, tested on VOLVB daily, got stoped out by the volatility and because of this missed one nice bull run and a very nice bear run. So I added this single line: if time("60", "1000-1600") regarding when to take exits: if time("60", "1000-1600") strategy.exit("Close Long", "Long", profit=2000, loss=500) strategy.exit("Close Short", "Short", profit=2000, loss=500) Sweden is UTC+2 so I guess UTC 1000 equals 12.00 in Stockholm. Not sure if this is correct, actually. Anyway, I hope this means the strategy will only take exits based on price action which occur in the afternoon, when there is a higher probability of a lower volatility. When I ran the new modified strategy on the same VOLVB daily it didn't get stoped out so easily. On the other hand I'll have to test this on various stocks . Reading and learning about how to properly test strategies is on my todo list - all tips on youtube videos or blogs to read on this topic is very welcome! Like I said the last time, I'm posting these strategies hoping to learn from the community - so any feedback, advice, or corrections is very much welcome and appreciated! /pbergden
Pine Script® stratejisi
pbergden tarafından
Max Drawdown (Asset-Based Lookback)Max Drawdown (Long-Term Trading) 🟦 Majors BTC, ETH, BNB, LTC 180 – 365 Captures full correction cycles and recovery patterns (6–12 months). 🟩 Altcoins SOL, ADA, DOT, LINK, AVAX 90 – 180 Alts move faster than majors; 3–6 months catches most large swings. 🟥 Meme coins DOGE, SHIB, PEPE, FLOKI 60 – 120 Volatile with quick trend reversals; 2–4 months captures parabolic runs + drawdowns. 📅 Chart Timeframe: Use Daily (1D) timeframe for all these. For extra macro insight, try Weekly (1W) with 52 bars (≈ 1 year). Compare multiple assets using the same period to assess relative risk. If you're building a long-term portfolio, combine this with: 200-day SMA or EMA for trend context. Sharpe Ratio or Sortino Ratio if you're looking for risk-adjusted return metrics.
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scottysavage tarafından
DT-FNO Screener//@version=5 indicator("DT-FNO Screener", overlay=true) // === INPUTS === lengthEMA1 = 20 lengthEMA2 = 50 lengthEMA3 = 200 lengthEMA4 = 10 rsiLength = 14 // === PRICE DATA === closePrice = close highPrev = high lowPrev = low openToday = open closeToday = close // === EMA CALCULATIONS === ema20D = ta.ema(close, 20) ema50D = ta.ema(close, 50) ema200D = ta.ema(close, 200) ema10D = ta.ema(close, 10) ema20W = ta.ema(request.security(syminfo.tickerid, "W", close), 20) ema50W = ta.ema(request.security(syminfo.tickerid, "W", close), 50) // === RSI === rsiVal = ta.rsi(close, rsiLength) // === % CHANGE STATS === percentChange = 100 * (close - close ) / close min7Change = ta.lowest(percentChange, 7) max5Change = ta.highest(percentChange, 5) // === CONDITIONS (from screener) === // Futures Segment cond1 = ema20W < ema50W cond2 = ema20D < ema50D cond3 = ema50D < ema200D cond4 = close > ema20D // Cash Segment cond5 = closeToday < highPrev cond6 = closeToday > lowPrev cond7 = openToday > lowPrev cond8 = openToday < highPrev cond9 = ((ema10D - close) / close) <= 0.02 cond10 = rsiVal <= 60 // % Change Conditions cond11 = min7Change <= -1.5 cond12 = max5Change <= 1.2 // === FINAL COMBINED CONDITION === all_conditions = cond1 and cond2 and cond3 and cond4 and cond5 and cond6 and cond7 and cond8 and cond9 and cond10 and cond11 and cond12 // === PLOT SIGNAL === bgcolor(all_conditions ? color.new(color.green, 80) : na) plotshape(all_conditions, title="DT-FNO Signal", location=location.belowbar, color=color.green, style=shape.labelup, text="DT")
Pine Script® göstergesi
yatinmarkets tarafından
Hybrid Strategy with Position Control & Breakout Filter//@version=6 indicator('Hybrid Strategy with Position Control & Breakout Filter', overlay=true) // === INPUTS === emaFastLen = input.int(8, 'Fast EMA') emaSlowLen = input.int(21, 'Slow EMA') rsiLen = input.int(14, 'RSI Length') rsiOverbought = input.int(70, 'RSI Overbought') rsiOversold = input.int(30, 'RSI Oversold') macdFast = input.int(12, 'MACD Fast') macdSlow = input.int(26, 'MACD Slow') macdSignal = input.int(9, 'MACD Signal') volatilityMultiplier = input.float(1.0, 'ATR Multiplier for Volatility Filter') // === CALCULATIONS === emaFast = ta.ema(close, emaFastLen) emaSlow = ta.ema(close, emaSlowLen) rsi = ta.rsi(close, rsiLen) = ta.macd(close, macdFast, macdSlow, macdSignal) atr = ta.atr(14) // === VOLATILITY FILTER === volatilityThreshold = ta.sma(atr, 14) * volatilityMultiplier isVolatile = atr > volatilityThreshold // === OPENING SPIKE LOGIC (first 15 mins of session only) === sessionStart = timestamp("America/New_York", year, month, dayofmonth, 9, 30) first15Min = time >= sessionStart and time < sessionStart + 15 * 60 * 1000 openingBreakout = first15Min and close > open and ta.change(close) > atr * 1.5 // === POSITION TRACKING === var int position = 0 // 0 = no position, 1 = long, -1 = short // === ENTRY CONDITIONS === longCondition = ((ta.crossover(emaFast, emaSlow) and rsi < rsiOverbought and macdLine > signalLine and isVolatile) or openingBreakout) and position != 1 shortCondition = ta.crossunder(emaFast, emaSlow) and rsi > rsiOversold and macdLine < signalLine and isVolatile and position != -1 // === EXIT CONDITIONS === exitLong = ta.crossunder(emaFast, emaSlow) exitShort = ta.crossover(emaFast, emaSlow) // === SIGNAL PLOTS === buySignal = longCondition sellSignal = shortCondition plotshape(buySignal, title='Buy Signal', location=location.belowbar, color=color.green, style=shape.triangleup, size=size.small, text='BUY') plotshape(sellSignal, title='Sell Signal', location=location.abovebar, color=color.red, style=shape.triangledown, size=size.small, text='SELL') // === STATE MANAGEMENT === if (longCondition) position := 1 if (shortCondition) position := -1 if (exitLong and position == 1) position := 0 if (exitShort and position == -1) position := 0 // === PLOT EMAs === plot(emaFast, color=color.orange, title='Fast EMA') plot(emaSlow, color=color.blue, title='Slow EMA')
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srikanthreddyinvst tarafından
SCPEM - Socionomic Crypto Peak Model (0-85 Scale)SCPEM Indicator Overview The SCPEM (Socionomic Crypto Peak Evaluation Model) indicator is a TradingView tool designed to approximate cycle peaks in cryptocurrency markets using socionomic theory, which links market behavior to collective social mood. It generates a score from 0-85 (where 85 signals extreme euphoria and high reversal risk) and plots it as a blue line on the chart for visual backtesting and real-time analysis. #### How It Works The indicator uses technical proxies to estimate social mood factors, as Pine Script cannot fetch external data like sentiment indices or social media directly. It calculates a weighted composite score on each bar: - Proxies derive from price, volume, and volatility data. - The raw sum of factor scores (max ~28) is normalized to 0-85. - The score updates historically for backtesting, showing mood progression over time. - Alerts trigger if the score exceeds 60, indicating high peak probability. Users can adjust inputs (e.g., lengths for RSI or pivots) to fine-tune for different assets or timeframes. Metrics Used (Technical Proxies) Crypto-Specific Sentiment Approximated by RSI (overbought levels indicate greed). Social Media Euphoria Based on volume relative to its SMA (spikes suggest herding/FOMO). Broader Social Mood Proxies Derived from ATR volatility (high values signal uncertain/mixed mood). Search and Cultural Interest Proxied by OBV trend (rising accumulation implies growing interest). Socionomic Wildcard Uses Bollinger Band width (expansion for positive mood, contraction for negative). Elliott Wave Position Counts recent price pivots (more swings indicate later wave stages and exhaustion).
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gtvsteve tarafından
Aggressive RSI + EMA Strategy with TP/SLWhat This Strategy Does 🔥 📉 It monitors RSI to find when the market is potentially oversold (RSI < 40) or overbought (RSI > 60). 📈 It checks the trend direction using two EMAs — fast EMA (short-term) and slow EMA (long-term). ✅ It only buys when the market looks oversold and the short-term trend is up (fast EMA > slow EMA). ❌ It only sells when the market looks overbought and the short-term trend is down (fast EMA < slow EMA). 💰 Once in a trade, it sets a take profit at 1% gain and a stop loss at 0.5% loss — so profits are locked and risks controlled. 🔄 This cycle repeats continuously, aiming to catch many small, quick moves rather than waiting for big swings. 🚀 The aggressive RSI thresholds mean it triggers trades more often — ideal for active traders who want lots of setups. 📊 It shows clear visual indicators and plots on the chart so you can easily see entries, exits, and indicator levels. 🔔 It also supports alerts, so you can get notified instantly when a trade setup happens. In short, it’s a fast, trend-aware momentum strategy with built-in risk control designed for active trading and consistent small wins.
Pine Script® stratejisi
MEDUSA7 tarafından
Multi-Timeframe Trend Analysis [Aaron Diaz]🧠 Indicator Review: Multi-Timeframe Trend Analysis 📌 What Does It Do? The "Multi-Timeframe Trend Analysis" indicator by Aaron Diaz performs a trend assessment across multiple timeframes using Exponential Moving Averages (EMAs) as internal logic. Instead of plotting EMAs on the chart, this version only displays a clean dashboard that shows whether each EMA is trending up or down, keeping your chart clutter-free. 🧾 Based on the original indicator by BigBeluga, this version was modified by Aaron Diaz to remove the EMA plots and focus solely on actionable trend information via a table. 🔍 How It Works It calculates 5 different EMAs (default: 20, 30, 40, 50, 60 periods). For each EMA, it checks if it’s trending up (EMA > EMA 2 candles ago) or down. These signals are then evaluated across 5 customizable timeframes (e.g., 1h, 2h, 3h, etc.). A dashboard/table appears on the top-right corner of your screen, showing: 🢁 = Uptrend for that EMA and timeframe. 🢃 = Downtrend. It uses color codes (green = bullish, purple = bearish) to make trend reading fast and intuitive. 🧱 Technical Foundations Exponential Moving Averages (EMAs): EMAs give more weight to recent prices, making them highly responsive to current trends. Widely used to detect momentum and reversals. Multi-Timeframe Analysis (MTF): Helps confirm trend strength by analyzing multiple timeframes. Reduces false signals and noise found in a single timeframe. 📈 Suggested Strategy: "MTF Trend Confluence" 🎯 Goal: Only trade when multiple timeframes confirm the same directional bias. ✅ Long Entry Rules: At least 3 out of 5 timeframes must show 🢁 on at least 4 of the 5 EMAs. Confirm entry with: A bullish candlestick pattern. A breakout above recent resistance. Optional filter: RSI or MACD not in overbought zone. 🔻 Short Entry Rules: At least 3 timeframes must show 🢃 on at least 4 EMAs. Confirm with: A bearish candle or breakdown below support. Optional filter: RSI or MACD not in oversold zone. 🛑 Exit Rules: Take Profit at key support/resistance levels or at a 2:1 risk-reward ratio. Stop Loss below/above the last swing or fixed % (e.g., 1.5–2%). Exit early if the dashboard shows a shift in trend across key timeframes. 🧪 Example Use Case You're trading on a 15-minute chart: The dashboard shows 🢁 across 1h, 2h, and 3h timeframes for EMA20, EMA30, and EMA40. Price breaks a local resistance level. You enter long and target the next liquidity zone, placing your stop-loss below the most recent swing low. ⚠️ Important Notes This is not a signal generator—it’s a trend confirmation tool. Best used for swing or intraday trend trading. Avoid using it in ranging or sideways markets.
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aaron0791 tarafından
Nasdaq Market Direction ProbabilitiesA table in the bottom-left corner showing bullish, bearish, and neutral probabilities for Nasdaq market direction, calculated from weighted indicators (moving averages, RSI, volume trend, futures change, and sentiment). A label on the chart with a recommendation ("Long", "Short", or "Monitor") based on the highest probability. A histogram of the bullish probability in a separate pane. The probabilities update on each confirmed bar, using the chart’s timeframe (ideally 60 minutes).
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EvilR8 tarafından
VoVix DEVMA🌌 VoVix DEVMA: A Deep Dive into Second-Order Volatility Dynamics Welcome to VoVix+, a sophisticated trading framework that transcends traditional price analysis. This is not merely another indicator; it is a complete system designed to dissect and interpret the very fabric of market volatility. VoVix+ operates on the principle that the most powerful signals are not found in price alone, but in the behavior of volatility itself. It analyzes the rate of change, the momentum, and the structure of market volatility to identify periods of expansion and contraction, providing a unique edge in anticipating major market moves. This document will serve as your comprehensive guide, breaking down every mathematical component, every user input, and every visual element to empower you with a profound understanding of how to harness its capabilities. 🔬 THEORETICAL FOUNDATION: THE MATHEMATICS OF MARKET DYNAMICS VoVix+ is built upon a multi-layered mathematical engine designed to measure what we call "second-order volatility." While standard indicators analyze price, and first-order volatility indicators (like ATR) analyze the range of price, VoVix+ analyzes the dynamics of the volatility itself. This provides insight into the market's underlying state of stability or chaos. 1. The VoVix Score: Measuring Volatility Thrust The core of the system begins with the VoVix Score. This is a normalized measure of volatility acceleration or deceleration. Mathematical Formula: VoVix Score = (ATR(fast) - ATR(slow)) / (StDev(ATR(fast)) + ε) Where: ATR(fast) is the Average True Range over a short period, representing current, immediate volatility. ATR(slow) is the Average True Range over a longer period, representing the baseline or established volatility. StDev(ATR(fast)) is the Standard Deviation of the fast ATR, which measures the "noisiness" or consistency of recent volatility. ε (epsilon) is a very small number to prevent division by zero. Market Implementation: Positive Score (Expansion): When the fast ATR is significantly higher than the slow ATR, it indicates a rapid increase in volatility. The market is "stretching" or expanding. Negative Score (Contraction): When the fast ATR falls below the slow ATR, it indicates a decrease in volatility. The market is "coiling" or contracting. Normalization: By dividing by the standard deviation, we normalize the score. This turns it into a standardized measure, allowing us to compare volatility thrust across different market conditions and timeframes. A score of 2.0 in a quiet market means the same, relatively, as a score of 2.0 in a volatile market. 2. Deviation Analysis (DEV): Gauging Volatility's Own Volatility The script then takes the analysis a step further. It calculates the standard deviation of the VoVix Score itself. Mathematical Formula: DEV = StDev(VoVix Score, lookback_period) Market Implementation: This DEV value represents the magnitude of chaos or stability in the market's volatility dynamics. A high DEV value means the volatility thrust is erratic and unpredictable. A low DEV value suggests the change in volatility is smooth and directional. 3. The DEVMA Crossover: Identifying Regime Shifts This is the primary signal generator. We take two moving averages of the DEV value. Mathematical Formula: fastDEVMA = SMA(DEV, fast_period) slowDEVMA = SMA(DEV, slow_period) The Core Signal: The strategy triggers on the crossover and crossunder of these two DEVMA lines. This is a profound concept: we are not looking at a moving average of price or even of volatility, but a moving average of the standard deviation of the normalized rate of change of volatility. Bullish Crossover (fastDEVMA > slowDEVMA): This signals that the short-term measure of volatility's chaos is increasing relative to the long-term measure. This often precedes a significant market expansion and is interpreted as a bullish volatility regime. Bearish Crossunder (fastDEVMA < slowDEVMA): This signals that the short-term measure of volatility's chaos is decreasing. The market is settling down or contracting, often leading to trending moves or range consolidation. ⚙️ INPUTS MENU: CONFIGURING YOUR ANALYSIS ENGINE Every input has been meticulously designed to give you full control over the strategy's behavior. Understanding these settings is key to adapting VoVix+ to your specific instrument, timeframe, and trading style. 🌀 VoVix DEVMA Configuration 🧬 Deviation Lookback: This sets the lookback period for calculating the DEV value. It defines the window for measuring the stability of the VoVix Score. A shorter value makes the system highly reactive to recent changes in volatility's character, ideal for scalping. A longer value provides a smoother, more stable reading, better for identifying major, long-term regime shifts. ⚡ Fast VoVix Length: This is the lookback period for the fastDEVMA. It represents the short-term trend of volatility's chaos. A smaller number will result in a faster, more sensitive signal line that reacts quickly to market shifts. 🐌 Slow VoVix Length: This is the lookback period for the slowDEVMA. It represents the long-term, baseline trend of volatility's chaos. A larger number creates a more stable, slower-moving anchor against which the fast line is compared. How to Optimize: The relationship between the Fast and Slow lengths is crucial. A wider gap (e.g., 20 and 60) will result in fewer, but potentially more significant, signals. A narrower gap (e.g., 25 and 40) will generate more frequent signals, suitable for more active trading styles. 🧠 Adaptive Intelligence 🧠 Enable Adaptive Features: When enabled, this activates the strategy's performance tracking module. The script will analyze the outcome of its last 50 trades to calculate a dynamic win rate. ⏰ Adaptive Time-Based Exit: If Enable Adaptive Features is on, this allows the strategy to adjust its Maximum Bars in Trade setting based on performance. It learns from the average duration of winning trades. If winning trades tend to be short, it may shorten the time exit to lock in profits. If winners tend to run, it will extend the time exit, allowing trades more room to develop. This helps prevent the strategy from cutting winning trades short or holding losing trades for too long. ⚡ Intelligent Execution 📊 Trade Quantity: A straightforward input that defines the number of contracts or shares for each trade. This is a fixed value for consistent position sizing. 🛡️ Smart Stop Loss: Enables the dynamic stop-loss mechanism. 🎯 Stop Loss ATR Multiplier: Determines the distance of the stop loss from the entry price, calculated as a multiple of the current 14-period ATR. A higher multiplier gives the trade more room to breathe but increases risk per trade. A lower multiplier creates a tighter stop, reducing risk but increasing the chance of being stopped out by normal market noise. 💰 Take Profit ATR Multiplier: Sets the take profit target, also as a multiple of the ATR. A common practice is to set this higher than the Stop Loss multiplier (e.g., a 2:1 or 3:1 reward-to-risk ratio). 🏃 Use Trailing Stop: This is a powerful feature for trend-following. When enabled, instead of a fixed stop loss, the stop will trail behind the price as the trade moves into profit, helping to lock in gains while letting winners run. 🎯 Trail Points & 📏 Trail Offset ATR Multipliers: These control the trailing stop's behavior. Trail Points defines how much profit is needed before the trail activates. Trail Offset defines how far the stop will trail behind the current price. Both are based on ATR, making them fully adaptive to market volatility. ⏰ Maximum Bars in Trade: This is a time-based stop. It forces an exit if a trade has been open for a specified number of bars, preventing positions from being held indefinitely in stagnant markets. ⏰ Session Management These inputs allow you to confine the strategy's trading activity to specific market hours, which is crucial for day trading instruments that have defined high-volume sessions (e.g., stock market open). 🎨 Visual Effects & Dashboard These toggles give you complete control over the on-chart visuals and the dashboard. You can disable any element to declutter your chart or focus only on the information that matters most to you. 📊 THE DASHBOARD: YOUR AT-A-GLANCE COMMAND CENTER The dashboard centralizes all critical information into one compact, easy-to-read panel. It provides a real-time summary of the market state and strategy performance. 🎯 VOVIX ANALYSIS Fast & Slow: Displays the current numerical values of the fastDEVMA and slowDEVMA. The color indicates their direction: green for rising, red for falling. This lets you see the underlying momentum of each line. Regime: This is your most important environmental cue. It tells you the market's current state based on the DEVMA relationship. 🚀 EXPANSION (Green) signifies a bullish volatility regime where explosive moves are more likely. ⚛️ CONTRACTION (Purple) signifies a bearish volatility regime, where the market may be consolidating or entering a smoother trend. Quality: Measures the strength of the last signal based on the magnitude of the DEVMA difference. An ELITE or STRONG signal indicates a high-conviction setup where the crossover had significant force. PERFORMANCE Win Rate & Trades: Displays the historical win rate of the strategy from the backtest, along with the total number of closed trades. This provides immediate feedback on the strategy's historical effectiveness on the current chart. EXECUTION Trade Qty: Shows your configured position size per trade. Session: Indicates whether trading is currently OPEN (allowed) or CLOSED based on your session management settings. POSITION Position & PnL: Displays your current position (LONG, SHORT, or FLAT) and the real-time Profit or Loss of the open trade. 🧠 ADAPTIVE STATUS Stop/Profit Mult: In this simplified version, these are placeholders. The primary adaptive feature currently modifies the time-based exit, which is reflected in how long trades are held on the chart. 🎨 THE VISUAL UNIVERSE: DECIPHERING MARKET GEOMETRY The visuals are not mere decorations; they are geometric representations of the underlying mathematical concepts, designed to give you an intuitive feel for the market's state. The Core Lines: FastDEVMA (Green/Maroon Line): The primary signal line. Green when rising, indicating an increase in short-term volatility chaos. Maroon when falling. SlowDEVMA (Aqua/Orange Line): The baseline. Aqua when rising, indicating a long-term increase in volatility chaos. Orange when falling. 🌊 Morphism Flow (Flowing Lines with Circles): What it represents: This visualizes the momentum and strength of the fastDEVMA. The width and intensity of the "beam" are proportional to the signal strength. Interpretation: A thick, steep, and vibrant flow indicates powerful, committed momentum in the current volatility regime. The floating '●' particles represent kinetic energy; more particles suggest stronger underlying force. 📐 Homotopy Paths (Layered Transparent Boxes): What it represents: These layered boxes are centered between the two DEVMA lines. Their height is determined by the DEV value. Interpretation: This visualizes the overall "volatility of volatility." Wider boxes indicate a chaotic, unpredictable market. Narrower boxes suggest a more stable, predictable environment. 🧠 Consciousness Field (The Grid): What it represents: This grid provides a historical lookback at the DEV range. Interpretation: It maps the recent "consciousness" or character of the market's volatility. A consistently wide grid suggests a prolonged period of chaos, while a narrowing grid can signal a transition to a more stable state. 📏 Functorial Levels (Projected Horizontal Lines): What it represents: These lines extend from the current fastDEVMA and slowDEVMA values into the future. Interpretation: Think of these as dynamic support and resistance levels for the volatility structure itself. A crossover becomes more significant if it breaks cleanly through a prior established level. 🌊 Flow Boxes (Spaced Out Boxes): What it represents: These are compact visual footprints of the current regime, colored green for Expansion and red for Contraction. Interpretation: They provide a quick, at-a-glance confirmation of the dominant volatility flow, reinforcing the background color. Background Color: This provides an immediate, unmistakable indication of the current volatility regime. Light Green for Expansion and Light Aqua/Blue for Contraction, allowing you to assess the market environment in a split second. 📊 BACKTESTING PERFORMANCE REVIEW & ANALYSIS The following is a factual, transparent review of a backtest conducted using the strategy's default settings on a specific instrument and timeframe. This information is presented for educational purposes to demonstrate how the strategy's mechanics performed over a historical period. It is crucial to understand that these results are historical, apply only to the specific conditions of this test, and are not a guarantee or promise of future performance. Market conditions are dynamic and constantly change. Test Parameters & Conditions To ensure the backtest reflects a degree of real-world conditions, the following parameters were used. The goal is to provide a transparent baseline, not an over-optimized or unrealistic scenario. Instrument: CME E-mini Nasdaq 100 Futures (NQ1!) Timeframe: 5-Minute Chart Backtesting Range: March 24, 2024, to July 09, 2024 Initial Capital: $100,000 Commission: $0.62 per contract (A realistic cost for futures trading). Slippage: 3 ticks per trade (A conservative setting to account for potential price discrepancies between order placement and execution). Trade Size: 1 contract per trade. Performance Overview (Historical Data) The test period generated 465 total trades , providing a statistically significant sample size for analysis, which is well above the recommended minimum of 100 trades for a strategy evaluation. Profit Factor: The historical Profit Factor was 2.663 . This metric represents the gross profit divided by the gross loss. In this test, it indicates that for every dollar lost, $2.663 was gained. Percent Profitable: Across all 465 trades, the strategy had a historical win rate of 84.09% . While a high figure, this is a historical artifact of this specific data set and settings, and should not be the sole basis for future expectations. Risk & Trade Characteristics Beyond the headline numbers, the following metrics provide deeper insight into the strategy's historical behavior. Sortino Ratio (Downside Risk): The Sortino Ratio was 6.828 . Unlike the Sharpe Ratio, this metric only measures the volatility of negative returns. A higher value, such as this one, suggests that during this test period, the strategy was highly efficient at managing downside volatility and large losing trades relative to the profits it generated. Average Trade Duration: A critical characteristic to understand is the strategy's holding period. With an average of only 2 bars per trade , this configuration operates as a very short-term, or scalping-style, system. Winning trades averaged 2 bars, while losing trades averaged 4 bars. This indicates the strategy's logic is designed to capture quick, high-probability moves and exit rapidly, either at a profit target or a stop loss. Conclusion and Final Disclaimer This backtest demonstrates one specific application of the VoVix+ framework. It highlights the strategy's behavior as a short-term system that, in this historical test on NQ1!, exhibited a high win rate and effective management of downside risk. Users are strongly encouraged to conduct their own backtests on different instruments, timeframes, and date ranges to understand how the strategy adapts to varying market structures. Past performance is not indicative of future results, and all trading involves significant risk. 🔧 THE DEVELOPMENT PHILOSOPHY: FROM VOLATILITY TO CLARITY The journey to create VoVix+ began with a simple question: "What drives major market moves?" The answer is often not a change in price direction, but a fundamental shift in market volatility. Standard indicators are reactive to price. We wanted to create a system that was predictive of market state. VoVix+ was designed to go one level deeper—to analyze the behavior, character, and momentum of volatility itself. The challenge was twofold. First, to create a robust mathematical model to quantify these abstract concepts. This led to the multi-layered analysis of ATR differentials and standard deviations. Second, to make this complex data intuitive and actionable. This drove the creation of the "Visual Universe," where abstract mathematical values are translated into geometric shapes, flows, and fields. The adaptive system was intentionally kept simple and transparent, focusing on a single, impactful parameter (time-based exits) to provide performance feedback without becoming an inscrutable "black box." The result is a tool that is both profoundly deep in its analysis and remarkably clear in its presentation. ⚠️ RISK DISCLAIMER AND BEST PRACTICES VoVix+ is an advanced analytical tool, not a guarantee of future profits. All financial markets carry inherent risk. The backtesting results shown by the strategy are historical and do not guarantee future performance. This strategy incorporates realistic commission and slippage settings by default, but market conditions can vary. Always practice sound risk management, use position sizes appropriate for your account equity, and never risk more than you can afford to lose. It is recommended to use this strategy as part of a comprehensive trading plan. This was developed specifically for Futures "The prevailing wisdom is that markets are always right. I take the opposite view. I assume that markets are always wrong. Even if my assumption is occasionally wrong, I use it as a working hypothesis." — George Soros — Dskyz, Trade with insight. Trade with anticipation.
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