Cyber Monday高达80%折扣

指标和策略

Prime-Time × Vortex (3/6/9) — Ace (clean v3)1️⃣ Prime-Time Index (PT) A bar becomes Prime-Time when the count satisfies the formula: 4·n − 3 is a perfect square This generates the sequence: 1, 3, 7, 13, 21, 31, 43, 57, 73, 91, … These are time windows where price is more likely to form: Shifts in market structure Impulses Reversals Liquidity expansions These PT bars are drawn as small circles above the candle. If labels are enabled, the counter value (n) is also shown. 2️⃣ Vortex 3/6/9 Digital-Root Timing Every bar also has a digital root, calculated from the counter: If n → digitalRoot(n) = 3, 6, or 9, the bar is considered a Vortex bar. These moments often align with: Swing highs / swing lows Micro shifts Mini-reversals Minor liquidity grabs When a Prime-Time bar is also a 3/6/9 bar → high-probability timing. These bars are highlighted in green by default. 3️⃣ Filters & Display You can customize: Anchor time → when counting begins Reset daily → restart counter each new trading day Show only 3/6/9 → hides normal PT hits Label offset → distance above the candle Color themes This makes the indicator usable on: 1Min 5Min 15Min 1H Any timeframe you want 4️⃣ How To Apply It in Trading Use it as a time confluence tool, not a signal generator. ✔ Best ways to use: Look for MSS, sweeps, OB retests, FVG reactions when they occur on or near a Prime-Time or 3/6/9 bar Expect volatility increases after PT bars Use 3/6/9 hits to anticipate internal turning points Combine with: Session High/Low Killzones (London, NYO, PM) Purge Protocol MMXM Execution ✔ Example: If price sweeps a level and prints a 3/6/9 vortex bar inside a PT window → you have a very strong timing alignment for reversal. 5️⃣ Simple Summary Feature Meaning Prime-Time Hit (PT) Major time window where price often shifts 3/6/9 Vortex Bar Micro-timing for internal swings PT + 3/6/9 together High-probability timing for entries Reset Daily Perfect for intraday models like NYO & London Anchor Time Defines the entire cycle structure
Pine Script®指标
由TIMEANDPRICEPR提供
Market Movers TrackerMarket Movers Tracker — Live Big-Move + Volume + Gap Screener (2025) The cleanest, fastest, most beautiful real-time scanner for stocks, crypto, forex — instantly tells you: • Daily / Session / Weekly % change • HUGE moves (5%+) and BIG moves (3%+) with glowing background • Volume spikes (2x+ average) with orange bar highlights • Gap-up / Gap-down detection with arrows • Live stats table (movable to any corner) • “HUGE” / “BIG” / “Normal” status with emoji • Built-in alerts for huge moves, volume spikes & gaps Perfect for: → Day traders hunting momentum → Swing traders catching breakouts → Scalpers riding volume explosions → Anyone who wants to see the hottest movers at a glance Works on ANY symbol, ANY timeframe. Zero lag. Zero repainting. Pure price + volume truth. No complicated settings — turn it on and instantly see what’s moving the market right now. Not financial advice. Just the sharpest scanner on TradingView. Made with love for the degens, apes, and momentum chads & volume junkies.
Pine Script®指标
由Timmy741提供
SCALPING PRO V2 - INTERMÉDIANT (Dashboard + TP/SL + Alerts)//@version=5 indicator("SCALPING PRO V2 - INTERMÉDIANT (Dashboard + TP/SL + Alerts)", overlay=true, max_labels_count=500) // ---------------- INPUTS ---------------- emaFastLen = input.int(9, "EMA Fast") emaSlowLen = input.int(21, "EMA Slow") atrLen = input.int(14, "ATR Length") atrMultSL = input.float(1.2, "SL = ATR *") tp1mult = input.float(1.0, "TP1 = ATR *") tp2mult = input.float(1.5, "TP2 = ATR *") tp3mult = input.float(2.0, "TP3 = ATR *") minBars = input.int(3, "Min bars between signals") showDashboard = input.bool(true, "Show Dashboard") // ---------------- INDICATORS ---------------- emaFast = ta.ema(close, emaFastLen) emaSlow = ta.ema(close, emaSlowLen) atr = ta.atr(atrLen) bullTrend = emaFast > emaSlow bearTrend = emaFast < emaSlow crossUp = ta.crossover(emaFast, emaSlow) and bullTrend crossDown = ta.crossunder(emaFast, emaSlow) and bearTrend var int lastSignal = na okSignal = na(lastSignal) or (bar_index - lastSignal > minBars) buySignal = crossUp and okSignal sellSignal = crossDown and okSignal if buySignal or sellSignal lastSignal := bar_index // ---------------- TP & SL ---------------- var float sl = na var float tp1 = na var float tp2 = na var float tp3 = na if buySignal sl := close - atr * atrMultSL tp1 := close + atr * tp1mult tp2 := close + atr * tp2mult tp3 := close + atr * tp3mult if sellSignal sl := close + atr * atrMultSL tp1 := close - atr * tp1mult tp2 := close - atr * tp2mult tp3 := close - atr * tp3mult // ---------------- ALERTS ---------------- alertcondition(buySignal, title="BUY", message="BUY Signal") alertcondition(sellSignal, title="SELL", message="SELL Signal") alertcondition(ta.cross(close, tp1), title="TP1", message="TP1 Hit") alertcondition(ta.cross(close, tp2), title="TP2", message="TP2 Hit") alertcondition(ta.cross(close, tp3), title="TP3", message="TP3 Hit") alertcondition(ta.cross(close, sl), title="SL", message="Stop Loss Hit") // ---------------- DASHBOARD ---------------- if showDashboard var table dash = table.new(position.top_right, 1, 5) if barstate.islast table.cell(dash, 0, 0, "SCALPING PRO V2", bgcolor=color.new(color.black, 0), text_color=color.white) table.cell(dash, 0, 1, "Trend: " + (bullTrend ? "Bull" : bearTrend ? "Bear" : "Neutral")) table.cell(dash, 0, 2, "ATR: " + str.tostring(atr, format.mintick)) table.cell(dash, 0, 3, "Last Signal: " + (buySignal ? "BUY" : sellSignal ? "SELL" : "NONE")) table.cell(dash, 0, 4, "EMA Fast/Slow OK")
Pine Script®指标
由chinellelynda提供
Levels S/R Boxes + Gaps + SL/TPWhat It Does: Automatically identifies and displays: 🟦 Support/Resistance zones (horizontal boxes) 🟨 Price gaps (unfilled gaps from market open/close) 🎯 Stop Loss levels (where to protect trades) 💰 Take Profit levels (where to exit trades) Purpose: Shows you exactly where price is likely to bounce, reverse, or break through. Best Practices: ✅ Trade at the boxes - Don't chase price ✅ Use SL/TP lines - Automatic risk management ✅ Wait for confirmation - Candle pattern + S/R level ✅ Gaps get filled - Trade towards yellow boxes ✅ Solid lines = stronger - Prefer 3+ touch levels ❌ Don't ignore SL - Always protect yourself ❌ Don't trade middle - Wait for S/R zones ❌ Don't fight strong levels - Respect solid boxes Settings (Quick Reference): S/R Strength: 10 (default) - Lower = more levels, Higher = fewer stronger levels Max Levels: 5 (default) - Number of S/R boxes to show Show Gaps: ON - Display yellow gap boxes Show SL/TP: ON - Display entry/exit suggestions
Pine Script®指标
由ognenmitev提供
Classic Wave: The Easy WayClassic Wave is a simple strategy with few rules and no over-optimization. Despite its simplicity, it is backed by a nearly century-long historical track record, delivering excellent returns on the weekly chart of the SPX (TVC). I also recommend observing its strong performance on the SPY (weekly), which is the perfect instrument for executing this strategy with futures in the future. Strategy Rules and Parameters When a bullish candle closes above the 20-period EMA, we place the stop-loss below the low of that candle and target a risk-reward ratio of 1:1. A second, more profitable variant is to change the risk-reward ratio in the code to 2:1. -Total capital: $10,000 -We use 10% of the total capital per trade. -Commissions: 0.1% per trade. The code construction is simple and very well detailed within the script itself. Risk-Reward Ratio 2:1 Using a 2:1 risk-reward ratio reduces the win rate but significantly increases profitability. Across the full historical data of the SPX index (weekly), the system would have generated 236 trades, with a win rate of 51.27% and a profit factor of 2.53. From January 1, 2023, to November 28, 2025, the system would have generated 5 trades, with an 80% win rate and a profit factor of 9.244. What makes this system so good? -It takes advantage of the long-term bullish bias of U.S. stock indices and traditional markets. -It filters out a lot of noise thanks to the weekly timeframe. -It uses simple parameters with no over-optimization. Final Notes: This strategy has consistently outperformed the returns offered by most traditional funds over time, with fewer drawdowns and significantly less stress. I hope you like it.
Pine Script®策略
由Especulador96提供
1
Mean-Reversion with CooldownThis strategy requires no indicators or fundamental analysis. It is designed for longer-term positions and works especially well on unleveraged instruments with strong long-term upward trends, such as precious metals. Feel free to experiment with different timeframes — I’ve found that 1-hour charts work particularly well for cryptocurrencies. The idea is to filter out ongoing bear phases as effectively as possible and capitalize on long-term bull runs. The script implements an idea that came to me in a state of complete sleep deprivation: open a random long position with a fixed take-profit (TP) and a tight stop-loss (SL). If the TP is hit — great, we simply try again. If the SL is triggered — too bad, we pause for a while and then try again. ## Cooldown (Waiting) Mechanism The waiting mechanism is simple: the more consecutive SL hits we get, the longer we wait before opening the next trade. The waiting time is measured in closed candles, and thus depends on the timeframe you are using. ## Two cooldown calculation modes are currently supported: ### 1. FIBONACCI The cooldown follows the Fibonacci sequence, based on the number of consecutive losses: 1st loss → wait 1 bar 2nd loss → wait 1 bar 3rd loss → wait 2 or 3 bars (depending on definition) 4th loss → wait 3 or 5 bars etc. ### 2. POWER OF TWO The cooldown increases exponentially: 1st loss → wait 2 bars 2nd loss → wait 4 bars 3rd loss → wait 8 bars 4th loss → wait 16 bars and so on, using the formula 2ⁿ. ## Configurable Parameters ### Cooldown Pause Calculation The settings allow you to define the SL and TP as percentages of the position value. The "Cooldown Pause Calculation" option determines how the next cooldown duration is computed after a losing trade. The system keeps track of how many consecutive losses have occurred since the last profitable trade. That counter is then used to compute how many bars we must wait before opening the next position. ### Maximum Cooldown The "Max Cooldown Candles" setting defines the maximum number of bars we are allowed to wait before placing a new trade. This prevents the strategy from “locking itself out” for too long and mitigates the fear of missing out (FOMO). Once the cooldown duration reaches this maximum, the system essentially wraps around and starts the progression again. In the script, this is handled using a simple modulo operation based on the chosen maximum.
Pine Script®策略
由jannisMCMXCV提供
Candlestick PatternsWhat It Does: Automatically identifies and displays: 🟢 16+ Bullish patterns (Hammer, Engulfing ↑, Morning Star, etc.) 🔴 Bearish patterns (Shooting Star, Engulfing ↓, Evening Star, etc.) 🔵 Break & Retest signals (70-80% win rate setups) ⚪ Neutral patterns (Doji, Spinning Top - indecision) 🎯 Automatic alerts for all major patterns Purpose: Shows you exactly when reversals are likely and identifies the highest-probability entry points (Break & Retest).Key Patterns:Bullish (Green labels above/below): HAMMER - Long lower wick, small body (reversal from bottom) ENGULF ↑ - Big green candle swallows previous red (strong reversal) MORNING★ - Three candles: red, doji, green (major bottom) 3 BULLS - Three consecutive green candles (strong momentum) PIERCE - Green closes above 50% of previous red RETEST ↑ (BEST!) - Price broke resistance, pulled back, bounced (cyan circle) Bearish (Red labels above/below): SHOOT★ - Long upper wick, small body (reversal from top) ENGULF ↓ - Big red candle swallows previous green (strong reversal) EVENING★ - Three candles: green, doji, red (major top) 3 BEARS - Three consecutive red candles (strong momentum) DARK☁ - Red closes below 50% of previous green RETEST ↓ (BEST!) - Price broke support, bounced back, rejected (orange circle) Neutral: DOJI - Indecision, potential reversal coming SPINNING TOP - Small body, long wicks (indecision) Best Practices:✅ Wait for confirmation - Don't trade pattern alone, check context ✅ Combine patterns - Retest + Candlestick = 80%+ win rate ✅ Check trend - Bullish patterns in uptrend work best ✅ Volume matters - Larger patterns with volume = stronger ✅ Fresh retests - First retest after break = highest probability ✅ Use alerts - Set alerts for Engulfing, Retest, Morning/Evening Star ✅ Size matters - Bigger candles = stronger signals❌ Don't trade every pattern - Quality over quantity ❌ Don't ignore context - Hammer at resistance = weak signal ❌ Don't trade against trend - Bearish in strong uptrend = risky ❌ Don't skip stop loss - Always protect your trades ❌ Don't trade small patterns - Need clear, visible patterns
Pine Script®指标
由ognenmitev提供
Dynamic SMA Trend System [Multi-Stage Risk Engine]Description: This script implements a robust Trend Following strategy based on a multiple Simple Moving Average (SMA) crossover logic (25, 50, 100, 200). What sets this strategy apart is its advanced "4-Stage Risk Engine" and a smart "High-Water Mark" Re-Entry system, designed to protect profits during parabolic moves while filtering out chop during sideways markets. How it works: The strategy operates on three core pillars: Trend Identification, Dynamic Risk Management, and Momentum Re-Entry. 1. Entry Logic (Trend Identification) The script looks for crossovers at different trend stages to capture early reversals as well as established trends: Short-Term: SMA 25 crosses over SMA 50. Mid-Term: SMA 50 crosses over SMA 100. Macro-Trend: SMA 100 crosses over SMA 200. 2. The 4-Stage Risk Engine (Dynamic Stop Loss) Instead of a static Stop Loss, this strategy uses a progressive system that adapts as the price increases: Stage 1 (Protection): Starts with a fixed Stop Loss (default -10%) to give the trade room to breathe. Stage 2 (Break-Even): Once the price rises by 12%, the Stop is moved to trailing mode (10% distance), effectively securing a near break-even state. Stage 3 (Profit Locking): At 25% profit, the trailing stop tightens to 8% to lock in gains. Stage 4 (Parabolic Mode): At 40% profit, the trailing stop tightens further to 5% to capture the peak of parabolic moves. 3. Dual Exit Mechanism The strategy exits a position if EITHER of the following happens: Stop Loss Hit: Price falls below the dynamic red line (Risk Engine). Dead Cross: The trend structure breaks (e.g., SMA 25 crosses under SMA 50), signaling a momentum loss even if the Stop Loss wasn't hit. 4. "High-Water Mark" Re-Entry To avoid "whipsaws" in choppy markets, the script does not re-enter immediately after a stop-out. It marks the highest price of the previous trade (Green Dotted Line). A Re-Entry only occurs if the price breaks above this previous high (showing renewed strength) AND the long-term trend is bullish (Price > SMA 200). Visuals: SMAs: 25 (Yellow), 50 (Orange), 100 (Blue), 200 (White). Red Line: Visualizes the dynamic Stop Loss level. Green Dots: Visualizes the target price needed for a valid re-entry. Settings: All parameters (SMA lengths, Stop Loss percentages, Staging triggers) are fully customizable in the settings menu to fit different assets (Crypto, Stocks, Forex) and timeframes.
Pine Script®策略
由oppliger79提供
Relative Volume EMA (RVOL)Relative Volume EMA (RVOL) measures the current bar’s volume relative to its typical volume over a selected lookback period. It helps traders identify whether a price move is supported by real participation or if it’s occurring on weak, low-quality volume. This version uses: RVOL = Current Volume ÷ Volume EMA Volume EMA Length: adjustable Signal Threshold: a customizable horizontal line (default = 1.2) How to Use 1. RVOL > 1.2 → High-Quality Momentum A value above 1.2 indicates that the current bar has at least 20% more volume than normal, suggesting: Strong conviction Algorithmic activity Momentum-backed breakout or breakdown Higher probability trend continuation These bars are ideal for confirming entries after a technical setup (e.g., pullback, engulfing pattern, Ichimoku trend confirmation, etc.). 2. RVOL < 1.0 → Weak or Low-Quality Move When RVOL is below 1.0: Volume is below average Moves are more likely to fail or reverse Breakouts are unreliable Triggers lack institutional participation These bars are best avoided for trade entries. Why This Indicator Is Useful In many strategies, price alone is not enough. RVOL acts as a filter to ensure that your signals occur during times when the market is actually active and committed. Typical use cases: Confirm trend-following entries Validate pullbacks and breakout candles Filter out low-volume chop Identify session-based volume surges Improve risk-to-reward quality by entering only during true momentum Recommended Settings EMA Length: 20 Threshold Line: 1.2 Works well on Forex, Crypto, and Indices Best used on 15m, 30m, 1H, and 4H charts
Pine Script®指标
由FXLoungeIN提供
️Omega RatioThe Omega Ratio is a risk-return performance measure of an investment asset, portfolio, or strategy. It is defined as the probability-weighted ratio, of gains versus losses for some threshold return target. The ratio is an alternative for the widely used Sharpe ratio and is based on information the Sharpe ratio discards. █ OVERVIEW As we have mentioned many times, stock market returns are usually not normally distributed. Therefore the models that assume a normal distribution of returns may provide us with misleading information. The Omega Ratio improves upon the common normality assumption among other risk-return ratios by taking into account the distribution as a whole. █ CONCEPTS Two distributions with the same mean and variance, would according to the most commonly used Sharpe Ratio suggest that the underlying assets of the distribution offer the same risk-return ratio. But as we have mentioned in our Moments indicator, variance and standard deviation are not a sufficient measure of risk in the stock market since other shape features of a distribution like skewness and excess kurtosis come into play. Omega Ratio tackles this problem by employing all four Moments of the distribution and therefore taking into account the differences in the shape features of the distributions. Another important feature of the Omega Ratio is that it does not require any estimation but is rather calculated directly from the observed data. This gives it an advantage over standard statistical estimators that require estimation of parameters and are therefore sampling uncertainty in its calculations. █ WAYS TO USE THIS INDICATOR Omega calculates a probability-adjusted ratio of gains to losses, relative to the Minimum Acceptable Return (MAR). This means that at a given MAR using the simple rule of preferring more to less, an asset with a higher value of Omega is preferable to one with a lower value. The indicator displays the values of Omega at increasing levels of MARs and creating the so-called Omega Curve. Knowing this one can compare Omega Curves of different assets and decide which is preferable given the MAR of your strategy. The indicator plots two Omega Curves. One for the on chart symbol and another for the off chart symbol that u can use for comparison. When comparing curves of different assets make sure their trading days are the same in order to ensure the same period for the Omega calculations. Value interpretation: Omega<1 will indicate that the risk outweighs the reward and therefore there are more excess negative returns than positive. Omega>1 will indicate that the reward outweighs the risk and that there are more excess positive returns than negative. Omega=1 will indicate that the minimum acceptable return equals the mean return of an asset. And that the probability of gain is equal to the probability of loss. █ FEATURES • "Low-Risk security" lets you select the security that you want to use as a benchmark for Omega calculations. • "Omega Period" is the size of the sample that is used for the calculations. • “Increments” is the number of Minimal Acceptable Return levels the calculation is carried on. • “Other Symbol” lets you select the source of the second curve. • “Color Settings” you can set the color for each curve.
Pine Script®指标
由Motgench提供
Historical Volatility EstimatorsHistorical volatility is a statistical measure of the dispersion of returns for a given security or market index over a given period. This indicator provides different historical volatility model estimators with percentile gradient coloring and volatility stats panel. █ OVERVIEW There are multiple ways to estimate historical volatility. Other than the traditional close-to-close estimator. This indicator provides different range-based volatility estimators that take high low open into account for volatility calculation and volatility estimators that use other statistics measurements instead of standard deviation. The gradient coloring and stats panel provides an overview of how high or low the current volatility is compared to its historical values. █ CONCEPTS We have mentioned the concepts of historical volatility in our previous indicators, Historical Volatility, Historical  Volatility  Rank, and Historical  Volatility  Percentile. You can check the definition of these scripts. The basic calculation is just the sample standard deviation of log return scaled with the square root of time. The main focus of this script is the difference between volatility models. Close-to-Close HV Estimator: Close-to-Close is the traditional historical volatility calculation. It uses sample standard deviation. Note: the TradingView build in historical volatility value is a bit off because it uses population standard deviation instead of sample deviation. N – 1 should be used here to get rid of the sampling bias. Pros:   • Close-to-Close HV estimators are the most commonly used estimators in finance. The calculation is straightforward and easy to understand. When people reference historical volatility, most of the time they are talking about the close to close estimator. Cons:   • The Close-to-close estimator only calculates volatility based on the closing price. It does not take account into intraday volatility drift such as high, low. It also does not take account into the jump when open and close prices are not the same.   • Close-to-Close weights past volatility equally during the lookback period, while there are other ways to weight the historical data.   • Close-to-Close is calculated based on standard deviation so it is vulnerable to returns that are not normally distributed and have fat tails. Mean and Median absolute   deviation makes the historical volatility more stable with extreme values. Parkinson Hv Estimator:   • Parkinson was one of the first to come up with improvements to historical volatility calculation. • Parkinson suggests using the High and Low of each bar can represent volatility better as it takes into account intraday volatility. So Parkinson HV is also known as Parkinson High Low HV. • It is about 5.2 times more efficient than Close-to-Close estimator. But it does not take account into jumps and drift. Therefore, it underestimates volatility. Note: By Dividing the Parkinson Volatility by Close-to-Close volatility you can get a similar result to Variance Ratio Test. It is called the Parkinson number. It can be used to test if the market follows a random walk. (It is mentioned in Nassim Taleb's Dynamic Hedging book but it seems like he made a mistake and wrote the ratio wrongly.) Garman-Klass Estimator:   • Garman Klass expanded on Parkinson’s Estimator. Instead of Parkinson’s estimator using high and low, Garman Klass’s method uses open, close, high, and low to find the minimum variance method.   • The estimator is about 7.4 more efficient than the traditional estimator. But like Parkinson HV, it ignores jumps and drifts. Therefore, it underestimates volatility. Rogers-Satchell Estimator:   • Rogers and Satchell found some drawbacks in Garman-Klass’s estimator. The Garman-Klass assumes price as Brownian motion with zero drift.   • The Rogers Satchell Estimator calculates based on open, close, high, and low. And it can also handle drift in the financial series.   • Rogers-Satchell HV is more efficient than Garman-Klass HV when there’s drift in the data. However, it is a little bit less efficient when drift is zero. The estimator doesn’t handle jumps, therefore it still underestimates volatility. Garman-Klass Yang-Zhang extension:   • Yang Zhang expanded Garman Klass HV so that it can handle jumps. However, unlike the Rogers-Satchell estimator, this estimator cannot handle drift. It is about 8 times more efficient than the traditional estimator.   • The Garman-Klass Yang-Zhang extension HV has the same value as Garman-Klass when there’s no gap in the data such as in cryptocurrencies. Yang-Zhang Estimator:   • The Yang Zhang Estimator combines Garman-Klass and Rogers-Satchell Estimator so that it is based on Open, close, high, and low and it can also handle non-zero drift. It also expands the calculation so that the estimator can also handle overnight jumps in the data.   • This estimator is the most powerful estimator among the range-based estimators. It has the minimum variance error among them, and it is 14 times more efficient than the close-to-close estimator. When the overnight and daily volatility are correlated, it might underestimate volatility a little.   • 1.34 is the optimal value for alpha according to their paper. The alpha constant in the calculation can be adjusted in the settings. Note: There are already some volatility estimators coded on TradingView. Some of them are right, some of them are wrong. But for Yang Zhang Estimator I have not seen a correct version on TV. EWMA Estimator: • EWMA stands for Exponentially Weighted Moving Average. The Close-to-Close and all other estimators here are all equally weighted.   • EWMA weighs more recent volatility more and older volatility less. The benefit of this is that volatility is usually autocorrelated. The autocorrelation has close to exponential decay as you can see using an Autocorrelation Function indicator on absolute or squared returns. The autocorrelation causes volatility clustering which values the recent volatility more. Therefore, exponentially weighted volatility can suit the property of volatility well.   • RiskMetrics uses 0.94 for lambda which equals 30 lookback period. In this indicator Lambda is coded to adjust with the lookback. It's also easy for EWMA to forecast one period volatility ahead.   • However, EWMA volatility is not often used because there are better options to weight volatility such as ARCH and GARCH. Adjusted Mean Absolute Deviation Estimator:   • This estimator does not use standard deviation to calculate volatility. It uses the distance log return is from its moving average as volatility.   • It’s a simple way to calculate volatility and it’s effective. The difference is the estimator does not have to square the log returns to get the volatility. The paper suggests this estimator has more predictive power.   • The mean absolute deviation here is adjusted to get rid of the bias. It scales the value so that it can be comparable to the other historical volatility estimators.   • In Nassim Taleb’s paper, he mentions people sometimes confuse MAD with standard deviation for volatility measurements. And he suggests people use mean absolute deviation instead of standard deviation when we talk about volatility. Adjusted Median Absolute Deviation Estimator:   • This is another estimator that does not use standard deviation to measure volatility.   • Using the median gives a more robust estimator when there are extreme values in the returns. It works better in fat-tailed distribution.   • The median absolute deviation is adjusted by maximum likelihood estimation so that its value is scaled to be comparable to other volatility estimators. █ FEATURES   • You can select the volatility estimator models in the Volatility Model input   • Historical Volatility is annualized. You can type in the numbers of trading days in a year in the Annual input based on the asset you are trading.   • Alpha is used to adjust the Yang Zhang volatility estimator value.   • Percentile Length is used to Adjust Percentile coloring lookbacks.   • The gradient coloring will be based on the percentile value (0- 100). The higher the percentile value, the warmer the color will be, which indicates high volatility. The lower the percentile value, the colder the color will be, which indicates low volatility.   • When percentile coloring is off, it won’t show the gradient color.   • You can also use invert color to make the high volatility a cold color and a low volatility high color. Volatility has some mean reversion properties. Therefore when volatility is very low, and color is close to aqua, you would expect it to expand soon. When volatility is very high, and close to red, you would it expect it to contract and cool down.   • When the background signal is on, it gives a signal when HVP is very low. Warning there might be a volatility expansion soon. • You can choose the plot style, such as lines, columns, areas in the plotstyle input.   • When the show information panel is on, a small panel will display on the right.   • The information panel displays the historical volatility model name, the 50th percentile of HV, and HV percentile. 50 the percentile of HV also means the median of HV. You can compare the value with the current HV value to see how much it is above or below so that you can get an idea of how high or low HV is. HV Percentile value is from 0 to 100. It tells us the percentage of periods over the entire lookback that historical volatility traded below the current level. Higher HVP, higher HV compared to its historical data. The gradient color is also based on this value. █ HOW TO USE If you haven’t used the hvp indicator, we suggest you use the HVP indicator first. This indicator is more like historical volatility with HVP coloring. So it displays HVP values in the color and panel, but it’s not range bound like the HVP and it displays HV values. The user can have a quick understanding of how high or low the current volatility is compared to its historical value based on the gradient color. They can also time the market better based on volatility mean reversion. High volatility means volatility contracts soon (Move about to End, Market will cooldown), low volatility means volatility expansion soon (Market About to Move). █ FINAL THOUGHTS HV vs ATR The above volatility estimator concepts are a display of history in the quantitative finance realm of the research of historical volatility estimations. It's a timeline of range based from the Parkinson Volatility to Yang Zhang volatility. We hope these descriptions make more people know that even though ATR is the most popular volatility indicator in technical analysis, it's not the best estimator. Almost no one in quant finance uses ATR to measure volatility (otherwise these papers will be based on how to improve ATR measurements instead of HV). As you can see, there are much more advanced volatility estimators that also take account into open, close, high, and low. HV values are based on log returns with some calculation adjustment. It can also be scaled in terms of price just like ATR. And for profit-taking ranges, ATR is not based on probabilities. Historical volatility can be used in a probability distribution function to calculated the probability of the ranges such as the Expected Move indicator. Other Estimators There are also other more advanced historical volatility estimators. There are high frequency sampled HV that uses intraday data to calculate volatility. We will publish the high frequency volatility estimator in the future. There's also ARCH and GARCH models that takes volatility clustering into account. GARCH models require maximum likelihood estimation which needs a solver to find the best weights for each component. This is currently not possible on TV due to large computational power requirements. All the other indicators claims to be GARCH are all wrong.
Pine Script®指标
由Motgench提供
Zonas de Liquidez Pro + Puntos de GiroRequirements for marking 💧:✅ High crosses the zone✅ Close returns inside (false breakout / fakeout)✅ Volume is 20% greater than the average✅ Occurs within the last 10 bars(Note: This last requirement is stated in the text but not explicitly in the code snippet provided)📚 Psychology Behind the SweepWho lost money?Traders with stops placed too tightlyBuyers who entered "on the breakout"Bots with automatic orders placed aboveWho made money?Smart Money / InstitutionsThey sold at a high priceThey hunted for liquidity before moving the priceThey know where retail stops are located🎯 How to Use the Drops in Your TradingGolden Rule:💧 near a strong zone + Multiple rejections = PROBABLE REVERSALStrategy:See 💧 at resistance → Look for SHORTSee 💧 at support → Look for LONGPrice returns to the swept zone → High-probability setupStop beyond the sweep high/low → ProtectionPractical Example:If you see 💧 LIQ at $111,263 (resistance)→ Wait for bearish rejection→ Entry: Sell at $110,800→ Stop: $111,500 (above the sweep high)→ Target: Next support level⚠️ Common Mistakes❌ Mistake 1: Trading the breakoutPrice breaks $111k → "It's going to the moon!" → Buy💧 LIQ appears → It was a trap → Drop → Loss✅ Correct Approach:Price breaks $111k → Check if there is 💧 LIQ💧 appears → "It's a trap" → Wait for rejection → Sell❌ Mistake 2: Ignoring the volumeNot all sweeps are equal.Sweeps with high volume are more reliable.No volume = it could be noise.🎓 Ultra-Fast SummaryElementMeaning💧 LIQLiquidity sweep detectedAt ResistanceBullish trap → Prepare for a shortAt SupportBearish trap → Prepare for a longWith High VolumeMore reliable signalNear Strong Zone High probability of reversal🔥 The Magic of Your IndicatorScenarioWithout this IndicatorWith this IndicatorAction"The price broke $111k, I'm buying!""There is 💧 LIQ + zone + rejections → It's a trap."ResultYou loseYou avoid a loss or gain on the short
Pine Script®指标
由acgcapital提供
NQUSB Sector Industry Stocks Strength A Comprehensive Multi-Industry Performance Comparison Tool The complete Pine Script code and supporting Python automation scripts are available on GitHub: GitHub Repository: github.com Original idea from by www.tradingview.com ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ ═══ WHAT'S NEW ═══ 4-Level Hierarchical Navigation: Primary: All 11 NQUSB sectors (NQUSB10, NQUSB15, NQUSB20, etc.) Secondary (Default): Broad sectors like Technology, Energy Tertiary: Industry groups within sectors Quaternary: Individual stocks within industries (37 semiconductors) Enhanced Stock Coverage: 1,176 total stocks across 129 industries 37 semiconductor stocks Market-cap weighted selection: 60% tech / 35% others Range: 1-37 stocks per industry ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ ═══ CORE FEATURES ═══ 1. Drill-Down/Drill-Up Navigation View NVDA at different granularity levels: Quaternary: ● NVDA ranks #3 of 37 semiconductors Tertiary: ✓ Semiconductors at 85% (strongest in tech hardware) Secondary: ✓ Tech Hardware at 82% (stronger than software) Primary: ✓ Technology at 78% (#1 sector overall) Insight: One indicator, one stock, four perspectives - instantly see if strength is stock-specific, industry-specific, or sector-wide. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 2. Visual Current Stock Identification Violet Markers - Instant Recognition: ● (dot) marker when current stock is in top N performers ✕ (cross) marker when current stock is below top N Violet color (#9C27B0) on both symbol and value labels Example: "NVDA ● ranks #3 of 37" ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 3. Rank Display in Title Dynamic title shows performance context: "Semiconductors (RS Rating - 3 Months) | NVDA ranks #3 of 37" #1 = Best performer, higher number = lower rank Total adjusts if current stock auto-added ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 4. Auto-Add Current Stock Always Included: Current stock automatically added if not in predefined list Example: Viewing PRSO → "PRSO ranks #37 of 39 ✕" Works for any stock - from NVDA to obscure small-caps Violet markers ensure visibility even when ranked low ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ ═══ DUAL PERFORMANCE METRICS ═══ RS Rating (Relative Strength): Normalized strength score 1-99 Compare stocks across different price ranges Default benchmark: SPX % Return: Simple percentage price change Direct performance comparison 11 Time Periods: 1 Week, 2 Weeks, 1 Month, 2 Months, 3 Months (Default) , 6 Months, 1 Year, YTD, MTD, QTD, Custom (1-500 days) Result: 22 analytical combinations (2 metrics × 11 periods) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ ═══ USE CASES ═══ Sector Rotation Analysis: Is NVDA's strength semiconductors-specific or tech-wide? Drill through all 4 levels to find answer Identify which industry groups are leading/lagging Finding Hidden Gems: JPM ranks #3 of 13 in Major Banks But Financials sector weak overall (68%) = Relative strength play in weak sector Cross-Industry Comparison: 129 industries covered Market-wide scan capability Find strongest performers across all sectors ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ ═══ TECHNICAL SPECIFICATIONS ═══ V32 Stats: Total Industries: 129 Total Stocks: 1,176 File Size: 82,032 bytes (80.1 KB) Request Limit: 39 max (Semiconductors), 10-16 typical Granularity Levels: 4 (Primary → Quaternary) Smart Stock Allocation: Technology industries: 60% coverage Other industries: 35% coverage Market-cap weighted selection Formula: MIN(39, MAX(5, CEILING(total × percentage))) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ ═══ KEY ADVANTAGES ═══ vs. Single Industry Tools: ✓ 129 industries vs 1 ✓ Market-wide perspective ✓ Hierarchical navigation ✓ Sector rotation detection vs. Manual Comparison: ✓ No ETF research needed ✓ Instant visual markers ✓ Automatic ranking ✓ One-click drill-down ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ For complete documentation, Python automation scripts, and CSV data files: github.com Version: V32 Last Updated: 2025-11-30 Pine Script Version: v5
Pine Script®指标
由ama0000提供
@Unwind Pressure Detector - AUDITED v3.0SQUEEZE → UNWIND PRESSURE DETECTOR v3.0 The first indicator that not only finds oversold squeezes… but tells you exactly when the move is exhausting and it’s time to take profits. Fully audited, clean Pine Script v6, zero repainting, zero lag tricks. WHAT IT DOES • Detects high-probability squeeze setups (RSI + Volume + VIX + Trend confluence) • Scores pressure from 0–115 with dynamic sensitivity (Low to Extreme) • Identifies CRITICAL zones where explosive moves are most likely • Most importantly → flags the UNWIND when trapped shorts are finally covering and the rally is running out of fuel (perfect profit-taking signal) FEATURES • Real-time pressure dashboard (top-right) • Color-coded background zones (Critical = red, High = orange) • Smart anti-spam labels with ATR offset • Three alert conditions: → Squeeze Setup → Critical Squeeze → Unwind / Take Profit • Works on all markets & timeframes (stocks, forex, crypto, futures) WHY THIS VERSION IS DIFFERENT - v3.0 completely rewrote the unwind logic (now requires rally + sharp pressure drop) - No false unwinds during strong trends - Built for real trading, not just pretty screenshots 100% Open Source • Fully commented • Free to modify & rep, I want this in the public library forever. Created with love for the TradingView community Drop a ♥ and follow if you find it useful! #squeeze #ttmsqueeze #unwind #volatility #vix #takeprofits #smartmoney
Pine Script®指标
由Timmy741提供
Psychological levels [Kodologic] Psychological levels Markets are not random, they are driven by human psychology and algorithmic order flow. A well-known phenomenon in trading is the "Whole Number Bias" — the tendency for price to react significantly at clean, round numbers (e.g., Bitcoin at $95,000 or EURUSD at 1.0500). Manually drawing horizontal lines at every round number is tedious, clutters your object tree, and distracts you from analyzing price action. Psychological levels Numbers is a workflow utility designed to solve this problem. It automatically projects a clean, customizable grid of key price levels onto your chart, helping you instantly identify areas where liquidity and orders are likely to cluster. Why This Indicator Helps Traders : Professional traders know that "00" and "50" levels act as magnets for price. Here is how this tool assists in your analysis: 1. Institutional Footprints : Large institutions and bank algorithms often execute orders at whole numbers to simplify accounting. This script highlights these potential liquidity zones automatically. 2. Support & Resistance Discovery: You will often notice price wicking or reversing exactly on these grid lines. This helps in spotting natural support and resistance without needing complex technical analysis. 3. Cognitive Load Reduction: Instead of calculating where the next "major level" is, the grid is visually present, allowing you to focus on candlestick patterns and market structure. Features : Dynamic Calculation : The grid updates automatically as price moves, you never have to redraw lines. Zero Clutter : The lines are drawn using code, meaning they do not appear in your manual drawing tools list or clutter your object tree. Fully Customizable Step : You define what constitutes a "Round Number" for your specific asset class (Forex, Crypto, Indices, or Stocks). Visual Control : Adjust line styles (Solid, Dotted, Dashed), colors, and transparency to keep your chart aesthetic and readable. How to Use in Your Strategy : 1. Target Setting (Take Profit) If you are in a long position, use the next upper grid line as a logical Take Profit area. Price often gravitates toward these whole numbers before reversing or consolidating. 2. Stop Loss Placement Avoid placing Stop Losses exactly on a round number, as these are often "stop hunted." Instead, use the grid to visualize the level and place your stop slightly *below* or *above* the round number for better protection. 3. Confluence Trading Do not use these lines in isolation. Look for Confluence : Example: If a Fibonacci 61.8% level lines up exactly with a Round Number grid line, that level becomes a high-probability reversal zone. Settings Guide (Important) Since every asset is priced differently, you must adjust the "levels Step Size" to match your instrument: Forex (e.g., EURUSD, GBPUSD): Set Step Size to `0.0050` (50 pips) or `0.0100` (100 pips). Crypto (e.g., BTCUSD): Set Step Size to `500` or `1000`. Indices (e.g., US30, SPX500): Set Step Size to `100` or `500`. Gold (XAUUSD):** Set Step Size to `10`. Disclaimer: This tool is for educational and visual aid purposes only. It does not provide buy or sell signals. Always manage your risk.
Pine Script®指标
由Kodologic提供
@Complete Squeeze Cycle Detector v2.0 FINALDescription: The Complete Squeeze Cycle Detector identifies and tracks the full lifecycle of squeeze formations, from pre-squeeze consolidation through active squeeze periods to squeeze completion. The indicator systematically detects the characteristic conditions that precede and accompany squeeze events. The indicator monitors multiple factors associated with squeeze development including: • Volatility compression relative to recent volume activity • Elevated market stress conditions as measured by VIX levels • Momentum compression through rate of change measurements across multiple time periods • Alignment of multiple exponential moving averages indicating consolidation The squeeze cycle is classified into three distinct phases: Pre-Squeeze Setup, Active Squeeze, and Squeeze Complete. Each phase is identified based on threshold levels of multiple compression metrics, with adjustable sensitivity settings to control the strictness of detection. The indicator provides visual identification of each phase through labels, background coloring, and an optional dashboard, allowing users to distinguish between the preparation phase where volatility contracts, the active squeeze phase where compression reaches critical levels, and the completion phase where the squeeze releases and directional movement resumes. This systematic approach enables users to identify squeeze formations throughout their complete development cycle rather than focusing only on the breakout phase.
Pine Script®指标
由Timmy741提供