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False Breakout (Expo)█ Overview False Breakout (Expo) is an indicator that detects false breakouts in real-time. A false breakout occurs when the price moves through a certain level but doesn't continue to accelerate in that direction. This is because the price does not have enough momentum and the buying interest at this level is not high enough to keep pushing the price in that direction. Instead, the market reverses! All breakout traders are now forced to close their positions at a loss. However, contrarian traders that have identified this false breakout do get a perfect entry for a great reversal trade! False Breakout is one of the most important price action trading patterns to learn because it can help traders understand whether a breakout is valid or false. █ How to use Identify False Breakouts Identify Reversal trades ----------------- Disclaimer The information contained in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell any securities of any type. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information. All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs. My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!
Pine Script® göstergesi
Zeiierman tarafından
59
American Approximation: Barone-Adesi and Whaley [Loxx]American Approximation: Barone-Adesi and Whaley is an American Options pricing model. This indicator also includes numerical greeks. You can compare the output of the American Approximation to the Black-Scholes-Merton value on the output of the options panel. An American option can be exercised at any time up to its expiration date. This added freedom complicates the valuation of American options relative to their European counterparts. With a few exceptions, it is not possible to find an exact formula for the value of American options. Several researchers have, however, come up with excellent closed-form approximations. These approximations have become especially popular because they execute quickly on computers compared to numerical techniques. At the end of the chapter, we look at closed-form solutions for perpetual American options. The Barone-Adesi and Whaley Approximation The quadratic approximation method by Barone-Adesi and Whaley (1987) can be used to price American call and put options on an underlying asset with cost-of-carry rate b. When b > r, the American call value is equal to the European call value and can then be found by using the generalized Black-Scholes-Merton (BSM) formula. The model is fast and accurate for most practical input values. American Call C(S, C, T) = Cbsm(S, X, T) + A2 / (S/S*)^q2 ... when S < S* C(S, C, T) = S - X ... when S >= S* where Cbsm(S, X, T) is the general Black-Scholes-Merton call formula, and A2 = S* / q2 * (1 - e^((b - r) * T)) * N(d1(S*))) d1(S) = (log(S/X) + (b + v^2/2) * T) / (v * T^0.5) q2 = (-(N-1) + ((N-1)^2 + 4M/K))^0.5) / 2 M = 2r/v^2 N = 2b/v^2 K = 1 - e^(-r*T) American Put P(S, C, T) = Pbsm(S, X, T) + A1 / (S/S**)^q1 ... when S < S** P(S, C, T) = X - S .... when S >= S** where Pbsm(S, X, T) is the generalized BSM put option formula, and A1 = -S** / q1 * (1 - e^((b - r) * T)) * N(-d1(S**))) q1 = (-(N-1) - ((N-1)^2 + 4M/K))^0.5) / 2 where S* is the critical commodity price for the call option that satisfies S* - X = c(S*, X, T) + (1 - e^((b - r) * T) * N(d1(S*))) * S* * 1/q2 These equations can be solved by using a Newton-Raphson algorithm. The iterative procedure should continue until the relative absolute error falls within an acceptable tolerance level. See code for details on the Newton-Raphson algorithm. Inputs S = Stock price. K = Strike price of option. T = Time to expiration in years. r = Risk-free rate c = Cost of Carry V = Variance of the underlying asset price cnd1(x) = Cumulative Normal Distribution cbnd3(x) = Cumulative Bivariate Normal Distribution nd(x) = Standard Normal Density Function convertingToCCRate(r, cmp) = Rate compounder Numerical Greeks or Greeks by Finite Difference Analytical Greeks are the standard approach to estimating Delta, Gamma etc... That is what we typically use when we can derive from closed form solutions. Normally, these are well-defined and available in text books. Previously, we relied on closed form solutions for the call or put formulae differentiated with respect to the Black Scholes parameters. When Greeks formulae are difficult to develop or tease out, we can alternatively employ numerical Greeks - sometimes referred to finite difference approximations. A key advantage of numerical Greeks relates to their estimation independent of deriving mathematical Greeks. This could be important when we examine American options where there may not technically exist an exact closed form solution that is straightforward to work with. (via VinegarHill FinanceLabs) Things to know Only works on the daily timeframe and for the current source price. You can adjust the text size to fit the screen
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loxx tarafından
TradingView Alerts (Expo)█ Overview The TradingView inbuilt alert feature inspires this alert tool. TradingView Alerts (Expo) enables traders to set alerts on any indicator on TradingView, both public, protected, and invite-only scripts (if you are granted access). In this way, traders can set the alerts they want for any indicator they have access to. This feature is highly needed since many indicators on TradingView do not have the particular alert the trader looks for, this alert tool solves that problem and lets everyone create the alert they need. Many predefined conditions are included, such as "crossings," "turning up/down," "entering a channel," and much more. █ TradingView alerts TradingView alerts are a popular and convenient way of getting an immediate notification when the asset meets your set alert criteria. It helps traders to stay updated on the assets and timeframe they follow. █ Alert table Keep track of the average amount of alerts that have been triggered per day, per month, and per week. It helps traders to understand how frequently they can expect an alert to trigger. █ Predefined alerts types Crossing The Crossing alert is triggered when the source input crosses (up or down) from the selected price or value. Crossing Down / Crossing Up The Crossing Down alert is triggered when the source input crosses down from the selected price or value. The Crossing Up alert is triggered when the source input crosses up from the selected price or value. Greater Than / Less Than The Greater Than alert is triggered when the source input reaches the selected value or price. The Less Than alert is triggered when the source input reaches the selected value or price. Entering Channel / Exiting Channel The Entering Channel alert is triggered when the source input enters the selected channel value. The Exiting Channel alert is triggered when the source input exits the selected channel value. Notice that this alert only works if you have selected "Channels." Inside Channel / Outside Channel The Inside Channel alert is triggered when the source input is within the selected Upper and Lower Channel boundaries. The Outside Channel alert is triggered when the source input is outside the selected Upper and Lower Channel boundaries. Notice that this alert only works if you have selected "Channels." Moving Up / Moving Down This alert is the same as "crossing up/down" within x-bars. The Moving Up alert is triggered when the source input increases by a certain value within x-bars. The Moving Down alert is triggered when the source input decreases by a certain value within x-bars. Notice that you have to set the Number of Bars parameter! The calculation starts from the last formed candlestick. Moving Up % / Moving Down % The Moving Up % alert is triggered when the source input increases by a certain percentage value within x-bars. The Moving Down % alert is triggered when the source input decreases by a certain percentage value within x-bars. Notice that you have to set the Number of Bars parameter! The calculation starts from the last formed candlestick. Turning Up / Turning Down The Turning Up alert is triggered when the source input turns up. The Turning Down alert is triggered when the source input turns down. ----------------- Disclaimer The information contained in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell any securities of any type. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information. All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs. My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!
Pine Script® göstergesi
Zeiierman tarafından
49
CFB-Adaptive Velocity Histogram [Loxx]CFB-Adaptive Velocity Histogram is a velocity indicator with One-More-Moving-Average Adaptive Smoothing of input source value and Jurik's Composite-Fractal-Behavior-Adaptive Price-Trend-Period input with Dynamic Zones. All Juirk smoothing allows for both single and double Jurik smoothing passes. Velocity is adjusted to pips but there is no input value for the user. This indicator is tuned for Forex but can be used on any time series data. What is Composite Fractal Behavior ( CFB )? All around you mechanisms adjust themselves to their environment. From simple thermostats that react to air temperature to computer chips in modern cars that respond to changes in engine temperature, r.p.m.'s, torque, and throttle position. It was only a matter of time before fast desktop computers applied the mathematics of self-adjustment to systems that trade the financial markets. Unlike basic systems with fixed formulas, an adaptive system adjusts its own equations. For example, start with a basic channel breakout system that uses the highest closing price of the last N bars as a threshold for detecting breakouts on the up side. An adaptive and improved version of this system would adjust N according to market conditions, such as momentum, price volatility or acceleration. Since many systems are based directly or indirectly on cycles, another useful measure of market condition is the periodic length of a price chart's dominant cycle, (DC), that cycle with the greatest influence on price action. The utility of this new DC measure was noted by author Murray Ruggiero in the January '96 issue of Futures Magazine. In it. Mr. Ruggiero used it to adaptive adjust the value of N in a channel breakout system. He then simulated trading 15 years of D-Mark futures in order to compare its performance to a similar system that had a fixed optimal value of N. The adaptive version produced 20% more profit! This DC index utilized the popular MESA algorithm (a formulation by John Ehlers adapted from Burg's maximum entropy algorithm, MEM). Unfortunately, the DC approach is problematic when the market has no real dominant cycle momentum, because the mathematics will produce a value whether or not one actually exists! Therefore, we developed a proprietary indicator that does not presuppose the presence of market cycles. It's called CFB (Composite Fractal Behavior) and it works well whether or not the market is cyclic. CFB examines price action for a particular fractal pattern, categorizes them by size, and then outputs a composite fractal size index. This index is smooth, timely and accurate Essentially, CFB reveals the length of the market's trending action time frame. Long trending activity produces a large CFB index and short choppy action produces a small index value. Investors have found many applications for CFB which involve scaling other existing technical indicators adaptively, on a bar-to-bar basis. What is Jurik Volty used in the Juirk Filter? One of the lesser known qualities of Juirk smoothing is that the Jurik smoothing process is adaptive. "Jurik Volty" (a sort of market volatility ) is what makes Jurik smoothing adaptive. The Jurik Volty calculation can be used as both a standalone indicator and to smooth other indicators that you wish to make adaptive. What is the Jurik Moving Average? Have you noticed how moving averages add some lag (delay) to your signals? ... especially when price gaps up or down in a big move, and you are waiting for your moving average to catch up? Wait no more! JMA eliminates this problem forever and gives you the best of both worlds: low lag and smooth lines. Ideally, you would like a filtered signal to be both smooth and lag-free. Lag causes delays in your trades, and increasing lag in your indicators typically result in lower profits. In other words, late comers get what's left on the table after the feast has already begun. What are Dynamic Zones? As explained in "Stocks & Commodities V15:7 (306-310): Dynamic Zones by Leo Zamansky, Ph .D., and David Stendahl" Most indicators use a fixed zone for buy and sell signals. Here’ s a concept based on zones that are responsive to past levels of the indicator. One approach to active investing employs the use of oscillators to exploit tradable market trends. This investing style follows a very simple form of logic: Enter the market only when an oscillator has moved far above or below traditional trading lev- els. However, these oscillator- driven systems lack the ability to evolve with the market because they use fixed buy and sell zones. Traders typically use one set of buy and sell zones for a bull market and substantially different zones for a bear market. And therein lies the problem. Once traders begin introducing their market opinions into trading equations, by changing the zones, they negate the system’s mechanical nature. The objective is to have a system automatically define its own buy and sell zones and thereby profitably trade in any market — bull or bear. Dynamic zones offer a solution to the problem of fixed buy and sell zones for any oscillator-driven system. An indicator’s extreme levels can be quantified using statistical methods. These extreme levels are calculated for a certain period and serve as the buy and sell zones for a trading system. The repetition of this statistical process for every value of the indicator creates values that become the dynamic zones. The zones are calculated in such a way that the probability of the indicator value rising above, or falling below, the dynamic zones is equal to a given probability input set by the trader. To better understand dynamic zones, let's first describe them mathematically and then explain their use. The dynamic zones definition: Find V such that: For dynamic zone buy: P{X <= V}=P1 For dynamic zone sell: P{X >= V}=P2 where P1 and P2 are the probabilities set by the trader, X is the value of the indicator for the selected period and V represents the value of the dynamic zone. The probability input P1 and P2 can be adjusted by the trader to encompass as much or as little data as the trader would like. The smaller the probability, the fewer data values above and below the dynamic zones. This translates into a wider range between the buy and sell zones. If a 10% probability is used for P1 and P2, only those data values that make up the top 10% and bottom 10% for an indicator are used in the construction of the zones. Of the values, 80% will fall between the two extreme levels. Because dynamic zone levels are penetrated so infrequently, when this happens, traders know that the market has truly moved into overbought or oversold territory. Calculating the Dynamic Zones The algorithm for the dynamic zones is a series of steps. First, decide the value of the lookback period t. Next, decide the value of the probability Pbuy for buy zone and value of the probability Psell for the sell zone. For i=1, to the last lookback period, build the distribution f(x) of the price during the lookback period i. Then find the value Vi1 such that the probability of the price less than or equal to Vi1 during the lookback period i is equal to Pbuy. Find the value Vi2 such that the probability of the price greater or equal to Vi2 during the lookback period i is equal to Psell. The sequence of Vi1 for all periods gives the buy zone. The sequence of Vi2 for all periods gives the sell zone. In the algorithm description, we have: Build the distribution f(x) of the price during the lookback period i. The distribution here is empirical namely, how many times a given value of x appeared during the lookback period. The problem is to find such x that the probability of a price being greater or equal to x will be equal to a probability selected by the user. Probability is the area under the distribution curve. The task is to find such value of x that the area under the distribution curve to the right of x will be equal to the probability selected by the user. That x is the dynamic zone. Included: Bar coloring 3 signal variations w/ alerts Divergences w/ alerts Loxx's Expanded Source Types
Pine Script® göstergesi
loxx tarafından
CFB-Adaptive, Williams %R w/ Dynamic Zones [Loxx]CFB-Adaptive, Williams %R w/ Dynamic Zones is a Jurik-Composite-Fractal-Behavior-Adaptive Williams % Range indicator with Dynamic Zones. These additions to the WPR calculation reduce noise and return a signal that is more viable than WPR alone. What is Williams %R? Williams %R , also known as the Williams Percent Range, is a type of momentum indicator that moves between 0 and -100 and measures overbought and oversold levels. The Williams %R may be used to find entry and exit points in the market. The indicator is very similar to the Stochastic oscillator and is used in the same way. It was developed by Larry Williams and it compares a stock’s closing price to the high-low range over a specific period, typically 14 days or periods. What is Composite Fractal Behavior ( CFB )? All around you mechanisms adjust themselves to their environment. From simple thermostats that react to air temperature to computer chips in modern cars that respond to changes in engine temperature, r.p.m.'s, torque, and throttle position. It was only a matter of time before fast desktop computers applied the mathematics of self-adjustment to systems that trade the financial markets. Unlike basic systems with fixed formulas, an adaptive system adjusts its own equations. For example, start with a basic channel breakout system that uses the highest closing price of the last N bars as a threshold for detecting breakouts on the up side. An adaptive and improved version of this system would adjust N according to market conditions, such as momentum, price volatility or acceleration. Since many systems are based directly or indirectly on cycles, another useful measure of market condition is the periodic length of a price chart's dominant cycle, (DC), that cycle with the greatest influence on price action. The utility of this new DC measure was noted by author Murray Ruggiero in the January '96 issue of Futures Magazine. In it. Mr. Ruggiero used it to adaptive adjust the value of N in a channel breakout system. He then simulated trading 15 years of D-Mark futures in order to compare its performance to a similar system that had a fixed optimal value of N. The adaptive version produced 20% more profit! This DC index utilized the popular MESA algorithm (a formulation by John Ehlers adapted from Burg's maximum entropy algorithm, MEM). Unfortunately, the DC approach is problematic when the market has no real dominant cycle momentum, because the mathematics will produce a value whether or not one actually exists! Therefore, we developed a proprietary indicator that does not presuppose the presence of market cycles. It's called CFB (Composite Fractal Behavior) and it works well whether or not the market is cyclic. CFB examines price action for a particular fractal pattern, categorizes them by size, and then outputs a composite fractal size index. This index is smooth, timely and accurate Essentially, CFB reveals the length of the market's trending action time frame. Long trending activity produces a large CFB index and short choppy action produces a small index value. Investors have found many applications for CFB which involve scaling other existing technical indicators adaptively, on a bar-to-bar basis. What is Jurik Volty used in the Juirk Filter? One of the lesser known qualities of Juirk smoothing is that the Jurik smoothing process is adaptive. "Jurik Volty" (a sort of market volatility ) is what makes Jurik smoothing adaptive. The Jurik Volty calculation can be used as both a standalone indicator and to smooth other indicators that you wish to make adaptive. What is the Jurik Moving Average? Have you noticed how moving averages add some lag (delay) to your signals? ... especially when price gaps up or down in a big move, and you are waiting for your moving average to catch up? Wait no more! JMA eliminates this problem forever and gives you the best of both worlds: low lag and smooth lines. Ideally, you would like a filtered signal to be both smooth and lag-free. Lag causes delays in your trades, and increasing lag in your indicators typically result in lower profits. In other words, late comers get what's left on the table after the feast has already begun. What are Dynamic Zones? As explained in "Stocks & Commodities V15:7 (306-310): Dynamic Zones by Leo Zamansky, Ph .D., and David Stendahl" Most indicators use a fixed zone for buy and sell signals. Here’ s a concept based on zones that are responsive to past levels of the indicator. One approach to active investing employs the use of oscillators to exploit tradable market trends. This investing style follows a very simple form of logic: Enter the market only when an oscillator has moved far above or below traditional trading lev- els. However, these oscillator- driven systems lack the ability to evolve with the market because they use fixed buy and sell zones. Traders typically use one set of buy and sell zones for a bull market and substantially different zones for a bear market. And therein lies the problem. Once traders begin introducing their market opinions into trading equations, by changing the zones, they negate the system’s mechanical nature. The objective is to have a system automatically define its own buy and sell zones and thereby profitably trade in any market — bull or bear. Dynamic zones offer a solution to the problem of fixed buy and sell zones for any oscillator-driven system. An indicator’s extreme levels can be quantified using statistical methods. These extreme levels are calculated for a certain period and serve as the buy and sell zones for a trading system. The repetition of this statistical process for every value of the indicator creates values that become the dynamic zones. The zones are calculated in such a way that the probability of the indicator value rising above, or falling below, the dynamic zones is equal to a given probability input set by the trader. To better understand dynamic zones, let's first describe them mathematically and then explain their use. The dynamic zones definition: Find V such that: For dynamic zone buy: P{X <= V}=P1 For dynamic zone sell: P{X >= V}=P2 where P1 and P2 are the probabilities set by the trader, X is the value of the indicator for the selected period and V represents the value of the dynamic zone. The probability input P1 and P2 can be adjusted by the trader to encompass as much or as little data as the trader would like. The smaller the probability, the fewer data values above and below the dynamic zones. This translates into a wider range between the buy and sell zones. If a 10% probability is used for P1 and P2, only those data values that make up the top 10% and bottom 10% for an indicator are used in the construction of the zones. Of the values, 80% will fall between the two extreme levels. Because dynamic zone levels are penetrated so infrequently, when this happens, traders know that the market has truly moved into overbought or oversold territory. Calculating the Dynamic Zones The algorithm for the dynamic zones is a series of steps. First, decide the value of the lookback period t. Next, decide the value of the probability Pbuy for buy zone and value of the probability Psell for the sell zone. For i=1, to the last lookback period, build the distribution f(x) of the price during the lookback period i. Then find the value Vi1 such that the probability of the price less than or equal to Vi1 during the lookback period i is equal to Pbuy. Find the value Vi2 such that the probability of the price greater or equal to Vi2 during the lookback period i is equal to Psell. The sequence of Vi1 for all periods gives the buy zone. The sequence of Vi2 for all periods gives the sell zone. In the algorithm description, we have: Build the distribution f(x) of the price during the lookback period i. The distribution here is empirical namely, how many times a given value of x appeared during the lookback period. The problem is to find such x that the probability of a price being greater or equal to x will be equal to a probability selected by the user. Probability is the area under the distribution curve. The task is to find such value of x that the area under the distribution curve to the right of x will be equal to the probability selected by the user. That x is the dynamic zone. Included: Bar coloring 3 signal variations w/ alerts Divergences w/ alerts Loxx's Expanded Source Types
Pine Script® göstergesi
loxx tarafından
1
Intermediate Williams %R w/ Discontinued Signal Lines [Loxx]Intermediate Williams %R w/ Discontinued Signal Lines is a Williams %R indicator with advanced options: -Williams %R smoothing, 30+ smoothing algos found here: -Williams %R signal, 30+ smoothing algos found here: -DSL lines with smoothing or fixed overbought/oversold boundaries, smoothing algos are EMA and FEMA -33 Expanded Source Type inputs including Heiken-Ashi and Heiken-Ashi Better, found here: What is Williams %R? Williams %R, also known as the Williams Percent Range, is a type of momentum indicator that moves between 0 and -100 and measures overbought and oversold levels. The Williams %R may be used to find entry and exit points in the market. The indicator is very similar to the Stochastic oscillator and is used in the same way. It was developed by Larry Williams and it compares a stock’s closing price to the high-low range over a specific period, typically 14 days or periods. Included: -Toggle on/off bar coloring -Toggle on/off signal line
Pine Script® göstergesi
loxx tarafından
4
OrdinaryLeastSquaresLibrary "OrdinaryLeastSquares" One of the most common ways to estimate the coefficients for a linear regression is to use the Ordinary Least Squares (OLS) method. This library implements OLS in pine. This implementation can be used to fit a linear regression of multiple independent variables onto one dependent variable, as long as the assumptions behind OLS hold. solve_xtx_inv(x, y) Solve a linear system of equations using the Ordinary Least Squares method. This function returns both the estimated OLS solution and a matrix that essentially measures the model stability (linear dependence between the columns of 'x'). NOTE: The latter is an intermediate step when estimating the OLS solution but is useful when calculating the covariance matrix and is returned here to save computation time so that this step doesn't have to be calculated again when things like standard errors should be calculated.   Parameters:      x : The matrix containing the independent variables. Each column is regarded by the algorithm as one independent variable. The row count of 'x' and 'y' must match.      y : The matrix containing the dependent variable. This matrix can only contain one dependent variable and can therefore only contain one column. The row count of 'x' and 'y' must match.   Returns: Returns both the estimated OLS solution and a matrix that essentially measures the model stability (xtx_inv is equal to (X'X)^-1). solve(x, y) Solve a linear system of equations using the Ordinary Least Squares method.   Parameters:      x : The matrix containing the independent variables. Each column is regarded by the algorithm as one independent variable. The row count of 'x' and 'y' must match.      y : The matrix containing the dependent variable. This matrix can only contain one dependent variable and can therefore only contain one column. The row count of 'x' and 'y' must match.   Returns: Returns the estimated OLS solution. standard_errors(x, y, beta_hat, xtx_inv) Calculate the standard errors.   Parameters:      x : The matrix containing the independent variables. Each column is regarded by the algorithm as one independent variable. The row count of 'x' and 'y' must match.      y : The matrix containing the dependent variable. This matrix can only contain one dependent variable and can therefore only contain one column. The row count of 'x' and 'y' must match.      beta_hat : The Ordinary Least Squares (OLS) solution provided by solve_xtx_inv() or solve().      xtx_inv : This is (X'X)^-1, which means we take the transpose of the X matrix, multiply that the X matrix and then take the inverse of the result. This essentially measures the linear dependence between the columns of the X matrix.   Returns: The standard errors. estimate(x, beta_hat) Estimate the next step of a linear model.   Parameters:      x : The matrix containing the independent variables. Each column is regarded by the algorithm as one independent variable. The row count of 'x' and 'y' must match.      beta_hat : The Ordinary Least Squares (OLS) solution provided by solve_xtx_inv() or solve().   Returns: Returns the new estimate of Y based on the linear model.
Pine Script® kütüphanesi
lejmer tarafından
1
Average Down [Zeiierman]AVERAGING DOWN   Averaging down  is an investment strategy that involves buying additional contracts of an asset when the price drops. This way, the investor increases the size of their position at discounted prices. The averaging down strategy is highly debated among traders and investors because it can either lead to huge losses or great returns. Nevertheless, averaging down is often used and favored by long-term investors and contrarian traders. With careful/proper risk management, averaging down can cover losses and magnify the returns when the asset rebounds. However, the main concern for a trader is that it can be hard to identify the difference between a pullback or the start of a new trend.   HOW DOES IT WORK  Averaging down  is a method to lower the average price at which the investor buys an asset. A lower average price can help investors come back to break even quicker and, if the price continues to rise, get an even bigger upside and thus increase the total profit from the trade. For example, We buy 100 shares at $60 per share, a total investment of $6000, and then the asset drops to $40 per share; in order to come back to break even, the price has to go up 50%. (($60/$40) - 1)*100 = 50%. The power of Averaging down  comes into play if the investor buys additional shares at a lower price, like another 100 shares at $40 per share; the total investment is ($6000+$4000 = $10000). The average price for the investment is now $50. (($60 x 100) + ($40 x 100))/200; in order to get back to break even, the price has to rise 25% ($50/$40)-1)*100 = 25%, and if the price continues up to $60 per share, the investor can secure a profit at 16%. So by averaging down, investors and traders can cover the losses easier and potentially have more profit to secure at the end.   THE AVERAGE DOWN TRADINGVIEW TOOL This script/indicator/trading tool helps traders and investors to get the average price of their position. The tool works for Long and Short and displays the entry price, average price, and the PnL in points.    HOW TO USE  Use the tool to calculate the average price of your long or short position in any market and timeframe.  Get the current PnL for the investment and keep track of your entry prices.  APPLY TO CHART  When you apply the tool on the chart, you have to select five entry points, and within the setting panel, you can choose how many of these five entry points are active and how many contracts each entry has. Then, the tool will display your average price based on the entries and the number of contracts used at each price level. LONG Set your entries and the number of contracts at each price level. The indicator will then display all your long entries and at what price you will break even. The entry line changes color based on if the entry is in profit or loss. SHORT Set your entries and the number of contracts at each price level. The indicator will then display all your short entries and at what price you will break even. The entry line changes color based on if the entry is in profit or loss. ----------------- Disclaimer Copyright by Zeiierman. The information contained in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell any securities of any type. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information. All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual’s trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs. My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!
Pine Script® göstergesi
Zeiierman tarafından
4
Weis pip zigzag jayyWhat you see here is the Weis pip zigzag wave plotted directly on the price chart.  This script is the companion to the Weis pip wave (  ) which is plotted in the lower panel of the displayed chart and can be used as an alternate way of plotting the same results.  The Weis pip zigzag wave shows how far in terms of price a Weis wave has traveled through the duration of a Weis wave.  The Weis pip zigzag wave is used in combination with the Weis cumulative volume wave.  The two waves must be set to the same "wave size". To use this script you must set the wave size.  Using the traditional Weis method simply enter the desired wave size in the box "Select Weis Wave Size"  In this example, it is set to 5.  Each wave for each security and each timeframe requires its own wave size.  Although not the traditional method a more automatic way to set wave size would be to use ATR.  This is not the true Weis method but it does give you similar waves and, importantly, without the hassle described above. Once the Weis wave size is set then the pip wave will be shown. I have put a pip zigzag of a 5 point Weis wave on the bar chart - that is a different script.  I have added it to allow your eye to see what a Weis wave looks like.  You will notice that the wave is not in straight lines connecting wave tops to bottoms this is a function of the limitations of Pinescript version 1.  This script would need to be in version 4 to allow straight lines.  There are too many calculations within this script to allow conversion to Pinescript version 4 or even Version 3.  I am in the process of rewriting this script to reduce the number of calculations and streamline the algorithm.    The numbers plotted on the chart are calculated to be relative numbers.  The script is limited to showing only three numbers vertically.  Only the highest three values of a number are shown.  For example, if the highest recent pip value is 12,345 only the first 3 numerals would be displayed ie 123.  But suppose there is a recent value of 691.  It would not be helpful to display 691 if the other wave size is shown as 123. To give the appropriate relative value the script will show a value of 7 instead of 691. This informs you of the relative magnitude of the values.  This is done automatically within the script.  There is likely no need to manually override the automatically calculated value.  I will create a video that demonstrates the manual override method. What is a Weis wave?  David Weis has been recognized as a Wyckoff method analyst he has written two books one of which, Trades About to Happen, describes the evolution of the now popular Weis wave.  The method employed by Weis is to identify waves of price action and to compare the strength of the waves on characteristics of wave strength.  Chief among the characteristics of strength is the cumulative volume of the wave.  There are other markers that Weis uses as well for example how the actual price difference between the start of the Weis wave from start to finish.  Weis also uses time, particularly when using a Renko chart.  Weis specifically uses candle or bar closes to define all wave action ie a line chart.   David Weis did a futures  io video which is a popular source of information about his method. This is the identical script with the identical settings but without the offending links. If you want to see the pip Weis method in practice then search Weis pip wave.  If you want to see Weis chart in pdf then message me and I will give a link or the Weis pdf.  Why would you want to see the Weis chart for May 27, 2020?  Merely to confirm the veracity of my algorithm.  You could compare my Weis chart here () from the same period to the David Weis chart from May 27. Both waves are for the ES!1 4 hour chart and both for a wave size of 5. 
Pine Script® göstergesi
jayy tarafından
22
Price Action and 3 EMAs Momentum plus Sessions FilterThis indicator plots on the chart the parameters and signals of the Price Action and 3 EMAs Momentum plus Sessions Filter Algorithmic Strategy. The strategy trades based on time-series (absolute) and relative momentum of price close, highs, lows and 3 EMAs. I am still learning PS and therefore I have only been able to write the indicator up to the Signal generation. I plan to expand the indicator to Entry Signals as well as the full Strategy. The strategy works best on EURUSD in the 15 minutes TF during London and New York sessions with 1 to 1 TP and SL of 30 pips with lots resulting in 3% risk of the account per trade. I have already written the full strategy in another language and platform and back tested it for ten years and it was profitable for 7 of the 10 years with average profit of 15% p.a which can be easily increased by increasing risk per trade. I have been trading it live in that platform for over two years and it is profitable. Contributions from experienced PS coders in completing the Indicator as well as writing the Strategy and back testing it on Trading View will be appreciated. STRATEGY AND INDICATOR PARAMETERS Three periods of 12, 48 and 96 in the 15 min TF which are equivalent to 3, 12 and 24 hours i.e (15 min * period / 60 min) are the foundational inputs for all the parameters of the PA & 3 EMAs Momentum + SF Algo Strategy and its Indicator. 3 EMAs momentum parameters and conditions • FastEMA = ema of 12 periods • MedEMA = ema of 48 periods • SlowEMA = ema of 96 periods • All the EMAs analyse price close for up to 96 (15 min periods) equivalent to 24 hours • There’s Upward EMA momentum if price close > FastEMA and FastEMA > MedEMA and MedEMA > SlowEMA • There’s Downward EMA momentum if price close < FastEMA and FastEMA < MedEMA and MedEMA < SlowEMA PA momentum parameters and conditions • HH = Highest High of 48 periods from 1st closed bar before current bar • LL = Lowest Low of 48 periods from 1st closed bar from current bar • Previous HH = Highest High of 84 periods from 12th closed bar before current bar • Previous LL = Lowest Low of 84 periods from 12th closed bar before current bar • All the HH & LL and prevHH & prevLL are within the 96 periods from the 1st closed bar before current bar and therefore indicative of momentum during the past 24 hours • There’s Upward PA momentum if price close > HH and HH > prevHH and LL > prevLL • There’s Downward PA momentum if price close < LL and LL < prevLL and HH < prevHH Signal conditions and Status (BuySignal, SellSignal or Neutral) • The strategy generates Buy or Sell Signals if both 3 EMAs and PA momentum conditions are met for each direction and these occur during the London and New York sessions • BuySignal if price close > FastEMA and FastEMA > MedEMA and MedEMA > SlowEMA and price close > HH and HH > prevHH and LL > prevLL and timeinrange (LDN&NY) else Neutral • SellSignal if price close < FastEMA and FastEMA < MedEMA and MedEMA < SlowEMA and price close < LL and LL < prevLL and HH < prevHH and timeinrange (LDN&NY) else Neutral Entry conditions and Status (EnterBuy, EnterSell or Neutral)(NOT CODED YET) • ENTRY IS NOT AT THE SIGNAL BAR but at the current bar tick price retracement to FastEMA after the signal • EnterBuy if current bar tick price <= FastEMA and current bar tick price > prevHH at the time of the Buy Signal • EnterSell if current bar tick price >= FastEMA and current bar tick price > prevLL at the time of the Sell Signal
Pine Script® göstergesi
MoqebeloEJD tarafından
3
NAND PerceptronExperimental NAND Perceptron based upon Python template that aims to predict NAND Gate Outputs. A Perceptron is one of the foundational building blocks of nearly all advanced Neural Network layers and models for Algo trading and Machine Learning. The goal behind this script was threefold: To prove and demonstrate that an ACTUAL working neural net can be implemented in Pine, even if incomplete. To pave the way for other traders and coders to iterate on this script and push the boundaries of Tradingview strategies and indicators. To see if a self-contained neural network component for parameter optimization within Pinescript was hypothetically possible. NOTE: This is a highly experimental proof of concept - this is NOT a ready-made template to include or integrate into existing strategies and indicators, yet (emphasis YET - neural networks have a lot of potential utility and potential when utilized and implemented properly). Hardcoded NAND Gate outputs with Bias column (X0): // NAND Gate + X0 Bias and Y-true // X0 // X1 // X2 // Y // 1 // 0 // 0 // 1 // 1 // 0 // 1 // 1 // 1 // 1 // 0 // 1 // 1 // 1 // 1 // 0 Column X0 is bias feature/input Column X1 and X2 are the NAND Gate Column Y is the y-true values for the NAND gate yhat is the prediction at that timestep F0,F1,F2,F3 are the Dot products of the Weights (W0,W1,W2) and the input features (X0,X1,X2) Learning rate and activation function threshold are enabled by default as input parameters Uncomment sections for more training iterations/epochs: Loop optimizations would be amazing to have for a selectable length for training iterations/epochs but I'm not sure if it's possible in Pine with how this script is structured. Error metrics and loss have not been implemented due to difficulty with script length and iterations vs epochs - I haven't been able to configure the input parameters to successfully predict the right values for all four y-true values for the NAND gate (only been able to get 3/4; If you're able to get all four predictions to be correct, let me know, please). // //---- REFERENCE for final output // A3 := 1, y0 true // B3 := 1, y1 true // C3 := 1, y2 true // D3 := 0, y3 true PLEASE READ: Source article/template and main code reference: towardsdatascience.com towardsdatascience.com towardsdatascience.com
Pine Script® göstergesi
auroagwei tarafından
14
Baseline-C [ID: AC-P]The "AC-P" version of jiehonglim's NNFX Baseline script is my personal customized version of the NNFX Baseline concept as part of the NNFX Algorithm stack/structure for 1D Trend Trading for Forex. Everget's JMA implementation is used for the baseline smoothing method, with optional ATR bands at 1.0x and 1.5x from the baseline. NNFX = No Nonsense Forex Baseline = Component of the NNFX Algorithm that consists of a single moving average Baseline ---> Meant to be used in conjunction with ATR/C1/C2/Vol Indicator/Exit Indicator as per NNFX Algorithm setup/structure. C1 is 1st Confirmation Indicator, C2 is 2nd Confirmation Indicator. JMA (Jurik Moving Average) is used for the baseline and slow baseline. A slow baseline option is included, but disabled by default. The faint orange/purple lines are 1.0x/1.5x ATR from the Baseline, and are what I use as potential TP/SL targets or to evaluate when to stay out of a trade (chop/missed entry/exit/other/ATR breach), depending on the trade setup (in conjunction with C1/C2/Vol Indicator/Exit Indicator) This script is heavily based upon jiehonglim's NNFX Baseline script for signaling, barcoloring, and ATR. SSL Channel option included but disabled by default (Erwinbeckers SSL component) POC (Point of Control) from Volume Profile is included/enabled by default for both the current timeframe and 12HR timeframe 03.freeman's InfoPanel Divergence Indicator was used a reference to replace the current/previous ATR information infopanel/info draw from jiehonglim's script. I'm not sure whether I like the previous way ATR info was displayed vs how I have it currently, but it's something that is completely optional: Specifically: I am tuning this baseline/indicator for 1D trading as part of the NNFX system, for Forex. DO NOT USE THIS INDICATOR WITHOUT PROPER TUNING/ADJUSTMENT for your timeframe and asset class. Note about lack of alerts: Alerts for baseline crosses (and other crosses) have been purposefully omitted for this version upon initial publication. While getting alerts for baseline crosses under certain conditions/filtered conditions that eliminate low-importance signals and crossover whipsaw would be great, it's something I'm still looking into. SPECIFICALLY: There are entry, exit, take profit, and continuation signal components in relation to the Baseline to the rest of the NNFX Algorithm stack (ATR/C1/C2/Vol Indicator/Exit Indicator), including but limited to the "1 candle rule" and the "7 candle rule" as per NNFX. Implementing alerts that are significant that also factor in these rules while reducing alert spam/false signals would be ideal, but it's also the HTF/Daily chart - visually, entry/exit/continuation signal alignment is easy to spot when trading 1D - alerts may be redundant/a pursuit in diminishing returns (for now). //------------------------------------------------------------------- // Acknowledgements/Reference: // jiehonglim, NNFX Baseline Script - Moving Averages // // Fractured, Many Moving Averages // // everget, Jurik Moving Average/JMA // // 03.freeman, InfoPanel Divergence Indicator // // Ggqmna Volume stops // // Libertus RSI Divs // // ChrisMoody, CM_Price-Action-Bars-Price Patterns That Work // // Erwinbeckers SSL Channel //
Pine Script® göstergesi
auroagwei tarafından
9
Alexmoku Genesis v0.2.6 — Runtime BulletproofAlexmoku Genesis v0.2.6 – Reinventing Ichimoku with Precision and Intelligence Built by Alex • Engineered for traders who demand more than lagging clouds 🔬 Overview Alexmoku Genesis is a ground-up reimagining of the traditional Ichimoku system — retaining its philosophical foundations of harmony, balance, and structure, while infusing it with modern logic, advanced volatility modeling, and AI-aligned signal classification. This is not your grandfather’s Ichimoku. Genesis transforms it into a forward-sensing, volatility-aware system that adapts in real time and guides discretionary and algorithmic traders alike with smarter signals, predictive structure, and built-in trade intelligence. ⚙️ Core Enhancements 📐 Volatility-Responsive Smoothing Tenkan-sen and Kijun-sen lengths are dynamically adjusted based on recent price volatility (ATR-based). Prevents overreaction in choppy markets and improves responsiveness during strong trends. 🌀 Adaptive Cloud Projection Span A and Span B are still projected 52 periods forward — but cloud width adapts to market rhythm, not just static values. 🕵️ Enhanced Chikou Span (CKS+) Chikou logic is upgraded to emphasize structure interaction, not just simple price overlay. Useful for identifying support/resistance echoes and divergence validation. 🌐 Multi-Timeframe Cloud Awareness (Genesis Core) Internal alignment checks between higher and lower timeframe Kumo positioning. Future module support for overlaying MTF clouds. 🔖 Signal Classifier Engine (Experimental) Each major structure event is tagged with signal intent: 📦 prep 🚀 launch 🔁 reversion 🪤 trap Enables faster discretionary reads or future automation. 🧠 Trust Score Logic (Coming soon) Future versions will assign numerical trust scores (1–10) to trade setups based on confluence. 🧰 Settings 🔧 Volatility Scaling Factor – Adjusts how reactive the indicator is to volatility. Default: 300. 🌫 Displacement (Kumo) – Cloud projection forward. Default (and required): 52. ⛅ Cloud Display Toggle – Show/hide Kumo visuals without affecting logic. ⚡️ Future expansion modules already scaffolded (MTF overlays, color-coded signal classifiers, Trust Score engine, etc.) 🧘 Philosophy Behind the System "This isn’t just about catching runners — it’s about becoming the kind of person who can trade with clarity, peace, and precision." Alexmoku Genesis reflects the W.E.A.L.T.H. System's holistic philosophy: Wealth Engineered Algorithmic Leveraged Trading Holistically Trading isn't just a strategy. It's a mirror. Genesis is designed to train both your execution and your awareness. ⚠️ Disclaimer This tool is designed for experienced technical traders and is still in active development. Use judgment and proper risk management. This is not financial advice.
Pine Script® göstergesi
Alex_A74 tarafından
ICT Macro Time Window NYThis script highlights the typical ICT “macro” algorithm activity windows on your chart. It marks 10 minutes before to 10 minutes after each full hour, based on New York time (NY). The display is restricted to the 00:00 – 16:00 NY time range. Overlay on chart with semi-transparent background Automatically adjusts to the chart timeframe Customizable: window start/end minutes, hours, and background color Ideal for traders following ICT concepts to visually identify high-probability algorithm activity periods.
Pine Script® göstergesi
pschloegl1 tarafından
Advanced Volume Profile Pro Delta + POC + VAH/VAL# Advanced Volume Profile Pro - Delta + POC + VAH/VAL Analysis System ## WHAT THIS SCRIPT DOES This script creates a comprehensive volume profile analysis system that combines traditional volume-at-price distribution with delta volume calculations, Point of Control (POC) identification, and Value Area (VAH/VAL) analysis. Unlike standard volume indicators that show only total volume over time, this script analyzes volume distribution across price levels and estimates buying vs selling pressure using multiple calculation methods to provide deeper market structure insights. ## WHY THIS COMBINATION IS ORIGINAL AND USEFUL **The Problem Solved:** Traditional volume indicators show when volume occurs but not where price finds acceptance or rejection. Standalone volume profiles lack directional bias information, while basic delta calculations don't provide structural context. Traders need to understand both volume distribution AND directional sentiment at key price levels. **The Solution:** This script implements an integrated approach that: - Maps volume distribution across price levels using configurable row density - Estimates delta (buying vs selling pressure) using three different methodologies - Identifies Point of Control (highest volume price level) for key support/resistance - Calculates Value Area boundaries where 70% of volume traded - Provides real-time alerts for key level interactions and volume imbalances **Unique Features:** 1. **Developing POC Visualization**: Real-time tracking of Point of Control migration throughout the session via blue dotted trail, revealing institutional accumulation/distribution patterns before they complete 2. **Multi-Method Delta Calculation**: Price Action-based, Bid/Ask estimation, and Cumulative methods for different market conditions 3. **Adaptive Timeframe System**: Auto-adjusts calculation parameters based on chart timeframe for optimal performance 4. **Flexible Profile Types**: N Bars Back (precise control), Days Back (calendar-based), and Session-based analysis modes 5. **Advanced Imbalance Detection**: Identifies and highlights significant buying/selling imbalances with configurable thresholds 6. **Comprehensive Alert System**: Monitors POC touches, Value Area entry/exit, and major volume imbalances ## HOW THE SCRIPT WORKS TECHNICALLY ### Core Volume Profile Methodology: **1. Price Level Distribution:** - Divides price range into user-defined rows (10-50 configurable) - Calculates row height: `(Highest Price - Lowest Price) / Number of Rows` - Distributes each bar's volume across price levels it touched proportionally **2. Delta Volume Calculation Methods:** **Price Action Method:** ``` Price Range = High - Low Buy Pressure = (Close - Low) / Price Range Sell Pressure = (High - Close) / Price Range Buy Volume = Total Volume × Buy Pressure Sell Volume = Total Volume × Sell Pressure Delta = Buy Volume - Sell Volume ``` **Bid/Ask Estimation Method:** ``` Average Price = (High + Low + Close) / 3 Buy Volume = Close > Average ? Volume × 0.6 : Volume × 0.4 Sell Volume = Total Volume - Buy Volume ``` **Cumulative Method:** ``` Buy Volume = Close > Open ? Volume : Volume × 0.3 Sell Volume = Close ≤ Open ? Volume : Volume × 0.3 ``` **3. Point of Control (POC) Identification:** - Scans all price levels to find maximum volume concentration - POC represents the price level with highest trading activity - Acts as significant support/resistance level - **Developing POC Feature**: Tracks POC evolution in real-time via blue dotted trail, showing how institutional interest migrates throughout the session. Upward POC migration indicates accumulation patterns, downward migration suggests distribution, providing early trend signals before price confirmation. **4. Value Area Calculation:** - Starts from POC and expands up/down to encompass 70% of total volume - VAH (Value Area High): Upper boundary of value area - VAL (Value Area Low): Lower boundary of value area - Expansion algorithm prioritizes direction with higher volume **5. Adaptive Range Selection:** Based on profile type and timeframe optimization: - **N Bars Back**: Fixed lookback period with performance optimization (20-500 bars) - **Days Back**: Calendar-based analysis with automatic timeframe adjustment (1-365 days) - **Session**: Current trading session or custom session times ### Performance Optimization Features: - **Sampling Algorithm**: Reduces calculation load on large datasets while maintaining accuracy - **Memory Management**: Clears previous drawings to prevent performance degradation - **Safety Constraints**: Prevents excessive memory usage with configurable limits ## HOW TO USE THIS SCRIPT ### Initial Setup: 1. **Profile Configuration**: Select profile type based on trading style: - N Bars Back: Precise control over data range - Days Back: Intuitive calendar-based analysis - Session: Real-time session development 2. **Row Density**: Set number of rows (30 default) - more rows = higher resolution, slower performance 3. **Delta Method**: Choose calculation method based on market type: - Price Action: Best for trending markets - Bid/Ask Estimate: Good for ranging markets - Cumulative: Smoothed approach for volatile markets 4. **Visual Settings**: Configure colors, position (left/right), and display options ### Reading the Profile: **Volume Bars:** - **Length**: Represents relative volume at that price level - **Color**: Green = net buying pressure, Red = net selling pressure - **Intensity**: Darker colors indicate volume imbalances above threshold **Key Levels:** - **POC (Blue Line)**: Highest volume price - major support/resistance - **VAH (Purple Dashed)**: Value Area High - upper boundary of fair value - **VAL (Orange Dashed)**: Value Area Low - lower boundary of fair value - **Value Area Fill**: Shaded region showing main trading range **Developing POC Trail:** - **Blue Dotted Lines**: Show real-time POC evolution throughout the session - **Migration Patterns**: Upward trail indicates bullish accumulation, downward trail suggests bearish distribution - **Early Signals**: POC movement often precedes price movement, providing advance warning of institutional activity - **Institutional Footprints**: Reveals where smart money concentrated volume before final POC establishment ### Trading Applications: **Support/Resistance Analysis:** - POC acts as magnetic price level - expect reactions - VAH/VAL provide intermediate support/resistance levels - Profile edges show areas of low volume acceptance **Developing POC Analysis:** - **Upward Migration**: POC moving higher = institutional accumulation, bullish bias - **Downward Migration**: POC moving lower = institutional distribution, bearish bias - **Stable POC**: Tight clustering = balanced market, range-bound conditions - **Early Trend Detection**: POC direction change often precedes price breakouts **Entry Strategies:** - Buy at VAL with POC as target (in uptrends) - Sell at VAH with POC as target (in downtrends) - Breakout plays above/below profile extremes **Volume Imbalance Trading:** - Strong buying imbalance (>60% threshold) suggests continued upward pressure - Strong selling imbalance suggests continued downward pressure - Imbalances near key levels provide high-probability setups **Multi-Timeframe Context:** - Use higher timeframe profiles for major levels - Lower timeframe profiles for precise entries - Session profiles for intraday trading structure ## SCRIPT SETTINGS EXPLANATION ### Volume Profile Settings: - **Profile Type**: Determines data range for calculation - N Bars Back: Exact number of bars (20-500 range) - Days Back: Calendar days with timeframe adaptation (1-365 days) - Session: Trading session-based (intraday focus) - **Number of Rows**: Profile resolution (10-50 range) - **Profile Width**: Visual width as chart percentage (10-50%) - **Value Area %**: Volume percentage for VA calculation (50-90%, 70% standard) - **Auto-Adjust**: Automatically optimizes for different timeframes ### Delta Volume Settings: - **Show Delta Volume**: Enable/disable delta calculations - **Delta Calculation Method**: Choose methodology based on market conditions - **Highlight Imbalances**: Visual emphasis for significant volume imbalances - **Imbalance Threshold**: Percentage for imbalance detection (50-90%) ### Session Settings: - **Session Type**: Daily, Weekly, Monthly, or Custom periods - **Custom Session Time**: Define specific trading hours - **Previous Sessions**: Number of historical sessions to display ### Days Back Settings: - **Lookback Days**: Number of calendar days to analyze (1-365) - **Automatic Calculation**: Script automatically converts days to bars based on timeframe: - Intraday: Accounts for 6.5 trading hours per day - Daily: 1 bar per day - Weekly/Monthly: Proportional adjustment ### N Bars Back Settings: - **Lookback Bars**: Exact number of bars to analyze (20-500) - **Precise Control**: Best for systematic analysis and backtesting ### Visual Customization: - **Colors**: Bullish (green), Bearish (red), and level colors - **Profile Position**: Left or Right side of chart - **Profile Offset**: Distance from current price action - **Labels**: Show/hide level labels and values - **Smooth Profile Bars**: Enhanced visual appearance ### Alert Configuration: - **POC Touch**: Alerts when price interacts with Point of Control - **VA Entry/Exit**: Alerts for Value Area boundary interactions - **Major Imbalance**: Alerts for significant volume imbalances ## VISUAL FEATURES ### Profile Display: - **Horizontal Bars**: Volume distribution across price levels - **Color Coding**: Delta-based coloring for directional bias - **Smooth Rendering**: Optional smoothing for cleaner appearance - **Transparency**: Configurable opacity for chart readability ### Level Lines: - **POC**: Solid blue line with optional label - **VAH/VAL**: Dashed colored lines with value displays - **Extension**: Lines extend across relevant time periods - **Value Area Fill**: Optional shaded region between VAH/VAL ### Information Table: - **Current Values**: Real-time POC, VAH, VAL prices - **VA Range**: Value Area width calculation - **Positioning**: Multiple table positions available - **Text Sizing**: Adjustable for different screen sizes ## IMPORTANT USAGE NOTES **Realistic Expectations:** - Volume profile analysis provides structural context, not trading signals - Delta calculations are estimations based on price action, not actual order flow - Past volume distribution does not guarantee future price behavior - Combine with other analysis methods for comprehensive market view **Best Practices:** - Use appropriate profile types for your trading style: - Day Trading: Session or Days Back (1-5 days) - Swing Trading: Days Back (10-30 days) or N Bars Back - Position Trading: Days Back (60-180 days) - Consider market context (trending vs ranging conditions) - Verify key levels with additional technical analysis - Monitor profile development for changing market structure **Performance Considerations:** - Higher row counts increase calculation complexity - Large lookback periods may affect chart performance - Auto-adjust feature optimizes for most use cases - Consider using session profiles for intraday efficiency **Limitations:** - Delta calculations are estimations, not actual transaction data - Profile accuracy depends on available price/volume history - Effectiveness varies across different instruments and market conditions - Requires understanding of volume profile concepts for optimal use **Data Requirements:** - Requires volume data for accurate calculations - Works best on liquid instruments with consistent volume - May be less effective on very low volume or exotic instruments This script serves as a comprehensive volume analysis tool for traders who need detailed market structure information with integrated directional bias analysis and real-time POC development tracking for informed trading decisions.
Pine Script® göstergesi
DeltaSpeedEdge tarafından
QFisher-R™ [ParadoxAlgo]QFISHER-R™ (Regime-Aware Fisher Transform) A research/education tool that helps visualize potential momentum exhaustion and probable inflection zones using a quantitative, non-repainting Fisher framework with regime filters and multi-timeframe (MTF) confirmation. What it does Converts normalized price movement into a stabilized Fisher domain to highlight potential turning points. Uses adaptive smoothing, robust (MAD/quantile) thresholds, and optional MTF alignment to contextualize extremes. Provides a Reversal Probability Score (0–100) to summarize signal confluence (extreme, slope, cross, divergence, regime, and MTF checks). Key features Non-repainting logic (bar-close confirmation; security() with no lookahead). Dynamic exhaustion bands (data-driven thresholds vs fixed ±2). Adaptive smoothing (efficiency-ratio based). Optional divergence tags on structurally valid pivots. MTF confirmation (same logic computed on a higher timeframe). Compact visuals with subtle plotting to reduce chart clutter. Inputs (high level) Source (e.g., HLC3 / Close / HA). Core lookback, fast/slow range blend, and ER length. Band sensitivity (robust thresholding). MTF timeframe(s) and agreement requirement. Toggle divergence & intrabar previews (default off). Signals & Alerts Turn Candidate (Up/Down) when multiple conditions align. Trade-Grade Turn when score ≥ threshold and MTF agrees. Divergence Confirmed when structural criteria are met. Alerts are generated on confirmed bar close by default. Optional “preview” mode is available for experimentation. How to use Start on your preferred timeframe; optionally enable an HTF (e.g., 4×) for confirmation. Look for RPS clusters near the exhaustion bands, slope inflections, and (optionally) divergences. Combine with your own risk management, liquidity, and trend context. Paper test first and calibrate thresholds to your instrument and timeframe. Notes & limitations This is not a buy/sell signal generator and does not predict future returns. Readings can remain extreme during strong trends; use HTF context and your own filters. Parameters are intentionally conservative by default; adjust carefully. Compliance / Disclaimer Educational & research tool only. Not financial advice. No recommendation to buy/sell any security or derivative. Past performance, backtests, or examples (if any) are not indicative of future results. Trading involves risk; you are responsible for your own decisions and risk management. Built upon the Fisher Transform concept (Ehlers); all modifications, smoothing, regime logic, scoring, and visualization are original work by Paradox Algo.
Pine Script® göstergesi
paradoxalgo tarafından
2
Time Window Optimizer [theUltimator5]The Time Window Optimizer is designed to identify the most profitable 30-minute trading windows during regular market hours (9:30 AM - 4:00 PM EST). This tool helps traders optimize their intraday strategies by automatically discovering time periods with the highest historical performance or allowing manual selection for custom analysis. It also allows you to select manual timeframes for custom time period analysis. 🏆 Automatic Window Discovery The core feature of this indicator is its intelligent Auto-Find Best 30min Window system that analyzes all 13 possible 30-minute time slots during market hours. How the Algorithm Works: Concurrent Analysis: The indicator simultaneously tracks performance across all 13 time windows (9:30-10:00, 10:00-10:30, 10:30-11:00... through 15:30-16:00) Daily Performance Tracking: For each window, it captures the percentage change from window open to window close on every trading day Cumulative Compounding: Daily returns are compounded over time to show the true long-term performance of each window, starting from a normalized value of 1.0 Dynamic Optimization: The system continuously identifies the window with the highest cumulative return and highlights it as the optimal choice Statistical Validation: Performance is validated through multiple metrics including average daily returns, win rates, and total sample size Visual Representation: Best Window Line: The top-performing window is displayed as a thick colored line for easy identification All 13 Lines (optional): Users can view performance lines for all time windows simultaneously to compare relative performance Smart Coloring: Lines are color-coded (green for gains, red for losses) with the best performer highlighted in a user-selected color 📊 Comprehensive Performance Analysis The indicator provides detailed statistics in an information table: Average Daily Return: Mean percentage change per trading session Cumulative Return: Total compounded performance over the analysis period Win Rate: Percentage of profitable days (colored green if ≥50%, red if <50%) Buy & Hold Comparison: Shows outperformance vs. simple buy-and-hold strategy Sample Size: Number of trading days analyzed for statistical significance 🛠️ User Settings imgur.com Auto-Optimization Controls: Auto-Find Best Window: Toggle to enable/disable automatic optimization Show All 13 Lines: Display all time window performance lines simultaneously Best Window Line Color: Customize the color of the top-performing window Manual Mode: imgur.com Custom Time Window: Set any desired time range using session format (HHMM-HHMM) Crypto Support: Built-in timezone offset adjustment for cryptocurrency markets Chart Type Options: Switch between candlestick and line chart visualization Visual Customization: imgur.com Background Highlighting: Optional background color during active time windows Candle Coloring: Custom colors for bullish/bearish candles within the time window Table Positioning: Flexible placement of the statistics table anywhere on the chart 🔧 Technical Features Market Compatibility: Stock Markets: Optimized for traditional market hours (9:30 AM - 4:00 PM EST) Cryptocurrency: Includes timezone offset adjustment for 24/7 crypto markets Exchange Detection: Automatically detects crypto exchanges and applies appropriate settings Performance Optimization: Efficient Calculation: Uses separate arrays for each time block to minimize computational overhead Real-time Updates: Dynamically updates the best-performing window as new data becomes available Memory Management: Optimized data structures to handle large datasets efficiently 💡 Use Cases Strategy Development: Identify the most profitable trading hours for your specific instruments Risk Management: Focus trading activity during historically successful time periods Performance Comparison: Evaluate whether time-specific strategies outperform buy-and-hold Market Analysis: Understand intraday patterns and market behavior across different time windows 📈 Key Benefits Data-Driven Decisions: Base trading schedules on historical performance data Automated Analysis: No manual calculation required - the algorithm does the work Flexible Implementation: Works in both automated discovery and manual selection modes Comprehensive Metrics: Multiple performance indicators for thorough analysis Visual Clarity: Clear, color-coded visualization makes interpretation intuitive This indicator transforms complex intraday analysis into actionable insights, helping traders optimize their time allocation and improve overall trading performance through systematic, data-driven approach to market timing.
Pine Script® göstergesi
TheUltimator5 tarafından
Bollinger Heatmap [Quantitative]Overview The Bollinger Heatmap is a composite indicator that synthesizes data derived from 30 Bollinger bands distributed over multiple time horizons, offering a high-dimensional characterization of the underlying asset. Algorithm The algorithm quantifies the current price’s relative position within each Bollinger band ensemble, generating a normalized position ratio. This ratio is subsequently transformed into a scalar heat value, which is then rendered on a continuous color gradient from red to blue. Red hues correspond to price proximity to or extension below the lower band, while blue hues denote price proximity to or extension above the upper band. Using default parameters, the indicator maps bands over timeframes increasing in a pattern approximating exponential growth, constrained to multiples of seven days. The lower region encodes relationships with shorter-term bands spanning between 1 and 14 weeks, whereas the upper region portrays interactions with longer-term bands ranging from 15 to 52 weeks. Conclusion By integrating Bollinger bands across a diverse array of time horizons, the heatmap indicator aims to mitigate the model risk inherent in selecting a single band length, capturing exposure across a richer parameter space.
Pine Script® göstergesi
Quantitative tarafından
1
MTF Dashboard 9 Timeframes + Signals# MTF Dashboard Pro - Multi-Timeframe Confluence Analysis System ## WHAT THIS SCRIPT DOES This script creates a comprehensive dashboard that simultaneously analyzes market conditions across 9 different timeframes (1m, 5m, 15m, 30m, 1H, 4H, Daily, Weekly, Monthly) using a proprietary confluence scoring methodology. Unlike simple multi-timeframe displays that show individual indicators separately, this script combines trend analysis, momentum, volatility signals, and volume analysis into unified confluence scores for each timeframe. ## WHY THIS COMBINATION IS ORIGINAL AND USEFUL **The Problem Solved:** Most traders manually check multiple timeframes and struggle to quickly assess overall market bias when different timeframes show conflicting signals. Existing MTF scripts typically display individual indicators without synthesizing them into actionable intelligence. **The Solution:** This script implements a mathematical confluence algorithm that: - Weights each indicator's signal strength (trend direction, RSI momentum, MACD volatility, volume analysis) - Calculates normalized scores across all active timeframes - Determines overall market bias with statistical confidence levels - Provides instant visual feedback through color-coded symbols and star ratings **Unique Features:** 1. **Confluence Scoring Algorithm**: Mathematically combines multiple indicator signals into a single confidence rating per timeframe 2. **Market Bias Engine**: Automatically calculates overall directional bias with percentage strength across all selected timeframes 3. **Dynamic Display System**: Real-time updates with customizable layouts, color schemes, and selective timeframe activation 4. **Statistical Analysis**: Provides bullish/bearish vote counts and overall confluence percentages ## HOW THE SCRIPT WORKS TECHNICALLY ### Core Calculation Methodology: **1. Trend Analysis (EMA-based):** - Fast EMA (default: 9) vs Slow EMA (default: 21) crossover analysis - Returns values: +1 (bullish), -1 (bearish), 0 (neutral) **2. Momentum Analysis (RSI-based):** - RSI levels: >70 (strong bullish +2), >50 (bullish +1), <30 (strong bearish -2), <50 (bearish -1) - Provides overbought/oversold context for trend confirmation **3. Volatility Analysis (MACD-based):** - MACD line vs Signal line positioning - Histogram strength comparison with previous bar - Combined score considering both direction and momentum strength **4. Volume Analysis:** - Current volume vs 20-period moving average - Thresholds: >150% MA (strong +2), >100% MA (bullish +1), <50% MA (weak -2) **5. Confluence Calculation:** ``` Confluence Score = (Trend + RSI + MACD + Volume) / 4.0 ``` **6. Market Bias Determination:** - Counts bullish vs bearish signals across all active timeframes - Calculates bias strength percentage: |Bullish Count - Bearish Count| / Total Active TFs * 100 - Determines overall market direction: BULLISH, BEARISH, or NEUTRAL ### Multi-Timeframe Implementation: Uses `request.security()` calls to fetch data from each timeframe, ensuring all calculations are performed on the respective timeframe's data rather than current chart timeframe, providing accurate multi-timeframe analysis. ## HOW TO USE THIS SCRIPT ### Initial Setup: 1. **Timeframe Selection**: Enable/disable specific timeframes in "Timeframe Selection" group based on your trading style 2. **Indicator Configuration**: Adjust EMA periods (Fast: 9, Slow: 21), RSI length (14), and MACD settings (12/26/9) to match your analysis preferences 3. **Display Options**: Choose table position, text size, and color scheme for optimal visibility ### Reading the Dashboard: **Symbol Interpretation:** - ⬆⬆ = Strong bullish signal (score ≥ 2) - ⬆ = Bullish signal (score > 0) - ➡ = Neutral signal (score = 0) - ⬇ = Bearish signal (score < 0) - ⬇⬇ = Strong bearish signal (score ≤ -2) **Confluence Stars:** - ★★★★★ = Very high confidence (score > 0.75) - ★★★★☆ = High confidence (score > 0.5) - ★★★☆☆ = Medium confidence (score > 0.25) - ★★☆☆☆ = Low confidence (score > 0) - ★☆☆☆☆ = Very low confidence (score > -0.25) **Market Bias Section:** - Shows overall market direction across all active timeframes - Strength percentage indicates conviction level - Overall confluence score represents average agreement across timeframes ### Trading Applications: **Entry Signals:** - Look for high confluence (4-5 stars) across multiple timeframes in same direction - Higher timeframe alignment provides stronger signal validation - Use confluence percentage >75% for high-probability setups **Risk Management:** - Lower timeframe conflicts may indicate choppy conditions - Neutral bias suggests ranging market - adjust position sizing - Strong bias with high confluence supports larger position sizes **Timeframe Harmony:** - Short-term trades: Focus on 1m-1H alignment - Swing trades: Emphasize 1H-Daily alignment - Position trades: Prioritize Daily-Monthly confluence ## SCRIPT SETTINGS EXPLANATION ### Dashboard Settings: - **Table Position**: Choose optimal location (Top Right recommended for most layouts) - **Text Size**: Adjust based on screen resolution and preferences - **Color Scheme**: Professional (default), Classic, Vibrant, or Dark themes - **Background Color/Transparency**: Customize table appearance ### Timeframe Selection: All timeframes optional - activate based on trading timeframe preference: - **Lower Timeframes (1m-30m)**: Scalping and day trading - **Medium Timeframes (1H-4H)**: Swing trading - **Higher Timeframes (D-M)**: Position trading and long-term bias ### Indicator Parameters: - **Fast EMA (Default: 9)**: Shorter period for trend sensitivity - **Slow EMA (Default: 21)**: Longer period for trend confirmation - **RSI Length (Default: 14)**: Standard momentum calculation period - **MACD Settings (12/26/9)**: Standard MACD configuration for volatility analysis ### Alert Configuration: - **Strong Signals**: Alerts when confluence >75% with clear directional bias - **High Confluence**: Alerts when multiple timeframes strongly agree - All alerts use `alert.freq_once_per_bar` to prevent spam ## VISUAL FEATURES ### Chart Elements: - **Background Coloring**: Subtle background tint reflects overall market bias - **Signal Labels**: Strong buy/sell labels appear on chart during high-confluence signals - **Clean Presentation**: Dashboard overlays chart without interfering with price action ### Color Coding: - **Green/Bullish**: Various green shades for positive signals - **Red/Bearish**: Various red shades for negative signals - **Gray/Neutral**: Neutral color for conflicting or weak signals - **Transparency**: Configurable transparency maintains chart readability ## IMPORTANT USAGE NOTES **Realistic Expectations:** - This tool provides analysis framework, not trading signals - Always combine with proper risk management - Past performance does not guarantee future results - Market conditions can change rapidly - use appropriate position sizing **Best Practices:** - Verify signals with additional analysis methods - Consider fundamental factors affecting the instrument - Use appropriate timeframes for your trading style - Regular parameter optimization may be beneficial for different market conditions **Limitations:** - Effectiveness may vary across different instruments and market conditions - Confluence scoring is mathematical model - not predictive guarantee - Requires understanding of underlying indicators for optimal use This script serves as a comprehensive analysis tool for traders who need quick, organized access to multi-timeframe market information with statistical confidence levels.
Pine Script® göstergesi
DeltaSpeedEdge tarafından
Volume Footprint Anomaly Scanner [PhenLabs]📊 PhenLabs - Volume Footprint Anomaly Scanner (VFAS) Version: PineScript™ v6 📌 Description The PhenLabs Volume Footprint Anomaly Scanner (VFAS) is an advanced Pine Script indicator designed to detect and highlight significant imbalances in buying and selling pressure within individual price bars. By analyzing a calculated "Delta" – the net difference between estimated buy and sell volume – and employing statistical Z-score analysis, VFAS pinpoints moments when buying or selling activity becomes unusually dominant. This script was created not in hopes of creating a "Buy and Sell" indicator but rather providing the user with a more in-depth insight into the intrabar volume delta and how it can fluctuate in unusual ways, leading to anomalies that can be capitalized on. This indicator helps traders identify high-conviction points where strong market participants are active, signaling potential shifts in momentum or continuation of a trend. It aims to provide a clearer understanding of underlying market dynamics, allowing for more informed decision-making in various trading strategies, from identifying entry points to confirming trend strength. 🚀 Points of Innovation ●​ Z-Score for Delta Analysis : Utilizes statistical Z-scores to objectively identify statistically significant anomalies in buying/selling pressure, moving beyond simple, arbitrary thresholds. ●​ Dynamic Confidence Scoring : Assigns a multi-star confidence rating (1-4 stars) to each signal, factoring in high volume, trend alignment, and specific confirmation criteria, providing a nuanced view of signal strength. ●​ Integrated Trend Filtering : Offers an optional Exponential Moving Average (EMA)-based trend filter to ensure signals align with the broader market direction, reducing false positives in ranging markets. ●​ Strict Confirmation Logic : Implements specific confirmation criteria for higher-confidence signals, including price action and a time-based gap from previous signals, enhancing reliability. ●​ Intuitive Info Dashboard : Provides a real-time summary of market trend and the latest signal's direction and confidence directly on the chart, streamlining information access. 🔧 Core Components ●​ Core Delta Engine : Estimates the net buying/selling pressure (bar Delta) by analyzing price movement within each bar relative to volume. It also calculates average volume to identify bars with unusually high activity. ●​ Anomaly Detection (Z-Score) : Computes the Z-score for the current bar's Delta, indicating how many standard deviations it is from its recent average. This statistical measure is central to identifying significant anomalies. ●​ Trend Filter : Utilizes a dual Exponential Moving Average (EMA) cross-over system to define the prevailing market trend (uptrend, downtrend, or range), providing contextual awareness. ●​ Signal Processing & Confidence Algorithm : Evaluates anomaly conditions against trend filters and confirmation rules, then calculates a dynamic confidence score to produce actionable, contextualized signal information. 🔥 Key Features ●​ Advanced Delta Anomaly Detection : Pinpoints bars with exceptionally high buying or selling pressure, indicating potential institutional activity or strong market conviction. ●​ Multi-Factor Confidence Scoring : Each signal comes with a 1-4 star rating, clearly communicating its reliability based on high volume, trend alignment, and specific confirmation criteria. ●​ Optional Trend Alignment : Users can choose to filter signals, so only those aligned with the prevailing EMA-defined trend are displayed, enhancing signal quality. ●​ Interactive Signal Labels : Displays compact labels on the chart at anomaly points, offering detailed tooltips upon hover, including signal type, direction, confidence, and contextual information. ●​ Customizable Bar Colors : Visually highlights bars with Delta anomalies, providing an immediate visual cue for strong buying or selling activity. ●​ Real-time Info Dashboard : A clean, customizable dashboard shows the current market trend and details of the latest detected signal, keeping key information accessible at a glance. ●​ Configurable Alerts : Set up alerts for bullish or bearish Delta anomalies to receive real-time notifications when significant market pressure shifts occur. 🎨 Visualization Signal Labels : * Placed at the top/bottom of anomaly bars, showing a "📈" (bullish) or "📉" (bearish) icon. * Tooltip: Hovering over a label reveals detailed information: Signal Type (e.g., "Delta Anomaly"), Direction, Confidence (e.g., "★★★☆"), and a descriptive explanation of the anomaly. * Interpretation: Clearly marks actionable signals and provides deep insights without cluttering the chart, enabling quick assessment of signal strength and context. ●​ Info Dashboard : * Located at the top-right of the chart, providing a clean summary. * Displays: "PhenLabs - VFAS" header, "Market Trend" (Uptrend/Downtrend/Range with color-coded status), and "Direction | Conf." (showing the last signal's direction and star confidence). * Optional "💡 Hover over signals for details" reminder. * Interpretation: A concise, real-time summary of the market's pulse and the most recent high-conviction event, helping traders stay informed at a glance. 📖 Usage Guidelines Setting Categories ⚙️ Core Delta & Volume Engine ●​ Minimum Volume Lookback (Bars) ○​ Default: 9 ○​ Range: Integer (e.g., 5-50) ○​ Description: Defines the number of preceding bars used to calculate the average volume and delta. Bars with volume below this average won't be considered for high-volume signals. A shorter lookback is more reactive to recent changes, while a longer one provides a smoother average. 📈 Anomaly Detection Settings Delta Z-Score Anomaly Threshold ○​ Default: 2.5 ○​ Range: Float (e.g., 1.0-5.0+) ○​ Description: The number of standard deviations from the mean that a bar's delta must exceed to be considered a significant anomaly. A higher threshold means fewer, but potentially stronger, signals. A lower threshold will generate more signals, which might include less significant events. Experiment to find the optimal balance for your trading style. 🔬 Context Filters Enable Trend Filter ○​ Default: False ○​ Range: Boolean (True/False) ○​ Description: When enabled, signals will only be generated if they align with the current market trend as determined by the EMAs (e.g., only bullish signals in an uptrend, bearish in a downtrend). This helps to filter out counter-trend noise. ●​ Trend EMA Fast ○​ Default: 50 ○​ Range: Integer (e.g., 10-100) ○​ Description: The period for the faster Exponential Moving Average used in the trend filter. In combination with the slow EMA, it defines the trend direction. ●​ Trend EMA Slow ○​ Default: 200 ○​ Range: Integer (e.g., 100-400) ○​ Description: The period for the slower Exponential Moving Average used in the trend filter. The relationship between the fast and slow EMA determines if the market is in an uptrend (fast > slow) or downtrend (fast < slow). 🎨 Visual & UI Settings ●​ Show Info Dashboard ○​ Default: True ○​ Range: Boolean (True/False) ○​ Description: Toggles the visibility of the dashboard on the chart, which provides a summary of market trend and the last detected signal. ●​ Show Dashboard Tooltip ○​ Default: True ○​ Range: Boolean (True/False) ○​ Description: Toggles a reminder message in the dashboard to hover over signal labels for more detailed information. ●​ Show Delta Anomaly Bar Colors ○​ Default: True ○​ Range: Boolean (True/False) ○​ Description: Enables or disables the coloring of bars based on their delta direction and whether they represent a significant anomaly. ●​ Show Signal Labels ○​ Default: True ○​ Range: Boolean (True/False) ○​ Description: Controls the visibility of the “📈” or “📉” labels that appear on the chart when a delta anomaly signal is generated. 🔔 Alert Settings ​ Alert on Delta Anomaly ○​ Default: True ○​ Range: Boolean (True/False) ○​ Description: When enabled, this setting allows you to set up alerts in TradingView that will trigger whenever a new bullish or bearish delta anomaly is detected. ✅ Best Use Cases ​ Early Trend Reversal / Continuation Detection: Identify strong surges of buying/selling pressure at key support/resistance levels that could indicate a reversal or the continuation of a strong move. ●​ Confirmation of Breakouts: Use high-confidence delta anomalies to confirm the validity of price breakouts, indicating strong conviction behind the move. ●​ Entry and Exit Points: Pinpoint precise entry opportunities when anomalies align with your trading strategy, or identify potential exhaustion signals for exiting trades. ●​ Scalping and Day Trading: The indicator’s sensitivity to intraday buying/selling imbalances makes it highly effective for short-term trading strategies. ●​ Market Sentiment Analysis: Gain a real-time understanding of underlying market sentiment by observing the prevalence and strength of bullish vs. bearish anomalies. ⚠️ Limitations Estimated Delta: The script uses a simplified method to estimate delta based on bar close relative to its range, not actual order book or footprint data. While effective, it’s an approximation. ●​ Sensitivity to Z-Score Threshold: The effectiveness heavily relies on the `Delta Z-Score Anomaly Threshold`. Too low, and you’ll get many false positives; too high, and you might miss valid signals. ●​ Confirmation Criteria: The 4-star confidence level’s “confirmation” relies on specific subsequent bar conditions and previous confirmed signals, which might be too strict or specific for all contexts. ●​ Requires Context: While powerful, VFAS is best used in conjunction with other technical analysis tools and price action to form a comprehensive trading strategy. It is not a standalone “buy/sell” signal. 💡 What Makes This Unique Statistical Rigor: The application of Z-score analysis to bar delta provides an objective, statistically-driven way to identify true anomalies, moving beyond arbitrary thresholds. ●​ Multi-Factor Confidence Scoring: The unique 1-4 star confidence system integrates multiple market dynamics (volume, trend alignment, specific follow-through) into a single, easy-to-interpret rating. ●​ User-Friendly Design: From the intuitive dashboard to the detailed signal tooltips, the indicator prioritizes clear and accessible information for traders of all experience levels. 🔬 How It Works 1. Bar Delta Calculation: ●​ The script first estimates the “buy volume” and “sell volume” for each bar. This is done by assuming that volume proportional to the distance from the low to the close represents buying, and volume proportional to the distance from the high to the close represents selling. ●​ How this contributes: This provides a proxy for the net buying or selling pressure (delta) within that specific price bar, even without access to actual footprint data. 2. Volume & Delta Z-Score Analysis: ●​ The average volume over a user-defined lookback period is calculated. Bars with volume less than twice this average are generally considered of lower interest. ●​ The Z-score for the calculated bar delta is computed. The Z-score measures how many standard deviations the current bar’s delta is from its average delta over the `Minimum Volume Lookback` period. ●​ How this contributes: A high positive Z-score indicates a bullish delta anomaly (significantly more buying than usual), while a high negative Z-score indicates a bearish delta anomaly (significantly more selling than usual). This identifies statistically unusual levels of pressure. 3. Trend Filtering (Optional): ●​ Two Exponential Moving Averages (Fast and Slow EMA) are used to determine the prevailing market trend. An uptrend is identified when the Fast EMA is above the Slow EMA, and a downtrend when the Fast EMA is below the Slow EMA. ●​ How this contributes: If enabled, the indicator will only display bullish delta anomalies during an uptrend and bearish delta anomalies during a downtrend, helping to confirm signals within the broader market context and avoid counter-trend signals. 4. Signal Generation & Confidence Scoring: ●​ When a delta Z-score exceeds the user-defined anomaly threshold, a signal is generated. ●​ This signal is then passed through a multi-factor confidence algorithm (`f_calculateConfidence`). It awards stars based on: high volume presence, alignment with the overall trend (if enabled), and a fourth star for very strong Z-scores (above 3.0) combined with specific follow-through candle patterns after a cooling-off period from a previous confirmed signal. ●​ How this contributes: Provides a qualitative rating (1-4 stars) for each anomaly, allowing traders to quickly assess the potential significance and reliability of the signal. 💡 Note: The PhenLabs Volume Footprint Anomaly Scanner is a powerful analytical tool, but it’s crucial to understand that no indicator guarantees profit. Always backtest and forward-test the indicator settings on your chosen assets and timeframes. Consider integrating VFAS with your existing trading strategy, using its signals as confirmation for entries, exits, or trend bias. The Z-score threshold is highly customizable; lower values will yield more signals (including potential noise), while higher values will provide fewer but potentially higher-conviction signals. Adjust this parameter based on market volatility and your risk tolerance. Remember to combine statistical insights from VFAS with price action, support/resistance levels, and your overall market outlook for optimal results.
Pine Script® göstergesi
PhenLabs tarafından
2