Garman-Klass-Yang-Zhang Volatility EstimatorThe Garman-Klass-Yang-Zhang Volatility Estimator (GKYZVE) is yet another attempt to robustly measure volatility, integrating intra-candle and inter-candle dynamics. It is an extension of the Garman-Klass Volatility Estimator (GKVE) incorporating insights from the Yang-Zhang Volatility Estimator (YZVE) . Like the YZVE, the GKYZVE holistically considers open, high, low, and close prices. The formula for GKYZ is:
GKYZVE = 0.5 * σ_HL² + * σ_CC² + σ_OC²
Where:
σ_HL² is the variance based on the high and low prices (σ_HL² = (high - low)² / (4 * math.log(2))), weighted at 0.5.
σ_CC² is the close-to-close variance (σ_CC² = (close - close)²), weighted at (2 ln 2) -1 for the logarithmic distribution of returns and emphasizing the impact of day-to-day price changes.
σ_OC² is the variance of the opening price against the closing price (σ_OC² = 0.5 * (open - close)²), weighted at 1.
The GKYZVE differs from the YZVE by using fixed weighing factors derived from theoretical calculations, leaning heavier into the assumption that returns are log-distributed.
This script also offers a choice for normalization between 0 and 1, turning the estimator into an oscillator for comparing current volatility to recent levels. Horizontal lines at user-defined levels are also available for clearer visualization. Both options are off by default.
References:
Garman, M. B., & Klass, M. J. (1980). On the estimation of security price volatilities from historical data. The Journal of Business, 53(1), 67-78.
Yang, D., & Zhang, Q. (2000). Drift-independent volatility estimation based on high, low, open, and close prices. The Journal of Business, 73(3), 477-492.
Oscillators
Volatility Estimator - YZ & RSThe Yang-Zheng Volatility Estimator (YZVE) integrates both intra-candle and inter-candle dynamics, such as overnight and weekend price changes, offering a more detailed analysis compared to traditional methods. The YZVE is proposed to improve over the standard deviation by accounting for the open, high, low, and close prices of trading periods, instead of only the close prices, and attempts to supplant the Parkinson's Volatility Estimator (PVE) by a also capturing inter-candle dynamics. The YZVE is calculated by this formula:
YZ Volatility Squared σ_YZ² = k * σ_o² + σ_rs² + (1 - k) * σ_c²
where k is a weighting factor that adjusts the emphasis between the overnight and close-to-close components, popularly estimated as:
k = 0.34 / (1.34 + (N+1) / (N-1))
where N is the lookback period. Optionally, users may opt to override this calculation with a specified constant (off by default). Next, the
Overnight Volatility Squared σ_o² = (log(O_t / C_(t-1)))²
measures the volatility associated with overnight price changes, from the previous candle's closing price C_(t-1) to the current candle's opening price O_t. It captures the market's reaction to news and events that occur outside of regular trading hours to reflect risk associated with holding positions over non-trading hours and gaps.
Next, the The Rogers-Satchell Volatility Estimator (RSVE) serves as an intermediary step in the computation of YZVE. It aggregates the logarithmic ratios between high, low, open, and close prices within each trading period, focusing on intra-candle volatility without assuming zero inter-candle drift as commonly implicitly assumed in other volatility models:
Rogers-Satchell Volatility Squared σ_rs² = (log(H_t / C_t) * log(H_t / O_t)) + (log(L_t / C_t) * log(L_t / O_t))
Finally,
Close-to-Close Volatility Squared σ_c² = (log(C_t / C_(t-1)))²
measures the volatility from the close of one candle to the close of the next. It reflects the typical candle volatility, similar to naive standard deviation.
This script also includes an option for users to apply the simpler RS Volatility exclusively, focusing on intraday price movements. Additionally, it offers a choice for normalization between 0 and 1, turning the estimator into an oscillator for comparing current volatility to recent levels. Horizontal lines at user-defined levels are also available for clearer visualization. Both are off by default.
References:
Yang, D., & Zhang, Q. (2000). Drift-independent volatility estimation based on high, low, open, and close prices. The Journal of Business, 73(3), 477-491.
Rogers, L.C.G., & Satchell, S.E. (1991). Estimating variance from high, low and closing prices. Annals of Applied Probability, 1(4), 504-512.
Parkinson's Volatility EstimatorThe Parkinson's Volatility Estimator (PVE) provides an alternative method for assessing market volatility using the highest and lowest prices within a given period. Unlike traditional models that predominantly rely on closing prices, the PVE considers the full range of intra-candle price movements, thereby potentially offering a more comprehensive gauge of market volatility. The estimator is derived from the logarithm of the ratio of the high to low prices, squared and then averaged over the period of interest. This calculation is rooted in the assumption that the logarithmic high-to-low ratio represents a normalized measure of price movements, capturing both upward and downward volatility in a symmetric manner (Parkinson, 1980).
In this specific implementation, the estimator is calculated as follows:
Parkinson’s Volatility = (1/4 log(2)) * (1/n) * Σ from i=1 to n of (log(High_i/Low_i))^2
where n is the lookback period defined by the user, and High_i and Low_i are the highest and lowest prices at each interval i within that period. This formulation takes advantage of the logarithmic properties to scale the volatility measure appropriately, utilizing a factor of 1/4 log(2) to normalize the variance estimate (Parkinson, 1980).
This implementation includes options for output normalization between 0 and 1 and for plotting horizontal lines at specified levels, allowing the estimator to function like an oscillator to evaluate volatility relative to recent market regimes. Users can customize these features through script inputs, enhancing flexibility for various trading scenarios and improving its utility for real-time volatility assessments on the TradingView platform.
Reference:
Parkinson, M. (1980). The extreme value method for estimating the variance of the rate of return. The Journal of Business, 53(1), 61-65.
Unmitigated Liquidity Imbalances [AlgoAlpha]🎉 Introducing the Unmitigated Liquidity Imbalance Indicator by AlgoAlpha! 🎉
Dive into the depths of market analytics with our "Unmitigated Liquidity Imbalance" indicator. This tool harnesses unique algorithms to detect liquidity imbalances between bulls and bears, helping traders spot trends and potential entry and exit points with greater accuracy. 📈🚀
🔍 Key Features:
🌟 Advanced Analysis : Analyses candle direction and length to forecast market peaks and valleys.
🎨 Customizable Visuals : Tailor the chart with your choice of bullish green or bearish red to reflect different market conditions.
🔄 Real-Time Updates : Continuously updates to reflect live market changes.
🔔 Configurable Alerts : Set up alerts for key trading signals such as bullish and bearish reversals, as well as trend shifts.
📐 How to Use:
🛠 Add the Indicator : Add the indicator to your favourites and customize the settings to suite your needs.
📊 Market Analysis : Monitor the oscillator threshold; readings above 0.5 suggest bullish sentiment, while below 0.5 indicate bearish conditions. And reversal signals are displayed to show potential entry points.
🔔 Set Alerts : Enable notifications for reversal conditions or trend changes to seize trading opportunities without constant chart watching.
🧠 How It Works:
The core mechanism of the indicator is based on detecting changes in candlestick size and direction to identify bullish and bearish liquidity levels from the peak & valley indicator's logic. By comparing the length of a current candle to the previous one and checking the change in direction, it pinpoints moments where market sentiment could be shifting, indicating if the liquidity at that point is bullish or bearish. The script then looks at what percentage of the past few unmitigated levels are bullish or bearish based on a customizable lookback and determines the liquidity imbalance which can then be interpreted as trend.
Empower your trading with the Unmitigated Liquidity Imbalance indicator and navigate the markets with confidence and precision. 🌟💹
Happy trading, and may your charts be ever in your favour! 🥳✨
💎 Related Indicator
RMVH by mycroftlearnstotradeThe RMVH indicator combines several popular technical analysis tools to provide a comprehensive view of market conditions. It includes Relative Strength Index (RSI), Moving Average Convergence Divergence (MACD), Volume, and Smoothed Heiken Ashi.
RSI (Relative Strength Index):
The RSI measures the strength and speed of price movements. It oscillates between 0 and 100, with levels above 70 indicating overbought conditions and levels below 30 indicating oversold conditions.
MACD (Moving Average Convergence Divergence):
The MACD is a trend-following momentum indicator that shows the relationship between two moving averages of a security’s price. It consists of the MACD line (the difference between a short-term and a long-term moving average) and the signal line (a moving average of the MACD line). The MACD histogram represents the difference between the MACD line and the signal line.
Volume:
The volume displays the total trading volume over a specified period. It helps traders gauge the strength or weakness of price movements. Typically, high volume accompanies strong price moves, while low volume may signal a lack of conviction in the market.
Smoothed Heiken Ashi:
The Smoothed Heiken Ashi is a variation of Japanese candlestick charts that aims to filter out market noise and highlight trends more effectively. It is calculated based on the open, high, low, and close prices, resulting in smoother candlesticks compared to traditional candlestick charts.
Usage:
Traders can use the RMVH indicator to identify potential trend reversals, overbought or oversold conditions, and divergence between price and momentum. Additionally, the volume component can help confirm the strength of price movements, while the Smoothed Heiken Ashi can provide a clearer visualization of trends.
Bullish signals may occur when the RSI and MACD indicate oversold conditions, accompanied by high volume and rising Smoothed Heiken Ashi values. Conversely, bearish signals may occur when the RSI and MACD indicate overbought conditions, accompanied by high volume and declining Smoothed Heiken Ashi values.
Note:
While the RMVH indicator combines multiple technical analysis tools, traders should exercise caution and use additional analysis to confirm signals before making trading decisions. No indicator is foolproof, and market conditions can change rapidly.
Hybrid Overbought/Oversold OverlayIntroduction
This is a new representation of my well-known oscillator Hybrid Overbought/Oversold Detector overlaid on the chart. The script utilizes the following 12 different oscillators to bring forth a new indicator which I call it Hybrid OB/OS .
Utilized Oscillators
The utilized oscillators here are:
Bollinger Bands %B
Chaikin Money Flow (CMF)
Chande Momentum Oscillator (CMO)
Commodity Channel Index (CCI)
Disparity Index (DIX)
Keltner Channel %K
Money Flow Index (MFI)
Rate Of Change (ROC)
Relative Strength Index (RSI)
Relative Vigor Index (RVI/RVGI)
Stochastic
Twiggs Money Flow (TMF)
The challenging part of utilizing mentioned oscillators was that some of their formulas range are not similar and some of them does not have a mathematical range at all. So I used a normalization function to normalize all their output values to (0, 100) interval.
Overbought/Oversold Levels Calculation
I noticed that the levels which considered as OB/OS level by various traders for each of the utilized oscillators are so different, e.g., many traders consider 30 as OS level and 70 as OB level for RSI and some others take 20 and 80 as the levels, or some traders consider 20 and 80 as OS/OB levels for Stochastic oscillator. Also these levels could be different on different assets, e.g., OB/OS levels for CCI on EURUSD chart might be 80 and 20 while the levels on BTCUSDT chart might be 75 and 25, and so on.
So I decided to make a routine to automate the calculation of these levels using historical data. By this feature, my indicator would calculate the corresponding levels for the oscillators on current chart and then decide about the overbought/oversold situation of each one, which leads to a more accurate Hybrid OB/OS indication.
As the result, if all 12 individual oscillators say it's overbought/oversold, the Hybrid OB/OS shows 100% overbought/oversold, vice versa, if none of them say it's overbought/oversold, the Hybrid OB/OS shows 0, and so on.
The Overlaying Oscillator Problem!
A programming-related challenge here was that Pine Script assigns two separate spaces to the oscillators and the overlaid indicators, and the programmers are limited to use just one of them in each of their codes.
Knowing this, I was forced to simulate the oscillator space on the chart and display my oscillator as a diagram somehow. Of course it won't be as nice as the oscillator itself, because the relation between the main chart bars and the oscillator bars could not be obtained, but it's better than nothing!
Settings and Usage
The indicator settings contain some options about the calculations, the diagram display and the signals appearance. By default they are fine, but you could change them as you prefer.
This indicator is better to be used alongside other indicators as a confirmation (specially in counter-trend strategies I believe). Also it generates an external signal which you could use it in your own designed indicators as well.
Feel free to test it and also the former form of the Hybrid OB/OS . Good Luck!
RSI and MACD Composite ScoreComponents of the Indicator
RSI Settings:
The RSI is set with a length parameter, which can be adjusted by the user but defaults to 14. This measures the speed and change of price movements.
MACD Settings:
The MACD is composed of two lines: the MACD line and the signal line, which are calculated from exponential moving averages (EMAs) of different lengths (fast and slow). The default settings are 9 for the fast length, 26 for the slow length, and 3 for the signal length.
The MACD histogram, which is the difference between the MACD line and the signal line, is also calculated.
Normalization and Combination
RSI Normalization : The RSI values are normalized around 0 by subtracting 50 from the RSI and then dividing by 50. This scaling adjusts the RSI to fluctuate around 0, where positive values indicate strength and negative values indicate weakness relative to the median RSI value of 50.
MACD Normalization : The MACD histogram is normalized by dividing it by the highest absolute value of the histogram over the slow length period. This adjustment scales the MACD histogram to fall between -1 and 1, making it comparable in magnitude to the normalized RSI.
Composite Score Calculation
The composite score is simply the sum of the normalized RSI and the normalized MACD histogram. This results in a combined score that reflects both momentum (from RSI) and trend (from MACD), providing a multifaceted view of market dynamics.
Visualization
The composite score is plotted as an oscillator, with a horizontal zero line that helps identify when the score shifts from positive to negative or vice versa.
The background color changes based on the trend: green if the composite score is above zero (bullish trend) and red if below zero (bearish trend).
Multi Timeframe ATR IndicatorThe Average True Range (ATR) indicator is a technical analysis tool used to measure market volatility. The ATR indicator is designed to capture the degree of price movement or price volatility over a specified period of time. It does this by calculating the true range for each bar or candlestick on a chart and then taking an average of these true range values over a set period.
In the provided Pine Script code, the ATR indicator is being calculated for two different timeframes, which allows traders to compare volatility across different periods. The script includes user-defined inputs for the length of the ATR calculation and the type of smoothing (RMA or SMA) to be applied to the true range values. The 'smoothingFunc' function within the script determines whether to use the RMA (Relative Moving Average) or SMA (Simple Moving Average) based on the user's selection.
The true range for each bar is calculated as the maximum of the following three values: the difference between the current high and low, the absolute value of the difference between the current high and the previous close, and the absolute value of the difference between the current low and the previous close. This calculation is designed to ensure that gaps and limit moves are properly accounted for in the volatility measurement.
The script then uses the 'smoothingFunc' to calculate the ATR values for the two timeframes, and these values are plotted on the chart as two separate lines, allowing traders to visually assess the volatility levels.
Overall, this custom ATR indicator is a versatile tool for traders who wish to analyse market volatility and compare it across different timeframes, potentially aiding in making more informed trading decisions based on the prevailing market conditions.
UM-Relative Strength Index with Trending EMA and Fill
Description
This is a different take on the traditional RSI - Relative Strength Index. This indicator turns the RSI line green when above 50 and red when below 50 making directional changes highly visual. Additionally, an exponential Moving Average is drawn of the RSI. The EMA is green when trending higher and red when trending lower. The area between the RSI and EMA lines are green when the RSI is above the RSI EMA and red when the RSI is below the EMA.
About
The RSI by itself is a good tool to determine trend with the colors. It can also be used to determined overbought and oversold extremes. The EMA of the RSI is a smoothing technique. The indicator can also be used to determine trend with the directional color changes.
Recommended Usage
I look for crossovers; bullish crossovers when the RSI crosses above the EMA AND the RSI crosses above 50. A bearish crossover is when the RSI crosses down through the EMA AND crosses below 50. It can also be used for trade confirmation; for example if the RSI EMA is green consider staying long. The indicator works on any timeframe and any security. I use it on smaller timeframes, 3 minute, 1 hour, and 3 hour, to better time entries/exits.
Default settings
The defaults are the author's preferred settings:
- RSI period is 10 using the open, high, low, and close for calculation. The additional data points using the OHLC give smoother effect.
- The EMA used by default is 34.
All parameters and colors are user-configurable.
Alerts
Alerts can be set on the indicator itself and/or alert on color changes of the EMA.
Helpful Hints:
Look for positive or negative crossovers.
Look for crosses above or below 50
Look for RSI divergences, for example if a security hits a new high, the RSI does not, this a sign of subtle weakness.
Draw trend lines on the RSI line. A violation of a recent trend line may indicate a change of trend for the security.
RSI, STOCHASTIC RSI AND MFI COMBOCombining the Relative Strength Index (RSI), Stochastic RSI (StochRSI), and Money Flow Index (MFI) can provide traders with a comprehensive approach to analyze market momentum, overbought/oversold conditions, and money flow. Each indicator offers unique insights, and their combination can help confirm trading signals and filter out false signals. Let's delve into each indicator and then discuss how they can be used together:
Relative Strength Index (RSI) 14: DA BLUE LINE
The RSI is a momentum oscillator that measures the speed and change of price movements. It oscillates between 0 and 100 and is typically used to identify overbought (>70) and oversold (<30) conditions. A reading above 70 may indicate that an asset is overbought and could be due for a pullback, while a reading below 30 may suggest that an asset is oversold and could be due for a bounce.
Stochastic RSI (StochRSI) 14: DA RED LINE
The StochRSI is an oscillator that combines the features of both the Stochastic Oscillator and RSI. It measures the relative position of the RSI within its range over a specific period (e.g., 14 periods). Like the RSI, the StochRSI oscillates between 0 and 100 and is used to identify overbought and oversold conditions. Typically:
A StochRSI above 0.8 may suggest overbought conditions.
A StochRSI below 0.2 may indicate oversold conditions.
Money Flow Index (MFI) 14: DA PURPLE LINE
The MFI is a momentum oscillator that measures the inflow and outflow of money into an asset over a specific period (e.g., 14 periods). It oscillates between 0 and 100 and is used to identify overbought and oversold conditions based on both price and volume. Generally:
An MFI above 80 may indicate overbought conditions.
An MFI below 20 may suggest oversold conditions.
Combining RSI, StochRSI, and MFI:
When combining RSI, StochRSI, and MFI, traders can use the following approach to analyze the market:
Identify Overbought/Oversold Conditions:
Look for confluence between RSI, StochRSI, and MFI readings to identify overbought and oversold conditions.
For example, if RSI > 70, StochRSI > 0.8, and MFI > 80, it may suggest a strong overbought condition, potentially indicating a reversal or pullback.
Confirm Trend Strength:
Use the RSI, StochRSI, and MFI to confirm the strength of a trend.
A rising trend with RSI, StochRSI, and MFI above 50 may suggest strong bullish momentum, while a falling trend with readings below 50 may indicate strong bearish momentum.
Divergence Analysis:
Look for divergences between price and RSI, StochRSI, or MFI to identify potential trend reversals.
For example, if the price makes a higher high, but RSI, StochRSI, or MFI makes a lower high (bearish divergence), it may suggest weakening bullish momentum and potential downside.
Combining RSI, StochRSI, and MFI can offer traders a more holistic view of market momentum, overbought/oversold conditions, and money flow. Backtest it let me know your success.
Market Structure RSIDescription:
The Market Structure RSI is an innovative indicator that combines the power of the Relative Strength Index (RSI) with market structure analysis to provide a unique perspective on the market. This indicator helps traders identify potential trend reversals and trading opportunities by analyzing the underlying market structure and generating overbought and oversold signals.
Key Features:
RSI Calculation: The indicator calculates a custom RSI based on the market structure, taking into account the formation of higher highs and lower lows. This unique approach to RSI calculation provides a more accurate representation of the market's strength and weakness.
Overbought and Oversold Levels: Users can customize the overbought and oversold levels according to their preferences. When the Market Structure RSI crosses above the oversold level, it generates a bullish signal, suggesting a potential long entry. Conversely, when the RSI crosses below the overbought level, it generates a bearish signal, indicating a potential short entry.
Moving Average: The indicator includes an optional moving average of the Market Structure RSI, which can be used to smooth out the RSI line and provide additional confirmation of trend reversals. Users can choose between EMA, SMA, and WMA and adjust the length of the moving average.
Customizable Close Type: The indicator allows users to define whether the market structure is deemed broken based on the candle close or the candle high/low. This flexibility enables traders to adapt the indicator to their preferred trading style and market conditions.
Visual Enhancements: The Market Structure RSI features gradient fills between the RSI line and the overbought/oversold levels, providing a clear visual representation of the market's strength. Additionally, the indicator plots bullish and bearish signals as circles on the RSI line, making it easy to identify potential entry points.
How to Use:
Add the Market Structure RSI to your chart and customize the settings according to your preferences, such as the RSI length, overbought and oversold levels, and moving average type and length.
Monitor the Market Structure RSI for crossovers above the oversold level or below the overbought level. A bullish signal occurs when the RSI crosses above the oversold level, while a bearish signal occurs when the RSI crosses below the overbought level.
Use the signals generated by the Market Structure RSI in conjunction with other technical analysis tools and price action patterns to confirm potential trade entries. The indicator works well as a complementary tool to support your existing trading strategy.
Consider the overall trend and market context when interpreting the signals generated by the Market Structure RSI. The indicator is most effective in trending markets and may produce less reliable signals in choppy or ranging market conditions.
Utilize sound risk management principles, such as setting appropriate stop-loss and take-profit levels, when trading based on the Market Structure RSI signals.
The Market Structure RSI offers a fresh perspective on the classic RSI indicator by incorporating market structure analysis. By combining the power of RSI with the identification of higher highs and lower lows, this indicator provides traders with a valuable tool for identifying potential trend reversals and trading opportunities. Whether you are a seasoned trader or just starting out, the Market Structure RSI can be a valuable addition to your technical analysis toolkit.
Bayesian Bias OscillatorWhat is a Bayes Estimator?
Bayesian estimation, or Bayesian inference, is a statistical method for estimating unknown parameters of a probability distribution based on observed data and prior knowledge about those parameters. At first , you will need a prior probability distribution, which is a prior belief about the distribution of the parameter that you are interested in estimating. This distribution represents your initial beliefs or knowledge about the parameter value before observing any data. Second , you need a likelihood function, which represents the probability of observing the data given different values of the parameter. This function quantifies how well different parameter values explain the observed data. Then , you will need a posterior probability distribution by combining the prior distribution and the likelihood function to obtain the posterior distribution of the parameter. The posterior distribution represents the updated belief about the parameter value after observing the data.
Bayesian Bias Oscillator
This tool calculates the Bayes bias of returns, which are directional probabilities that provide insight on the "trend" of the market or the directional bias of returns. It comes with two outputs: the default one, which is the Z-Score of the Bayes Bias, and the regular raw probability, which can be switched on in the settings of the indicator.
The Z-Score output value doesn't tell you the probability, but it does tell you how much of a standard deviation the value is from the mean. It uses both probabilities, the probability of a positive return and the probability of a negative return, which is just (1 - probability of a positive return).
The probability output value shows you the raw probability of a positive return vs. the probability of a negative return. The probability is the value of each line plotted (blue is the probability of a positive return, and purple is the probability of a negative return).
RSI Multi Strategies With Overlay SignalsHello everyone,
In this indicator, you will find 6 different entry and exit signals based on the RSI :
Entry into overbought and oversold zones
Exit from overbought and oversold zones
Crossing the 50 level
RSI cross RSI MA below or above the 50 level
RSI cross RSI MA in the overbought or oversold zones
RSI Divergence
With the signals identified, you can create your own strategy . (If you have any suggestions, please mention them in the comments).
Beyond these signals, you can set SL (Stop Loss) and TP (Take Profit) levels to better manage your positions.
SL Methods:
Percentage: The stop loss is determined by the percentage you specify.
ATR : The stop level is determined based on the Average True Range (ATR).
TP Methods:
Percentage: The take profit is determined by the percentage you specify.
RR ( Risk Reward ): The take profit level is determined based on the distance from the stop level.
You can mix and match these options as you like.
What makes the indicator unique and effective is its ability to display the RSI in the bottom chart and the signals, SL (Stop Loss), and TP (Take Profit) levels in the overlay chart simultaneously. This feature allows you to manage your trading quickly and easily without the need for using two separate indicators.
Let's try out a few strategies together.
My entry signal: RSI Entered OS (Oversold) Zone
My exit signal: RSI Entered OB (Overbought) Zone
I'm not using a stoploss for this strategy ("Fortune favors the brave").
Let's keep ourselves safe by adding a stop loss.
I'm adding an ATR-based stop loss.
I think it's better now.
If you have any questions or suggestions about the indicator, you can contact me.
Cheers
GM-8 and ADX Strategy with Second EMADescription:
This TradingView script implements a trading strategy based on the Moving Average (GM-8), the Average Directional Index (ADX), and the second Exponential Moving Average (EMA). The strategy utilizes these indicators to identify potential buy and sell signals on the chart.
Indicators:
GM-8 (Moving Average 8): This indicator calculates the average price of the last 8 periods and is used to identify trends.
ADX (Average Directional Index): The ADX measures the strength of a trend and is used to determine whether the market is moving in a particular direction or not.
Second EMA (Exponential Moving Average): This is an additional EMA line with a period of 59, which is used to provide additional confirmation signals for the trend.
Trading Conditions:
Buy Condition: A buy signal is generated when the closing price is above the GM-8 and the second EMA, and the ADX value is above the specified threshold.
Sell Condition: A sell signal is generated when the closing price is below the GM-8 and the second EMA, and the ADX value is above the specified threshold.
Trading Logic:
If a buy condition is met, a long position is opened with a user-defined lot size.
If a sell condition is met, a short position is opened with the same user-defined lot size.
Positions are closed when the opposite conditions are met.
User Parameters:
Users can adjust the periods for the GM-8, the second EMA, and the ADX, as well as the threshold for the ADX and the lot size according to their preferences.
Note:
This script has been developed for use on a $100,000 account with FTMO, therefore the account size is set to $100,000. Please ensure that the strategy parameters and settings meet the requirements of your trading strategy and carefully review the results before committing real capital.
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Beschreibung:
Dieses TradingView-Skript implementiert eine Handelsstrategie, die auf dem gleitenden Mittelwert (GM-8), dem Average Directional Index (ADX) und der zweiten exponentiellen gleitenden Durchschnittslinie (EMA) basiert. Die Strategie verwendet diese Indikatoren, um potenzielle Kauf- und Verkaufssignale auf dem Chart zu identifizieren.
Indikatoren:
GM-8 (Gleitender Mittelwert 8): Dieser Indikator berechnet den Durchschnittspreis der letzten 8 Perioden und wird verwendet, um Trends zu identifizieren.
ADX (Average Directional Index): Der ADX misst die Stärke eines Trends und wird verwendet, um festzustellen, ob sich der Markt in eine bestimmte Richtung bewegt oder nicht.
Zweite EMA (Exponential Moving Average): Dies ist eine zusätzliche EMA-Linie mit einer Periode von 59, die verwendet wird, um zusätzliche Bestätigungssignale für den Trend zu liefern.
Handelsbedingungen:
Kaufbedingung: Es wird ein Kaufsignal generiert, wenn der Schlusskurs über dem GM-8 und der zweiten EMA liegt und der ADX-Wert über dem angegebenen Schwellenwert liegt.
Verkaufsbedingung: Es wird ein Verkaufssignal generiert, wenn der Schlusskurs unter dem GM-8 und der zweiten EMA liegt und der ADX-Wert über dem angegebenen Schwellenwert liegt.
Handelslogik:
Wenn eine Kaufbedingung erfüllt ist, wird eine Long-Position mit einer benutzerdefinierten Losgröße eröffnet.
Wenn eine Verkaufsbedingung erfüllt ist, wird eine Short-Position mit derselben benutzerdefinierten Losgröße eröffnet.
Positionen werden geschlossen, wenn die Gegenbedingungen erfüllt sind.
Benutzerparameter:
Benutzer können die Perioden für den GM-8, die zweite EMA und den ADX sowie den Schwellenwert für den ADX und die Losgröße nach ihren eigenen Präferenzen anpassen.
Hinweis:
Dieses Skript wurde für die Verwendung auf einem $100.000-Konto bei FTMO entwickelt, daher ist die Kontogröße auf $100.000 festgelegt. Bitte stellen Sie sicher, dass die Strategieparameter und -einstellungen den Anforderungen Ihrer Handelsstrategie entsprechen und dass Sie die Ergebnisse sorgfältig überprüfen, bevor Sie echtes Kapital einsetzen.
Dynamic Price Oscillator (Zeiierman)█ Overview
The Dynamic Price Oscillator (DPO) by Zeiierman is designed to gauge the momentum and volatility of asset prices in trading markets. By integrating elements of traditional oscillators with volatility adjustments and Bollinger Bands, the DPO offers a unique approach to understanding market dynamics. This indicator is particularly useful for identifying overbought and oversold conditions, capturing price trends, and detecting potential reversal points.
█ How It Works
The DPO operates by calculating the difference between the current closing price and a moving average of the closing price, adjusted for volatility using the True Range method. This difference is then smoothed over a user-defined period to create the oscillator. Additionally, Bollinger Bands are applied to the oscillator itself, providing visual cues for volatility and potential breakout signals.
█ How to Use
⚪ Trend Confirmation
The DPO can serve as a confirmation tool for existing trends. Traders might look for the oscillator to maintain above or below its mean line to confirm bullish or bearish trends, respectively. A consistent direction in the oscillator's movement alongside price trend can provide additional confidence in the strength and sustainability of the trend.
⚪ Overbought/Oversold Conditions
With the application of Bollinger Bands directly on the oscillator, the DPO can highlight overbought or oversold conditions in a unique manner. When the oscillator moves outside the Bollinger Bands, it signifies an extreme condition.
⚪ Volatility Breakouts
The width of the Bollinger Bands on the oscillator reflects market volatility. Sudden expansions in the bands can indicate a breakout from a consolidation phase, which traders can use to enter trades in the direction of the breakout. Conversely, a contraction suggests a quieter market, which might be a signal for traders to wait or to look for range-bound strategies.
⚪ Momentum Trading
Momentum traders can use the DPO to spot moments when the market momentum is picking up. A sharp move of the oscillator towards either direction, especially when crossing the Bollinger Bands, can indicate the start of a strong price movement.
⚪ Mean Reversion
The DPO is also useful for mean reversion strategies, especially considering its volatility adjustment feature. When the oscillator touches or breaches the Bollinger Bands, it indicates a deviation from the normal price range. Traders might look for opportunities to enter trades anticipating a reversion to the mean.
⚪ Divergence Trading
Divergences between the oscillator and price action can be a powerful signal for reversals. For instance, if the price makes a new high but the oscillator fails to make a corresponding high, it may indicate weakening momentum and a potential reversal. Traders can use these divergence signals to initiate counter-trend moves.
█ Settings
Length: Determines the lookback period for the oscillator and Bollinger Bands calculation. Increasing this value smooths the oscillator and widens the Bollinger Bands, leading to fewer, more significant signals. Decreasing this value makes the oscillator more sensitive to recent price changes, offering more frequent signals but with increased noise.
Smoothing Factor: Adjusts the degree of smoothing applied to the oscillator's calculation. A higher smoothing factor reduces noise, offering clearer trend identification at the cost of signal timeliness. Conversely, a lower smoothing factor increases the oscillator's responsiveness to price movements, which may be useful for short-term trading but at the risk of false signals.
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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!
Market Trend OscillatorMarket Trend Oscillator segments the market into ranged bound and trending aspect. The threshold level segregates both types of market. With higher level, both the risk and reward lower down.
The MTO indicator, is based on Standard Deviation, difference between highest high and lowest low, ATR and ADR. There are two different volatility aspect which are:
Volatility according to the movement of one price e.g. closing price.
Volatility according to the candles.
The minimum of both these aspects gives an insight into the volatility of the market. To segregate a dynamic value with ATR and ADR is used with the threshold level. Moreover, the volatilities can be smoothed to have a smoother decision making.
RSI Confirm Trend with Williams (W%R)RSI Confirm Trend with Williams (W%R)
This is the "RSI Confirm Trend with Williams (W%R)" indicator
This is a modification of the "RSI Trends" indicator by zzzcrypto123.
What Is the Relative Strength Index (RSI)?
The relative strength index (RSI) is a momentum indicator used in technical analysis. RSI measures the speed and magnitude of a security's recent price changes to evaluate overvalued or undervalued conditions in the price of that security.
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.
How Does "RSI Confirm Trend with Williams (W%R)" work?
This indicator combines the momentum of both RSI and Williams %R by adding upper and lower thresholds. When the thresholds are broken, this indicator changes color from gray to either green or red.
What Are The Thresholds?
The default RSI thresholds are 55 and 45. These values are configurable.
The default Williams %R thresholds are 80 and 20. These values are configurable and made positive so it can be plotted against the RSI line.
How To Use?
When the RSI exceeded the upper/lower thresholds, the RSI line color will change from gray to lighter green/red color.
When the Williams %R exceeded the upper/lower thresholds, the RSI color will change to darker green/red color signifying a strong momentum in that direction.
When the RSI color is gray, this means the RSI and Williams %R thresholds are not broken which can also signify as no trend or consolidation.
The Williams %R line is not displayed by default but can be enabled using the checkbox provided in the Style tab.
This "RSI Confirm Trend with Williams (W%R)" indicator can be combined with other technical indicators to verify the idea behind this theory.
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Disclaimer
The information contained in this indicator does not constitute any financial advice or a solicitation to buy or sell any securities of any type.
My scripts/indicators/ideas are for educational purposes only!
RSI AcceleratorThe Relative Strength Index (RSI) is like a fitness tracker for the underlying time series. It measures how overbought or oversold an asset is, which is kinda like saying how tired or energized it is.
When the RSI goes too high, it suggests the asset might be tired and due for a rest, so it could be a sign it's gonna drop. On the flip side, when the RSI goes too low, it's like the asset is pumped up and ready to go, so it might be a sign it's gonna bounce back up. Basically, it helps traders figure out if a stock is worn out or revved up, which can be handy for making decisions about buying or selling.
The RSI Accelerator takes the difference between a short-term RSI(5) and a longer-term RSI(14) to detect short-term movements. When the short-term RSI rises more than the long-term RSI, it typically refers to a short-term upside acceleration.
The conditions of the signals through the RSI Accelerator are as follows:
* A bullish signal is generated whenever the Accelerator surpasses -20 after having been below it.
* A bearish signal is generated whenever the Accelerator breaks 20 after having been above it.
Volume RSIRelative strength index based on volume data.
Indicate volume momentum, and help you define divergences on volume.
The goal is to have an idea and represent in another form volumes and kept eyes on volume momentum on a certain period.
RSI is an indicator about the strength, I keep the oversold/overbought thresholds. I think it still makes sense to interpret.
the calculations is simple, we use the average volume up (avg_vol_up) and average volume down (avg_vol_down) over the period.
then calculate the relatives strength : ( avg_vol_up / ( avg_vol_up + avg_vol_down ) ) * 100
The period is 14 by default. The period is used for calculating mean.
I also add MA it helps to have a global look on the indicator.
In my code I used the idea of @Padronhosnai in his code "positve/negative volume" to get volumes in the right form.
For pictures I also use his indicator it's the one above.
RS Rating for Indian MarketRS Rating for Trading View
This Trading View script calculates the Relative Price Strength (RS) Rating for a given stock. It's a measure of a stock's price performance over the last twelve months, compared to all stocks in a selected Index. The rating scale ranges from 1 (lowest) to 99 (highest).
Features
- Adaptation for Indian Market
- Option to choose the index to compare to (NSE:NIFTY, NSE:CNX500, NSE:NIFTYSMLCAP250, NSE:CNXSMALLCAP)
- Option to compare to a different index
- Option to hide the RS rating
- Option to plot RS new highs
- Option to adjust the offset of the line for display purposes
- Option to change the color of the RS Line & Rating
- Option to change the color of the dots for RS new highs
- Option to choose which new high to plot (RS New Highs, RS New Highs Before Price, Historical RS New Highs, Historical RS New Highs Before Price)
- Option to adjust the recent high look-back count
Please note that the script is designed to work best in the daily timeframe. Results may not be accurate in other timeframes.
This script uses three methods to calculate the RS Rating:
1. A method that calculates how the stock behaves vs SMA.
2. A classic performance method that calculates the performance of the stock's closing price vs the closing price 3 months back.
3. A method that measures how the stock performs against the comparative Symbol.
The final RS Rating is a combination of the results from these three methods. The script also includes some adjustments based on observations to improve the accuracy of the rating.
RSI Overbought/Oversold [Overlay Highlighter]Indicator to show when the RSI is in oversold(Below 30) or overbought (Above 70) conditions. The background color of the chart changes colors in the areas where the above conditions are met.
Price can often reverse in these areas. However, this depends on the strength of the trend and price may continue higher or lower in the direction of the overall trend.
Divergence has been added to aid the user in timing reversals. Divergences are plotted by circles above or below the candles. Divergence is confirmed so there is a delay of one candle before the signal is given on the previous candle. Again, everything depends on the strength of the trend so use proper risk management.
Once the RSI has entered into oversold/overbought conditions, it is recommended to wait for divergence before entering into the trade near areas of support or resistance. It is recommended to utilize this strategy on the H4 timeframe, however, this particular strategy works on all timeframes.
This indicator is a modified version of seoco's RSI Overbought/Oversold + Divergence Indicator . The user interface has been refined, is now overlayed on the chart, and my own divergence code has been inserted.
Squeeze Momentum Oscillator [AlgoAlpha]🎉📈 Introducing the Squeeze Momentum Oscillator by AlgoAlpha 📉🎊
Unlock the secrets of market dynamics with our innovative Squeeze Momentum Oscillator! Crafted for those who seek to stay ahead in the fast-paced trading environment, this tool amalgamates critical market momentum and volatility indicators to offer a multifaceted view of potential market movements. Here's why it's an indispensable part of your trading toolkit:
Key Features:
🌈 Customizable Color Schemes: Easily distinguish between bullish (green) and bearish (red) momentum phases for intuitive analysis.
🔧 Extensive Input Settings: Tailor the oscillator lengths for both Underlying and Swing Momentum to match your unique trading approach.
📊 Dedicated Squeeze Settings: Leverage precise volatility insights to identify market squeeze scenarios, signaling potential breakouts or consolidations.
🔍 Advanced Divergence Detection: Utilize sophisticated algorithms to detect and visualize both bullish and bearish divergences, pointing towards possible market reversals.
📈 Hyper Squeeze Detection: Stay alert to high-momentum market movements with our hyper squeeze feature, designed to extremely suppressed market volatility.
🔔 Comprehensive Alert System: Never miss a trading opportunity with alerts for momentum changes, squeeze conditions, and more.
Quick Guide to Using the Squeeze Momentum Oscillator:
🛠 Add the Indicator: Add the indicator to your favourites. Adjust the oscillator and squeeze settings to suit your trading preferences.
📊 Market Analysis: Keep an eye on the squeeze value and momentum z-score for insights into volatility and market direction. Hyper Squeeze signals are your cue for high momentum trading opportunities.
🔔 Alerts: Configure alerts for shifts in underlying and swing momentum, as well as entry and exit points for squeeze conditions, to capture market moves efficiently.
How It Works:
The Squeeze Momentum Oscillator by AlgoAlpha synergistically combines the principles of momentum tracking and market squeeze detection. By integrating the core logic of the Squeeze & Release indicator, it calculates the Squeeze Value (SV) through a comparison of the Exponential Moving Average (EMA) of the Average True Range (ATR) against the high-low price EMA. This SV is further analyzed alongside its EMA to pinpoint squeeze conditions, indicative of potential market breakouts or consolidations. In addition to this, the oscillator employs Hyper Squeeze Detection for identifying extremely low volatility. The momentum aspect of the oscillator evaluates the price movement relative to EMAs of significant highs and lows, refining these observations with a z-score normalization for short-term momentum insights. Moreover, the incorporation of divergence detection aids in identifying potential reversals, making this oscillator a comprehensive tool for traders looking to harness the power of volatility and momentum in their market analysis. The combination of the Squeeze & Release and the Momentum Oscillator allows traders to time their trades with more precision by entering when the market is in a squeeze and front running the volatility of a major move.
Elevate your trading strategy with the Squeeze Momentum Oscillator by AlgoAlpha and gain a competitive edge in deciphering market dynamics! 🌟💼 Happy trading!
UT Bot Stochastic RSIUT Bot Stochastic RSI is a powerful trading tool designed to help traders identify potential buy and sell signals in the market. This indicator combines the Stochastic and RSI (Relative Strength Index) oscillators, two of the most popular and effective technical analysis tools, to provide a comprehensive view of market conditions.
The Stochastic oscillator is a momentum indicator that compares a security's closing price to its price range over a given time period. The RSI, on the other hand, is a momentum oscillator that measures the speed and change of price movements. By combining these two indicators, the UT Bot Stochastic RSI can help traders identify overbought and oversold conditions, as well as potential trend reversals.
The UT Bot Stochastic RSI also includes an ATR (Average True Range) trailing stop, which can be used to set stop-loss levels and manage risk. This feature is particularly useful in volatile markets, where price movements can be large and unpredictable.
In addition to its powerful technical analysis tools, the UT Bot Stochastic RSI also includes a backtesting feature, allowing traders to test their strategies on historical data. This can help traders identify the most effective settings for the indicator and improve their trading performance.
Overall, the UT Bot Stochastic RSI is a versatile and effective tool for traders of all levels, providing valuable insights into market conditions and helping to improve trading decisions
