RSI Chart LevelsThe RSI Chart Levels shows you in a simple way where Support/Resistance might be. You want to make sure all settings are the same in the RSI that you are using with this overlay to be accurate.
This is also good at spotting divergence in real-time. If price goes over the Higher High but the RSI hasn't gained a new Higher High it is showing divergence, vice versa for Lower Low.
This overlay was created with the idea of RSI Divergence Scanner by zdmre indicator. Add his RSI and match the settings to the chart overlay. The default Zigzag is set to 7 which zdmre settings is different so change to whatever you prefer.
Shoutout to zdmre original work!
M-oscillator
Price and Indicator CorrelationFIRST, CHANGE SOURCE OF INDICATOR FROM CLOSE TO WHATEVER INDICATOR YOU ARE COMPARING TO PRICE!!!!
Confirming Indicator Validity: By calculating the correlation coefficient between the price and a specific indicator, you can assess the degree to which the indicator and price move together. If there is a high positive correlation, it suggests that the indicator tends to move in the same direction as the price, increasing confidence in the indicator's validity. On the other hand, a low or negative correlation may indicate a weaker relationship between the indicator and price, signaling caution in relying solely on that indicator for trading decisions.
Identifying Divergence: Divergence occurs when the price and the indicator move in opposite directions. By monitoring the correlation coefficient, you can identify periods of divergence between the price and the selected indicator. Divergence may signal a potential reversal or significant price move, providing an opportunity to enter or exit trades.
Enhancing Trading Strategies: The correlation coefficient can be used to enhance trading strategies by incorporating the relationship between the price and the indicator. For example, if the correlation coefficient consistently shows a strong positive correlation, you may use the indicator as a confirmation tool for price-based trading signals. Conversely, if the correlation is consistently negative, it may indicate an inverse relationship that could be used for contrarian trading strategies.
Indicator Optimization : The correlation coefficient can help traders compare the effectiveness of different indicators. By calculating the correlation coefficient for multiple indicators against the price, you can identify which indicators have a stronger or weaker relationship with price movements. This information can guide the selection and optimization of indicators in your trading strategy.
Example:
RSI MACDDifferent Perspective : By using the RSI as the source for MACD calculation, you are incorporating the RSI's characteristics into the MACD indicator. The RSI measures the speed and change of price movements, while the MACD focuses on the convergence and divergence of moving averages. Combining these two indicators may provide a different perspective on market conditions.
Smoothed MACD : Since the RSI is being used as the source for the MACD calculation, the resulting MACD line (macd1 in the code) may exhibit smoother movements compared to a traditional MACD calculated directly from price data. This smoothing effect could potentially help filter out noise and provide a clearer representation of trend changes.
RSI Confirmation : The RSI is often used to identify overbought and oversold conditions. By incorporating the RSI into the MACD calculation, you can potentially gain additional confirmation when the MACD line crosses above or below zero. For example, if the MACD line crosses above zero and the RSI is in an oversold region, it could provide stronger confirmation for a bullish signal.
Example:
Stochastic Zone Strength Trend [wbburgin](This script was originally invite-only, but I'd vastly prefer contributing to the TradingView community more than anything else, so I am making it public :) I'd much rather share my ideas with you all.)
The Stochastic Zone Strength Trend indicator is a very powerful momentum and trend indicator that 1) identifies trend direction and strength, 2) determines pullbacks and reversals (including oversold and overbought conditions), 3) identifies divergences, and 4) can filter out ranges. I have some examples below on how to use it to its full effectiveness. It is composed of two components: Stochastic Zone Strength and Stochastic Trend Strength.
Stochastic Zone Strength
At its most basic level, the stochastic Zone Strength plots the momentum of the price action of the instrument, and identifies bearish and bullish changes with a high degree of accuracy. Think of the stochastic Zone Strength as a much more robust equivalent of the RSI. Momentum-change thresholds are demonstrated by the "20" and "80" levels on the indicator (see below image).
Stochastic Trend Strength
The stochastic Trend Strength component of the script uses resistance in each candlestick to calculate the trend strength of the instrument. I'll go more into detail about the settings after my description of how to use the indicator, but there are two forms of the stochastic Trend Strength:
Anchored at 50 (directional stochastic Trend Strength):
The directional stochastic Trend Strength can be used similarly to the MACD difference or other histogram-like indicators : a rising plot indicates an upward trend, while a falling plot indicates a downward trend.
Anchored at 0 (nondirectional stochastic Trend Strength):
The nondirectional stochastic Trend Strength can be used similarly to the ADX or other non-directional indicators : a rising plot indicates increasing trend strength, and look at the stochastic Zone Strength component and your instrument to determine if this indicates increasing bullish strength or increasing bearish strength (see photo below):
(In the above photo, a bearish divergence indicated that the high Trend Strength predicted a strong downwards move, which was confirmed shortly after. Later, a bullish move upward by the Zone Strength while the Trend Strength was elevated predicated a strong upwards move, which was also confirmed. Note the period where the Trend Strength never reached above 80, which indicated a ranging period (and thus unprofitable to enter or exit)).
How to Use the Indicator
The above image is a good example on how to use the indicator to determine divergences and possible pivot points (lines and circles, respectively). I recommend using both the stochastic Zone Strength and the stochastic Trend Strength at the same time, as it can give you a robust picture of where momentum is in relation to the price action and its trajectory. Every color is changeable in the settings.
Settings
The Amplitude of the indicator is essentially the high-low lookback for both components.
The Wavelength of the indicator is how stretched-out you want the indicator to be: how many amplitudes do you want the indicator to process in one given bar.
A useful analogy that I use (and that I derived the names from) is from traditional physics. In wave motion, the Amplitude is the up-down sensitivity of the wave, and the Wavelength is the side-side stretch of the wave.
The Smoothing Factor of the settings is simply how smoothed you want the stochastic to be. It's not that important in most circumstances.
Trend Anchor was covered above (see my description of Trend Strength). The "Trend Transform MA Length" is the EMA length of the Trend Strength that you use to transform it into the directional oscillator. Think of the EMA being transformed onto the 50 line and then the Trend Strength being dragged relative to that.
Trend Transform MA Length is the EMA length you want to use for transforming the nondirectional Trend Strength (anchored at 0) into the directional Trend Strength (anchored at 50). I suggest this be the same as the wavelength.
Trend Plot Type can transform the Nondirectional Trend Strength into a line plot so that it doesn't murk up the background.
Finally, the colors are changeable on the bottom.
Explanation of Zone Strength
If you're knowledgeable in Pine Script, I encourage you to look at the code to try to understand the concept, as it's a little complicated. The theory behind my Zone Strength concept is that the wicks in every bar can be used create an index of bullish and bearish resistance, as a wick signifies that the price crossed above a threshold before returning to its origin. This distance metric is unique because most indicators/formulas for calculating relative strength use a displacement metric (such as close - open) instead of measuring how far the price actually moved (up and down) within a candlestick. This is what the Zone Strength concept represents - the hesitation within the bar that is not typically represented in typical momentum indicators.
In the script's code I have step by step explanations of how the formula is calculated and why it is calculated as such. I encourage you to play around with the amplitude and wavelength inputs as they can make the zone strength look very different and perform differently depending on your interests.
Enjoy!
Walker
Z-Score Heikin-Ashi TransformedThe Z-Score Heikin-Ashi Transformed (𝘡 𝘏-𝘈) indicator is a powerful technical tool that combines the principles of Z-Score and Heikin Ashi to provide traders with a smoothed representation of price movements and a standardized measure of market volatility.
The 𝘡 𝘏-𝘈 indicator applies the Z-Score calculation to price data and then transforms the resulting Z-Scores using the Heikin Ashi technique. Understanding the individual components of Z-Score and Heikin Ashi will provide a foundation for comprehending the methodology and unique features of this indicator.
Z-Score:
Z-Score is a statistical measure that quantifies the distance between a data point and the mean, relative to the standard deviation. It provides a standardized value that allows traders to compare different data points on a common scale. In the context of the 𝘡 𝘏-𝘈 indicator, Z-Score is calculated based on price data, enabling the identification of extreme price movements and the assessment of their significance.
Heikin Ashi:
Heikin Ashi is a popular charting technique that aims to filter out market noise and provide a smoother representation of price trends. It involves calculating each candlestick based on the average of the previous candle's open, close, high, and low prices. This approach results in a chart that reduces the impact of short-term price fluctuations and reveals the underlying trend more clearly.
Methodology:
The 𝘡 𝘏-𝘈 indicator starts by calculating the Z-Score of the price data, which provides a standardized measure of how far each price point deviates from the mean. Next, the resulting Z-Scores are transformed using the Heikin Ashi technique. Each Z-Score value is modified according to the Heikin Ashi formula, which incorporates the average of the previous Heikin Ashi candle's open and close prices. This transformation smooths out the Z-Score values and reduces the impact of short-term price fluctuations, providing a clearer view of market trends.
This tool enables traders to identify significant price movements and assess their relative strength compared to historical data. Positive transformed Z-Scores indicate that prices are above the average, suggesting potential overbought conditions, while negative transformed Z-Scores indicate prices below the average, suggesting potential oversold conditions. Traders can utilize this information to identify potential reversals, confirm trend strength, and generate trading signals.
Utility:
The indicator offers valuable insights into price volatility and trend analysis. By combining the standardized measure of Z-Score with the smoothing effect of Heikin Ashi, traders can make more informed trading decisions and improve their understanding of market dynamics. 𝘡 𝘏-𝘈 can be used in various trading strategies, including identifying overbought or oversold conditions, confirming trend reversals, and establishing entry and exit points.
Note that the 𝘡 𝘏-𝘈 should be used in conjunction with other technical indicators and analysis tools to validate signals and avoid false positives. Additionally, traders are encouraged to conduct thorough backtesting and experimentation with different parameter settings to optimize the effectiveness of the indicator for their specific trading approach.
Key Features:
Optional Reversion Doritos
Adjustable Reversion Threshold
2 Adjustable EMAs
Example Charts:
See Also:
On Balance Volume Heikin-Ashi Transformed
RSI Trend Transform [wbburgin]The RSI Trend Transform indicator is a dual-concept indicator that transforms volume data and price data into two different RSI values, which can then be used together to determine trend strength and momentum. The volume RSI does not use any price data in its calculation - it is purely a transform from nondirectional volume into a directional indicator.
The RSI for all three RSI values (price, volume,combined average) can be plotted as either stochastic or normal. The RSI calculation is adapted for use on volume, which is why the normal ta.rsi() function is not used for the price RSI calculation; both use the same formula for indicator consistency.
How to Use the Indicator
In the examples below, the Price RSI is plotted in yellow and the Volume RSI is plotted in red (length = 200, which is why the indicator is large in these examples). The indicator can be used on any timeframe and any asset, provided volume data is provided by the vendor to TradingView.
Identifying Bullish Trends
A rising volume RSI with a rising price RSI signifies a bullish trend. Example 1:
Example 2:
You can use the combined RSI (the average of the volume RSI and the price RSI) to help with the identification of these trends:
Identifying Bearish Trends
A falling volume RSI with a falling price RSI signifies a bearish trend:
Example 2:
Settings
Source is the source of the price RSI, the volume RSI will by default use volume in its calculations. If you have other indicators on-chart, you could even use the ATR, a volatility indicator, or any nondirectional or directional indicator and transform it into the "price" RSI.
Length is both the length of the RSI and the stochastic.
The next three rows are for each RSI you can plot on the indicator: price RSI, volume RSI, and combined RSI (average of price and volume). The first checkbox plots/removes them from the chart, you can subsequently choose the type of RSI (regular or stochastic), the color of the plot, and the length of the EMA smoothing applied afterward to the plot.
Upper Band and Lower Band refer to the overbought and oversold lines, respectively.
A note about the combined RSI- you will be unable to spot divergences if the combined RSI is the only plot on the indicator, so I encourage you to use the combined RSI as a way to confirm the overall trend if you notice the price RSI and the volume RSI and trending similarly.
Lune Oscillator Premium⬛️ Overview
Lune Oscillator is an advanced and innovative TradingView indicator designed to enhance your market analysis. Rather than merely improving visuals or merging traditional indicators, it introduces a series of unique features, each with its unique value proposition. This script stands out due to its originality, and the significant utility it brings to traders.
🟦 Features
Oscillator features an assortment of sophisticated tools aimed at refining your trading strategies:
🔹 Trend Oscillator: This feature integrates market trend and momentum analysis into one dynamic oscillator. It's designed to facilitate market trend and momentum analysis, and is invaluable to traders as it combines both trend and momentum analysis into one tool. For instance, if a ticker shows signs of slowing momentum after a recent rally, the Trend Oscillator could predict a potential trend reversal. The Trend Oscillator’s sensitivity and velocity settings can be tailored to suit your trading style and strategy. It is developed using a custom formula similar to WaveTrend but optimized for better detection of trend and momentum shifts.
🔹 Market Peak: Market Peak identifies potential market peaks and troughs using a percentile-based system. It's aimed at detecting overextensions in the Trend Oscillator, indicating potential market reversals. Compact and user-friendly, this feature signals potential trade exit points in case of an impending market reversal. Its sensitivity can be adjusted to react to either short-term or long-term market changes. By analyzing the market's average move, it detects overbought or oversold conditions when the percentage gets too extreme.
🔹 Money Pulse: The Money Pulse feature serves as a radar for money inflow or outflow, helping users detect nascent trends and reversals. It enables traders to spot early opportunities and reversals and align their strategies with institutional and large players. For example, a bullish Money Pulse during market consolidation could signal money influx and the beginning of an accumulation phase. The sensitivity of the Market Pulse can be adapted to short-term or long-term changes. This feature employs an improved version of the Money Flow concept.
🔹 Liquidity Pulse: Liquidity Pulse provides a unique perspective of asset liquidity by tracking market inflow and outflow volumes. It assists traders in understanding the market's liquidity sentiment, which is particularly useful for long-term trades and confluence. For instance, a bullish Liquidity Pulse could signal abundant liquidity, potentially driving up the price. The sensitivity setting can be adjusted for short-term or long-term liquidity changes. This feature utilizes an enhanced version of the On-Balance Volume concept.
🔹 Institutional Wave: This feature tracks the cumulative inflow and outflow for a specific ticker, helping traders monitor institutional money flows. It enables the analysis of a ticker's accumulation and distribution, assisting in detecting early trade entries and avoiding dumps. For example, a decrease in volume during consolidation after a price rally could indicate sell-off and potential price drop. The Institutional Wave's sensitivity can be adapted to either short-term or long-term changes. It operates on the Accumulation and Distribution concept.
🔹 Power Wave: The Power Wave evaluates market strength and momentum, indicating market power shifts. It helps traders understand the true power behind a market move. For instance, a decreasing Power Wave during a bullish move could indicate a weakening trend, suggesting a bearish strategy instead. The sensitivity of the Power Wave can be set for short-term or long-term market changes. The Power Wave calculates market strength by evaluating price change volatility.
🔹 Market Pressure: This feature detects shifts in buy and sell pressure, signaling potential turning points. It helps traders understand the power balance in the market. For example, a bullish Market Pressure shift during a short trade could suggest a momentum gain by bulls, indicating a trade exit. The Market Pressure's sensitivity can be adjusted for short-term or long-term changes. This feature uses volume data and moving averages to detect market pressure shifts, filtering out false and volatile signals.
🔹 Oscillator Copilot: Incorporating Smart Bias and Reversal Radar, the Oscillator Copilot helps identify market trends and potential reversals. It searches for confluence within multiple Oscillator features, providing a straightforward assistive tool. For example, a bullish Smart Bias signal during a long trade could suggest staying in the trade longer, while a bearish Reversal Radar signal could indicate the need to exit the trade.
🔹 Divergence Detection: This feature offers a sophisticated detection system for both regular and hidden market divergences, providing additional confluence and highlighting hard-to-detect divergences. For instance, a bullish Regular Divergence could signal a potential trade entry or exit depending on your overall market sentiment and bias. This feature uses fractals to effectively detect divergences in the market based on the Trend Oscillator.
🔹 Color Themes: Personalize your charting experience with various color themes. This feature enhances the visual appeal of your chart, offering easy setup and use. For example, use the “Ice” theme for a unique and colorful experience or the “Dark” theme for a more subdued look. Themes available include Default, Light, Dark, and Ice. This feature modifies the colors of your candles and features based on the selected theme.
These features and tools collectively offer a comprehensive solution for traders to understand and navigate the financial markets. It's important to remember that they are designed to assist in making informed trading decisions and should be used as part of a balanced trading strategy.
🟧 Usage
Lune Oscillator's features are designed to be both standalone tools and components of a larger, integrated trading strategy. It is important to understand each feature and experiment with different configurations to best suit your unique trading needs.
🔸 Example #1: The following demonstrates how the Oscillator Copilot can be an excellent trade assistant.
The Oscillator Copilot leverages multiple Lune Oscillator features, allowing traders to quickly assess overall market sentiment. It uses Smart Bias and Reversal Radar tools to deliver these insights. For instance, at point 1, a bullish Smart Bias (denoted by a green circle) represents a collective bullish sentiment from multiple components of Lune Oscillator, often leading to a price increase. Conversely, at point 2, we identify two bearish reversal signals from the Reversal Radar (highlighted by red triangles). This convergence of bearish signals from multiple components hints at a potential market reversal, often followed by a gradual price decline.
🔸 Example #2: This example shows how the Market Peak feature can aid in detecting potential market tops and bottoms.
Market Peak calculates how overbought or oversold a ticker is using a percentile system, offering insights into potential reversals. At points 1 and 2, we observe bearish Market Peaks suggesting overbought conditions and indicating a possible shift in trend. Subsequent to these peaks, we witness a price drop, mirroring the overbought market conditions. In contrast, at point 3, a bullish Market Peak suggests an oversold market, indicating a potential trend reversal and subsequent price increase.
🔸 Example #3: This is an example of how combining various features such as the Money Pulse, Liquidity Pulse, Institutional Wave, and Market Peak, can help make more informed trades.
Money Pulse and Liquidity Pulse provide insights into the money and liquidity flow in the market, respectively, while the Institutional Wave monitors the cumulative volume shifts and changes. Together with Market Peak, they offer a comprehensive view of the market's state.
At point 1, the positive Liquidity Wave (crossing above 0) suggests a bullish market volume. At point 2, a bullish Market Pressure indicates an increase in buying pressure, reinforcing the bullish sentiment. At point 3, a negative Liquidity Wave (crossing below 0) indicates a bearish sentiment, suggesting that market participants are exiting their positions. The concurrent Market Pressure hints at an increase in selling activity. Taking all these factors into account provides a strong indicator that the market sentiment has turned bearish.
🟥 Conclusion
Lune Oscillator aims to provide a suite of tools that bring unique value to traders. Each feature is designed to offer different, yet complementary, perspectives on the market, allowing users to piece together a more comprehensive understanding of their trading environment.
🔻 Access
You can see the Author's instructions below to get instant access to this indicator & our Premium Suite.
🔻 Disclaimer
Lune Oscillator is a tool for aiding in market analysis and is not a guarantee of future market performance or individual trading success. We strongly recommend that users combine our tool with their trading strategies and do their due diligence before making any trading decisions.
Remember, past performance is not indicative of future results. Please trade responsibly.
Boom Hunter X AlertsThis is a supplementary tool for Boom Hunter X. It has two main purposes. Firstly it handles setting alerts for all 3 Boom Hunter X presets with the convenience of only using one alert. The second purpose is as a chart assistance to display pivots and first pullbacks directly on your chart. By default the script is set to only show the last few bars but this can be modified in the settings up to 20000 to show all bars, this is handy for backtesting.
Signals are only lightly filtered and are designed to get you looking at the charts are the right times.
There are alerts for all 3 presets including:
- Pivots: HL, LH, HH, LL, 1st HL, 1st LH, Reversal up, Reversal down.
- Median crossings
- Kernel Regression crossing (kreg)
- First pullbacks
To use simply tick all the signals you wish to be alerted for in the settings.
Choose the frequency of the alerts in the settings to either on bar close or once per bar.
Click the create alert button, find BHX Alerts and select Any alert() function call.
Z-Score CandlesThe Z-Score Candles indicator is a powerful tool designed to help traders identify overbought and oversold conditions in the market. It utilizes the concept of the Z-score, which measures the deviation of a data point from its mean in terms of standard deviations.
By applying a sigmoid transformation to the Z-score values of the price candles, this indicator provides a visual representation of the market sentiment. The resulting sigmoid candles offer a clearer view of potential trend reversals and market extremes.
Parameters:
Length: The length parameter determines the number of bars used in the calculations. A higher value results in a smoother representation of the Z-scores, while a lower value makes the indicator more responsive to short-term price movements.
Features:
Sigmoid Function: The indicator incorporates a sigmoid function to transform the Z-score values, making them more suitable for visual analysis.
Original Price Candles: The indicator plots the sigmoid candles, representing the open, high, low, and close values of the price action. Green candles indicate a positive sentiment (szopen < szclose), while red candles indicate a negative sentiment (szopen >= szclose).
Oversold and Overbought Areas: The indicator creates horizontal lines at 0.1 and 0.9 on the y-axis, representing oversold and overbought levels, respectively. Additionally, it adds shaded areas to highlight the extreme regions.
Usage: Traders can utilize the Z-Score Candles indicator to identify potential market turning points, reversals, and overextended price levels. When the sigmoid candles reach the oversold or overbought areas, it may suggest a possible trend reversal or the initiation of a new trend.
Note: This indicator should be used in conjunction with other technical analysis tools and indicators to confirm trading decisions.
Momentum Oscillator, Divergences & Signals [TrendAlpha]The "Momentum, Real Time Divergences & Signals " indicator is designed to provide traders with insights into market momentum, identify potential divergences, and generate buy and sell signals. It offers a comprehensive set of features to assist traders in making informed trading decisions.
The indicator starts by calculating the momentum oscillator based on user-defined parameters.
- Traders can adjust the "Length" parameter to customize the sensitivity of the oscillator. The default value is set to 7, but it can be modified according to individual preferences.
- The "Source" parameter allows traders to select the input source for the oscillator calculation, with the default being the closing price of the asset.
- Traders have the option to display divergence lines by switching on the "Show Lines" parameter. This feature helps identify potential divergences between the oscillator and the price.
The oscillator is calculated using a two-step process. First, a smoothing function is applied to the source data using the "sma" (simple moving average) function. Then, the rate of change is computed over the specified length using the "mom" (momentum) function. Positive oscillator values indicate upward momentum, while negative values indicate downward momentum.
The indicator also generates buy and sell signals by identifying bullish and bearish divergences. A bullish divergence occurs when the oscillator is negative and crosses above zero, while a bearish divergence occurs when the oscillator is positive and crosses below zero. The indicator checks for specific conditions to confirm the divergences, such as comparing the current oscillator value with the previous value and validating the corresponding price action.
When a bullish or bearish divergence is detected, the indicator plots circles to highlight these signals on the chart. A green circle indicates a bullish signal, suggesting a potential buying opportunity, while a red circle indicates a bearish signal, suggesting a potential selling opportunity. In addition to circles, the indicator also displays labels to provide further clarity on the signals. A "Buy" label is shown for bullish signals, and a "Sell" label is shown for bearish signals.
To visually represent the divergences, the indicator plots lines connecting the corresponding points on the oscillator. A green line is drawn for bullish divergences, while a red line is drawn for bearish divergences. Traders can easily observe the divergence patterns and their relationships with the price action, aiding them in making trading decisions.
- The indicator also includes alert conditions for both bullish and bearish divergences. Traders can set up alerts to receive notifications when potential divergences occur, allowing them to take timely action.
MultiTimeFrame Choppiness IndexThe Choppiness Index (CHOP) is an oscillator (range 0-100) designed to determine if the market is choppy (trading sideways, value is going up) or not choppy (trading within a trend, value is going down). In case of trend moves it do not determine trend direction (other indicators are needed to predict trend direction). Some see it as fuel for the upcoming movement.
This implementation shows the graph for 4 different time frames simultaneously. Time frames are selected in settings. The default set: 1h, 4h, 1D, 1W.
For each time frame we can show/hide chart line, pick timeframe, assigned a color and line width.
Troubleshooting:
In case od any problems, please send error details to the author of the script.
MACDh with divergences & impulse system-----------------------------------------------------------------
General Description:
This indicator ( the one on the low panel ) is a classic MACD that also shows regular divergences between its histogram and the prices. This script is special because it can be adjusted to fit several criteria when trading divergences filtering them according to the "height" and "width" of the patterns. The script also includes the "extra feature" Impulse System, which you will hardly find anywhere else in similar classic MACD histogram divergence indicators.
The indicator helps to find trend reversals, and it works on any market, any instrument, any timeframe, and any market condition (except against really strong trends that do not show any other sign of reversion yet).
Please take on consideration that divergences should be taken with caution.
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Definition of classic Bullish and Bearish divergences:
* Bearish divergences occur in uptrends identifying market tops. A classical or regular bearish divergence occurs when prices reach a new high and then pull back, with an oscillator (MACD histogram in this case) dropping below its zero line. Prices stabilize and rally to a higher high, but the oscillator reaches a lower peak than it did on a previous rally.
In the chart above (weekly charts of NKE, Nike, Inc.), in area X (around August 2021), NKE rallied to a new bull market high and MACD-Histogram rallied with it, rising above its previous peak and showing that bulls were extremely strong. In area Y, MACD-H fell below its centerline and at the same time prices punched below the zone between the two moving averages. In area Z, NKE rallied to a new bull market high, but the rally of MACD-H was feeble, reflecting the bulls’ weakness. Its downtick from peak Z completed a bearish divergence, giving a strong sell signal and auguring a nasty bear market.
* Bullish divergences , in the other hand, occur towards the ends of downtrends identifying market bottoms. A classical (also called regular) bullish divergence occurs when prices and an oscillator (MACD histogram in this case) both fall to a new low, rally, with the oscillator rising above its zero line, then both fall again. This time, prices drop to a lower low, but the oscillator traces a higher bottom than during its previous decline.
In the example in the chart above (weekly charts of NKE, Nike, Inc.), you see a bearish divergence that signaled the October 2022 bear market bottom, giving a strong buy signal right near the lows. In area A, NKE (weekly charts) appeared in a free fall. The record low A of MACD-H indicated that bears were extremely strong. In area B, MACD-H rallied above its centerline. Notice the brief rally of prices at that moment. In area C, NKE slid to a new bear market low, but MACD-H traced a much more shallow low. Its uptick completed a bullish divergence, giving a strong buy signal.
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Extra feature: Impulse System
This indicator also includes the “ Impulse System ”. The Impulse System is based on two indicators, a 13-day exponential moving average and the MACD-Histogram, and identifies inflection points where a trend speeds up or slows down. The moving average identifies the trend, while the MACD-Histogram measures momentum. This unique indicator combination is color coded into the price bars or macd histogram bars for easy reference.
Calculation:
Green Price Bar: (13-period EMA > previous 13-period EMA) and
(MACD-Histogram > previous period's MACD-Histogram)
Red Price Bar: (13-period EMA < previous 13-period EMA) and
(MACD-Histogram < previous period's MACD-Histogram)
Histogram bars are colored blue when conditions for a Red Histogram Bar or Green Histogram Bar are not met. The MACD-Histogram is based on MACD(12,26,9).
The Impulse System works more like a censorship system. Green histogram bars show that the bulls are in control of both trend and momentum as both the 13-day EMA and MACD-Histogram are rising (you don't have permission to sell). A red histogram bar indicates that the bears have taken control because the 13-day EMA and MACD Histogram are falling (you don't have permission to buy). A blue histogram bar indicates mixed technical signals, with neither buying nor selling pressure predominating (either both buying or selling are permitted).
The impulse system can be removed from the chart any time.
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Options/adjustments for this indicator:
*Horizontal Distance (width) between two tops/bottoms criteria.
Refers to the horizontal distance between the MACH histogram peaks involved in the divergence
*Height of tops/bottoms criteria (for Histogram).
Refers to the difference/relation/vertical distance between the MACH HISTOGRAM peaks involved in the divergence: 1st Histogram Peak is X times the 2nd.
*Height/Vertical deviation of tops/bottoms criteria (for Price).
Deviation refers to the difference/relation/vertical distance between the PRICE peaks involved in the divergence.
*Plot Regular Bullish Divergences?.
*Plot Regular Bearish Divergences?.
*Delete Previous Cancelled Divergences?.
*This indicator also has the option to show the Impulse System over the MACD histogram bars
Rough AverageThe Rough Average indicator is a unique technical tool that calculates a modified average to provide insights into market conditions. It incorporates a combination of mathematical operations and existing indicators to offer traders a different perspective on price movements.
The Rough Average indicator aims to capture market dynamics through a specific calculation method. It utilizes two main components: a check for the approximate scale of the price and a profile calculation based on the Relative Strength Index (RSI) of the closing price.
Methodology:
Approximate Scale: The indicator determines the approximate scale of the price by analyzing the magnitude of the closing price. This step involves a mathematical process that identifies the power of 10 that best represents the scale. This function reduces overall lag and gives a better smoothing to the output of the calculation
Profile Calculation: The indicator calculates a profile value by summing the absolute values of the RSI of the closing price over a specified period. The RSI provides insights into the strength or weakness of price movements. The profile calculation considers a range of prices based on the determined scale.
Indicator Calculation:
The Rough Average is derived by applying the Exponential Moving Average (EMA) to the calculated profile. The EMA is a smoothing technique that emphasizes recent price data. The resulting value represents the modified average of the indicator.
Utility:
The Rough Average indicator offers traders an alternative perspective on market conditions. By utilizing a modified average calculation, it can reveal potential trends, reversals, or periods of market strength or weakness. Traders can use the Rough Average to complement their analysis and identify possible trading opportunities.
It is important to note that the effectiveness of the Rough Average indicator may vary depending on the specific market and trading strategy. It is recommended to combine its analysis with other technical indicators and conduct thorough testing before making trading decisions.
Key Features:
Customizable OB\OS Levels
Bar coloring methods: Trend, Reversions, Extremities
Example Charts:
Open interest flow / quantifytools- Overview
Open interest flow detects inflows (positions opening) and outflows (positions closing) using open interest and estimates delta (net buyers/sellers) for the flows. Users are able to choose any open interest source available on Tradingview, by default set to BTCUSDT OI fetched from Binance. Using historical open interest flows, bands depicting typical magnitude of flows are formed for benchmarking intensity of flows. On the inflow side, +1 represents average inflows while +2 represents 2x above average inflows, a level considered an extreme. In a vice versa manner, -1 represents average outflows while -2 represents 2x above average outflows. Extreme inflows indicate aggressive position opening, in other words exuberance. Extreme outflows on the other hand indicate forced exiting of positions, in other words liquidations.
- Concept
Open interest flow is calculated using position of OI source relative to its moving average (by default set to SMA 10), referred to as relative open interest from hereon. When relative OI is positive (open interest is above its moving average), new positions are considered to enter the market. When relative OI is negative (open interest is below its moving average), existing positions are considered to exit the market. Open interest delta (side opening/closing positions, either net buyers/sellers) is calculated using relative price in a similar fashion to relative OI, but using close of viewed symbol as source. Price is considered to be up when relative price is positive, down when relative price is negative. Using relative OI and relative price in tandem, the following assumptions are applied:
Price up, open interest up = longs entering market
Price down, open interest up = shorts entering market
Price down, open interest down = longs exiting market
Price up, open interest down = shorts exiting market
Bands depicting magnitude of open interest flows are calculated using average turning points in relative OI. +1 and -1 represent levels where flows on average turn towards mean rather than continue to increase/decrease. These levels are then multiplied up to +2 and -2, representing two times larger deviations from the normal. When inflows are above 1, positions opening have reached a point where flows historically turn down. Therefore, anything above 1 would be abnormal amount of open interest entering, an extreme stretch being at 2 or above. Same logic applies to outflows, but in a vice versa manner (below -1 abnormal, extreme at -2)
Flow bursts further refine indications of aggressive inflows/outflows by taking into account change in open interest flows. Burst indications are activated when open interest is above its average turning point, coupled with a sufficient increase/decrease in flows simultaneously. Bursts are essentially a filtered version of abnormal flows and therefore a more reliable indication of exuberance/liquidations. Burst sensitivity can be adjusted via input menu, available in 5 settings. 1 sets OI burst requirements to loosest (more signals, more noise) while 5 sets OI burst requirements to strictest (less signals, less noise). Exact criteria applied to bursts can be viewed via input menu tooltip.
- Features
Users can opt for OI source auto-select for CRYPTO/USDT pairs. When auto-select is enabled and another chart is opened, corresponding open interest source is automatically selected as long as requirements mentioned above are met.
Open interest flows can be visualized as chart color, available separately for flow states and flow bursts.
Relative price line and flow guidelines (reminders for flow interpretation) can be enabled via input menu. All colors are customizable.
- Alerts
Available alerts are the following:
- Abnormal long inflows/outflows
- Abnormal short inflows/outflows
- Abnormal inflows/outflows from either side
- Aggressive longs/shorts (flow burst up)
- Liquidated longs/shorts (flow burst down)
- Aggressive or liquidated longs/shorts
- Practical guide
Open interest as a standalone data point does not reveal which side is likely opening/exiting positions and how extreme the participant behavior is. Using the additional data provided by open interest flows, moments of greed and fear can be detected. Smart money does not short into dips and buy into rips. When buyers or sellers have participated in a large move and continue to show interest even when efforts are not rewarded at an already overextended price, participants are asking for trouble.
Similar events can be observed when extreme outflows take place, indicating forced exits such as stop-losses triggering. When enough participants are forced out, price is likely to take the path of least resistance which is to the opposite direction.
Autocorrelation OscillatorReleasing the autocorrelation oscillator.
NOTE! Please be sure to read the description. This is a theoretical indicator and its important to understand the theory behind its use.
About the indicator:
Before getting into the indicator and its functionality, its important to discuss the theoretical underpinnings of the indicator.
The autocorrelation oscillator operates on two theories of market behaviour that go hand in hand. Those theories are the market efficiency theory and the random walk theory (or hypothesis ).
Market efficiency theory: The market efficiency theory or "Efficient Market Hypothesis (EMH)" postulates that all available information is reflected in a ticker's price almost instantaneously and thus it is impossible for an investor or trader to get ahead of the market because we cannot respond to the speed that the market responds. Of course, there are many holes in this theory, the most notable being that the market is a function of humans. Absent humans and their technological integrations into the market, the market would cease to react at all. But that's besides the point. This is a widely accepted theory and one in which I can mathematically observe through statistical tests. The truth behind this theory is the market is efficient for responding to evolving economic and financial information, likely owning to huge amounts of computer and algorithmic integration into trading, and thus the market is more efficient than the average person is capable (absent computerized algorithms and integration) of ascertaining nuanced financial and economic circumstances. By the time we the people can appraise information, the market has already acted on it. And that is the main premise of the EMH.
The next theory is the Random Walk Theory or Hypothesis (RWH). This builds on the EMH and essentially postulates that the market reacts so quickly to price in current circumstances that it is too random for people to truly exploit and benefit from.
The result of these two theories is two-fold and can be summarized as such:
a) The market behaves in a chaotic fashion that is seemingly random and is incapable of being predicted effectively; and
b) The market is more efficient than a person in incorporating key fundamental information, contributing to the high degree of seemingly random behaviour.
So, how does this help us?
It is said, because of the EMH and the RWH, the only way to truly exploit the market for profit is by:
a) Buying and holding and investing under the bias that stocks will eventually rise in value; or
b) For short term trading, exploiting the pricing anomalies within the data.
So how do we exploit pricing anomalies within the data?
Well, in my own research on market efficiency and behaviour, I have identified many ways of figuring out some anomalies. One of the most effective ways is by looking at simple correlation of lagged values, or autocorrelation for short.
What is autocorrelation and how to use it in relation to EMH and RWH?
Autocorrelation refers to the correlative relationship among the values in a series. Put simply, its the relationship of the same variable over time. For example, if we wanted to look at the auto-correlation of a ticker's high price, we would take, say, 5 to 7 previous high prices and correlate them with the current high price in a series dataset. If the EMH and RWH are true, the correlation among all the variables should have an average less than 0.5 or greater than -0.5. This would indicate true randomness in the dataset and thus an efficient market.
However, if the average of all of the sum's of these correlations are greater than or equal to 0.5 or less than or equal to -0.5, that indicates there is a high degree of autocorrelation and thus the EMH ad RWH is being invalidated as the market is not operating efficiently. This is an anomaly and this anomaly can be exploited.
So how do we exploit it?
Well, when the EMH and RWH hypothesis is being invalidated, we can expect what I coin as a "Regression to Chaos" i.e. the market will revert back to an efficient equilibrium state. So if we have a high correlation of the lagged variables and a strong uptrend or downtrend correlation, we can expect an inefficient market to correct back to an efficient market (i.e. have a reversal from the current trend).
So how does the indicator work?
The indicator measures the lagged correlation of the previous 5 highs and lows of a ticker. A high correlation among all of the highs and lows that exceeds 0.8 would be an invalidation of the EMH and RWH and thus signal a correction to come (i.e. a Regression to Chaos).
The indicator will display this by changing colour. Red for a bearish reversal and green for a bullish. Let's take a look below using the ticker MSFT:
Above we can see the indicator identifying observed inefficiencies within the MSFT ticker on the 1 minute timeframe. The green vertical lines correspond to potential bullish reversals as a result of bearish inefficiencies, the red correspond to bearish reversals as a result of bullish inefficiencies.
You can see these lead to reversals within the ticker.
Components of the indicator:
In the chart above we see the following that are being indicated by arrows:
Red Arrows: Show the identified inefficiencies. Red for bullish inefficiencies (i.e. bearish reversal), green for bearish inefficiencies (i.e. bullish reversal)
Yellow Arrow: The lagged variable chart. This will display the current correlation among all the lagged variables the indicator is assessing.
Teal arrow: Displays the current strength of the trend by correlating the trend to time. A strong negative value (i.e. a value less than or equal to -0.5) indicates a strong downtrend, a strong positive value indicates the inverse.
You can unselect the data-tables in the settings menu if you just want to view the correlation line itself. This part of the indicator is customizable. You can also define the lookback period; however, it is strongly recommended to leave it at 14 as this maintains the use of this indicator as an oscillator.
And that is the indicator! Let me know your comments, questions and feedback below.
Safe trades everyone!
Alpha Trading - Pseudo Laplace Z ScoreAlpha Trading - Pseudo Laplace Z Score
Slowly, very slowly a lot of quant and statistical methods have diffused the world of traditional technical analysis with the world of real math - VEPS (Volatility, Entropy, Probability and Statistics).
‘Alpha Trading' is showing the world how VEPS can show the best probabilities of success with your trading journey.
We send a big thank you to tradingview platform and pine coding team, for this great platform and the possibility to show the methods to trade with quant and statistical methods.
There appears to be resistance in the industry about these methods, so it is even more important now than ever, to support this awesome platform and amazing talented team at trading view and pine coders who enable us all with this wonderful platform to produce tools based on VEPS (Volatility, Entropy, Probability and Statistics).
The newest indicator from the Alpha Trading stable is the “Pseudo Laplace Z Score” which combines the established statistical method of z score applied on asset data. Which is based on our previous indicator called the “Alpha Trading – RMS-Z score”. We have made some optimizations, to give an even better fit to the specific returns of price. Optimizations are on the observation that returns are more Laplace distributed than Normal distributed.
figure 1: pink distribution of the real signal (BTC, 2D), gray is perfect theoretical Laplace distribution.
Therefore, the data is not Normal distributed, but Laplace distributed. Our new indicator calculates the real Z-Score of an underlying asset.
As Z Score is a standardized Normal distribution, it relies upon the definition of Normal distribution. If it deviates from this, it still can give useful information, but the absolute value (distance from the mean in standard deviations) is not reliable, and therefore the use of Normal distribution has some uncertainties.
Therefore, this indicator calculates a pseudo standard deviation, based on the Laplace distribution formulas and the relating Z Score.
By looking at the resulting distribution of the indicator itself, it is close to a perfect theoretical Normal distribution. It is much closer to the theoretical curve (gray), and thus indicates that the use of this approach is correct. Now we can show absolute values (i.e. distance to mean, in standard deviations) which can thus be considered to assist in determining the probabilities with your trading.
figure 2: distribution of indicator AT - Pseudo Laplace Z Score vs a theoretical perfect Normal distribution on BTC 4h
Looking at the indicator directly, it appears that the probability of 99% is crossed very rarely, like expected. Because only 1% of all candles we would expect this probability line to be exceeded.
figure 3: BTC 8h with AT-Pseudo Laplace Z Score
Coming back to the method of a Z Score in general. What is a Z-Score?
A Z-score is a numerical measurement that describes a value's relationship to the mean of a group of values. Z-score is measured in terms of standard deviations from the mean. If a Z-score is 0, it indicates that the data point's score is identical to the mean score. A Z-score of 1.0 would indicate a value that is one standard deviation from the mean. Z-scores may be positive or negative, with a positive value indicating the score is above the mean and a negative score indicating it is below the mean.
Simply put, a z-score (also called a standard score) gives you an idea of how far from the mean a data point is.
Basic guidelines How to Use this indicator:
Consider Entering a Long Position when the indicator is low. Best moves are generally when the indicator Turns yellow(outlier)
Consider Entering a Short Position when the indicator is high. Best moves are generally when the indicator Turns yellow(outlier)
Consider the 3 confidence interval lines (gray lines) at 90%, 95%, and 99%, as possible reversal point (with related probability that it is not getting exceeded 🡪 reversal)
Relative Trend Index (RTI) by Zeiierman█ Overview
The Relative Trend Index (RTI) developed by Zeiierman is an innovative technical analysis tool designed to measure the strength and direction of the market trend. Unlike some traditional indicators, the RTI boasts a distinctive ability to adapt and respond to market volatility, while still minimizing the effects of minor, short-term market fluctuations.
The Relative Trend Index blends trend-following and mean-reverting characteristics, paired with a customizable and intuitive approach to trend strength, and its sensitivity to price action makes this indicator stand out.
█ Benefits of using this RTI instead of RSI
The Relative Strength Index (RSI) and the Relative Trend Index (RTI) are both powerful technical indicators, each with its own unique strengths.
However, there are key differences that make the RTI arguably more sophisticated and precise, especially when it comes to identifying trends and overbought/oversold (OB/OS) areas.
The RSI is a momentum oscillator that measures the speed and change of price movements and is typically used to identify overbought and oversold conditions in a market. However, its primary limitation lies in its tendency to produce false signals during extended trending periods.
On the other hand, the RTI is designed specifically to identify and adapt to market trends. Instead of solely focusing on price changes, the RTI measures the relative positioning of the current closing price within its recent range, providing a more comprehensive view of market conditions.
The RTI's adaptable nature is particularly valuable. The user-adjustable sensitivity percentage allows traders to fine-tune the indicator's responsiveness, making it more resilient to sudden market fluctuations and noise that could otherwise produce false signals. This feature is advantageous in various market conditions, from trending to choppy and sideways-moving markets.
Furthermore, the RTI's unique method of defining OB/OS zones takes into account the prevailing trend, which can provide a more precise reflection of the market's condition.
While the RSI is an invaluable tool in many traders' toolkits, the RTI's unique approach to trend identification, adaptability, and enhanced definition of OB/OS zones can provide traders with a more nuanced understanding of market conditions and potential trading opportunities. This makes the RTI an especially powerful tool for those seeking to ride long-term trends and avoid false signals.
█ Calculations
In summary, while simple enough, the math behind the RTI indicator is quite powerful. It combines the quantification of price volatility with the flexibility to adjust the trend sensitivity. It provides a normalized output that can be interpreted consistently across various trading scenarios.
The math behind the Relative Trend Index (RTI) indicator is rooted in some fundamental statistical concepts: Standard Deviation and Percentiles.
Standard Deviation: The Standard Deviation is a measure of dispersion or variability in a dataset. It quantifies the degree to which each data point deviates from the mean (or average) of the data set. In this script, the standard deviation is computed on the 'close' prices over a specified number of periods. This provides a measure of the volatility in the price over that period. The higher the standard deviation, the more volatile the price has been.
Percentiles: The percentile is a measure used in statistics indicating the value below which a given percentage of observations in a group falls. After calculating the upper and lower trends for the last 'length' periods and sorting these values, the script uses the 'Sensitivity ' parameter to extract percentiles from these sorted arrays. This is a powerful concept because it allows us to adjust the sensitivity of our signals. By choosing different percentiles (controlled through the 'Sensitivity' parameter), we can decide whether we want to react only to extreme events (high percentiles) or be more reactive and consider smaller deviations from the norm as significant (lower percentiles).
Finally, the script calculates the Relative Trend Index value, which is essentially a normalized measure indicating where the current price falls between the upper and lower trend values. This simple ratio is incredibly powerful as it provides a standardized measure that can be used across different securities and market conditions to identify potential trading signals.
Core Components
Trend Data Count: This parameter denotes the number of data points used in the RTI's calculation, determining the trend length. A higher count captures a more extended market view (long-term trend), providing smoother results that are more resistant to sudden market changes. In contrast, a lower count focuses on more recent data (short-term trend), yielding faster responses to market changes, albeit at the cost of increased susceptibility to market noise.
Trend Sensitivity Percentage: This parameter is employed to select the indices within the trend arrays used for upper and lower trend definitions. By adjusting this value, users can affect the sensitivity of the trend, with higher percentages leading to a less sensitive trend.
█ How to use
The RTI plots a line that revolves around a mid-point of 50. When the RTI is above 50, it implies that the market trend is bullish (upward), and when it's below 50, it indicates a bearish (downward) trend. Furthermore, the farther the RTI deviates from the 50 line, the stronger the trend is perceived to be.
Bullish
Bearish
The RTI includes user-defined Overbought and Oversold levels. These thresholds suggest potential trading opportunities when they are crossed, serving as a cue for traders to possibly buy or sell. This gives the RTI an additional use case as a mean-reversion tool, in addition to being a trend-following indicator.
In short
Trend Confirmation and Reversals: If the percentage trend value is consistently closer to the upper level, it can indicate a strong uptrend. Similarly, if it's closer to the lower level, a downtrend may be in play. If the percentage trend line begins to move away from one trend line towards the other, it could suggest a potential trend reversal.
Identifying Overbought and Oversold Conditions: When the percentage trend value reaches the upper trend line (signified by a value of 1), it suggests an overbought condition - i.e., the price has been pushed up, perhaps too far, and could be due for a pullback, or indicating a strong positive trend. Conversely, when the percentage trend value hits the lower trend line (a value of 0), it indicates an oversold condition - the price may have been driven down and could be set to rebound, or indicate a strong negative trend. Traders often use these overbought and oversold signals as contrarian indicators, considering them potential signs to sell (in overbought conditions) or buy (in oversold conditions). If the RTI line remains overbought or oversold for an extended period, it indicates a strong trend in that direction.
█ Settings
One key feature of the RTI is its configurability. It allows users to set the trend data length and trend sensitivity.
The trend data length represents the number of data points used in the trend calculation. A longer trend data length will reflect a more long-term trend, whereas a shorter trend data length will capture short-term movements.
Trend sensitivity refers to the threshold for determining what constitutes a significant trend. High sensitivity levels will deem fewer price movements as significant, hence making the trend less sensitive. Conversely, low sensitivity levels will deem more price movements as significant, hence making the trend more sensitive.
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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!
[volfgang] WAVEA compass to the financial charts.
The Volfgang WAVE Indicator helps you to decode complex market trends and make informed decisions in your trading.
Quick Summary
The WAVE has a signal line which alternates between Red or Blue.
Red is bearish and Blue is bullish.
It turns Blue when the WAVE line crosses above the signal and holds for 1 bar.
it turns Red when the WAVE line crosses below the signal and holds for 1 bar.
(You can change the signal line’s length in the settings, the default is 3 which is suited towards Day Trading – For Swing Traders I recommend 4 or 5 – For Investors 6 to 9).
The WAVE line will change colour to alert you when price is potentially pivoting.
When the WAVE is WHITE, the trend is currently Bearish but could flip bullish soon.
When the WAVE is GREEN, the trend is Bullish and there is strong Bullish momentum.
When the WAVE is ORANGE, it means trend is bullish but there is danger of a Bearish Reversal.
When the WAVE is PINK it means there is strong Bearish Momentum.
WAVETrend Scanner
The WAVETrend Scanner can be enabled in the settings and gives you a quick overview of the current trend across 8 potential timeframes:
You can use this to make sure the trades you are taking on lower timeframes align with the current bias on higher term timeframes, thus ensuring a higher chance of success.
WAVE Colours
The background colour of the WAVE also changes according to the current trend across multiple timeframes. The scanner is constantly measuring the current trend across 7 timeframes;
When 4 timeframes line up Bullish, the WAVE is LIGHT BLUE (Cyan)
When 5 timeframes line up Bullish, the WAVE is DARK BLUE (Navy)
When 6+ timeframes line up Bullish, the WAVE is GREEN
When 4 timeframes line up Bearish, the WAVE is ORANGE
When 5 timeframes line up Bearish, the WAVE is RED
When 6+ timeframes line up Bearish, the WAVE is PINK
Divergence Checker & Buy/Sell Signals
The BUY and SELL Signals are represented by a BLUE or RED Histogram line that extends from the WAVE to the 0 Line.
A BUY signal shows when a Crossover occurs & there is a Bullish Diversion Present within the last 50 bars.
A SELL signal appears when a Crossunder occurs & there is Bearish Diversion present within the last 50 bars.
You can change the length of the Divergence Checker in the settings, default is 50 bars.
Under The Hood
The WAVE pulls information from multiple sources within a set period such as;
Close Price
Highest Price
Lowest Price
EMA
The script applies a set of complicated algebraic equations. Which essentially measures the and of recent price action.
Then it uses EMA's to measure from the and , whilst applying more weight to recent price action.
The functions then calculate more averages which measure the difference from and .
Next, it uses all of these calculated averages to create a value that represents the current WAVE condition. This calculation will determine whether the WAVE is in a bullish or bearish trend.
This sum is then smoothed out to get one more value, which is used to display the info box content that allows us to see exactly at what price the WAVE will keep rising or keep falling.
One final calculation also predicts the point at which the WAVE will flip trend. It uses similar calculations to the "Keep Rising/Falling" prediction function, but its aim is to predict the exact price at which the WAVE will cross.
What gives the WAVE indicator an edge over most Stochastic Indicators, is how it uses Pinescript's "request.security" function to pull information from multiple timeframes in order to generate plots, info data and colours to add much more relevant information to the chart which you can use to make informed trading decisions. This is what allows the WAVETrend Scanner to work.
The WAVE indicator is designed to work with all markets and asset types.
Correlation for Major Markets This indicator plots the correlation of major markets as an indicator. The major markets covered are the following:
DXY
GC
CL
ES
RTY
ZN
The chart shows all the correlations and cross-correlations of the above instruments plotted together. The user can go in the settings and choose what correlation to see, or if multiple correlations, choose to plot the indicator a second time.
Revolution SMA-EMA DivergenceThis is an MACD inspired indicator and it analyzes the difference between the SMA and EMA using the same time period. Unlike the MACD, it can give you a better understanding of the overall trend. Values above 0 is bullish and below 0 bearish. It consists of two cycles: Black histogram - the long-term cycle and orange histogram - the short-term cycle, as well as timing signal (red line).
RSI MTF [Market Yogi]The Multi-Time Frame RSI with Money Flow Index and Average is a powerful trading indicator designed to help traders identify overbought and oversold conditions across multiple time frames. It combines the Relative Strength Index (RSI) with the Money Flow Index (MFI) and provides an average value for better accuracy.
The Relative Strength Index (RSI) is a popular momentum oscillator that measures the speed and change of price movements. It oscillates between 0 and 100 and is used to identify overbought and oversold conditions in an asset. By incorporating the RSI across multiple time frames, this indicator offers a broader perspective on market sentiment.
In addition to the RSI, this indicator also includes the Money Flow Index (MFI). The MFI is a volume-based oscillator that measures the inflow and outflow of money into an asset. It takes into account both price and volume, providing insights into the strength and direction of buying and selling pressure.
By combining the RSI and MFI across multiple time frames, traders gain a comprehensive understanding of market dynamics. The indicator allows for comparing the RSI and MFI values across different time frames, enabling traders to identify divergences and potential trend reversals.
Furthermore, this indicator provides an average value of the multi-time frame RSI, offering a consolidated signal that helps filter out noise and enhance the accuracy of trading decisions.
Key Features:
1. Multi-Time Frame RSI: Combines the RSI across different time frames to provide a comprehensive view of market sentiment.
2. Money Flow Index (MFI): Incorporates the MFI to gauge buying and selling pressure based on both price and volume.
3. Average Calculation: Computes the average value of the multi-time frame RSI to generate a consolidated trading signal.
4. Divergence Detection: Enables traders to spot divergences between the RSI and MFI values, indicating potential trend reversals.
5. Overbought and Oversold Levels: Highlights overbought and oversold levels on the RSI, aiding in timing entry and exit points.
The Multi-Time Frame RSI with Money Flow Index and Average is a versatile tool that can be applied to various trading strategies, including trend following, swing trading, and mean reversion. Traders can adjust the time frame settings to suit their preferences and trading style.
Note: It's important to use this indicator in conjunction with other technical analysis tools and indicators to validate signals and make informed trading decisions.
Linear Correlation Coefficient W/ MAs and Significance TestsThis Linear CC takes into account the log-normal distribution of stock prices and performs Pearson correlation on that data set. It also smoothens the results into an easy to read oscillator, and performs a two-tail t-test on the correlation coefficient data (with a = 0.05) to determine the significance of the coefficients. Significant results are shown in a solid yellow color while insignificant results are shown in a dark yellow color (you can eyeball this with a normal LCC by looking at results around -0.5 to +0.5).
Two MAs are provided as well for a quick trend analysis. You can reduce the lookback period, but it defaults to 31 for the sake of statistical standards.
Futures All List / Sell SignalAs of May 2023, there are more than 180 usdt perpetual coins on the binance futures exchange. These coins are included in the indicator in lists of 40. They are sorted instantly in the table from largest to smallest. The sorting style can be changed in the indicator settings. This indicator collects RSI and TSI values at desired values. The result has a maximum value of 600. A value of 600 signals that the price will decrease or remain stable for a certain period of time. Generally, a short can be expected from the closest point to 600. If 3 separate lists are selected by using 3 of these indicators, 120 coins can be analyzed at the same time. Available in all time zones. Examine it in a 3-minute timeframe. The line inside the indicator draws the instantaneous values of the relevant coin.
