Hodrick-Prescott Cycle Component (YavuzAkbay)The Hodrick-Prescott Cycle Component indicator in Pine Script™ is an advanced tool that helps traders isolate and analyze the cyclical deviations in asset prices from their underlying trend. This script calculates the cycle component of the price series using the Hodrick-Prescott (HP) filter, allowing traders to observe and interpret the short-term price movements around the long-term trend. By providing two views—Percentage and Price Difference—this indicator gives flexibility in how these cyclical movements are visualized and interpreted.
What This Script Does
This indicator focuses exclusively on the cycle component of the price, which is the deviation of the current price from the long-term trend calculated by the HP filter. This deviation (or "cycle") is what traders analyze for mean-reversion opportunities and overbought/oversold conditions. The script allows users to see this deviation in two ways:
Percentage Difference: Shows the deviation as a percentage of the trend, giving a normalized view of the price’s distance from its trend component.
Price Difference: Shows the deviation in absolute price terms, reflecting how many price units the price is above or below the trend.
How It Works
Trend Component Calculation with the HP Filter: Using the HP filter, the script isolates the trend component of the price. The smoothness of this trend is controlled by the smoothness parameter (λ), which can be adjusted by the user. A higher λ value results in a smoother trend, while a lower λ value makes it more responsive to short-term changes.
Cycle Component Calculation: Percentage Deviation (cycle_pct) calculated as the difference between the current price and the trend, divided by the trend, and then multiplied by 100. This metric shows how far the price deviates from the trend in relative terms. Price Difference (cycle_price) simply the difference between the current price and the trend component, displaying the deviation in absolute price units.
Conditional Plotting: The user can choose to view the cycle component as either a percentage or a price difference by selecting the Display Mode input. The indicator will plot the chosen mode in a separate pane, helping traders focus on the preferred measure of deviation.
How to Use This Indicator
Identify Overbought/Oversold Conditions: When the cycle component deviates significantly from the zero line (shown with a dashed horizontal line), it may indicate overbought or oversold conditions. For instance, a high positive cycle component suggests the price may be overbought relative to the trend, while a large negative cycle suggests potential oversold conditions.
Mean-Reversion Strategy: In mean-reverting markets, traders can use this indicator to spot potential reversal points. For example, if the cycle component shows an extreme deviation from zero, it could signal that the price is likely to revert to the trend. This can help traders with entry and exit points when the asset is expected to correct back toward its trend.
Trend Strength and Cycle Analysis: By comparing the magnitude and duration of deviations, traders can gauge the strength of cycles and assess if a new trend might be forming. If the cycle component remains consistently positive or negative, it may indicate a persistent market bias, even as prices fluctuate around the trend.
Percentage vs. Price Difference Views: Use the Percentage Difference mode to standardize deviations and compare across assets or different timeframes. This is especially helpful when analyzing assets with varying price levels. Use the Price Difference mode when an absolute deviation (price units) is more intuitive for spotting overbought/oversold levels based on the asset’s actual price.
Using with Hodrick-Prescott: You can also use Hodrick-Prescott, another indicator that I have adapted to the Tradingview platform, to see the trend on the chart, and you can also use this indicator to see how far the price is deviating from the trend. This gives you a multifaceted perspective on your trades.
Practical Tips for Traders
Set the Smoothness Parameter (λ): Adjust the λ parameter to match your trading timeframe and asset characteristics. Lower values make the trend more sensitive, which might suit short-term trading, while higher values smooth out the trend for long-term analysis.
Cycle Component as Confirmation: Combine this indicator with other momentum or trend indicators for confirmation of overbought/oversold signals. For example, use the cycle component with RSI or MACD to validate the likelihood of mean-reversion.
Observe Divergences: Divergences between price movements and the cycle component can indicate potential reversals. If the price hits a new high, but the cycle component shows a smaller deviation than previous highs, it could signal a weakening trend.
Cerca negli script per "Divergence"
Jason's Simple Moving Averages WaveUnderstanding the Script:
Purpose: This script identifies potential trend direction and momentum using a moving average and wave amplitude calculation. It shows a green line when the price is trending upwards and a red line when trending downwards.
Strategy: This script doesn't provide a complete trading strategy. It's an indicator designed to be used alongside other tools.
Parameters: You can adjust the "Moving Average Length" input to change the sensitivity of the indicator. A shorter length will react quicker to price changes, while a longer length will be smoother but less responsive.
How to Use it:
Load the Script: In TradingView, navigate to the indicator creation section and paste the provided script code.
Adjust Parameters: Set the "Moving Average Length" based on your preferred timeframe and trading style.
Combine with Other Tools: Use the indicator along with other technical indicators or price action analysis to confirm potential entry and exit points for trades.
Here are some additional points to consider:
Crossovers: You could look for buy signals when the price crosses above the green line and sell signals when it crosses below the red line. However, these can be prone to false signals.
Divergence: Look for divergences between the price movement and the wave indicator. For example, a rising price with a falling wave could indicate overbought conditions and a potential reversal.
Confirmation: Don't rely solely on this indicator. Use it alongside other confirmations from price action, volume analysis, or other indicators to identify higher probability trades.
Important Note:
Relative Strength with 3 SMAMansfield RS with 3 SMAs
Overview
The Mansfield Relative Strength (RS) indicator with three Simple Moving Averages (SMAs) enhances traditional RS analysis by adding more clarity and precision to trend identification. This personalized version aims to define RS trends more clearly and end them sooner, helping traders make better-informed decisions.
Key Features
Relative Strength Calculation:
Comparison: Calculates the RS of a chosen symbol against a benchmark (default: S&P 500).
Normalization: Uses the stock’s closing price divided by the closing price of the benchmark over a specified period.
Three SMAs:
Periods: Configurable periods for three SMAs (default: 10, 20, 50).
Trend Smoothing: SMAs help smooth the RS line, making it easier to spot trends and potential reversals.
Visualization:
Area Plot: The RS line is displayed as an area plot.
Color Coding: Different colors for each SMA to distinguish them easily (yellow, orange, purple).
Customization Options:
Comparative Symbol: Choose any benchmark symbol.
Period Adjustment: Customize the periods for both the RS calculation and the SMAs.
Visibility: Option to show or hide the SMAs.
How to Use
Setup:
Add to Chart: Apply the indicator to your TradingView chart.
Customize: Adjust the comparative symbol, RS period, and SMA periods as per your preference.
Interpretation:
Rising RS Line: Indicates the stock is outperforming the benchmark.
Falling RS Line: Suggests underperformance.
SMA Crossovers: Watch for the RS line crossing above or below the SMAs to signal potential buy or sell points.
Trend Direction: SMAs help confirm the trend direction. A rising RS line above the SMAs indicates a strong relative performance.
Trading Strategy:
Trend Confirmation: Use SMA crossovers to confirm trends.
Divergence: Identify divergences between the price action and the RS line for potential reversal signals.
Slow Volume Strength Index (SVSI)The Slow Volume Strength Index (SVSI), introduced by Vitali Apirine in Stocks & Commodities (Volume 33, Chapter 6, Page 28-31), is a momentum oscillator inspired by the Relative Strength Index (RSI). It gauges buying and selling pressure by analyzing the disparity between average volume on up days and down days, relative to the underlying price trend. Positive volume signifies closes above the exponential moving average (EMA), while negative volume indicates closes below. Flat closes register zero volume. The SVSI then applies a smoothing technique to this data and transforms it into an oscillator with values ranging from 0 to 100.
Traders can leverage the SVSI in several ways:
1. Overbought/Oversold Levels: Standard thresholds of 80 and 20 define overbought and oversold zones, respectively.
2. Centerline Crossovers and Divergences: Signals can be generated by the indicator line crossing a midline or by divergences from price movements.
3. Confirmation for Slow RSI: The SVSI can be used to confirm signals generated by the Slow Relative Strength Index (SRSI), another oscillator developed by Apirine.
🔹 Algorithm
In the original article, the SVSI is calculated using the following formula:
SVSI = 100 - (100 / (1 + SVS))
where:
SVS = Average Positive Volume / Average Negative Volume
* Volume is considered positive when the closing price is higher than the six-day EMA.
* Volume is considered negative when the closing price is lower than the six-day EMA.
* Negative volume values are expressed as absolute values (positive).
* If the closing price equals the six-day EMA, volume is considered zero (no change).
* When calculating the average volume, the indicator utilizes Wilder's smoothing technique, as described in his book "New Concepts In Technical Trading Systems."
Note that this indicator, the formula has been simplified to be
SVSI = 100 * Average Positive Volume / (Average Positive Volume + Average Negative Volume)
This formula achieves the same result as the original article's proposal, but in a more concise way and without the need for special handling of division by zero
🔹 Parameters
The SVSI calculation offers configurable parameters that can be adjusted to suit individual trading styles and goals. While the default lookback periods are 6 for the EMA and 14 for volume smoothing, alternative values can be explored. Additionally, the standard overbought and oversold thresholds of 80 and 20 can be adapted to better align with the specific security being analyzed.
Standardized Orderflow [AlgoAlpha]Introducing the Standardized Orderflow indicator by AlgoAlpha. This innovative tool is designed to enhance your trading strategy by providing a detailed analysis of order flow and velocity. Perfect for traders who seek a deeper insight into market dynamics, it's packed with features that cater to various trading styles. 🚀📊
Key Features:
📈 Order Flow Analysis: At its core, the indicator analyzes order flow, distinguishing between bullish and bearish volume within a specified period. It uses a unique standard deviation calculation for normalization, offering a clear view of market sentiment.
🔄 Smoothing Options: Users can opt for a smoothed representation of order flow, using a Hull Moving Average (HMA) for a more refined analysis.
🌪️ Velocity Tracking: The indicator tracks the velocity of order flow changes, providing insights into the market's momentum.
🎨 Customizable Display: Tailor the display mode to focus on either order flow, order velocity, or both, depending on your analysis needs.
🔔 Alerts for Critical Events: Set up alerts for crucial market events like crossover/crossunder of the zero line and overbought/oversold conditions.
How to Use:
1. Setup: Easily configure the indicator to match your trading strategy with customizable input parameters such as order flow period, smoothing length, and moving average types.
2. Interpretation: Watch for bullish and bearish columns in the order flow chart, utilize the Heiken Ashi RSI candle calculation, and look our for reversal notations for additional market insights.
3. Alerts: Stay informed with real-time alerts for key market events.
Code Explanation:
- Order Flow Calculation:
The core of the indicator is the calculation of order flow, which is the sum of volumes for bullish or bearish price movements. This is followed by normalization using standard deviation.
orderFlow = math.sum(close > close ? volume : (close < close ? -volume : 0), orderFlowWindow)
orderFlow := useSmoothing ? ta.hma(orderFlow, smoothingLength) : orderFlow
stdDev = ta.stdev(orderFlow, 45) * 1
normalizedOrderFlow = orderFlow/(stdDev + stdDev)
- Velocity Calculation:
The velocity of order flow changes is calculated using moving averages, providing a dynamic view of market momentum.
velocityDiff = ma((normalizedOrderFlow - ma(normalizedOrderFlow, velocitySignalLength, maTypeInput)) * 10, velocityCalcLength, maTypeInput)
- Display Options:
Users can choose their preferred display mode, focusing on either order flow, order velocity, or both.
orderFlowDisplayCond = displayMode != "Order Velocity" ? display.all : display.none
wideDisplayCond = displayMode != "Order Flow" ? display.all : display.none
- Reversal Indicators and Divergences:
The indicator also includes plots for potential bullish and bearish reversals, as well as regular and hidden divergences, adding depth to your market analysis.
bullishReversalCond = reversalType == "Order Flow" ? ta.crossover(normalizedOrderFlow, -1.5) : (reversalType == "Order Velocity" ? ta.crossover(velocityDiff, -4) : (ta.crossover(velocityDiff, -4) or ta.crossover(normalizedOrderFlow, -1.5)) )
bearishReversalCond = reversalType == "Order Flow" ? ta.crossunder(normalizedOrderFlow, 1.5) : (reversalType == "Order Velocity" ? ta.crossunder(velocityDiff, 4) : (ta.crossunder(velocityDiff, 4) or ta.crossunder(normalizedOrderFlow, 1.5)) )
In summary, the Standardized Orderflow indicator by AlgoAlpha is a versatile tool for traders aiming to enhance their market analysis. Whether you're focused on short-term momentum or long-term trends, this indicator provides valuable insights into market dynamics. 🌟📉📈
Bolton-Tremblay IndexThe Bolton-Tremblay Index (BOLTR) is a dynamic cumulative advance-decline indicator which incorporates the count of unchanged issues as a fundamental element. This index serves as a valuable tool for identifying shifts in market trends and gauging the overall strength or weakness of the market. To enhance its effectiveness and reveal underlying trends, BOLTR has been refined through a Heiken-Ashi transformation, resulting in a smoother and more insightful representation.
Calculation and Methodology:
r = (adv - dec) / unch
var float bt = na
bt := r > 0 ? nz(bt ) + math.sqrt(math.abs(r)) : nz(bt ) - math.sqrt(math.abs(r))
The BOLTR index is derived from a calculation involving three essential components: advancing issues (ADV), declining issues (DEC), and securities with unchanged closing prices (UNC). By formulating the ratio (ADV - DEC) / UNC, BOLTR captures the relationship between market movements and unchanged securities. This ratio then dictates whether the BOLTR index increases or decreases in the following period. If the ratio is positive, the index advances, and if negative, it retreats. This iterative process yields a cumulative index that reflects the evolving dynamics of market trends.
Heiken-Ashi Transformation:
The addition of a Heiken-Ashi transformation imparts a smoothing effect to the BOLTR index, revealing the underlying trend with greater clarity. This transformation diminishes noise and fluctuations, making it easier to identify meaningful shifts in market sentiment and overall market health.
Utility and Use Cases:
-The Bolton-Tremblay Index offers a range of applications that contribute to informed decision-making-
1. Trend Analysis: BOLTR provides insights into the changing trends of the market, helping traders and investors identify potential shifts in market sentiment.
2. Market Strength Assessment: By considering advancing, declining, and unchanged issues, BOLTR offers a comprehensive assessment of market strength and potential weaknesses.
3. Divergences: Traders can use BOLTR to detect divergences between price movements and the cumulative advance-decline dynamics, potentially signaling shifts in market direction.
The Bolton-Tremblay Index offers a versatile toolset for interpreting market trends, evaluating market health, and making better informed trading decisions.
See Also:
- Other Market Breadth Indicators-
RVol LabelThis Code is update version of Code Provided by @ssbukam, Here is Link to his original Code and review the Description
Below is Original Description
1. When chart resolution is Daily or Intraday (D, 4H, 1H, 5min, etc), Relative Volume shows value based on DAILY. RVol is measured on daily basis to compare past N number of days.
2. When resolution is changed to Weekly or Monthly, then Relative Volume shows corresponding value. i.e. Weekly shows weekly relative volume of this week compared to past 'N' weeks. Likewise for Monthly. You would see change in label name. Like, Weekly chart shows W_RVol (Weekly Relative Volume). Likewise, Daily & Intraday shows D_RVol. Monthly shows M_RVol (Monthly Relative Volume).
3. Added a plot (by default hidden) for this specific reason: When you move the cursor to focus specific candle, then Indicator Value displays relative volume of that specific candle. This applies to Intraday as well. So if you're in 1HR chart and move the cursor to a specific candle, Indicator Value shows relative volume for that specific candlestick bar.
4. Updating the script so that text size and location can be customized.
Changes to Updated Label by me
1. Added Today's Volume to the Label
2. Added Total Average Volume to the Label
3. Comparison vs Both in Single Line and showing how much volume has traded vs the average volume for that time of the day
4. Aesthetic Look of the Label
How to Use Relative Volume for Trading
Using Relative Volume (RVol) in trading can be a valuable tool to help you identify potential trading opportunities and gain insight into market behavior. Here are some ways to use RVol in your trading strategy:
Identifying High-Volume Breakouts: RVol can help you spot potential breakouts when the volume surges significantly above its average. High RVol during a breakout suggests strong market interest, increasing the probability of a sustained move in the direction of the breakout.
Confirming Trends and Reversals: RVol can act as a confirmation tool for trends and reversals. A trend accompanied by rising RVol indicates a strong and sustainable move. Conversely, a trend with declining RVol might suggest a weakening trend or potential reversal.
Spotting Volume Divergence: When the price is moving in one direction, but RVol is declining or not confirming the move, it may indicate a divergence. This discrepancy could suggest a potential reversal or trend change.
Support and Resistance Confirmation: High RVol near key support or resistance levels can indicate potential price reactions at those levels. This confirmation can be valuable in determining whether a level is likely to hold or break.
Filtering Trade Signals: Incorporate RVol into your existing trading strategy as a filter. For example, you might consider taking trades only if RVol is above a certain threshold, ensuring that you focus on high-impact trading opportunities.
Avoiding Low-Volume Traps: Low RVol can indicate a lack of interest or participation in the market. In such situations, price movements may be erratic and less reliable, so it's often wise to avoid trading during low RVol periods.
Monitoring News Events: Around significant news events or earnings releases, RVol can help you gauge the market's reaction to the information. High RVol during such events can present trading opportunities but be cautious of increased volatility and potential gaps.
Adjusting Trade Size: During periods of extremely high RVol, it might be prudent to adjust your position size to account for higher risk.
Using Relative Volume in Morning Session
If the Volume traded in first 15 minute to 30 Minutes is already at 50% or 100% depending upon the ticker, it means that it is going to have very high Volume vs average by end of the day.
This gives me conviction for Long or Short Trades
Remember that RVol is not a standalone indicator; it works best when used in conjunction with other technical and fundamental analysis tools. Additionally, RVol's effectiveness may vary across different markets and trading strategies. Therefore, backtesting and validating the use of RVol in your trading approach is essential.
Lastly, risk management is crucial in trading. While RVol can provide valuable insights, it cannot guarantee profitable trades. Always use appropriate risk management strategies, such as setting stop-loss levels, and avoid overexposing yourself to the market based solely on RVol readings.
Volume Price Trend (VPT)
The Volume Price Trend (VPT) is a technical analysis indicator that combines price and volume data. It's used to identify the direction of a trend or to confirm the strength of a trend. The indicator was developed on the premise that volume often precedes price.
Working of VPT:
VPT is calculated by adding or subtracting a multiple of the percentage change in the share price trend and current volume, depending upon the direction of the share price. The starting point of the VPT line is arbitrary.
The formula for calculating VPT is:
VPT = Previous VPT + Volume x (Today's Close - Previous Close)
This formula adds the total volume traded on the days the price went up, and subtracts the total volume on the days the price went down.
For each period:
If the closing price is higher than the previous closing price, the volume for that period is added to the previous VPT.
If the closing price is lower than the previous closing price, the volume for that period is subtracted from the previous VPT.
If the closing price is the same as the previous closing price, the volume for that period does not affect the VPT (i.e., it remains the same as the previous VPT).
Usage and Interpretation of VPT:
The primary use of the VPT is to help confirm the condition of prices. It’s usually used in combination with other technical analysis indicators. Here are some ways traders use the VPT:
Trend Confirmation: A rising VPT line typically confirms an uptrend as it shows that volume is increasing as prices increase. Conversely, a falling VPT line confirms a downtrend.
Divergences: Traders often look for divergences between the VPT and price movements as a sign of upcoming reversals. If prices are rising and the VPT is falling, it suggests that the upward trend may not sustain because it isn't being supported by volume. Similarly, if prices are falling and the VPT is rising, it suggests the downward trend may reverse soon.
Change in Trend: A sudden sharp increase in the VPT could signal a possible change in trend. This is based on the belief that volume changes before price.
In the script provided, the VPT is calculated and then rescaled to a 0-100 scale, which makes it easier to compare across different stocks or time periods. This script also colors the VPT line based on whether it's increasing or decreasing. The color is green when VPT is increasing, and red when it's decreasing.
Enjoy!
Price Cross ━ [whvntr]This oscillator is an attractive way to view hidden price divergence... The formula originated from the Lark, but I have cleanly displayed this information. When the two moving averages (ema) cross with a simple moving average, you find the hidden price divergence. What kind of market should you use this in? It works well when a trend is already established.
Disclaimer: This indicator does not constitute investment advice. Trade at your own
risk with this method of identifying hidden price divergence.
+ Klinger OscillatorThis is a version of Stephen J. Klinger's, Klinger Oscillator (sometimes called Klinger Volume Oscillator). I've changed virtually nothing about the indicator itself, but added some lookback inputs for the EMAs the oscillator is derived from (traditionally 34 and 55), and added a few other things, as is my wont.
But what is the Klinger Oscillator? Essentially, the calculation looks at the high, low, and close of the current period, and compares that to the previous period's. If it is greater, it adds volume, and if it is less, it subtracts volume. It then takes an EMA of two different lookback periods of that calculation and subtracts one from the other. That's your oscillator. There is then made a signal line of the oscillator that a trader can use, in combination with the zero line, for taking trades. Investopedia has a good article on it, so if you're looking for more specifics, check there.
What I've done is add a selection of different moving averages that you may choose for the signal line. Usually it's a 13 period EMA, and that comes default, but here you could use an ALMA or HMA, or modular filter, etc. Find something that works for your style/algorithm.
Of course there are all the usual additions of mine with the various ways of coloring the indicator and candles, adjustable Donchian Bands, and alerts. A new addition that I've just added to all my indicators (oscillators, anyway) are divergences. This is more or less just a copy and paste of the divergence indicator available in TradingView. In this case you can set it to plot divergences off either the Klinger or the signal line. Depending on which one you choose you may have to adjust pivot lookbacks, and lookback range. I've kept the settings default from the RSI TradingView version.
KDJ stochastic indicatorThis is a special calculation of KDJ indicator. As you may know this is based on stochastic indicator. Stochastic indicator is a method to normalize a trending time serie (here price). the calculation of stochastic itself is a built in function in pine but it is straight forward:
In sudo code:
RSV for n days=(Cn－Ln)/(Hn－Ln)×100
In which, Cn is the closing price on the nth day; Ln is the lowest price in n days; Hn is the highest price in n days.
To calculate other indices K, D and J we use this formulas:
K = (2/3) * K + (1/3) * RSV
D = (2/3) * D + (1/3) * K
J = 3 * K - 2 * D
As you can see it is a recursive calculation. It means any value of the indices are affected by it's own previous value (and I'm passionate about recursive functions!) It may concern you that in the initial calculation there is no previous value and you are right. For the initial values we use value of 50 because it is an oscillator and the mean value is always 50 so we replace the first NAs with 50 using nz() function in pine.
After doing this calculations we reach to the smoothing section. I used simple moving averages, you may replace it with other more advanced smoothing techniqes like EMA or ALMA.
After I wrote this indicator I saw that it is a good indicator for reading divergences. As you can see I showed couple of these divergences to you on the chart. Notice that I analyzed divergence between price and J (very light green) line and not to K or D. I really appreciate any suggestion on this indicator and hope to improve it. The other ones present in the public library wasn't good and they differ a lot in the calculation and also the graphics doesn't look good.
Be free to change the parameter i saw these parameter are good to daily Bitcoin chart.
Sentiment OscillatorPrice moves when there are more market takers than there are market makers at a certain price (i.e. price moves up when there are more market buys than limit sells and vice versa). The idea of this indicator is to show the ratio between market takers and market makers in a way that is intuitive to technical analysis methods, and hopefully revealing the overall sentiment of the market in doing so. You can use it in the same way you would other oscillators (histogram crossing zero, divergences, etc). The main difference between this and most volume-weighted indicators is that the price is divided by volume instead of multiplied by it, thus giving you a rough idea of how much "effort" it took to move the price. My hypothesis is that when more volume is needed to move the price, that means bulls and bears are not in agreement of what the "fair price" should be for an asset (e.g. if the candle closes only a bit higher than its open but there's a huge spike in volume, that tells you that a majority of the market are starting to think the price is too high and they've started selling).
Methods of Calculation
1. Price Change Per Volume
The main method this indicator uses to reveal market sentiment is by comparing price change to the volume of trades in a bar.
You will see this calculation plotted in its most basic form by ticking the "Show Bar per Bar Change/Volume" box in the inputs dialog. I personally found that the plots were too noisy and cannot be used in real time reliably due to the fact that there is not much volume at the open of a new bar. I decided to leave in the option to use this method, in case you'd like to experiment with it or get a better grasp of how the indicator works.
2. Exponential Moving Averages
In my quest to smooth out the plotted data, I experimented with exponential moving averages. Applying an EMA on the change per volume data did smooth it out a bit, but still left in a lot of noise. So I worked around it by applying the EMA to the price change first, and then dividing it by the EMA of the volume. The term I use for the result of this calculation is "Market Sentiment" (do let me know if you have a better-fitting term for it ;-)), and I have kept it as an option that you can use in the way you would use other oscillators like CMF, OBV, etc. This option is unticked by default.
3. MACD
I left "Market Sentiment" unchecked as the default option because I thought an easier way to use this indicator would be as a momentum indicator like the MACD . So that's what I turned it into! I applied another EMA on the Market Sentiment, added a slower EMA to subtract from the first, and now we have a MACD line. I added a signal line to subtract from the MACD , and the result is plotted as a histogram... ish . I used area instead of columns for plot style so you don't get confused when comparing with a regular MACD indicator, but you can always change it if an actual histogram is more your taste.
The "histogram" is the main gauge of sentiment change momentum and it is easiest to use, that is why it is the only calculation plotted by default.
Methods of Use
As I have mentioned before, you can use this as you would other oscillators.
-The easiest way to use this indicator is with the Momentum histogram, where crosses over 0 indicate increasing bullish sentiment, and crosses below 0 indicate increasing bearish sentiment. You may also spot occasional divergences with the histogram.
-For the Market Sentiment option, the easiest way to use it is to look for divergences.
-And if you use the "Price Change per Volume of Each Bar", well... I honestly don't know. I guess divergences would be apparent towards the close of a bar, but in realtime, I don't recommend you use this. Maybe if you'd like to study the market movement, looking at historical data and comparing price, volume , and Change per Volume of each bar would come in handy in a pseudo-tape-reading kind of way.
Anyway, that's my explanation of this indicator. The default values were tested on BTC/USDT (Binance) 4h with decent results. You'll have to adjust the parameters for different markets and timeframes.
I have published this as a strategy so you can test out how the indicator performs as you're tweaking the parameters.
I'm aware that the code might not be the cleanest as I have only started learning pine (and code in general) for about a month, so any suggestions to improve the script would be appreciated!
Good luck and happy trading :-)
Open Interest Money Flow Index (OIMFI)CAUTION : This system was inspired from seiglerj' s "Money Flow Index " script. Open Interests are used instead of volume.
What is the Money Flow Index ( MFI )?
The Money Flow Index ( MFI ) is a technical oscillator that uses price and volume for identifying overbought or oversold conditions in an asset. It can also be used to spot divergences which warn of a trend change in price. The oscillator moves between 0 and 100.
Unlike conventional oscillators such as the Relative Strength Index ( RSI ), the Money Flow Index incorporates both price and volume data, as opposed to just price. For this reason, some analysts call MFI the volume-weighted RSI .
What Does the Money Flow Index ( MFI ) Tell You?
One of the primary ways to use the Money Flow Index is when there is a divergence. A divergence is when the oscillator is moving in the opposite direction of price. This is a signal of a potential reversal in the prevailing price trend.
For example, a very high Money Flow Index that begins to fall below a reading of 80 while the underlying security continues to climb is a price reversal signal to the downside. Conversely, a very low MFI reading that climbs above a reading of 20 while the underlying security continues to sell off is a price reversal signal to the upside.
Traders also watch for larger divergences using multiple waves in the price and MFI . For example, a stock peaks at $10, pulls back to $8, and then rallies to $12. The price has made two successive highs, at $10 and $12. If MFI makes a lower higher when the price reaches $12, the indicator is not confirming the new high. This could foreshadow a decline in price.
The overbought and oversold levels are also used to signal possible trading opportunities. Moves below 10 and above 90 are rare. Traders watch for the MFI to move back above 10 to signal a long trade, and to drop below 90 to signal a short trade.
Other moves out of overbought or oversold territory can also be useful. For example, when an asset is in an uptrend, a drop below 20 (or even 30) and then a rally back above it could indicate a pullback is over and the price uptrend is resuming. The same goes for a downtrend. A short-term rally could push the MFI up to 70 or 80, but when it drops back below that could be the time to enter a short trade in preparation for another drop .
Reference : www.investopedia.com
WARNING :
** Since each instrument in the list has its own unique contract data, you must first enter its name to display it. I recommend you to select OANDA from the markets. Finally, when the COT reports are issued, it may repaints. However, this repaint is usually close to closing or after close .(When COT reports are so sharp ) So use this script only 1W ( 1 week ) or 1 M ( 1 month ) timeframe.
** This data is taken to Tradingview with the help of Quandl. This is a very low possibility, but the system will not work if there is a malfunction.
FEATURES :
*** Working with all futures (Including : Bitcoin )
*** If you dont work with "Futures" , you can select "Others" from switchable menu and use volume for all instruments.
*** New generation elegant design used : Adaptive coloring Overbought - Oversold Levels according to the closing price.
NOTE : This code is open source under the MIT License. If you have any improvements or corrections to suggest, please send me a pull request via the github repository github.com
Stay tuned. Best wishes !
Adaptive Resonance Oscillator [AlgoAlpha]Introducing the Adaptive Resonance Oscillator , an advanced momentum-based oscillator designed to dynamically adjust to changing market conditions. This innovative indicator detects market frequency through a Hilbert Transform approach, adapting in real-time to identify overbought and oversold conditions with improved accuracy. With built-in divergence detection, trend analysis, and customizable smoothing, this tool is perfect for traders looking to refine their entries and exits based on adaptive oscillation mechanics.
🚀 Key Features :
🔹 Adaptive Frequency Detection – Uses Hilbert Transform principles to dynamically determine market cycle length for precise oscillator calculation.
⚙️ Customizable Smoothing – Option to apply a Hull Moving Average (HMA) for enhanced signal clarity.
📈 Divergence Detection – Identifies bullish and bearish divergences with visual markers, helping traders spot early trend reversals.
🟢 Overbought & Oversold Signals – Highlights extreme momentum conditions with adjustable thresholds.
🔔 Real-Time Alerts – Get notified for crossovers, divergences, and strong trend shifts directly on your TradingView chart.
🎨 Fully Customizable Appearance – Modify colors, divergence sensitivity, and smoothing options to fit your trading style.
🛠 How to Use :
Add the Adaptive Resonance Oscillator to your TradingView chart by clicking the ★ to favorite it.
Monitor the Charts , switch between smoothed and I smoothed modes to identify trend and price swings, use divergences and reversal signals for potential entry/exits.
Set alerts for bullish/bearish crossovers and divergence signals to stay ahead of market moves.
⚙ How It Works :
The indicator begins by applying a Hilbert Transform frequency estimation to the price series, identifying the dominant market cycle length. This is used to calculate a period for the RSI that matches its resonant frequency with the dominant market frequency, dynamically adjusting the Oscillator. The oscillator then applies an optional Hull Moving Average (HMA) smoothing for signal refinement. Additionally, the indicator scans for bullish and bearish divergences by comparing oscillator movements against price action, plotting signals accordingly. When overbought/oversold conditions or divergence events occur, alerts are triggered to notify the trader in real time.
MERCURY-PRO by DrAbhiramSivprasd“MERCURYPRO”
The MERCURYPRO indicator is a custom technical analysis tool designed to provide dynamic trend signals based on a combination of the Chande Momentum Oscillator (CMO) and Standard Deviation (StDev). This indicator helps traders identify trend reversals or continuation based on the behavior of the price and momentum.
Key Features:
• Source Input: The indicator works with any price data, with the default set to close, which represents the closing price of each bar.
• Length Input: A period (default value 9) is used to determine the calculation window for the Chande Momentum Oscillator and Standard Deviation.
• Fixed CMO Length Option: Users can choose whether to use a fixed CMO length of 9 or adjust the length to the user-defined pds value.
• Calculation Method: The indicator allows switching between using the Chande Momentum Oscillator (CMO) or Standard Deviation (StDev) for the momentum calculation.
• Alpha: The smoothing factor used in the calculation of the MERCURYPRO value, which is based on the length of the period input (pds).
Core Calculation:
1. Momentum Calculation: The script calculates the momentum by determining the change in the source price (e.g., close) from one period to the next.
2. Chande Momentum Oscillator (CMO): The positive and negative momentum components are calculated and then summed over the specified period. This value is normalized to a percentage to determine the momentum strength.
3. K Value Calculation: The script selects either the CMO or Standard Deviation (depending on the user setting) to calculate the k value, which represents the dynamic price momentum.
4. MERCURYPRO Line: The final output of the indicator, MERCURYPRO, is computed using a weighted average of the k value and the previous MERCURYPRO value. The line is smoothed using the Alpha parameter.
Plot and Signal Generation:
• Color Coding: The line is color-coded based on the direction of MERCURYPRO:
• Blue: The trend is bullish (MERCURYPRO is rising).
• Maroon: The trend is bearish (MERCURYPRO is falling).
• Default Blue: Neutral or sideways market conditions.
• Plotting: The MERCURYPRO line is plotted with varying colors depending on the trend direction.
Alerts:
• Color Change Alert: The indicator has an alert condition based on when the MERCURYPRO line crosses its previous value. This helps traders stay informed about potential trend reversals or continuation signals.
Use Case:
• Trend Confirmation: Traders can use the MERCURYPRO indicator to identify whether the market is in a strong trend or not.
• Signal for Entries/Exits: The color change and crossovers of the MERCURYPRO line can be used as entry or exit signals, depending on the trader’s strategy.
Overall Purpose:
The MERCURYPRO indicator combines momentum analysis with smoothing techniques to offer a dynamic, responsive tool for identifying market trends and potential reversals. It is particularly useful in conjunction with other technical indicators to provide confirmation for trade setups.
How to Use the MERCURYPRO Indicator:
The MERCURYPRO indicator is designed to help traders identify trend reversals and market conditions. Here are a few ways you can use it:
1. Trend Confirmation (Bullish or Bearish)
• Bullish Trend: When the MERCURYPRO line is colored Blue, it indicates a rising trend, suggesting that the market is bullish.
• Action: You can consider entering long positions when the line turns blue, or holding your existing positions if you’re already long.
• Bearish Trend: When the MERCURYPRO line is colored Maroon, it signals a downward trend, indicating a bearish market.
• Action: You may consider entering short positions or closing any long positions when the line turns maroon.
2. Trend Reversal Alerts
• Color Change: The MERCURYPRO indicator changes color when there’s a trend reversal. The alert condition triggers when the MERCURYPRO crosses above or below its previous value, signaling a potential shift in the trend.
• Action: You can use this alert as a signal to monitor potential entry or exit points for trades. For example, a crossover from maroon to blue could indicate a potential buying opportunity, while a crossover from blue to maroon could suggest a selling opportunity.
3. Use with Other Indicators for Confirmation
• While the MERCURYPRO provides valuable trend insights, it’s often more effective when used in combination with other indicators like RSI (Relative Strength Index), MACD, or moving averages to confirm signals.
• Example: If MERCURYPRO turns blue and RSI is above 50, it may signal a strong bullish trend, enhancing the confidence to enter a long trade.
4. Divergence
• Watch for divergence between the MERCURYPRO line and the price chart:
• Bullish Divergence: If the price makes new lows while MERCURYPRO is showing higher lows, it suggests a potential bullish reversal.
• Bearish Divergence: If the price makes new highs while MERCURYPRO is showing lower highs, it suggests a potential bearish reversal.
Example of Use:
• Example 1: If the MERCURYPRO line changes from maroon to blue, you might enter a long position. After the MERCURYPRO line turns blue, use an alert to monitor the price action. If other indicators (like RSI) also suggest strength, your confidence in the trade will increase.
• Example 2: If the MERCURYPRO line shifts from blue to maroon, it could be a signal to close long positions and consider shorting the market if other conditions align (e.g., moving averages also turn bearish).
Warning for Using the MERCURYPRO Indicator:
1. Lagging Indicator:
• The MERCURYPRO is a lagging indicator, meaning it responds to price changes after they have occurred. This may delay entry and exit signals, and it’s crucial to combine it with other leading indicators to get timely information.
2. False Signals in Range-bound Markets:
• In choppy or sideways markets, the MERCURYPRO line can produce false signals, flipping between blue and maroon frequently without showing a clear trend. It’s important to avoid trading based on these false signals when the market is not trending.
3. Overreliance on One Indicator:
• Relying solely on MERCURYPRO can be risky. Always confirm signals with additional tools like volume analysis, price action, or other indicators to increase the accuracy of your trades.
4. Market Conditions Matter:
• The indicator may work well in trending markets, but in highly volatile or news-driven environments, it may provide misleading signals. Ensure that you take market fundamentals and external news events into consideration before acting on the indicator’s signals.
5. Risk Management:
• As with any technical indicator, MERCURYPRO is not infallible. Always use appropriate risk management techniques such as stop-loss orders to protect your capital. Never risk more than you can afford to lose on a trade.
6. Backtest First:
• Before implementing MERCURYPRO in live trading, make sure to backtest it on historical data. Test the strategy with various market conditions to assess its effectiveness and identify any potential weaknesses.
By considering these guidelines and warnings, you can use the MERCURYPRO indicator more effectively and mitigate potential risks in your trading strategy.
Vishnu's Magics**Vishnu's Magics** is a powerful RSI (Relative Strength Index) indicator designed to enhance trading strategies through effective divergence detection and alerting features. This indicator provides the following key functionalities:
1. **RSI Calculation**: Calculates the RSI over a customizable length, allowing traders to identify overbought and oversold conditions.
2. **Customizable Bands**: Users can set multiple upper and lower bands to define different overbought and oversold levels, facilitating precise trading decisions.
3. **Divergence Detection**: The indicator identifies both bullish and bearish divergences by comparing price action with RSI movements. It highlights these divergences on the chart, helping traders anticipate potential reversals.
4. **Visual Alerts**: When divergences are detected, the indicator visually marks the points on the chart with labeled shapes ("Bull" for bullish divergence and "Bear" for bearish divergence) and changes the background color to indicate the condition.
5. **Alert System**: Users can set alerts for significant events, such as crossing specified bands or detecting divergences, ensuring timely notifications for trading opportunities.
6. **Custom Line Values**: Traders can edit the values for the divergence lines, providing flexibility to tailor the indicator according to their trading strategies.
Overall, **Vishnu's Magics** serves as an intuitive tool for traders looking to leverage RSI analysis and divergence strategies for informed trading decisions.
Volume True Range (VTR) and Volume Average True Range (VATR)This indicator uses lower-timeframe cumulative volume delta (CVD) candles to calculate the Volume True Range (VTR) of your instrument. The VTR is calculated similarly to the traditional true range, but uses volume instead (no price is involved in the calculation other than in the lower timeframe bar delta assignments). I haven't seen this concept developed before on TradingView or frankly the Internet, but I thought it seemed fairly intuitive; we can calculate the lower timeframe volume delta candles, so it makes sense to calculate a volume true range, which could show divergences in volume and price.
The VTR is calculated by the following code which uses the lower-timeframe CVD candles:
volumeTR = math.max(cvd_high - cvd_low, math.abs(cvd_high - nz(cvd_close )), math.abs(cvd_low - nz(cvd_close )))
The Volume Average True Range (VATR) is calculated by taking the RMA of the VTR, similarly to the ATR.
I would like to thank TradingView for the calculation of up/down intrabar volumes, which I referenced from their 'CVD - Cumulative Volume Delta Candles' indicator.
How to Use
The VTR and VATR can be used to identify price-volume trends and volatility divergences. A strong VTR (above the VATR of your specified length) can indicate the start or continuation of a trend, which you can identify via the VTR color (determined via price candle colors). Similarly, a rising VATR with most VTR bars of a specific color (green or red) will show that volume is moving in a specific price direction.
Additionally, the VATR plotted next to the ATR of the same length will show you volume volatility divergences. A strong VATR next to a muted/flat ATR indicates strong volume movement, which price might follow in the upcoming bars. Or, for trend reversals, a decreasing ATR after a strong trend combined with a rising VATR of the opposite trend may show a possible reversal.
Hope you all enjoy this.
-wbburgin
* Quick note: lower timeframe analysis returns only so much data. If you are on a high timeframe and the indicator is showing only a limited amount of bars, raise the lower timeframe (but still keep it below your current timeframe) so that the arrays can return more bars for you.
Kzx | RSI + Div + MACDComponents Description:
Relative Strength Index (RSI):
Purpose: Measures the magnitude of recent price changes to evaluate overbought or oversold conditions in the price of a stock or other asset.
Implementation: The script allows users to set the length of the RSI calculation and defines overbought and oversold levels, which can be visually represented on the chart. Additional features include options to fill and/or color the background of the chart when overbought or oversold levels are reached.
Divergence (Div):
Purpose: Identifies instances where the price of an asset is moving in the opposite direction of a momentum indicator, such as the RSI in this script. Divergences can signal potential trend reversals.
Implementation: The script provides options for users to define the conditions under which divergences are identified, including the source of price tops/bottoms, detection limits, and the maximum lookback period for divergence analysis. It visually highlights these divergences on the chart.
Moving Average Convergence Divergence (MACD):
Purpose: Tracks the relationship between two moving averages of a security's price. The MACD is used to identify trend direction, momentum, and potential reversal points through crossovers.
Implementation: The script calculates the MACD line and its signal line. It plots buy or sell markers based on crossovers between these two lines, indicating potential entry or exit points.
Script Category:
Category: Technical Analysis / Indicators and Strategies
Subcategory: Oscillators (for RSI and MACD) and Trend Analysis (for Divergence)
Usage:
The script is designed for traders and analysts who rely on technical analysis to make informed decisions in the financial markets. By integrating RSI, divergence detection, and MACD analysis into a single script, users can gain a more nuanced understanding of market conditions, potentially improving their trading strategies.
Customization and Visualization:
Users can customize various parameters, including lengths for RSI and MACD, overbought/oversold levels, divergence detection criteria, and visual aspects like colors and marker sizes.
The script provides visual cues directly on the price chart, making it easy to spot potential buy/sell signals, overbought/oversold conditions, and divergences without the need to switch between different indicators.
Kashif_MFI+RSI+BBMerging Money Flow Index (MFI), Relative Strength Index (RSI), and Bollinger Bands in TradingView can offer traders a comprehensive view of market conditions, providing insights into potential price reversals, overbought or oversold conditions, and potential trend changes. Here are some benefits of combining these indicators:
Confirmation of Overbought and Oversold Conditions:
MFI and RSI are both oscillators that measure overbought and oversold conditions. When MFI and RSI readings are high (above their respective overbought levels), and the price is near or above the upper Bollinger Band, it may suggest that the asset is overextended and a reversal could be imminent. Conversely, when MFI and RSI readings are low (below their respective oversold levels) and the price is near or below the lower Bollinger Band, it may indicate potential buying opportunities.
Divergence Analysis:
Traders often look for divergences between price action and MFI/RSI. If the price is making new highs, but MFI/RSI is not confirming these highs (bearish divergence), it could signal weakening momentum and a possible reversal. Combining this analysis with Bollinger Bands can add another layer of confirmation, especially if the price is touching or exceeding the upper Bollinger Band during this divergence.
Volatility Confirmation:
Bollinger Bands provide a measure of volatility by expanding and contracting based on price volatility. If the bands are widening, it indicates increased volatility. Combining this information with MFI and RSI readings can help traders assess the strength of a trend. For example, during a strong uptrend, if MFI and RSI are high and Bollinger Bands are expanding, it may suggest a sustained bullish trend.
Identifying Trend Reversals:
The combination of MFI, RSI, and Bollinger Bands can be useful in identifying potential trend reversals. For instance, if MFI and RSI are in overbought conditions and the price is significantly above the upper Bollinger Band, it may signal that the trend is reaching an extreme and could reverse. Conversely, if MFI and RSI are in oversold conditions and the price is near or below the lower Bollinger Band, it may suggest that selling pressure is exhausted, and a reversal might be in play.
Comprehensive Market Assessment:
By merging these indicators, traders get a more comprehensive view of market conditions. They can assess both momentum (MFI and RSI) and volatility (Bollinger Bands) simultaneously, helping them make more informed trading decisions.
It's important to note that no single indicator or combination of indicators guarantees accurate predictions in trading. Traders should use these tools as part of a broader analysis and consider other factors such as fundamental analysis, market trends, and risk management.
R-sqrd Adapt. Fisher Transform w/ D. Zones & Divs. [Loxx]The full name of this indicator is R-Squared Adaptive Fisher Transform w/ Dynamic Zones and Divergences. This is an R-squared adaptive Fisher transform with adjustable dynamic zones, signals, alerts, and divergences.
What is Fisher Transform?
The Fisher Transform is a technical indicator created by John F. Ehlers that converts prices into a Gaussian normal distribution.
The indicator highlights when prices have moved to an extreme, based on recent prices. This may help in spotting turning points in the price of an asset. It also helps show the trend and isolate the price waves within a trend.
What is R-squared Adaptive?
One tool available in forecasting the trendiness of the breakout is the coefficient of determination ( R-squared ), a statistical measurement.
The R-squared indicates linear strength between the security's price (the Y - axis) and time (the X - axis). The R-squared is the percentage of squared error that the linear regression can eliminate if it were used as the predictor instead of the mean value. If the R-squared were 0.99, then the linear regression would eliminate 99% of the error for prediction versus predicting closing prices using a simple moving average .
R-squared is used here to derive an r-squared value that is then modified by a user input "factor"
What are Dynamic Zones?
As explained in "Stocks & Commodities V15:7 (306-310): Dynamic Zones by Leo Zamansky, Ph .D., and David Stendahl"
Most indicators use a fixed zone for buy and sell signals. Here’ s a concept based on zones that are responsive to past levels of the indicator.
One approach to active investing employs the use of oscillators to exploit tradable market trends. This investing style follows a very simple form of logic: Enter the market only when an oscillator has moved far above or below traditional trading lev- els. However, these oscillator- driven systems lack the ability to evolve with the market because they use fixed buy and sell zones. Traders typically use one set of buy and sell zones for a bull market and substantially different zones for a bear market. And therein lies the problem.
Once traders begin introducing their market opinions into trading equations, by changing the zones, they negate the system’s mechanical nature. The objective is to have a system automatically define its own buy and sell zones and thereby profitably trade in any market — bull or bear. Dynamic zones offer a solution to the problem of fixed buy and sell zones for any oscillator-driven system.
An indicator’s extreme levels can be quantified using statistical methods. These extreme levels are calculated for a certain period and serve as the buy and sell zones for a trading system. The repetition of this statistical process for every value of the indicator creates values that become the dynamic zones. The zones are calculated in such a way that the probability of the indicator value rising above, or falling below, the dynamic zones is equal to a given probability input set by the trader.
To better understand dynamic zones, let's first describe them mathematically and then explain their use. The dynamic zones definition:
Find V such that:
For dynamic zone buy: P{X <= V}=P1
For dynamic zone sell: P{X >= V}=P2
where P1 and P2 are the probabilities set by the trader, X is the value of the indicator for the selected period and V represents the value of the dynamic zone.
The probability input P1 and P2 can be adjusted by the trader to encompass as much or as little data as the trader would like. The smaller the probability, the fewer data values above and below the dynamic zones. This translates into a wider range between the buy and sell zones. If a 10% probability is used for P1 and P2, only those data values that make up the top 10% and bottom 10% for an indicator are used in the construction of the zones. Of the values, 80% will fall between the two extreme levels. Because dynamic zone levels are penetrated so infrequently, when this happens, traders know that the market has truly moved into overbought or oversold territory.
Calculating the Dynamic Zones
The algorithm for the dynamic zones is a series of steps. First, decide the value of the lookback period t. Next, decide the value of the probability Pbuy for buy zone and value of the probability Psell for the sell zone.
For i=1, to the last lookback period, build the distribution f(x) of the price during the lookback period i. Then find the value Vi1 such that the probability of the price less than or equal to Vi1 during the lookback period i is equal to Pbuy. Find the value Vi2 such that the probability of the price greater or equal to Vi2 during the lookback period i is equal to Psell. The sequence of Vi1 for all periods gives the buy zone. The sequence of Vi2 for all periods gives the sell zone.
In the algorithm description, we have: Build the distribution f(x) of the price during the lookback period i. The distribution here is empirical namely, how many times a given value of x appeared during the lookback period. The problem is to find such x that the probability of a price being greater or equal to x will be equal to a probability selected by the user. Probability is the area under the distribution curve. The task is to find such value of x that the area under the distribution curve to the right of x will be equal to the probability selected by the user. That x is the dynamic zone.
Included:
Bar coloring
4 signal variations w/ alerts
Divergences w/ alerts
Loxx's Expanded Source Types
Multi-Timeframe Volume-Weighted RSIA multiple timeframe volume-weighted RSI.
Blue Line = Current Time Frame
Orange Line = Select your desired Time Frame
e.g. Blue = Daily, Orange = Weekly
1. Incorporates Market Commitment
Value: By factoring in volume, the volume-weighted RSI captures the intensity of trading activity behind price movements.
Why it’s useful:
Regular RSI measures price momentum but does not differentiate between moves with high or low trading activity.
A volume-weighted RSI assigns greater importance to price changes occurring on high volume, reflecting stronger market conviction.
2. Improved Signal Reliability
Value: Signals generated by a volume-weighted RSI (e.g., overbought or oversold conditions) may be more reliable because they account for the level of trader participation.
Why it’s useful:
Low-volume price movements often result in false signals or "noise."
A volume-weighted RSI helps filter out such noise, reducing the likelihood of false breakouts or fake reversals.
3. Better Divergence Detection
Value: Divergences between price action and the RSI (bullish or bearish divergences) are more meaningful when confirmed by volume.
Why it’s useful:
Regular RSI might show divergence in price momentum, but this divergence might lack substance if the underlying volume is weak.
A volume-weighted RSI ensures that divergence signals align with periods of significant market participation.
4. Enhanced Trend Analysis
Value: Trends supported by strong volume are given more weight, helping traders better identify and follow trends.
Why it’s useful:
Regular RSI might show overbought or oversold signals prematurely during strong trends.
Volume-weighted RSI considers whether trends are backed by significant market activity, helping avoid early exits.
5. More Meaningful Overbought/Oversold Levels
Value: Levels like 70 (overbought) and 30 (oversold) are more credible when supported by volume.
Why it’s useful:
In a regular RSI, overbought or oversold levels might occur on light trading, leading to false reversals.
A volume-weighted RSI ensures these levels are triggered by substantial market participation, increasing their reliability.
Practical Applications:
Trend Confirmation: Use the volume-weighted RSI to confirm whether momentum in a trend is supported by strong participation.
Divergence Spotting: Identify divergences with more confidence by prioritizing those with volume support.
Filtering False Breakouts: Avoid entering trades during weak volume phases by focusing on volume-weighted RSI signals.
Limitations:
Market Type Dependency: Its usefulness may diminish in low-volume assets or markets where volume data is unavailable (e.g., forex).
Musashi_Fractal_Dimension === Musashi-Fractal-Dimension ===
This tool is part of my research on the fractal nature of the markets and understanding the relation between fractal dimension and chaos theory.
To take full advantage of this indicator, you need to incorporate some principles and concepts:
- Traditional Technical Analysis is linear and Euclidean, which makes very difficult its modeling.
- Linear techniques cannot quantify non-linear behavior
- Is it possible to measure accurately a wave or the surface of a mountain with a simple ruler?
- Fractals quantify what Euclidean Geometry can’t, they measure chaos, as they identify order in apparent randomness.
- Remember: Chaos is order disguised as randomness.
- Chaos is the study of unstable aperiodic behavior in deterministic non-linear dynamic systems
- Order and randomness can coexist, allowing predictability.
- There is a reason why Fractal Dimension was invented, we had no way of measuring fractal-based structures.
- Benoit Mandelbrot used to explain it by asking: How do we measure the coast of Great Britain?
- An easy way of getting the need of a dimension in between is looking at the Koch snowflake.
- Market prices tend to seek natural levels of ranges of balance. These levels can be described as attractors and are determinant.
Fractal Dimension Index ('FDI')
Determines the persistence or anti-persistence of a market.
- A persistent market follows a market trend. An anti-persistent market results in substantial volatility around the trend (with a low r2), and is more vulnerable to price reversals
- An easy way to see this is to think that fractal dimension measures what is in between mainstream dimensions. These are:
- One dimension: a line
- Two dimensions: a square
- Three dimensions: a cube.
--> This will hint you that at certain moment, if the market has a Fractal Dimension of 1.25 (which is low), the market is behaving more “line-like”, while if the market has a high Fractal Dimension, it could be interpreted as “square-like”.
- 'FDI' is trend agnostic, which means that doesn't consider trend. This makes it super useful as gives you clean information about the market without trying to include trend stuff.
Question: If we have a game where you must choose between two options.
1. a horizontal line
2. a vertical line.
Each iteration a Horizontal Line or a Square will appear as continuation of a figure. If it that iteration shows a square and you bet vertical you win, same as if it is horizontal and it is a line.
- Wouldn’t be useful to know that Fractal dimension is 1.8? This will hint square. In the markets you can use 'FD' to filter mean-reversal signals like Bollinger bands, stochastics, Regular RSI divergences, etc.
- Wouldn’t be useful to know that Fractal dimension is 1.2? This will hint Line. In the markets you can use 'FD' to confirm trend following strategies like Moving averages, MACD, Hidden RSI divergences.
Calculation method:
Fractal dimension is obtained from the ‘hurst exponent’.
'FDI' = 2 - 'Hurst Exponent'
Musashi version of the Classic 'OG' Fractal Dimension Index ('FDI')
- By default, you get 3 fast 'FDI's (11,12,13) + 1 Slow 'FDI' (21), their interaction gives useful information.
- Fast 'FDI' cross will give you gray or red dots while Slow 'FDI' cross with the slowest of the fast 'FDI's will give white and orange dots. This are great to early spot trend beginnings or trend ends.
- A baseline (purple) is also provided, this is calculated using a 21 period Bollinger bands with 1.618 'SD', once calculated, you just take midpoint, this is the 'TDI's (Traders Dynamic Index) way. The indicator will print purple dots when Slow 'FDI' and baseline crosses, I see them as Short-Term cycle changes.
- Negative slope 'FDI' means trending asset.
- Positive most of the times hints correction, but if it got overextended it might hint a rocket-shot.
TDI Ranges:
- 'FDI' between 1.0≤ 'FDI' ≤1.4 will confirm trend following continuation signals.
- 'FDI' between 1.6≥ 'FDI' ≥2.0 will confirm reversal signals.
- 'FDI' == 1.5 hints a random unpredictable market.
Fractal Attractors
- As you must know, fractals tend orbit certain spots, this are named Attractors, this happens with any fractal behavior. The market of course also shows them, in form of Support & Resistance, Supply Demand, etc. It’s obvious they are there, but now we understand that they’re not linear, as the market is fractal, so simple trendline might not be the best tool to model this.
- I’ve noticed that when the Musashi version of the 'FDI' indicator start making a cluster of multicolor dots, this end up being an attractor, I tend to draw a rectangle as that area as price tend to come back (I still researching here).
Extra useful stuff
- Momentum / speed: Included by checking RSI Study in the indicator properties. This will add two RSI’s (9 and a 7 periods) plus a baseline calculated same way as explained for 'FDI'. This gives accurate short-term trends. It also includes RSI divergences (regular and hidden), deactivate with a simple check in the RSI section of the properties.
- BBWP (Bollinger Bands with Percentile): Efficient way of visualizing volatility as the percentile of Bollinger bands expansion. This line varies color from Iced blue when low volatility and magma red when high. By default, comes with the High vols deactivated for better view of 'FDI' and RSI while all studies are included. DDWP is trend agnostic, just like 'FDI', which make it very clean at providing information.
- Ultra Slow 'FDI': I noticed that while using BBWP and RSI, the indicator gets overcrowded, so there is the possibility of adding only one 'FDI' + its baseline.
Final Note: I’ve shown you few ways of using this indicator, please backtest before using in real trading. As you know trading is more about risk and trade management than the strategy used. This still a work in progress, I really hope you find value out of it. I use it combination with a tool named “Musashi_Katana” (also found in TradingView).
Best!
Musashi
Goethe B - Mutiple Leading Indicator PackageGoethe B is an Indicator Package that contains multiple leading and lagging indicators.
The background is that shows the local trend is calculated by either two Moving Averages or by a Kumo Cloud. By default the Kumo Cloud calculation is used.
What is the main oscillator?
- The main oscillator is TSV, or time segmented volume. It is one of the more interesting leading indicators.
What is the top bar?
-The top bar shows a trend confirmation based on the wolfpack ID indicator.
What are those circles on the second top bar?
-Those are Divergences of an internally calculated PVT oscillator. Red for Regular-Bearish, Green for Regular-Bullish.
What are those circles on the main oscillator?
-These are Divergences. Red for Regular-Bearish. Orange for Hidden-Bearish. Green for Regular-Bullish. Aqua for Hidden-Bullish.
What are those circles on the second lower bar?
-Those are Divergences of an internally calculated CCI indicator. Red for Regular-Bearish, Green for Regular-Bullish.
What is the lower bar?
-The lower bar shows a trend confirmation based on the Acceleration Oscillator, in best case it showes how far in the trend the current price action is.
What are those orange or aqua squares?
- These are TSI (true strength indicator) entry signals . They are calculated by the TSI entry signal, the TSI oscillator threshold.
Most settings of the indicator package can be modified to your liking and based on your chosen strategy might have to be modified. Please keep in mind that this indicator is a tool and not a strategy, do not blindly trade signals, do your own research first! Use this indicator in conjunction with other indicators to get multiple confirmations.
