Directional ATROANDA:EURUSD
TLDR: A custom volatility indicator that combines Average True Range with candle direction.
The Directional ATR (DATR) is an indicator that enhances the traditional Average True Range (ATR) by incorporating the direction of the candle (bullish or bearish).
This indicator is designed to help traders identify trend strength, potential trend reversals, and market volatility.
Key Features:
Trend Confirmation: Positive and increasing DATR values suggest a bullish trend, while negative and decreasing values indicate a bearish trend. A higher absolute DATR value signifies a stronger trend.
Trend Reversal: A change in the direction of the DATR from positive to negative or vice versa may signal a potential trend reversal.
Volatility: Like the standard ATR, the DATR can be used to gauge market volatility, with larger absolute values indicating higher volatility and smaller values suggesting lower volatility.
Divergence: Divergence between the price and the DATR could signal a potential weakening of the trend and an upcoming reversal.
Overbought/Oversold Levels: Extreme DATR values can be used to identify overbought or oversold market conditions, signaling potential reversals or corrections.
Please note that the Directional ATR is just an indicator, and the interpretations provided are based on its underlying logic.
It is essential to combine the DATR with other technical analysis tools and test the indicator on historical data before using it in your trading strategy. Additionally, consider other factors such as risk management, and your own trading style.
在腳本中搜尋"Divergence"
Open Close TrendThis is a simple trend indicator that gives you a few options on how to view the data. The way this works is it takes the open, close, high and low and it smooths them with an exponential moving average. Next we smooth a bit with a simple moving average to clear up the data. Finally we normalize everything to the average high and low. With this you can compare the average closing price to the average opening price. If the closing price is greater than the opening price then it is in an up trend and visa versa. You can also find reversals by looking for divergences. I have included a few features in this script including: Normalization, 200ma centering, Background color divergence convergence, histogram to see convergence divergence, and custom colors. I hope you all enjoy this simple release! I know I had fun making this.
Investment Protector - A Rule of Thumb V1The Flash Crash of September 8 showed once more how many are falling to greed. On top of it one also add leverage to long positions. It's just insane the risk people are taking. Anyhow, for all my noobies and friends here is a very very simple indicator that shows when NOT to buy nor increase positions and when there is window of opportunities.
A few remarks:
This script does NOT provide trading signals
Merely points out windows of opportunities - candles with green background. You still need to find the entry in this area yourself. Apply geomeric Technical Analysis, use indicators or divergences.
Windows of opportunities can still go south, use the stop-loss! (and check for bearish divergence)
The script urges you NOT to trade below ema200 of the 4h timeframe, which is marked with a red background (the most smooh timeframe there is).
Push yourself to take profits. It is marked with on the cancles to support you. Yes, it could always go higher, but try to avoid to be in a crash (and again, use a stop-loss at all time. You can make it a generous one if you want, fine. As long as you have one.).
TA speaking:
The scripts uses EMA and RSI only.
Bearish divergence will be added in V2.
disclaimer: yes, not financial advise. It's educational.
CT Reverse True Strength Indicator On ChartIntroducing the Caretakers “On Chart” Reverse True Strength Index.
According to Wikipedia….
“The True Strength Index (TSI) is a technical indicator used in the analysis of financial markets that attempts to show both trend direction and overbought/oversold conditions. It was first published William Blau in 1991.
The indicator uses moving averages of the underlying momentum of a financial instrument.
Momentum is considered a leading indicator of price movements, and a moving average characteristically lags behind price.
The TSI combines these characteristics to create an indication of price and direction more in sync with market turns than either momentum or moving average.”
The TSI has a normal range of values between +100 and -100.
Traditionally traders and analysts will consider:
Positives values above 25 to indicate an “overbought” condition
Negative values below -25 to indicate an “oversold” condition
I have reverse engineered the True Strength Index formula to derive 2 new functions.
1) The reverse TSI function is dual purpose which can be used to calculate….
The chart price at which the TSI will reach a particular TSI scale value.
The chart price at which the TSI will equal its previous value.
2) The reverse TSI signal cross function can be used to calculate the chart price at which the TSI will cross its signal line.
I have employed these functions here to return the price levels where the True Strength Index would equal :
Upper alert level ( default 25 )
Zero-Line
Lower alert level ( default -25 )
Previous TSI (eq) value
TSI signal line
In this “On Chart” version of the reverse True Strength Index the crossover levels are displayed both as lines on the chart and via an optional info-box with choice of user selected info.
Chart Line Colors
Upper alert level... ( Fuchsia )
Zero-Line............ ( White )
Lower alert level... ( Aqua )
TSI (eq)...............( TSI (eq) > close..Orange, TSI (eq) < close..Lime )
TSI signal line........( Signal Cross Line > Close..Aqua, Signal Cross Line < Close..Fuchsia )
How to interpret the displayed prices returned from the TSI scale zero line and upper and lower alert levels.
Closing exactly at the given price will cause the True Strength Index value to equal the scale value.
Closing above the given price will cause the True Strength Index to cross above the scale value.
Closing below the given price will cause the True Strength Index to cross below the scale value.
How to interpret the displayed price returned from the TSI (eq)
Closing exactly at the price will cause the True Strength Index value to equal the previous TSI value.
Closing above the price will cause the True Strength Index value to increase.
Closing below the price will cause the True Strength Index value to decrease.
How to interpret the displayed price returned from the TSI signal line crossover.
Closing exactly at the given price will cause the True Strength Index value to equal the signal line.
Closing above the given price will cause the True Strength Index to cross above the signal line.
Closing below the given price will cause the True Strength Index to cross below the signal line.
Common methods to derive signals from the TSI :
Zero-line crossovers
When the CMO crosses above the zero-line, a buy signal is generated.
When the CMO crosses below the zero-line, a sell signal is generated.
“Overbought” and “Oversold” crossovers
When the SMI crosses below -25 and then moves back above it, a buy signal is generated.
When the SMI crosses above +25 and then moves back below it, a sell signal is generated.
What Does the True Strength Index (TSI) Tell You?
The indicator is primarily used to identify overbought and oversold conditions in an asset's price, spot divergence, identify trend direction and changes via the zero-line, and highlight short-term price momentum with signal line crossovers.
Since the TSI is based on price movements, oversold and overbought levels will vary by the asset being traded. Some stocks may reach +30 and -30 before tending to see price reversals, while another stock may reverse near +20 and -20.
Mark extreme TSI levels, on the asset being traded, to see where overbought and oversold is. Being oversold doesn't necessarily mean it is time to buy, and when an asset is overbought it doesn't necessarily mean it is time to sell. Traders will typically watch for other signals to trigger a trade decision. For example, they may wait for the price or TSI to start dropping before selling in overbought territory. Alternatively, they may wait for a signal line crossover.
Signal Line Crossovers
The true strength index has a signal line, which is usually a seven- to 13-period EMA of the TSI line. A signal line crossover occurs when the TSI line crosses the signal line. When the TSI crosses above the signal line from below, that may warrant a long position. When the TSI crosses below the signal line from above, that may warrant selling or short selling.
Signal line crossovers occur frequently, so should be utilized only in conjunction with other signals from the TSI. For example, buy signals may be favoured when the TSI is above the zero-line. Or sell signals may be favoured when the TSI is in overbought territory.
Zero-line Crossovers
The zero-line crossover is another signal the TSI generates. Price momentum is positive when the indicator is above zero and negative when it is below zero. Some traders use the zero-line for a directional bias. For example, a trader may decide only to enter a long position if the indicator is above its zero-line. Conversely, the trader would be bearish and only consider short positions if the indicator's value is below zero.
Breakouts and Divergence
Traders can use support and resistance levels created by the true strength index to identify breakouts and price momentum shifts. For instance, if the indicator breaks below a trendline, the price may see continued selling.
Divergence is another tool the TSI provides. If the price of an asset is moving higher, while the TSI is dropping, that is called bearish divergence and could result in a downside price move. If the TSI is rising while the price is falling, that could signal higher prices to come. This is called bullish divergence.
Divergence is a poor timing signal, so it should only be used in conjunction with other signals generated by the TSI or other technical indicators.
The Difference Between the True Strength Index (TSI) and the Moving Average Convergence Divergence (MACD) Indicator.
The TSI is smoothing price changes to create a technical oscillator. The moving average convergence divergence (MACD) indicator is measuring the separation between two moving averages. Both indicators are used in similar ways for trading purposes, yet they are not calculated the same and will provide different signals at different times.
The Limitations of Using the True Strength Index (TSI)
Many of the signals provided by the TSI will be false signals. That means the price action will be different than expected following a trade signal. For example, during an uptrend, the TSI may cross below the zero-line several times, but then the price proceeds higher even though the TSI indicates momentum has shifted down.
Signal line crossovers also occur so frequently that they may not provide a lot of trading benefit. Such signals need to be heavily filtered based on other elements of the indicator or through other forms of analysis. The TSI will also sometimes change direction without price changing direction, resulting in trade signals that look good on the TSI but continue to lose money based on price.
Divergence also tends to unreliable on the indicator. Divergence can last so long that it provides little insight into when a reversal will actually occur. Also, divergence isn't always present when price reversals actually do occur.
The TSI should only be used in conjunction with other forms of analysis, such as price action analysis and other technical indicators.
This is not financial advice, use at your own risk.
CT Reverse True Strength IndicatorIntroducing the Caretakers Reverse True Strength Index.
According to Wikipedia….
“The True Strength Index (TSI) is a technical indicator used in the analysis of financial markets that attempts to show both trend direction and overbought/oversold conditions. It was first published William Blau in 1991.
The indicator uses moving averages of the underlying momentum of a financial instrument.
Momentum is considered a leading indicator of price movements, and a moving average characteristically lags behind price.
The TSI combines these characteristics to create an indication of price and direction more in sync with market turns than either momentum or moving average.”
The TSI has a normal range of values between +100 and -100.
Traditionally traders and analysts will consider:
Positives values above 25 to indicate an “overbought” condition
Negative values below -25 to indicate an “oversold” condition
I have reverse engineered the True Strength Index formula to derive 2 new functions.
The reverse TSI function is dual purpose which can be used to calculate….
The chart price at which the TSI will reach a particular TSI scale value.
The chart price at which the TSI will equal its previous value.
The reverse TSI signal cross function can be used to calculate the chart price at which the TSI will cross its signal line.
I have employed these functions here to return the price levels where the True Strength Index would equal :
Upper alert level ( default 25 )
Zero-Line
Lower alert level ( default -25 )
Previous TSI (eq) value.
TSI signal line
These crossover levels are displayed via an optional info-box with choice of user selected info.
How to interpret the displayed prices returned from the TSI scale zero line and upper and lower alert levels.
Closing exactly at the given price will cause the True Strength Index value to equal the scale value.
Closing above the given price will cause the True Strength Index to cross above the scale value.
Closing below the given price will cause the True Strength Index to cross below the scale value.
How to interpret the displayed price returned from the TSI (eq)
Closing exactly at the price will cause the True Strength Index value to equal the previous TSI value.
Closing above the price will cause the True Strength Index value to increase.
Closing below the price will cause the True Strength Index value to decrease.
How to interpret the displayed price returned from the TSI signal line crossover.
Closing exactly at the given price will cause the True Strength Index value to equal the signal line.
Closing above the given price will cause the True Strength Index to cross above the signal line.
Closing below the given price will cause the True Strength Index to cross below the signal line.
Common methods to derive signals from the TSI :
Zero-line crossovers
When the CMO crosses above the zero-line, a buy signal is generated.
When the CMO crosses below the zero-line, a sell signal is generated.
“Overbought” and “Oversold” crossover
When the SMI crosses below -25 and then moves back above it, a buy signal is generated.
When the SMI crosses above +25 and then moves back below it, a sell signal is generated.
What Does the True Strength Index (TSI) Tell You?
The indicator is primarily used to identify overbought and oversold conditions in an asset's price, spot divergence, identify trend direction and changes via the zero-line, and highlight short-term price momentum with signal line crossovers.
Since the TSI is based on price movements, oversold and overbought levels will vary by the asset being traded. Some stocks may reach +30 and -30 before tending to see price reversals, while another stock may reverse near +20 and -20.
Mark extreme TSI levels, on the asset being traded, to see where overbought and oversold is. Being oversold doesn't necessarily mean it is time to buy, and when an asset is overbought it doesn't necessarily mean it is time to sell. Traders will typically watch for other signals to trigger a trade decision. For example, they may wait for the price or TSI to start dropping before selling in overbought territory. Alternatively, they may wait for a signal line crossover.
Signal Line Crossovers
The true strength index has a signal line, which is usually a seven- to 13-period EMA of the TSI line. A signal line crossover occurs when the TSI line crosses the signal line. When the TSI crosses above the signal line from below, that may warrant a long position. When the TSI crosses below the signal line from above, that may warrant selling or short selling.
Signal line crossovers occur frequently, so should be utilized only in conjunction with other signals from the TSI. For example, buy signals may be favoured when the TSI is above the zero-line. Or sell signals may be favoured when the TSI is in overbought territory.
Zero-line Crossovers
The zero-line crossover is another signal the TSI generates. Price momentum is positive when the indicator is above zero and negative when it is below zero. Some traders use the zero-line for a directional bias. For example, a trader may decide only to enter a long position if the indicator is above its zero-line. Conversely, the trader would be bearish and only consider short positions if the indicator's value is below zero.
Breakouts and Divergence
Traders can use support and resistance levels created by the true strength index to identify breakouts and price momentum shifts. For instance, if the indicator breaks below a trendline, the price may see continued selling.
Divergence is another tool the TSI provides. If the price of an asset is moving higher, while the TSI is dropping, that is called bearish divergence and could result in a downside price move. If the TSI is rising while the price is falling, that could signal higher prices to come. This is called bullish divergence.
Divergence is a poor timing signal, so it should only be used in conjunction with other signals generated by the TSI or other technical indicators.
The Difference Between the True Strength Index (TSI) and the Moving Average Convergence Divergence (MACD) Indicator.
The TSI is smoothing price changes to create a technical oscillator. The moving average convergence divergence (MACD) indicator is measuring the separation between two moving averages. Both indicators are used in similar ways for trading purposes, yet they are not calculated the same and will provide different signals at different times.
The Limitations of Using the True Strength Index (TSI)
Many of the signals provided by the TSI will be false signals. That means the price action will be different than expected following a trade signal. For example, during an uptrend, the TSI may cross below the zero-line several times, but then the price proceeds higher even though the TSI indicates momentum has shifted down.
Signal line crossovers also occur so frequently that they may not provide a lot of trading benefit. Such signals need to be heavily filtered based on other elements of the indicator or through other forms of analysis. The TSI will also sometimes change direction without price changing direction, resulting in trade signals that look good on the TSI but continue to lose money based on price.
Divergence also tends to unreliable on the indicator. Divergence can last so long that it provides little insight into when a reversal will actually occur. Also, divergence isn't always present when price reversals actually do occur.
The TSI should only be used in conjunction with other forms of analysis, such as price action analysis and other technical indicators.
This is not financial advice, use at your own risk.
Better OBVOBV with William C. Garrett's Approximation
In the classical OBV (On-Balance Volume) indicator, it simply takes the idea from traditional tape reading - treat the "up tick" as Buy, "down tick" as Sell, and it assumes no change in price as neutral* (*which is not the case in tape reading).
When it comes to interpret the daily volume as such, errors will add up cumulatively. For example, there are days when a Doji Star with high volume just merely one cent higher than yesterday price and the whole day volume would be taken as a BUY Volume....
Here is a gentlemen, William C. Garrett, attempted to break down the daily volume into two parts in his book - "Torque Analysis of Stock Market Cycle".
Published indicator has two modes: Cumulative and Time Segmented. Time Segmented Volume (TSV) - performs a MACD operation on the Garrett Money Flow.
Note on Divergence:
When using a indicator as Time Segmented Money Flow, divergence would surely occur on and off. This is where Wyckoff 3rd principle comes into play - "Effort vs Result" that is not matching. Meaning that the cumulation of shares goes in one direction while the price goes another direction.
[blackcat] L3 Composite MACD-KDJ-RSI-WR-DMI Trading SystemLevel: 3
Background
The moving average convergence / divergence (MACD) indicator is a pulse oscillator that is mainly used to trade trends. Although it is an oscillator, it is not typically used to identify overbought or oversold conditions. It appears in the diagram as two lines that oscillate without limits. The crossing of the two lines provides trading signals similar to a system with two moving averages.
The KDJ indicator is a technical indicator used to analyze and predict changes in stock performance and the price patterns of a traded asset. The KDJ indicator is also known as the random index. It is a very useful technical indicator that is most commonly used in short term stock market trend analysis. KDJ is a derived form of the Stochastic Oscillator Indicator with the only difference that an additional line is called the J-line. Values of% K and% D indicate whether the security is overbought (over 80) or oversold (under 20). The moments when% K exceeds% D are the moments to sell or buy. The J line represents the deviation of the% D value from% K. The value of J can exceed for the% K and% D lines on the graph.
The Relative Strength Index (RSI) developed by J. Welles Wilder is a pulse oscillator that measures the speed and change of price movements. The RSI hovers between zero and 100. Traditionally, the RSI is considered overbought when it is above 70 and oversold when below 30. Signals can be generated by looking for divergences and error fluctuations.
Williams% R, also known as the Williams Percent Range, is a type of momentum indicator that moves between 0 and -100 and measures overbought and oversold levels. The Williams% R can be used to find entry and exit points in the market. The indicator is very similar to the stochastic oscillator and is used in the same way.
The Directional Movement Index (DMI) is an indicator developed by J. Welles Wilder in 1978 to determine in which direction asset prices are moving. The indicator does this by comparing previous highs and lows and drawing two lines: a positive movement line (+DI) and a negative movement line (-DI). The optional third line is called "Directional Movement (DX)" and it shows the difference between the two lines. When +DI is higher than -DI, the upward pressure on the price is greater than the downward pressure. If -DI is higher than +DI, the price will have greater downward pressure. This indicator can help traders assess the trend direction. Crosses between lines are sometimes used as buying and selling signals.
Function
L3 Composite MACD-KDJ-RSI-WR-DMI Trading System is a simple trading system composed of MACD-KDJ-RSI-WR-DMI together. It can produce 6 types of long entries and 3 types of short entries. It utilizes divergence effect from MACD, KDJ and RSI to detect trend reversal. 6 types of Bottom and top divergence labels are displayed in the chart together with "BUY" and "SELL".
NOTE:In order to make the actual label of the chart more clear, this script does not add stop loss and take profit functions and according labels.
Signal
b1~b3 ---> MACD, KDJ, RSI bottom divergence signal respectively, which hint bull trend may start soon.
d1~d3 ---> MACD, KDJ, RSI top divergence signal respectively, which hint bear trend may start soon.
longentry1~6 ---> with composite indicators together, 6 types of long entry signal are produced.
shortentry1~3 ---> with composite indicators together, 3 types of short entry signal are produced.
Pros and Cons
Pros:
1. excellent open-close, long-short entry signal generation with multiple powerful indicators
2. indicator resonance can help to promote the confidence level of signal and divergence alerts
Cons:
1. integration of multiple indicators is not deeply optimized. fake signal may be produced without filtering schemes
2. no range filter is added
Remarks
To celebrate number of followers exceeds 100. This is my first L3 script published.
Readme
In real life, I am a prolific inventor. I have successfully applied for more than 60 international and regional patents in the past 12 years. But in the past two years or so, I have tried to transfer my creativity to the development of trading strategies. Tradingview is the ideal platform for me. I am selecting and contributing some of the hundreds of scripts to publish in Tradingview community. Welcome everyone to interact with me to discuss these interesting pine scripts.
The scripts posted are categorized into 5 levels according to my efforts or manhours put into these works.
Level 1 : interesting script snippets or distinctive improvement from classic indicators or strategy. Level 1 scripts can usually appear in more complex indicators as a function module or element.
Level 2 : composite indicator/strategy. By selecting or combining several independent or dependent functions or sub indicators in proper way, the composite script exhibits a resonance phenomenon which can filter out noise or fake trading signal to enhance trading confidence level.
Level 3 : comprehensive indicator/strategy. They are simple trading systems based on my strategies. They are commonly containing several or all of entry signal, close signal, stop loss, take profit, re-entry, risk management, and position sizing techniques. Even some interesting fundamental and mass psychological aspects are incorporated.
Level 4 : script snippets or functions that do not disclose source code. Interesting element that can reveal market laws and work as raw material for indicators and strategies. If you find Level 1~2 scripts are helpful, Level 4 is a private version that took me far more efforts to develop.
Level 5 : indicator/strategy that do not disclose source code. private version of Level 3 script with my accumulated script processing skills or a large number of custom functions. I had a private function library built in past two years. Level 5 scripts use many of them to achieve private trading strategy.
VFI - Volume Flow Indicator [UTS]The Volume Flow Indicator (VFI) indicator was first introduced in my June 2004 and is is based on the popular On Balance Volume (OBV) but with three very important modifications:
Unlike the OBV, indicator values are no longer meaningless. Positive readings are bullish and negative bearish.
The calculation is based on the day's median instead of the closing price.
A volatility threshold takes into account minimal price changes and another threshold eliminates excessive volume.
The indicator takes into account only the latest 6 month volume action and not the entire data loaded in the chart.
General Usage
A simplified interpretation of the VFI is that values above zero indicate a bullish state and the crossing of the zero line is the trigger or buy signal.
The strongest signal with all money flow indicators is of course divergence.
The classic form of divergence is when the indicator refuses to follow the price action and makes lower highs while price makes higher highs (negative divergence). If price reaches a new low but the indicator fails to do so, then price probably traveled lower than it should have. In this instance, you have positive divergence.
Default settings
130 VFI Length
0.2 Coef
2.5 Volume cutoff
3 Smoothing Period
Further setting examples can be found on www.precisiontradingsystems.com
Trend Visualisation
Optional Setting:
If the trend direction is DOWN the moving average is painted red. If the trend direction is UP the moving average is painted in green.
If the movement is FLAT then the color is grey.
Moving Averages
4 different types of Moving Averages are available for both FVI and the optional Moving Average of the FVI.
ALMA (Arnaud Legoux Moving Average)
EMA (Exponential Moving Average)
SMA (Simple Moving Average)
WMA (Weighted Moving Average)
Notes
This indicator is using the exact formula from mkatsanos.com where EMA has been taken as default value for FVI smoothing calculation.
Accumulation/Distribution Percentage (ADP) [Cyrus c|:D]Accumulation/Distribution Percentage ( ADP ) is used to measure money flow similar to Chaikin Money Flow ( CMF ) and Money Flow. It is the range-bound version of my previous indicator ADMF. This indicator can be used for analyzing momentum, buy/sell pressure, and overbought/oversold conditions. I believe that this indicator is more accurate than CMF and MFI (I will publish a TA about it one day!).
What to look for:
- When this indicator moves up, it means buy pressure is increasing and the other way around for sell pressure. Crossing 0 means that trend has changed in the given period (it is best to look for confirmation of buy/sell pressure in larger TFs)
- Overbought above 40 and oversold below -40 (these numbers vary depending on the security. Look for historical levels to determine overbought and oversold conditions of each security)
- Regular divergence shows that momentum of a trend is declining. Hidden divergence implies continuation of a trend. The non-bound mode should be more accurate for identifying divergence.
- Failure swings can detect potential reversals.
Please read Relative Strength Index and Money Flow for more information and similar disclaimers.
Recommendations:
- hlc3 (AKA typical price) as input source might be better than "close" as it captures more information. If you use hlc3 as a source, then change the chart type to line and set hlc3 as the source for identifying divergence.
- Use hybrid tickers e.g.(BITFINEX:BTCUSD+COINBASE:BTCUSD+BITSTAMP:BTCUSD)/3. Volume-based indicators are susceptible to wash trading/volume printing and hybrid tickers mitigate this issue.
- In non-bound mode, small TFs with longer length should be more accurate than larger TFs with standard length (same is true for many other indicators)
Background:
I have developed 4 indicators based on a simple but elegant concept of A/D ratio. A/D ratio is equal to (current close - previous close)/True Range (when there are no price gaps, True Range = High - Low)
1) What you see on ADV indicator as darker green and red is equal to A/D ratio x volume.
2) ADL indicator shows the summation of ADV
3) ADMF (or ADP in non-bound mode) shows Moving Average of ADV
4) ADP shows relative accumulation strength which is calculated as RMA (accumulations)/RMA(accumulation + distribution). ADP equation is based on RSI equation which is RMA(gains)/RMA(gains + losses). That is why these two indicators look quite similar.
PS: Please leave a like if you find these indicators useful. I am working on improvements on these and other indicators. I am trying my best to keep them as simple as possible. Please let me know in the comments if you want me to make future indicators even simpler.
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Complementary indicators based on the same concept:
ADL: a replacement for Chaikin's Accum/Dist, On Balance Volume, and Price Volume Trend
ADV: a replacement for regular volume indicator
ADP also has a scaled RSI and ADMF built in (ie ADMF is obsolete).
Green*DiamondGreen*Diamond (GD1)
Unleash Dynamic Trading Signals with Volatility and Momentum
Overview
GreenDiamond is a versatile overlay indicator designed for traders seeking actionable buy and sell signals across various markets and timeframes. Combining Volatility Bands (VB) bands, Consolidation Detection, MACD, RSI, and a unique Ribbon Wave, it highlights high-probability setups while filtering out noise. With customizable signals like Green-Yellow Buy, Pullback Sell, and Inverse Pullback Buy, plus vibrant candle and volume visuals, GreenDiamond adapts to your trading style—whether you’re scalping, day trading, or swing trading.
Key Features
Volatility Bands (VB): Plots dynamic upper and lower bands to identify breakouts or reversals, with toggleable buy/sell signals outside consolidation zones.
Consolidation Detection: Marks low-range periods to avoid choppy markets, ensuring signals fire during trending conditions.
MACD Signals: Offers flexible buy/sell conditions (e.g., cross above signal, above zero, histogram up) with RSI divergence integration for precision.
RSI Filter: Enhances signals with customizable levels (midline, oversold/overbought) and bullish divergence detection.
Ribbon Wave: Visualizes trend strength using three EMAs, colored by MACD and RSI for intuitive momentum cues.
Custom Signals: Includes Green-Yellow Buy, Pullback Sell, and Inverse Pullback Buy, with limits on consecutive signals to prevent overtrading.
Candle & Volume Styling: Blends MACD/RSI colors on candles and scales volume bars to highlight momentum spikes.
Alerts: Set up alerts for VB signals, MACD crosses, Green*Diamond signals, and custom conditions to stay on top of opportunities.
How It Works
Green*Diamond integrates multiple indicators to generate signals:
Volatility Bands: Calculates bands using a pivot SMA and standard deviation. Buy signals trigger on crossovers above the lower band, sell signals on crossunders below the upper band (if enabled).
Consolidation Filter: Suppresses signals when candle ranges are below a threshold, keeping you out of flat markets.
MACD & RSI: Combines MACD conditions (e.g., cross above signal) with RSI filters (e.g., above midline) and optional volume spikes for robust signals.
Custom Logic: Green-Yellow Buy uses MACD bullishness, Pullback Sell targets retracements, and Inverse Pullback Buy catches reversals after downmoves—all filtered to avoid consolidation.
Visuals: Ribbon Wave shows trend direction, candles blend momentum colors, and volume bars scale dynamically to confirm signals.
Settings
Volatility Bands Settings:
VB Lookback Period (20): Adjust to 10–15 for faster markets (e.g., 1-minute scalping) or 25–30 for daily charts.
Upper/Lower Band Multiplier (1.0): Increase to 1.5–2.0 for wider bands in volatile stocks like AEHL; decrease to 0.5 for calmer markets.
Show Volatility Bands: Toggle off to reduce chart clutter.
Use VB Signals: Enable for breakout-focused trades; disable to focus on Green*Diamond signals.
Consolidation Settings:
Consolidation Lookback (14): Set to 5–10 for small caps (e.g., AEHL) to catch quick consolidations; 20 for higher timeframes.
Range Threshold (0.5): Lower to 0.3 for stricter filtering in choppy markets; raise to 0.7 for looser signals.
MACD Settings:
Fast/Slow Length (12/26): Shorten to 8/21 for scalping; extend to 15/34 for swing trading.
Signal Smoothing (9): Reduce to 5 for faster signals; increase to 12 for smoother trends.
Buy/Sell Signal Options: Choose “Cross Above Signal” for classic MACD; “Histogram Up” for momentum plays.
Use RSI Div + MACD Cross: Enable for high-probability reversal signals.
RSI Settings:
RSI Period (14): Drop to 10 for 1-minute charts; raise to 20 for daily.
Filter Level (50): Set to 55 for stricter buys; 45 for sells.
Overbought/Oversold (70/30): Tighten to 65/35 for small caps; widen to 75/25 for indices.
RSI Buy/Sell Options: Select “Bullish Divergence” for reversals; “Cross Above Oversold” for momentum.
Color Settings:
Adjust bullish/bearish colors for visibility (e.g., brighter green/red for dark themes).
Border Thickness (1): Increase to 2–3 for clearer candle outlines.
Volume Settings:
Volume Average Length (20): Shorten to 10 for scalping; extend to 30 for swing trades.
Volume Multiplier (2.0): Raise to 3.0 for AEHL’s volume surges; lower to 1.5 for steady stocks.
Bar Height (10%): Increase to 15% for prominent bars; decrease to 5% to reduce clutter.
Ribbon Settings:
EMA Periods (10/20/30): Tighten to 5/10/15 for scalping; widen to 20/40/60 for trends.
Color by MACD/RSI: Disable for simpler visuals; enable for dynamic momentum cues.
Gradient Fill: Toggle on for trend clarity; off for minimalism.
Custom Signals:
Enable Green-Yellow Buy: Use for momentum confirmation; limit to 1–2 signals to avoid spam.
Pullback/Inverse Pullback % (50): Set to 30–40% for small caps; 60–70% for indices.
Max Buy Signals (1): Increase to 2–3 for active markets; keep at 1 for discipline.
Tips and Tricks
Scalping Small Caps (e.g., AEHL):
Use 1-minute charts with VB Lookback = 10, Consolidation Lookback = 5, and Volume Multiplier = 3.0 to catch $0.10–$0.20 moves.
Enable Green-Yellow Buy and Inverse Pullback Buy for quick entries; disable VB Signals to focus on Green*Diamond logic.
Pair with SMC+ green boxes (if you use them) for reversal confirmation.
Day Trading:
Try 5-minute charts with MACD Fast/Slow = 8/21 and RSI Period = 10.
Enable RSI Divergence + MACD Cross for high-probability setups; set Max Buy Signals = 2.
Watch for volume bars turning yellow to confirm entries.
Swing Trading:
Use daily charts with VB Lookback = 30, Ribbon EMAs = 20/40/60.
Enable Pullback Sell (60%) to exit after rallies; disable RSI Color for cleaner candles.
Check Ribbon Wave gradient for trend strength—bright green signals strong bulls.
Avoiding Noise:
Increase Consolidation Threshold to 0.7 on volatile days to skip false breakouts.
Disable Ribbon Wave or Volume Bars if the chart feels crowded.
Limit Max Buy Signals to 1 for disciplined trading.
Alert Setup:
In TradingView’s Alerts panel, select:
“GD Buy Signal” for standard entries.
“RSI Div + MACD Cross Buy” for reversals.
“VB Buy Signal” for breakout plays.
Set to “Once Per Bar Close” for confirmed signals; “Once Per Bar” for scalping.
Backtesting:
Replay on small caps ( Float < 5M, Price $0.50–$5) to test signals.
Focus on “GD Buy Signal” with yellow volume bars and green Ribbon Wave.
Avoid signals during gray consolidation squares unless paired with RSI Divergence.
Usage Notes
Markets: Works on stocks, forex, crypto, and indices. Best for volatile assets (e.g., small-cap stocks, BTCUSD).
Timeframes: Scalping (1–5 minutes), day trading (15–60 minutes), or swing trading (daily). Adjust settings per timeframe.
Risk Management: Combine with stop-losses (e.g., 1% risk, $0.05 below AEHL entry) and take-profits (3–5%).
Customization: Tweak inputs to match your strategy—experiment in replay to find your sweet spot.
Disclaimer
Green*Diamond is a technical tool to assist with trade identification, not a guarantee of profits. Trading involves risks, and past performance doesn’t predict future results. Always conduct your own analysis, manage risk, and test settings before live trading.
Feedback
Love Green*Diamond? Found a killer setup?
AsianRange&Midnight 2.2### Midnight Setup: Trading Strategy
#### **Bias Definition (Trend Identification)**
- The Daily (D) bias is defined the previous day and validated on the line chart.
- On the Daily chart, identify the nearest V-shaped formation that has broken close to the current price. This formation determines the Daily bias direction.
#### **H4 Bias Analysis (Trend Confirmation)**
- Switch to an H4 chart to refine the analysis.
- Identify a similar V-shaped formation that has broken in the H4 timeframe.
- If the Daily and H4 biases are aligned, the setup is valid.
#### **Entry Strategy (Position Entries)**
- **Bearish Bias (D and H4 identical):**
- Short entry at the high level of the Midnight range.
- **Bullish Bias (D and H4 identical):**
- Long entry at the low level of the Midnight range.
#### **Bias Divergence (Context Adaptation)**
- If the H4 bias is opposite to the Daily bias, this indicates an H4 retracement of the Daily bias.
- Enter a counter-trend trade with reduced risk.
- No TP target beyond 50% of the extension validating the Daily break. It is also not recommended to enter against this divergence beyond 50%.
#### **Divergence Scenarios (Reactions to Divergences)**
- **Daily Bearish Bias, H4 Bullish Bias:**
- Long entry at the Midnight Low.
- **Daily Bullish Bias, H4 Bearish Bias:**
- Short entry at the Midnight High.
#### **Daily Bias Resumption (Trend Alignment)**
- As soon as the H4 bias resumes the Daily bias direction, follow this trend and adjust the position accordingly.
#### **Instructions for Divergent Bias (Managing Divergence)**
- When holding a position with a divergent bias, it is crucial to manage it carefully.
- Exit counter-trend trades as soon as the H4 bias realigns with the Daily bias.
- Limit the duration of counter-trend trades per session and adjust the H4 bias for the next session if needed.
#### **SL/TP Management (Profit Taking and Protection Optimization)**
- **Take Profit (TP):**
- Entry in M15 with a minimum RR of 3.
- TP at 5H NYE, or RR 5, or 15H NYE.
- **Stop Loss (SL):**
- Minimum 15 pips, placed just above the nearest swing to the entry point to protect capital.
- **Red Announcement Days:**
- Either abstain from trading or set a 40-pip SL to limit volatility impact.
- **At 6H/7H NYE:**
- Manage the trade based on its progress: exit, set to BE (Break Even), or keep the SL in place.
- Any SL adjustment outside these rules can only be made if supported by data or backtests.
#### **Risk Management (Capital Protection)**
- Maximum risk of **1% of capital per trade** (allowing for **10 consecutive losses** without significantly affecting capital).
- In case of a loss, **reduce risk by 50% on the next trade** until the loss is recovered.
#### **Efficiency Conditions (When This Setup Works Best)**
- This setup is particularly effective in **strong trends**, where the market has a clear direction.
- It is **less effective in ranging markets**, where prices move within a narrow range without a clear trend.
Setup Midnight : Stratégie de Trading
Auto TrendLines [TradingFinder] Support Resistance Signal Alerts🔵 Introduction
The trendline is one of the most essential tools in technical analysis, widely used in financial markets such as Forex, cryptocurrency, and stocks. A trendline is a straight line that connects swing highs or swing lows and visually indicates the market’s trend direction.
Traders use trendlines to identify price structure, the strength of buyers and sellers, dynamic support and resistance zones, and optimal entry and exit points.
In technical analysis, trendlines are typically classified into three categories: uptrend lines (drawn by connecting higher lows), downtrend lines (formed by connecting lower highs), and sideways trends (moving horizontally). A valid trendline usually requires at least three confirmed touchpoints to be considered reliable for trading decisions.
Trendlines can serve as the foundation for a variety of trading strategies, such as the trendline bounce strategy, valid breakout setups, and confluence-based analysis with other tools like candlestick patterns, divergences, moving averages, and Fibonacci levels.
Additionally, trendlines are categorized into internal and external, and further into major and minor levels, each serving unique roles in market structure analysis.
🔵 How to Use
Trendlines are a key component in technical analysis, used to identify market direction, define dynamic support and resistance zones, highlight strategic entry and exit points, and manage risk. For a trendline to be reliable, it must be drawn based on structural principles—not by simply connecting two arbitrary points.
🟣 Selecting Pivot Types Based on Trend Direction
The first step is to determine the market trend: uptrend, downtrend, or sideways.
Then, choose pivot points that match the trend type :
In an uptrend, trendlines are drawn by connecting low pivots, especially higher lows.
In a downtrend, trendlines are formed by connecting high pivots, specifically lower highs.
It is crucial to connect pivots of the same type and structure to ensure the trendline is valid and analytically sound.
🟣 Pivot Classification
This indicator automatically classifies pivot points into two categories :
Major Pivots :
MLL : Major Lower Low
MHL : Major Higher Low
MHH : Major Higher High
MLH : Major Lower High
These define the primary structure of the market and are typically used in broader structural analysis.
Minor Pivots :
mLL: minor Lower Low
mHL: minor Higher Low
mHH: minor Higher High
mLH: minor Lower High
These are used for drawing more precise trendlines within corrective waves or internal price movements.
Example : In a downtrend, drawing a trendline from an MHH to an mHH creates structural inconsistency and introduces noise. Instead, connect points like MHL to MHL or mLH to mLH for a valid trendline.
🟣 Drawing High-Precision Trendlines
To ensure a reliable trendline :
Use pivots of the same classification (Major with Major or Minor with Minor).
Ensure at least three valid contact points (three touches = structural confirmation).
Draw through candles with the least deviation (choose wicks or bodies based on confluence).
Preferably draw from right to left for better alignment with current market behavior.
Use parallel lines to turn a single trendline into a trendline zone, if needed.
🟣 Using Trendlines for Trade Entries
Bounce Entry: When price approaches the trendline and shows signs of reversal (e.g., a reversal candle, divergence, or support/resistance), enter in the direction of the trend with a logical stop-loss.
Breakout Entry: When price breaks through the trendline with strong momentum and a confirmation (such as a retest or break of structure), consider trading in the direction of the breakout.
🟣 Trendline-Based Risk Management
For bounce entries, the stop-loss is placed below the trendline or the last pivot low (in an uptrend).
For breakout entries, the stop-loss is set behind the breakout candle or the last structural level.
A broken trendline can also act as an exit signal from a trade.
🟣 Combining Trendlines with Other Tools (Confluence)
Trendlines gain much more strength when used alongside other analytical tools :
Horizontal support and resistance levels
Moving averages (such as EMA 50 or EMA 200)
Fibonacci retracement zones
Candlestick patterns (e.g., Engulfing, Pin Bar)
RSI or MACD divergences
Market structure breaks (BoS / ChoCH)
🔵 Settings
Pivot Period : This defines how sensitive the pivot detection is. A higher number means the algorithm will identify more significant pivot points, resulting in longer-term trendlines.
Alerts
Alert :
Enable or disable the entire alert system
Set a custom alert name
Choose how often alerts trigger (every time, once per bar, or on bar close)
Select the time zone for alert timestamps (e.g., UTC)
Each trendline type supports two alert types :
Break Alert : Triggered when price breaks the trendline
React Alert : Triggered when price reacts or bounces off the trendline
These alerts can be independently enabled or disabled for all trendline categories (Major/Minor, Internal/External, Up/Down).
Display :
For each of the eight trendline types, you can control :
Whether to show or hide the line
Whether to delete the previous line when a new one is drawn
Color, line style (solid, dashed, dotted), extension direction (e.g., right only), and width
Major lines are typically thicker and more opaque, while minor lines appear thinner and more transparent.
All settings are designed to give the user full control over the appearance, behavior, and alert system of the indicator, without requiring manual drawing or adjustments.
🔵 Conclusion
A trendline is more than just a line on the chart—it is a structural, strategic, and flexible tool in technical analysis that can serve as the foundation for understanding price behavior and making trading decisions. Whether in trending markets or during corrections, trendlines help traders identify market direction, key zones, and high-potential entry and exit points with precision.
The accuracy and effectiveness of a trendline depend on using structurally valid pivot points and adhering to proper market logic, rather than relying on guesswork or personal bias.
This indicator is built to solve that exact problem. It automatically detects and draws multiple types of trendlines based on actual price structure, separating them into Major/Minor and Internal/External categories, and respecting professional analytical principles such as pivot type, trend direction, and structural location.
Multi-Timeframe PSAR Indicator ver 1.0Enhance your trend analysis with the Multi-Timeframe Parabolic SAR (MTF PSAR) indicator! This powerful tool displays the Parabolic SAR (Stop and Reverse) from both the current chart's timeframe and a higher timeframe, all in one convenient view. Identify potential trend reversals and set dynamic trailing stops with greater confidence by understanding the broader market context.
Key Features:
Dual Timeframe Analysis: Simultaneously visualize the PSAR on your current chart and a user-defined higher timeframe (e.g., see the Daily PSAR while trading on the 1-hour chart). This helps you align your trades with the dominant trend.
Customizable PSAR Settings: Fine-tune the PSAR calculation with adjustable Start, Increment, and Maximum values. Optimize the indicator's sensitivity to match your trading style and the volatility of the asset.
Independent Timeframe Control: Choose to display either or both the current timeframe PSAR and the higher timeframe PSAR. Focus on the information most relevant to your analysis.
Clear Visual Representation: Distinct colors for the current and higher timeframe PSAR dots make it easy to differentiate between the two. Quickly identify potential entry and exit points.
Configurable Colors You can easily change colors of Current and HTF PSAR.
Standard PSAR Logic: Uses the classic Parabolic SAR algorithm, providing a reliable and widely-understood trend-following indicator.
lookahead=barmerge.lookahead_off used in the security function, there is no data leak or repainting.
Benefits:
Improved Trend Identification: Spot potential trend changes earlier by observing divergences between the current and higher timeframe PSAR.
Enhanced Risk Management: Use the PSAR as a dynamic trailing stop-loss to protect profits and limit potential losses.
Greater Trading Confidence: Make more informed decisions by considering the broader market trend.
Reduced Chart Clutter: Avoid the need to switch between multiple charts to analyze different timeframes.
Versatile Application: Suitable for various trading styles (swing trading, day trading, trend following) and markets (stocks, forex, crypto, etc.).
How to Use:
Add to Chart: Add the "Multi-Timeframe PSAR" indicator to your TradingView chart.
Configure Settings:
PSAR Settings: Adjust the Start, Increment, and Maximum values to control the PSAR's sensitivity.
Multi-Timeframe Settings: Select the desired "Higher Timeframe PSAR" resolution (e.g., "D" for Daily). Enable or disable the display of the current and/or higher timeframe PSAR using the checkboxes.
Interpret Signals:
Current Timeframe PSAR: Dots below the price suggest an uptrend; dots above the price suggest a downtrend.
Higher Timeframe PSAR: Provides context for the overall trend. Agreement between the current and higher timeframe PSAR strengthens the trend signal. Divergences may indicate potential reversals.
Trade Management:
Use PSAR dots as dynamic trailing stop.
Example Use Cases:
Confirming Trend Strength: A trader on a 1-hour chart sees the 1-hour PSAR flip bullish (dots below the price). They check the MTF PSAR and see that the Daily PSAR is also bullish, confirming the strength of the uptrend.
Identifying Potential Reversals: A trader sees the current timeframe PSAR flip bearish, but the higher timeframe PSAR remains bullish. This divergence could signal a potential pullback within a larger uptrend, or a warning of a more significant reversal.
Trailing Stops: A trader enters a long position and uses the current timeframe PSAR as a trailing stop, moving their stop-loss up as the PSAR dots rise.
Disclaimer: The Parabolic SAR is a lagging indicator and may produce false signals, especially in ranging markets. It is recommended to use this indicator in conjunction with other technical analysis tools and risk management strategies. Past performance is not indicative of future results.
MTF Volume Flow IndicatorThe MTF Volume Flow Indicator (MTF VFI) is an advanced and versatile tool that enhances market analysis by tracking the flow of volume across multiple timeframes. By integrating volume flow with multi-timeframe analysis, this indicator provides traders with a comprehensive understanding of market trends, momentum, and potential reversals.
Key Features
Multi-Timeframe Volume Flow Analysis: The MTF VFI computes the Volume Flow Indicator across various timeframes, ranging from 1 minute to 1 month. This multi-timeframe analysis enables traders to observe and compare volume flow dynamics across different time horizons, offering deeper insights into market behavior.
Customizable VFI Settings: The indicator includes configurable VFI parameters such as length, coefficient, and volume cutoff, allowing users to tailor the analysis to different market conditions and trading strategies. This flexibility ensures that the indicator remains relevant across diverse market environments.
Signal Line and Delta Calculations: The script features a signal line derived from the VFI and calculates the delta values (the difference between VFI and the signal line). These delta values are essential for identifying potential buy or sell signals and are presented as histograms for easy visual interpretation.
Cumulative Delta with Dynamic Bands: The indicator introduces cumulative delta, a powerful tool that combines average and median VFI values to provide a clearer picture of market sentiment. Two standard deviation bands are plotted around the cumulative delta, offering a range within which price movements are likely to remain. These bands are smoothed using a 21-period EMA, providing a more refined view of market volatility.
Multi-Timeframe and Analysis Tables: The MTF VFI includes optional tables that display VFI, signal line, and delta values across all selected timeframes. Additionally, an analysis table presents key statistical metrics such as the highest, lowest, average, standard deviation, range, and median VFI values. These tables provide a concise summary of market conditions, aiding in strategic decision-making.
Dynamic Display Options: The indicator offers extensive customization options, allowing traders to display or hide elements such as delta histograms, delta bands, and tables. This ensures that users can focus on the most relevant information for their trading strategy.
Neutral Candle Coloring Option: Traders can enable neutral candle colors, where bearish candles are gray and bullish candles are white. This feature helps to reduce noise and maintain focus on the overall trend and volume flow analysis.
How It Works
Volume Flow Indicator Calculation: The VFI is calculated using a combination of typical price, volume, and the standard deviation of price changes. The indicator smooths the VFI based on user preferences, allowing traders to adjust the sensitivity of the analysis to better match their trading style.
Multi-Timeframe Integration: The script pulls VFI calculations from multiple timeframes, providing a holistic view of market trends. By analyzing VFI across different timeframes, traders can detect alignments or divergences in volume flow that might indicate trend strength or weakness.
Cumulative Delta and Dynamic Bands: The cumulative delta is computed by combining the average and median VFI values. Dynamic two-standard-deviation bands are plotted around this cumulative delta, providing upper and lower bounds for expected price movements. These bands are further smoothed with a 21-period EMA, enhancing their effectiveness in volatile markets.
Delta Analysis and Histogram Display: The difference between the VFI and its signal line (delta) is calculated and displayed as histograms. This visual representation helps traders quickly assess momentum and identify potential reversals or trend continuations. The cumulative delta is color-coded dynamically based on its direction, adding an extra layer of visual clarity.
Alerts
VFI Crossover Alerts: The indicator includes customizable alerts that notify traders when the VFI crosses above or below its signal line. These alerts are crucial for catching potential trend reversals or continuation signals, even when the trader is not actively monitoring the chart.
Customizable Alert Conditions: Traders can tailor alert conditions to their preferred timeframes and VFI settings, ensuring that the notifications they receive are relevant and timely for their specific trading strategies.
Application
Trend Identification and Confirmation: The MTF VFI aids in identifying and confirming trends by analyzing volume flow across multiple timeframes. This capability is particularly useful for detecting trends that may not be visible on a single timeframe.
Momentum and Divergence Analysis: By comparing VFI and delta values across timeframes, and analyzing cumulative delta with dynamic bands, traders can gain insights into market momentum and potential divergences, which are often precursors to reversals.
Strategic Decision-Making: With its comprehensive multi-timeframe analysis, cumulative delta, and statistical summaries, the MTF VFI equips traders with the information needed to make informed trading decisions, whether for short-term trades or long-term investments.
Visual Clarity and Customization: The indicator’s dynamic display options and neutral candle coloring help traders maintain a clear and focused view of the market, customizing the visualization to match their specific needs.
The MTF Volume Flow Indicator (MTF VFI) by CryptoSea is an essential tool for traders who seek to gain a deeper understanding of market trends and volume dynamics across multiple timeframes. Its advanced features and customization options make it a valuable addition to any trader’s toolkit.
FCNC SpreadTitle: FCNC Spread Indicator
Description:
The FCNC Spread Indicator is designed to help traders analyze the price difference (spread) between two futures contracts: the front contract and the next contract. This type of analysis is commonly used in futures trading to identify market sentiment, arbitrage opportunities, and potential roll yield strategies.
How It Works:
Front Contract: The front contract represents the futures contract closest to expiration, often referred to as the near-month contract.
Next Contract: The next contract is the futures contract that follows the front contract in the expiration cycle, typically the next available month.
Spread Calculation: frontContract - nextContract represents the difference between the price of the front contract and the next contract.
Positive Spread: A positive value means that the front contract is more expensive than the next contract, indicating backwardation.
Negative Spread: A negative value means that the front contract is cheaper than the next contract, indicating contango.
How to Use:
Input Selection: Select your desired futures contracts for the front and next contract through the input settings. The script will fetch and calculate the closing prices of these contracts.
Spread Plotting: The calculated spread is plotted on the chart, with color-coding based on the spread's value (green for positive, red for negative).
Labeling: The spread value is dynamically labeled on the chart for quick reference.
Moving Average: A 20-period Simple Moving Average (SMA) of the spread is also plotted to help identify trends and smooth out fluctuations.
Applications:
Trend Identification: Analyze the spread to determine market sentiment and potential trend reversals.
Divergence Detection: Look for divergences between the spread and the underlying market to identify possible shifts in trend or market sentiment. Divergences can signal upcoming reversals or provide early warning signs of a change in market dynamics.
This indicator is particularly useful for futures traders who are looking to gain insights into the market structure and to exploit differences in contract pricing. By providing a clear visualization of the spread between two key futures contracts, traders can make more informed decisions about their trading strategies.
SqueeZe Score [UAlgo]The "SqueeZe Score" is a script based on the "Squeeze Momentum Indicator". It utilizes Bollinger Bands (BB) and Keltner Channels (KC) to identify periods of low volatility, indicating potential upcoming price movements. The Z-Score method is employed to measure deviations from the mean, highlighting extreme price movements within the context of the current volatility environment. This script provides traders with visual cues for potential bullish and bearish divergences, aiding in decision-making during trading activities.
🔶Key Features:
SqueeZe Settings: Users can customize parameters such as the length and multiplier factors for Bollinger Bands and Keltner Channels, providing flexibility to adapt the indicator to different trading strategies and market conditions.
Divergence Detection: The script includes options to detect and display both bullish and bearish divergences, providing additional insights into potential trend reversals or continuations.
Customizable Z-Score Thresholds: Thresholds for the Z-Score are user-defined, enabling traders to set levels at which extreme price movements are highlighted on the chart, facilitating quick identification of significant market conditions.
🔶Credit:
This script is inspired by the work of @LazyBear, who contributed to the original concept and development of the Squeeze Momentum indicator.
🔶Disclaimer:
- The information provided by this script is for educational and informational purposes only and should not be construed as financial advice.
- Users are encouraged to conduct their own research and analysis before making any investment decisions.
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
Composite MomentumComposite Momentum Indicator - Enhancing Trading Insights with RSI & Williams %R
The Composite Momentum Indicator is a powerful technical tool that combines the Relative Strength Index (RSI) and Williams %R indicators from TradingView. This unique composite indicator offers enhanced insights into market momentum and provides traders with a comprehensive perspective on price movements. By leveraging the strengths of both RSI and Williams %R, the Composite Momentum Indicator offers distinct advantages over a simple RSI calculation.
1. Comprehensive Momentum Analysis:
The Composite Momentum Indicator integrates the RSI and Williams %R indicators to provide a comprehensive analysis of market momentum. It takes into account both the strength of recent price gains and losses (RSI) and the relationship between the current closing price and the highest-high and lowest-low price range (Williams %R). By combining these two momentum indicators, traders gain a more holistic view of market conditions.
2. Increased Accuracy:
While the RSI is widely used for measuring overbought and oversold conditions, it can sometimes generate false signals in certain market environments. The Composite Momentum Indicator addresses this limitation by incorporating the Williams %R, which focuses on the price range and can offer more accurate signals in volatile market conditions. This combination enhances the accuracy of momentum analysis, allowing traders to make more informed trading decisions.
3. Improved Timing of Reversals:
One of the key advantages of the Composite Momentum Indicator is its ability to provide improved timing for trend reversals. By incorporating both RSI and Williams %R, traders can identify potential turning points more effectively. The Composite Momentum Indicator offers an early warning system for identifying overbought and oversold conditions and potential trend shifts, helping traders seize opportunities with better timing.
4. Enhanced Divergence Analysis:
Divergence analysis is a popular technique among traders, and the Composite Momentum Indicator strengthens this analysis further. By comparing the RSI and Williams %R within the composite calculation, traders can identify divergences between the two indicators more easily. Divergence between the RSI and Williams %R can signal potential trend reversals or the weakening of an existing trend, providing valuable insights for traders.
5. Customizable Moving Average:
The Composite Momentum Indicator also features a customizable moving average (MA), allowing traders to further fine-tune their analysis. By incorporating the MA, traders can smooth out the composite momentum line and identify longer-term trends. This additional layer of customization enhances the versatility of the indicator, catering to various trading styles and timeframes.
The Composite Momentum Indicator, developed using the popular TradingView indicators RSI and Williams %R, offers a powerful tool for comprehensive momentum analysis. By combining the strengths of both indicators, traders can gain deeper insights into market conditions, improve accuracy, enhance timing for reversals, and leverage divergence analysis. With the added customization of the moving average, the Composite Momentum Indicator provides traders with a versatile and effective tool to make more informed trading decisions.
On-Balance Accumulation Distribution (Volume-Weighted)The On-Balance Accumulation Distribution (OBAD) indicator is designed to analyze the accumulation and distribution of assets based on volume-weighted price movements. The indicator helps traders identify periods of buying and selling pressure and assess the strength of market trends. By incorporating volume and price data, the OBAD indicator provides valuable insights into the flow of funds in the market.
To calculate the OBAD, the indicator multiplies the volume, price, and volume factor (user-defined) with the price change and aggregates the values over a specified length. This results in a histogram and a line plot representing the OBAD values. The OBAD signal line is derived by applying a simple moving average (SMA) to the OBAD values over a shorter period (9 by default). The crossover of the OBAD line and signal line can indicate potential entry or exit points.
The OBAD indicator utilizes coloration to enhance its visual representation and interpretation. The OBAD background is colored based on the relationship between the OBAD values and the OBAD signal line. When the OBAD values are above the signal line, the background is displayed in lime, suggesting a bullish accumulation scenario. Conversely, when the OBAD values are below the signal line, the background is colored fuchsia, indicating a bearish distribution pattern. The bar coloration is also applied to provide further visual cues, with lime representing bullish conditions and fuchsia denoting bearish conditions. When the OBAD signal line is above 0, it is colored green. Conversely, if the signal line is below 0, it is colored maroon.
The length parameter in the OBAD indicator determines the number of periods used in the calculation. Shorter lengths, such as 10 or 20, can make the indicator more responsive to recent price and volume changes, providing quicker signals. This can be beneficial for short-term traders or in fast-paced markets. Conversely, longer lengths, such as 50 or 100, smooth out the indicator and provide a broader view of accumulation and distribution over a more extended period. This may suit longer-term traders or when analyzing trends in less volatile markets. Traders should experiment with different lengths to find the optimal balance between responsiveness and smoothness that aligns with their trading goals.
The volume factor parameter allows traders to adjust the weighting of volume in the OBAD calculation. By modifying this factor, traders can emphasize the impact of volume on the indicator. Increasing the volume factor amplifies the influence of volume in the OBAD calculation, making it more sensitive to volume changes. This can be advantageous when volume is considered a significant driver of price movements, such as during news events or market catalysts. On the other hand, decreasing the volume factor reduces the impact of volume, making the indicator less sensitive to volume fluctuations. Traders can experiment with different volume factors to align the indicator's responsiveness with their analysis of volume patterns and its importance in their trading decisions.
The signal line period parameter determines the number of periods used to calculate the moving average of the OBAD values. Adjusting this parameter can help smooth out the indicator and filter out short-term noise or provide more timely signals. A shorter signal line period, such as 5 or 7, provides more sensitive and frequent crossovers with the OBAD values, potentially offering early entry or exit signals. This can be useful for traders seeking shorter-term trades or more agile trading strategies. Conversely, a longer signal line period, such as 9 or 14, smooths out the indicator and provides more stable signals. This may suit traders who prefer longer-term trends or a more conservative approach. Traders should consider their trading timeframe and the desired balance between responsiveness and stability when adjusting the signal line period.
The OBAD indicator can be applied in various trading strategies and scenarios. It helps traders identify potential trend reversals, confirm existing trends, and generate entry and exit signals. For example, when the OBAD histogram transitions from fuchsia to lime, it may suggest a shift from selling to buying pressure, signaling a potential buying opportunity. Traders can also use the OBAD indicator in conjunction with other technical analysis tools, such as trendlines or support/resistance levels, to confirm signals and make more informed trading decisions.
-- Trend Reversal Identification : The OBAD indicator can be useful in identifying potential trend reversals. When the OBAD values cross above the signal line after being below it, it may suggest a shift from bearish distribution to bullish accumulation. Conversely, when the OBAD values cross below the signal line after being above it, it may indicate a transition from bullish accumulation to bearish distribution. Traders can use these crossovers as potential signals to enter or exit trades in anticipation of a trend reversal.
-- Confirmation of Trend Strength : The OBAD indicator can act as a confirmation tool for assessing the strength of existing trends. When the OBAD values remain consistently above the signal line, it confirms the presence of strong bullish accumulation and validates the upward trend. Similarly, when the OBAD values stay consistently below the signal line, it confirms the presence of strong bearish distribution and validates the downward trend. Traders can use this confirmation to have more confidence in the prevailing trend and adjust their trading strategies accordingly.
-- Divergence Analysis : Divergence between the price and the OBAD indicator can provide valuable insights. Bullish divergence occurs when the price forms lower lows while the OBAD indicator forms higher lows, suggesting a potential trend reversal to the upside. Conversely, bearish divergence occurs when the price forms higher highs while the OBAD indicator forms lower highs, indicating a potential trend reversal to the downside. Traders can use these divergences as additional confirmation signals in their trading decisions.
-- Volume Analysis : The OBAD indicator incorporates volume data, making it particularly useful for volume analysis. Traders can analyze the relationship between OBAD values and volume levels to gauge the strength and validity of price movements. Higher OBAD values accompanied by higher volume can indicate strong accumulation or distribution, providing confirmation for potential trade setups. On the other hand, lower OBAD values accompanied by low volume may suggest a lack of participation and potentially signal caution in trading decisions.
It is important to note that the OBAD indicator, like any other technical indicator, has certain limitations. It relies on historical price and volume data, which may not always accurately reflect current market conditions or future price movements. Traders should exercise caution and use the OBAD indicator in conjunction with other analysis techniques and risk management strategies. Additionally, customization of the OBAD parameters, such as adjusting the length or volume factor, can provide flexibility to adapt the indicator to different market conditions and trading preferences.
Overall, the OBAD indicator serves as a valuable tool for traders to gauge the accumulation and distribution patterns in the market. Its calculation based on volume-weighted price movements and the coloration enhancements make it visually appealing and intuitive to interpret. By incorporating the OBAD indicator into trading strategies and considering its limitations, traders can potentially improve their decision-making process and enhance their trading outcomes.
Crypto McClellan Oscillator (SLN Fix)This is an adaption of the Mcclellan Oscillator for crypto. Instead of tracking the S&P500 it tracks a selection of cryptos to make sure the indicator follows this sector instead.
Full credit goes to the creator of this indicator: Fadior. It has since been fixed by SLN.
The following description explains the standard McClellan Oscillator. Full credit to Investopedia , my fav source of financial explanations.
The same principles applies to its use in the crypto sector, but please be cautious of the last point, the limitations. Since crypto is more volatile, that could amplify choppy behavior.
This is not financial advice, please be extremely cautious. This indicator is only suitable as a confirmation signal and needs support of other signals to be profitable.
This indicator usually produces the best signals on slightly above daily time frame. I personally like 2 or 3 day, but you have to find the settings suitable for your trading style.
What Is the McClellan Oscillator?
The McClellan Oscillator is a market breadth indicator that is based on the difference between the number of advancing and declining issues on a stock exchange, such as the New York Stock Exchange (NYSE) or NASDAQ.
The indicator is used to show strong shifts in sentiment in the indexes, called breadth thrusts. It also helps in analyzing the strength of an index trend via divergence or confirmation.
The McClellan Oscillator formula can be applied to any stock exchange or group of stocks.
A reading above zero helps confirm a rise in the index, while readings below zero confirm a decline in the index.
When the index is rising but the oscillator is falling, that warns that the index could start declining too. When the index is falling and the oscillator is rising, that indicates the index could start rising soon. This is called divergence.
A significant change, such as moving 100 points or more, from a negative reading to a positive reading is called a breadth thrust. It may indicate a strong reversal from downtrend to uptrend is underway on the stock exchange.
How to Calculate the McClellan Oscillator
To get the calculation started, track Advances - Declines on a stock exchange for 19 and 39 days. Calculate a simple average for these, not exponential moving average (EMA).
Use these simple values as the Prior Day EMA values in the 19- and 39-day EMA formulas.
Calculate the 19- and 39-day EMAs.
Calculate the McClellan Oscillator value.
Now that the value has been calculated, on the next calculation use this value for the Prior Day EMA. Start calculating EMAs for the formula instead of simple averages.
If using the adjusted formula, the steps are the same, except use ANA instead of using Advances - Declines.
What Does the McClellan Oscillator Tell You?
The McClellan Oscillator is an indicator based on market breadth which technical analysts can use in conjunction with other technical tools to determine the overall state of the stock market and assess the strength of its current trend.
Since the indicator is based on all the stocks in an exchange, it is compared to the price movements of indexes that reflect that exchange, or compared to major indexes such as the S&P 500.
Positive and negative values indicate whether more stocks, on average, are advancing or declining. The indicator is positive when the 19-day EMA is above the 39-day EMA, and negative when the 19-day EMA is below the 39-day EMA.
A positive and rising indicator suggests that stocks on the exchange are being accumulated. A negative and falling indicator signals that stocks are being sold. Typically such action confirms the current trend in the index.
Crossovers from positive to negative, or vice versa, may signal the trend has changed in the index or exchange being tracked. When the indicator makes a large move, typically of 100 points or more, from negative to positive territory, that is called a breadth thrust.
It means a large number of stocks moved up after a bearish move. Since the stock market tends to rise over time, this a positive signal and may indicate that a bottom in the index is in and prices are heading higher overall.
When index prices and the indicator are moving in different directions, then the current index trend may lack strength. Bullish divergence occurs when the oscillator is rising while the index is falling. This indicates the index could head higher soon since more stocks are starting to advance.
Bearish divergence is when the index is rising and the indicator is falling. This means fewer stocks are keeping the advance going and prices may start to head lower.
Limitations of Using the McClellan Oscillator
The indicator tends to produce lots of signals. Breadth thrusts, divergence, and crossovers all occur with some frequency, but not all these signals will result in the price/index moving in the expected direction.
The indicator is prone to producing false signals and therefore should be used in conjunction with price action analysis and other technical indicators.
The indicator can also be quite choppy, moving between positive and negative territory rapidly. Such action indicates a choppy market, but this isn't evident until the indicator has made this whipsaw move a few times.
Good luck and a big thanks to Fadior!
Volume-Supported Linear Regression TrendHello Traders,
Linear Regression gives us some abilities to calculate the trend and if we combine it with volume then we may get very good results. Because if there is no volume support at up/downtrends then the trend may have a reversal soon. we also need to check the trend in different periods. With all this info, I developed Volume-Supported Linear Regression Trend script. The script checks linear regression of price and volume and then calculates trend direction and strength.
You have option to set Source, Short-Term Period and Long-Term Period. you can set them as you wish.
By default:
Close is used as "Source"
Short-Term Period is 20
Long-Term Period is 50
in following screenshot I tried to explain short term trend (for uptrend). Volume supports the trend? any volume pressure on trend? possible reversal? same idea while there is downtrend.
in following screenshot I tried to explain long term trend:
You can also check Positive/Negative Divergences to figure out possible reversals (to automate it, you can use Divergence for Many Indicators v4 , it has ability to check divergences on external indicators)
Enjoy!
Market Zone Analyzer[BullByte]Understanding the Market Zone Analyzer
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1. Purpose of the Indicator
The Market Zone Analyzer is a Pine Script™ (version 6) indicator designed to streamline market analysis on TradingView. Rather than scanning multiple separate tools, it unifies four core dimensions—trend strength, momentum, price action, and market activity—into a single, consolidated view. By doing so, it helps traders:
• Save time by avoiding manual cross-referencing of disparate signals.
• Reduce decision-making errors that can arise from juggling multiple indicators.
• Gain a clear, reliable read on whether the market is in a bullish, bearish, or sideways phase, so they can more confidently decide to enter, exit, or hold a position.
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2. Why a Trader Should Use It
• Unified View: Combines all essential market dimensions into one easy-to-read score and dashboard, eliminating the need to piece together signals manually.
• Adaptability: Automatically adjusts its internal weighting for trend, momentum, and price action based on current volatility. Whether markets are choppy or calm, the indicator remains relevant.
• Ease of Interpretation: Outputs a simple “BULLISH,” “BEARISH,” or “SIDEWAYS” label, supplemented by an intuitive on-chart dashboard and an oscillator plot that visually highlights market direction.
• Reliability Features: Built-in smoothing of the net score and hysteresis logic (requiring consecutive confirmations before flips) minimize false signals during noisy or range-bound phases.
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3. Why These Specific Indicators?
This script relies on a curated set of well-established technical tools, each chosen for its particular strength in measuring one of the four core dimensions:
1. Trend Strength:
• ADX/DMI (Average Directional Index / Directional Movement Index): Measures how strong a trend is, and whether the +DI line is above the –DI line (bullish) or vice versa (bearish).
• Moving Average Slope (Fast MA vs. Slow MA): Compares a shorter-period SMA to a longer-period SMA; if the fast MA sits above the slow MA, it confirms an uptrend, and vice versa for a downtrend.
• Ichimoku Cloud Differential (Senkou A vs. Senkou B): Provides a forward-looking view of trend direction; Senkou A above Senkou B signals bullishness, and the opposite signals bearishness.
2. Momentum:
• Relative Strength Index (RSI): Identifies overbought (above its dynamically calculated upper bound) or oversold (below its lower bound) conditions; changes in RSI often precede price reversals.
• Stochastic %K: Highlights shifts in short-term momentum by comparing closing price to the recent high/low range; values above its upper band signal bullish momentum, below its lower band signal bearish momentum.
• MACD Histogram: Measures the difference between the MACD line and its signal line; a positive histogram indicates upward momentum, a negative histogram indicates downward momentum.
3. Price Action:
• Highest High / Lowest Low (HH/LL) Range: Over a defined lookback period, this captures breakout or breakdown levels. A closing price near the recent highs (with a positive MA slope) yields a bullish score, and near the lows (with a negative MA slope) yields a bearish score.
• Heikin-Ashi Doji Detection: Uses Heikin-Ashi candles to identify indecision or continuation patterns. A small Heikin-Ashi body (doji) relative to recent volatility is scored as neutral; a larger body in the direction of the MA slope is scored bullish or bearish.
• Candle Range Measurement: Compares each candle’s high-low range against its own dynamic band (average range ± standard deviation). Large candles aligning with the prevailing trend score bullish or bearish accordingly; unusually small candles can indicate exhaustion or consolidation.
4. Market Activity:
• Bollinger Bands Width (BBW): Measures the distance between BB upper and lower bands; wide bands indicate high volatility, narrow bands indicate low volatility.
• Average True Range (ATR): Quantifies average price movement (volatility). A sudden spike in ATR suggests a volatile environment, while a contraction suggests calm.
• Keltner Channels Width (KCW): Similar to BBW but uses ATR around an EMA. Provides a second layer of volatility context, confirming or contrasting BBW readings.
• Volume (with Moving Average): Compares current volume to its moving average ± standard deviation. High volume validates strong moves; low volume signals potential lack of conviction.
By combining these tools, the indicator captures trend direction, momentum strength, price-action nuances, and overall market energy, yielding a more balanced and comprehensive assessment than any single tool alone.
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4. What Makes This Indicator Stand Out
• Multi-Dimensional Analysis: Rather than relying on a lone oscillator or moving average crossover, it simultaneously evaluates trend, momentum, price action, and activity.
• Dynamic Weighting: The relative importance of trend, momentum, and price action adjusts automatically based on real-time volatility (Market Activity State). For example, in highly volatile conditions, trend and momentum signals carry more weight; in calm markets, price action signals are prioritized.
• Stability Mechanisms:
• Smoothing: The net score is passed through a short moving average, filtering out noise, especially on lower timeframes.
• Hysteresis: Both Market Activity State and the final bullish/bearish/sideways zone require two consecutive confirmations before flipping, reducing whipsaw.
• Visual Interpretation: A fully customizable on-chart dashboard displays each sub-indicator’s value, regime, score, and comment, all color-coded. The oscillator plot changes color to reflect the current market zone (green for bullish, red for bearish, gray for sideways) and shows horizontal threshold lines at +2, 0, and –2.
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5. Recommended Timeframes
• Short-Term (5 min, 15 min): Day traders and scalpers can benefit from rapid signals, but should enable smoothing (and possibly disable hysteresis) to reduce false whipsaws.
• Medium-Term (1 h, 4 h): Swing traders find a balance between responsiveness and reliability. Less smoothing is required here, and the default parameters (e.g., ADX length = 14, RSI length = 14) perform well.
• Long-Term (Daily, Weekly): Position traders tracking major trends can disable smoothing for immediate raw readings, since higher-timeframe noise is minimal. Adjust lookback lengths (e.g., increase adxLength, rsiLength) if desired for slower signals.
Tip: If you keep smoothing off, stick to timeframes of 1 h or higher to avoid excessive signal “chatter.”
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6. How Scoring Works
A. Individual Indicator Scores
Each sub-indicator is assigned one of three discrete scores:
• +1 if it indicates a bullish condition (e.g., RSI above its dynamically calculated upper bound).
• 0 if it is neutral (e.g., RSI between upper and lower bounds).
• –1 if it indicates a bearish condition (e.g., RSI below its dynamically calculated lower bound).
Examples of individual score assignments:
• ADX/DMI:
• +1 if ADX ≥ adxThreshold and +DI > –DI (strong bullish trend)
• –1 if ADX ≥ adxThreshold and –DI > +DI (strong bearish trend)
• 0 if ADX < adxThreshold (trend strength below threshold)
• RSI:
• +1 if RSI > RSI_upperBound
• –1 if RSI < RSI_lowerBound
• 0 otherwise
• ATR (as part of Market Activity):
• +1 if ATR > (ATR_MA + stdev(ATR))
• –1 if ATR < (ATR_MA – stdev(ATR))
• 0 otherwise
Each of the four main categories shares this same +1/0/–1 logic across their sub-components.
B. Category Scores
Once each sub-indicator reports +1, 0, or –1, these are summed within their categories as follows:
• Trend Score = (ADX score) + (MA slope score) + (Ichimoku differential score)
• Momentum Score = (RSI score) + (Stochastic %K score) + (MACD histogram score)
• Price Action Score = (Highest-High/Lowest-Low score) + (Heikin-Ashi doji score) + (Candle range score)
• Market Activity Raw Score = (BBW score) + (ATR score) + (KC width score) + (Volume score)
Each category’s summed value can range between –3 and +3 (for Trend, Momentum, and Price Action), and between –4 and +4 for Market Activity raw.
C. Market Activity State and Dynamic Weight Adjustments
Rather than contributing directly to the netScore like the other three categories, Market Activity determines how much weight to assign to Trend, Momentum, and Price Action:
1. Compute Market Activity Raw Score by summing BBW, ATR, KCW, and Volume individual scores (each +1/0/–1).
2. Bucket into High, Medium, or Low Activity:
• High if raw Score ≥ 2 (volatile market).
• Low if raw Score ≤ –2 (calm market).
• Medium otherwise.
3. Apply Hysteresis (if enabled): The state only flips after two consecutive bars register the same high/low/medium label.
4. Set Category Weights:
• High Activity: Trend = 50 %, Momentum = 35 %, Price Action = 15 %.
• Low Activity: Trend = 25 %, Momentum = 20 %, Price Action = 55 %.
• Medium Activity: Use the trader’s base weight inputs (e.g., Trend = 40 %, Momentum = 30 %, Price Action = 30 % by default).
D. Calculating the Net Score
5. Normalize Base Weights (so that the sum of Trend + Momentum + Price Action always equals 100 %).
6. Determine Current Weights based on the Market Activity State (High/Medium/Low).
7. Compute Each Category’s Contribution: Multiply (categoryScore) × (currentWeight).
8. Sum Contributions to get the raw netScore (a floating-point value that can exceed ±3 when scores are strong).
9. Smooth the netScore over two bars (if smoothing is enabled) to reduce noise.
10. Apply Hysteresis to the Final Zone:
• If the smoothed netScore ≥ +2, the bar is classified as “Bullish.”
• If the smoothed netScore ≤ –2, the bar is classified as “Bearish.”
• Otherwise, it is “Sideways.”
• To prevent rapid flips, the script requires two consecutive bars in the new zone before officially changing the displayed zone (if hysteresis is on).
E. Thresholds for Zone Classification
• BULLISH: netScore ≥ +2
• BEARISH: netScore ≤ –2
• SIDEWAYS: –2 < netScore < +2
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7. Role of Volatility (Market Activity State) in Scoring
Volatility acts as a dynamic switch that shifts which category carries the most influence:
1. High Activity (Volatile):
• Detected when at least two sub-scores out of BBW, ATR, KCW, and Volume equal +1.
• The script sets Trend weight = 50 % and Momentum weight = 35 %. Price Action weight is minimized at 15 %.
• Rationale: In volatile markets, strong trending moves and momentum surges dominate, so those signals are more reliable than nuanced candle patterns.
2. Low Activity (Calm):
• Detected when at least two sub-scores out of BBW, ATR, KCW, and Volume equal –1.
• The script sets Price Action weight = 55 %, Trend = 25 %, and Momentum = 20 %.
• Rationale: In quiet, sideways markets, subtle price-action signals (breakouts, doji patterns, small-range candles) are often the best early indicators of a new move.
3. Medium Activity (Balanced):
• Raw Score between –1 and +1 from the four volatility metrics.
• Uses whatever base weights the trader has specified (e.g., Trend = 40 %, Momentum = 30 %, Price Action = 30 %).
Because volatility can fluctuate rapidly, the script employs hysteresis on Market Activity State: a new High or Low state must occur on two consecutive bars before weights actually shift. This avoids constant back-and-forth weight changes and provides more stability.
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8. Scoring Example (Hypothetical Scenario)
• Symbol: Bitcoin on a 1-hour chart.
• Market Activity: Raw volatility sub-scores show BBW (+1), ATR (+1), KCW (0), Volume (+1) → Total raw Score = +3 → High Activity.
• Weights Selected: Trend = 50 %, Momentum = 35 %, Price Action = 15 %.
• Trend Signals:
• ADX strong and +DI > –DI → +1
• Fast MA above Slow MA → +1
• Ichimoku Senkou A > Senkou B → +1
→ Trend Score = +3
• Momentum Signals:
• RSI above upper bound → +1
• MACD histogram positive → +1
• Stochastic %K within neutral zone → 0
→ Momentum Score = +2
• Price Action Signals:
• Highest High/Lowest Low check yields 0 (close not near extremes)
• Heikin-Ashi doji reading is neutral → 0
• Candle range slightly above upper bound but trend is strong, so → +1
→ Price Action Score = +1
• Compute Net Score (before smoothing):
• Trend contribution = 3 × 0.50 = 1.50
• Momentum contribution = 2 × 0.35 = 0.70
• Price Action contribution = 1 × 0.15 = 0.15
• Raw netScore = 1.50 + 0.70 + 0.15 = 2.35
• Since 2.35 ≥ +2 and hysteresis is met, the final zone is “Bullish.”
Although the netScore lands at 2.35 (Bullish), smoothing might bring it slightly below 2.00 on the first bar (e.g., 1.90), in which case the script would wait for a second consecutive reading above +2 before officially classifying the zone as Bullish (if hysteresis is enabled).
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9. Correlation Between Categories
The four categories—Trend Strength, Momentum, Price Action, and Market Activity—often reinforce or offset one another. The script takes advantage of these natural correlations:
• Bullish Alignment: If ADX is strong and pointed upward, fast MA is above slow MA, and Ichimoku is positive, that usually coincides with RSI climbing above its upper bound and the MACD histogram turning positive. In such cases, both Trend and Momentum categories generate +1 or +2. Because the Market Activity State is likely High (given the accompanying volatility), Trend and Momentum weights are at their peak, so the netScore quickly crosses into Bullish territory.
• Sideways/Consolidation: During a low-volatility, sideways phase, ADX may fall below its threshold, MAs may flatten, and RSI might hover in the neutral band. However, subtle price-action signals (like a small breakout candle or a Heikin-Ashi candle with a slight bias) can still produce a +1 in the Price Action category. If Market Activity is Low, Price Action’s weight (55 %) can carry enough influence—even if Trend and Momentum are neutral—to push the netScore out of “Sideways” into a mild bullish or bearish bias.
• Opposing Signals: When Trend is bullish but Momentum turns negative (for example, price continues up but RSI rolls over), the two scores can partially cancel. Market Activity may remain Medium, in which case the netScore lingers near zero (Sideways). The trader can then wait for either a clearer momentum shift or a fresh price-action breakout before committing.
By dynamically recognizing these correlations and adjusting weights, the indicator ensures that:
• When Trend and Momentum align (and volatility supports it), the netScore leaps strongly into Bullish or Bearish.
• When Trend is neutral but Price Action shows an early move in a low-volatility environment, Price Action’s extra weight in the Low Activity State can still produce actionable signals.
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10. Market Activity State & Its Role (Detailed)
The Market Activity State is not a direct category score—it is an overarching context setter for how heavily to trust Trend, Momentum, or Price Action. Here’s how it is derived and applied:
1. Calculate Four Volatility Sub-Scores:
• BBW: Compare the current band width to its own moving average ± standard deviation. If BBW > (BBW_MA + stdev), assign +1 (high volatility); if BBW < (BBW_MA × 0.5), assign –1 (low volatility); else 0.
• ATR: Compare ATR to its moving average ± standard deviation. A spike above the upper threshold is +1; a contraction below the lower threshold is –1; otherwise 0.
• KCW: Same logic as ATR but around the KCW mean.
• Volume: Compare current volume to its volume MA ± standard deviation. Above the upper threshold is +1; below the lower threshold is –1; else 0.
2. Sum Sub-Scores → Raw Market Activity Score: Range between –4 and +4.
3. Assign Market Activity State:
• High Activity: Raw Score ≥ +2 (at least two volatility metrics are strongly spiking).
• Low Activity: Raw Score ≤ –2 (at least two metrics signal unusually low volatility or thin volume).
• Medium Activity: Raw Score is between –1 and +1 inclusive.
4. Hysteresis for Stability:
• If hysteresis is enabled, a new state only takes hold after two consecutive bars confirm the same High, Medium, or Low label.
• This prevents the Market Activity State from bouncing around when volatility is on the fence.
5. Set Category Weights Based on Activity State:
• High Activity: Trend = 50 %, Momentum = 35 %, Price Action = 15 %.
• Low Activity: Trend = 25 %, Momentum = 20 %, Price Action = 55 %.
• Medium Activity: Use trader’s base weights (e.g., Trend = 40 %, Momentum = 30 %, Price Action = 30 %).
6. Impact on netScore: Because category scores (–3 to +3) multiply by these weights, High Activity amplifies the effect of strong Trend and Momentum scores; Low Activity amplifies the effect of Price Action.
7. Market Context Tooltip: The dashboard includes a tooltip summarizing the current state—e.g., “High activity, trend and momentum prioritized,” “Low activity, price action prioritized,” or “Balanced market, all categories considered.”
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11. Category Weights: Base vs. Dynamic
Traders begin by specifying base weights for Trend Strength, Momentum, and Price Action that sum to 100 %. These apply only when volatility is in the Medium band. Once volatility shifts:
• High Volatility Overrides:
• Trend jumps from its base (e.g., 40 %) to 50 %.
• Momentum jumps from its base (e.g., 30 %) to 35 %.
• Price Action is reduced to 15 %.
Example: If base weights were Trend = 40 %, Momentum = 30 %, Price Action = 30 %, then in High Activity they become 50/35/15. A Trend score of +3 now contributes 3 × 0.50 = +1.50 to netScore; a Momentum +2 contributes 2 × 0.35 = +0.70. In total, Trend + Momentum can easily push netScore above the +2 threshold on its own.
• Low Volatility Overrides:
• Price Action leaps from its base (30 %) to 55 %.
• Trend falls to 25 %, Momentum falls to 20 %.
Why? When markets are quiet, subtle candle breakouts, doji patterns, and small-range expansions tend to foreshadow the next swing more effectively than raw trend readings. A Price Action score of +3 in this state contributes 3 × 0.55 = +1.65, which can carry the netScore toward +2—even if Trend and Momentum are neutral or only mildly positive.
Because these weight shifts happen only after two consecutive bars confirm a High or Low state (if hysteresis is on), the indicator avoids constantly flipping its emphasis during borderline volatility phases.
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12. Dominant Category Explained
Within the dashboard, a label such as “Trend Dominant,” “Momentum Dominant,” or “Price Action Dominant” appears when one category’s absolute weighted contribution to netScore is the largest. Concretely:
• Compute each category’s weighted contribution = (raw category score) × (current weight).
• Compare the absolute values of those three contributions.
• The category with the highest absolute value is flagged as Dominant for that bar.
Why It Matters:
• Momentum Dominant: Indicates that the combined force of RSI, Stochastic, and MACD (after weighting) is pushing netScore farther than either Trend or Price Action. In practice, it means that short-term sentiment and speed of change are the primary drivers right now, so traders should watch for continued momentum signals before committing to a trade.
• Trend Dominant: Means ADX, MA slope, and Ichimoku (once weighted) outweigh the other categories. This suggests a strong directional move is in place; trend-following entries or confirming pullbacks are likely to succeed.
• Price Action Dominant: Occurs when breakout/breakdown patterns, Heikin-Ashi candle readings, and range expansions (after weighting) are the most influential. This often happens in calmer markets, where subtle shifts in candle structure can foreshadow bigger moves.
By explicitly calling out which category is carrying the most weight at any moment, the dashboard gives traders immediate insight into why the netScore is tilting toward bullish, bearish, or sideways.
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13. Oscillator Plot: How to Read It
The “Net Score” oscillator sits below the dashboard and visually displays the smoothed netScore as a line graph. Key features:
1. Value Range: In normal conditions it oscillates roughly between –3 and +3, but extreme confluences can push it outside that range.
2. Horizontal Threshold Lines:
• +2 Line (Bullish threshold)
• 0 Line (Neutral midline)
• –2 Line (Bearish threshold)
3. Zone Coloring:
• Green Background (Bullish Zone): When netScore ≥ +2.
• Red Background (Bearish Zone): When netScore ≤ –2.
• Gray Background (Sideways Zone): When –2 < netScore < +2.
4. Dynamic Line Color:
• The plotted netScore line itself is colored green in a Bullish Zone, red in a Bearish Zone, or gray in a Sideways Zone, creating an immediate visual cue.
Interpretation Tips:
• Crossing Above +2: Signals a strong enough combined trend/momentum/price-action reading to classify as Bullish. Many traders wait for a clear crossing plus a confirmation candle before entering a long position.
• Crossing Below –2: Indicates a strong Bearish signal. Traders may consider short or exit strategies.
• Rising Slope, Even Below +2: If netScore climbs steadily from neutral toward +2, it demonstrates building bullish momentum.
• Divergence: If price makes a higher high but the oscillator fails to reach a new high, it can warn of weakening momentum and a potential reversal.
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14. Comments and Their Necessity
Every sub-indicator (ADX, MA slope, Ichimoku, RSI, Stochastic, MACD, HH/LL, Heikin-Ashi, Candle Range, BBW, ATR, KCW, Volume) generates a short comment that appears in the detailed dashboard. Examples:
• “Strong bullish trend” or “Strong bearish trend” for ADX/DMI
• “Fast MA above slow MA” or “Fast MA below slow MA” for MA slope
• “RSI above dynamic threshold” or “RSI below dynamic threshold” for RSI
• “MACD histogram positive” or “MACD histogram negative” for MACD Hist
• “Price near highs” or “Price near lows” for HH/LL checks
• “Bullish Heikin Ashi” or “Bearish Heikin Ashi” for HA Doji scoring
• “Large range, trend confirmed” or “Small range, trend contradicted” for Candle Range
Additionally, the top-row comment for each category is:
• Trend: “Highly Bullish,” “Highly Bearish,” or “Neutral Trend.”
• Momentum: “Strong Momentum,” “Weak Momentum,” or “Neutral Momentum.”
• Price Action: “Bullish Action,” “Bearish Action,” or “Neutral Action.”
• Market Activity: “Volatile Market,” “Calm Market,” or “Stable Market.”
Reasons for These Comments:
• Transparency: Shows exactly how each sub-indicator contributed to its category score.
• Education: Helps traders learn why a category is labeled bullish, bearish, or neutral, building intuition over time.
• Customization: If, for example, the RSI comment says “RSI neutral” despite an impending trend shift, a trader might choose to adjust RSI length or thresholds.
In the detailed dashboard, hovering over each comment cell also reveals a tooltip with additional context (e.g., “Fast MA above slow MA” or “Senkou A above Senkou B”), helping traders understand the precise rule behind that +1, 0, or –1 assignment.
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15. Real-Life Example (Consolidated)
• Instrument & Timeframe: Bitcoin (BTCUSD), 1-hour chart.
• Current Market Activity: BBW and ATR both spike (+1 each), KCW is moderately high (+1), but volume is only neutral (0) → Raw Market Activity Score = +2 → State = High Activity (after two bars, if hysteresis is on).
• Category Weights Applied: Trend = 50 %, Momentum = 35 %, Price Action = 15 %.
• Trend Sub-Scores:
1. ADX = 25 (above threshold 20) with +DI > –DI → +1.
2. Fast MA (20-period) sits above Slow MA (50-period) → +1.
3. Ichimoku: Senkou A > Senkou B → +1.
→ Trend Score = +3.
• Momentum Sub-Scores:
4. RSI = 75 (above its moving average +1 stdev) → +1.
5. MACD histogram = +0.15 → +1.
6. Stochastic %K = 50 (mid-range) → 0.
→ Momentum Score = +2.
• Price Action Sub-Scores:
7. Price is not within 1 % of the 20-period high/low and slope = positive → 0.
8. Heikin-Ashi body is slightly larger than stdev over last 5 bars with haClose > haOpen → +1.
9. Candle range is just above its dynamic upper bound but trend is already captured, so → +1.
→ Price Action Score = +2.
• Calculate netScore (before smoothing):
• Trend contribution = 3 × 0.50 = 1.50
• Momentum contribution = 2 × 0.35 = 0.70
• Price Action contribution = 2 × 0.15 = 0.30
• Raw netScore = 1.50 + 0.70 + 0.30 = 2.50 → Immediately classified as Bullish.
• Oscillator & Dashboard Output:
• The oscillator line crosses above +2 and turns green.
• Dashboard displays:
• Trend Regime “BULLISH,” Trend Score = 3, Comment = “Highly Bullish.”
• Momentum Regime “BULLISH,” Momentum Score = 2, Comment = “Strong Momentum.”
• Price Action Regime “BULLISH,” Price Action Score = 2, Comment = “Bullish Action.”
• Market Activity State “High,” Comment = “Volatile Market.”
• Weights: Trend 50 %, Momentum 35 %, Price Action 15 %.
• Dominant Category: Trend (because 1.50 > 0.70 > 0.30).
• Overall Score: 2.50, posCount = (three +1s in Trend) + (two +1s in Momentum) + (two +1s in Price Action) = 7 bullish signals, negCount = 0.
• Final Zone = “BULLISH.”
• The trader sees that both Trend and Momentum are reinforcing each other under high volatility. They might wait one more candle for confirmation but already have strong evidence to consider a long.
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• .
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Disclaimer
This indicator is strictly a technical analysis tool and does not constitute financial advice. All trading involves risk, including potential loss of capital. Past performance is not indicative of future results. Traders should:
• Always backtest the “Market Zone Analyzer ” on their chosen symbols and timeframes before committing real capital.
• Combine this tool with sound risk management, position sizing, and, if possible, fundamental analysis.
• Understand that no indicator is foolproof; always be prepared for unexpected market moves.
Goodluck
-BullByte!
---
Advanced Petroleum Market Model (APMM)Advanced Petroleum Market Model (APMM): A Multi-Factor Fundamental Analysis Framework for Oil Market Assessment
## 1. Introduction
The petroleum market represents one of the most complex and globally significant commodity markets, characterized by intricate supply-demand dynamics, geopolitical influences, and substantial price volatility (Hamilton, 2009). Traditional fundamental analysis approaches often struggle to synthesize the multitude of relevant indicators into actionable insights due to data heterogeneity, temporal misalignment, and subjective weighting schemes (Baumeister & Kilian, 2016).
The Advanced Petroleum Market Model addresses these limitations through a systematic, quantitative approach that integrates 16 verified fundamental indicators across five critical market dimensions. The model builds upon established financial engineering principles while incorporating petroleum-specific market dynamics and adaptive learning mechanisms.
## 2. Theoretical Framework
### 2.1 Market Efficiency and Information Integration
The model operates under the assumption of semi-strong market efficiency, where fundamental information is gradually incorporated into prices with varying degrees of lag (Fama, 1970). The petroleum market's unique characteristics, including storage costs, transportation constraints, and geopolitical risk premiums, create opportunities for fundamental analysis to provide predictive value (Kilian, 2009).
### 2.2 Multi-Factor Asset Pricing Theory
Drawing from Ross's (1976) Arbitrage Pricing Theory, the model treats petroleum prices as driven by multiple systematic risk factors. The five-factor decomposition (Supply, Inventory, Demand, Trade, Sentiment) represents economically meaningful sources of systematic risk in petroleum markets (Chen et al., 1986).
## 3. Methodology
### 3.1 Data Sources and Quality Framework
The model integrates 16 fundamental indicators sourced from verified TradingView economic data feeds:
Supply Indicators:
- US Oil Production (ECONOMICS:USCOP)
- US Oil Rigs Count (ECONOMICS:USCOR)
- API Crude Runs (ECONOMICS:USACR)
Inventory Indicators:
- US Crude Stock Changes (ECONOMICS:USCOSC)
- Cushing Stocks (ECONOMICS:USCCOS)
- API Crude Stocks (ECONOMICS:USCSC)
- API Gasoline Stocks (ECONOMICS:USGS)
- API Distillate Stocks (ECONOMICS:USDS)
Demand Indicators:
- Refinery Crude Runs (ECONOMICS:USRCR)
- Gasoline Production (ECONOMICS:USGPRO)
- Distillate Production (ECONOMICS:USDFP)
- Industrial Production Index (FRED:INDPRO)
Trade Indicators:
- US Crude Imports (ECONOMICS:USCOI)
- US Oil Exports (ECONOMICS:USOE)
- API Crude Imports (ECONOMICS:USCI)
- Dollar Index (TVC:DXY)
Sentiment Indicators:
- Oil Volatility Index (CBOE:OVX)
### 3.2 Data Quality Monitoring System
Following best practices in quantitative finance (Lopez de Prado, 2018), the model implements comprehensive data quality monitoring:
Data Quality Score = Σ(Individual Indicator Validity) / Total Indicators
Where validity is determined by:
- Non-null data availability
- Positive value validation
- Temporal consistency checks
### 3.3 Statistical Normalization Framework
#### 3.3.1 Z-Score Normalization
The model employs robust Z-score normalization as established by Sharpe (1994) for cross-indicator comparability:
Z_i,t = (X_i,t - μ_i) / σ_i
Where:
- X_i,t = Raw value of indicator i at time t
- μ_i = Sample mean of indicator i
- σ_i = Sample standard deviation of indicator i
Z-scores are capped at ±3 to mitigate outlier influence (Tukey, 1977).
#### 3.3.2 Percentile Rank Transformation
For intuitive interpretation, Z-scores are converted to percentile ranks following the methodology of Conover (1999):
Percentile_Rank = (Number of values < current_value) / Total_observations × 100
### 3.4 Exponential Smoothing Framework
Signal smoothing employs exponential weighted moving averages (Brown, 1963) with adaptive alpha parameter:
S_t = α × X_t + (1-α) × S_{t-1}
Where α = 2/(N+1) and N represents the smoothing period.
### 3.5 Dynamic Threshold Optimization
The model implements adaptive thresholds using Bollinger Band methodology (Bollinger, 1992):
Dynamic_Threshold = μ ± (k × σ)
Where k is the threshold multiplier adjusted for market volatility regime.
### 3.6 Composite Score Calculation
The fundamental score integrates component scores through weighted averaging:
Fundamental_Score = Σ(w_i × Score_i × Quality_i)
Where:
- w_i = Normalized component weight
- Score_i = Component fundamental score
- Quality_i = Data quality adjustment factor
## 4. Implementation Architecture
### 4.1 Adaptive Parameter Framework
The model incorporates regime-specific adjustments based on market volatility:
Volatility_Regime = σ_price / μ_price × 100
High volatility regimes (>25%) trigger enhanced weighting for inventory and sentiment components, reflecting increased market sensitivity to supply disruptions and psychological factors.
### 4.2 Data Synchronization Protocol
Given varying publication frequencies (daily, weekly, monthly), the model employs forward-fill synchronization to maintain temporal alignment across all indicators.
### 4.3 Quality-Adjusted Scoring
Component scores are adjusted for data quality to prevent degraded inputs from contaminating the composite signal:
Adjusted_Score = Raw_Score × Quality_Factor + 50 × (1 - Quality_Factor)
This formulation ensures that poor-quality data reverts toward neutral (50) rather than contributing noise.
## 5. Usage Guidelines and Best Practices
### 5.1 Configuration Recommendations
For Short-term Analysis (1-4 weeks):
- Lookback Period: 26 weeks
- Smoothing Length: 3-5 periods
- Confidence Period: 13 weeks
- Increase inventory and sentiment weights
For Medium-term Analysis (1-3 months):
- Lookback Period: 52 weeks
- Smoothing Length: 5-8 periods
- Confidence Period: 26 weeks
- Balanced component weights
For Long-term Analysis (3+ months):
- Lookback Period: 104 weeks
- Smoothing Length: 8-12 periods
- Confidence Period: 52 weeks
- Increase supply and demand weights
### 5.2 Signal Interpretation Framework
Bullish Signals (Score > 70):
- Fundamental conditions favor price appreciation
- Consider long positions or reduced short exposure
- Monitor for trend confirmation across multiple timeframes
Bearish Signals (Score < 30):
- Fundamental conditions suggest price weakness
- Consider short positions or reduced long exposure
- Evaluate downside protection strategies
Neutral Range (30-70):
- Mixed fundamental environment
- Favor range-bound or volatility strategies
- Wait for clearer directional signals
### 5.3 Risk Management Considerations
1. Data Quality Monitoring: Continuously monitor the data quality dashboard. Scores below 75% warrant increased caution.
2. Regime Awareness: Adjust position sizing based on volatility regime indicators. High volatility periods require reduced exposure.
3. Correlation Analysis: Monitor correlation with crude oil prices to validate model effectiveness.
4. Fundamental-Technical Divergence: Pay attention when fundamental signals diverge from technical indicators, as this may signal regime changes.
### 5.4 Alert System Optimization
Configure alerts conservatively to avoid false signals:
- Set alert threshold at 75+ for high-confidence signals
- Enable data quality warnings to maintain system integrity
- Use trend reversal alerts for early regime change detection
## 6. Model Validation and Performance Metrics
### 6.1 Statistical Validation
The model's statistical robustness is ensured through:
- Out-of-sample testing protocols
- Rolling window validation
- Bootstrap confidence intervals
- Regime-specific performance analysis
### 6.2 Economic Validation
Fundamental accuracy is validated against:
- Energy Information Administration (EIA) official reports
- International Energy Agency (IEA) market assessments
- Commercial inventory data verification
## 7. Limitations and Considerations
### 7.1 Model Limitations
1. Data Dependency: Model performance is contingent on data availability and quality from external sources.
2. US Market Focus: Primary data sources are US-centric, potentially limiting global applicability.
3. Lag Effects: Some fundamental indicators exhibit publication lags that may delay signal generation.
4. Regime Shifts: Structural market changes may require model recalibration.
### 7.2 Market Environment Considerations
The model is optimized for normal market conditions. During extreme events (e.g., geopolitical crises, pandemics), additional qualitative factors should be considered alongside quantitative signals.
## References
Baumeister, C., & Kilian, L. (2016). Forty years of oil price fluctuations: Why the price of oil may still surprise us. *Journal of Economic Perspectives*, 30(1), 139-160.
Bollinger, J. (1992). *Bollinger on Bollinger Bands*. McGraw-Hill.
Brown, R. G. (1963). *Smoothing, Forecasting and Prediction of Discrete Time Series*. Prentice-Hall.
Chen, N. F., Roll, R., & Ross, S. A. (1986). Economic forces and the stock market. *Journal of Business*, 59(3), 383-403.
Conover, W. J. (1999). *Practical Nonparametric Statistics* (3rd ed.). John Wiley & Sons.
Fama, E. F. (1970). Efficient capital markets: A review of theory and empirical work. *Journal of Finance*, 25(2), 383-417.
Hamilton, J. D. (2009). Understanding crude oil prices. *Energy Journal*, 30(2), 179-206.
Kilian, L. (2009). Not all oil price shocks are alike: Disentangling demand and supply shocks in the crude oil market. *American Economic Review*, 99(3), 1053-1069.
Lopez de Prado, M. (2018). *Advances in Financial Machine Learning*. John Wiley & Sons.
Ross, S. A. (1976). The arbitrage theory of capital asset pricing. *Journal of Economic Theory*, 13(3), 341-360.
Sharpe, W. F. (1994). The Sharpe ratio. *Journal of Portfolio Management*, 21(1), 49-58.
Tukey, J. W. (1977). *Exploratory Data Analysis*. Addison-Wesley.
