Pro Momentum CalculatorThe Pro Momentum Calculator Indicator is a tool for traders seeking to gauge market momentum and predict future price movements. It achieves this by counting consecutive candle periods above or below a chosen Simple Moving Average (SMA) and then providing a percentage-based probability for the direction of the next candle.
Here's how this principle works:
1. Counting Consecutive Periods: The indicator continuously tracks whether the closing prices of candles are either above or below the chosen SMA.
- When closing prices are above the SMA, it counts consecutive periods as "green" or indicating potential upward momentum.
- When closing prices are below the SMA, it counts consecutive periods as "red" or suggesting potential downward momentum.
2. Assessing Momentum: By monitoring these consecutive periods, the indicator assesses the strength and duration of the current market trend.
This is important information for traders looking to understand the market's behavior.
3. Predicting the Next Candle: Based on the historical data of consecutive green and red periods, the indicator calculates a percentage probability for the direction of the next candle:
- If there have been more consecutive green periods, it suggests a higher likelihood of the next candle being green (indicating a potential upward movement).
- If there have been more consecutive red periods, it suggests a higher likelihood of the next candle being red (indicating a potential downward movement).
The Pro Momentum Calculator indicator's versatility makes it suitable for a wide range of financial markets, including stocks, Forex, indices, commodities, cryptocurrencies...
在腳本中搜尋"momentum"
Slight Swing Momentum Strategy.Introduction:
The Swing Momentum Strategy is a quantitative trading strategy designed to capture mid-term opportunities in the financial markets by combining swing trading principles with momentum indicators. It utilizes a combination of technical indicators, including moving averages, crossover signals, and volume analysis, to generate buy and sell signals. The strategy aims to identify market trends and capitalize on price momentum for profit generation.
Highlights:
The strategy offers several key highlights that make it unique and potentially attractive to traders:
Swing Trading with Momentum: The strategy combines the principles of swing trading, which aim to capture short-to-medium-term price swings, with momentum indicators that help identify strong price trends and potential breakout opportunities.
Technical Indicator Optimization: The strategy utilizes a selection of optimized technical indicators, including moving averages and crossover signals, to filter out the noise and focus on high-probability trading setups. This optimization enhances the strategy's ability to identify favourable entry and exit points.
Risk Management: The strategy incorporates risk management techniques, such as position sizing based on equity and dynamic stop loss levels, to manage risk exposure and protect capital. This helps to minimize drawdowns and preserve profits.
Buy Condition:
The buy condition in the strategy is determined by a combination of factors, including A1, A2, A3, XG, and weeklySlope. Let's break it down:
A1 Condition: The A1 condition checks for specific price relationships. It verifies that the ratio of the highest price to the closing price is less than 1.03, the ratio of the opening price to the lowest price is less than 1.03, and the ratio of the highest price to the previous day's closing price is greater than 1.06. This condition looks for a specific pattern indicating potential bullish momentum.
A2 Condition: The A2 condition checks for price relationships related to the closing price. It verifies that the ratio of the closing price to the opening price is greater than 1.05 or that the ratio of the closing price to the previous day's closing price is greater than 1.05. This condition looks for signs of upward price movement and momentum.
A3 Condition: The A3 condition focuses on volume. It checks if the current volume crosses above the highest volume over the last 60 periods. This condition aims to identify increased buying interest and potentially confirms the strength of the potential upward price movement.
XG Condition: The XG condition combines the A1 and A2 conditions and checks if they are true for both the current and previous bars. It also verifies that the ratio of the closing price to the 5-period EMA crosses above the 9-period SMA of the same ratio. This condition helps identify potential buy signals when multiple factors align, indicating a strong bullish momentum and potential entry point.
Weekly Trend Factor: The weekly slope condition calculates the slope of the 50-period SMA over a weekly timeframe. It checks if the slope is positive, indicating an overall upward trend on a weekly basis. This condition provides additional confirmation that the stock is in an upward trend.
When all of these conditions align, the buy condition is triggered, indicating a favourable time to enter a long position.
Sell Condition:
The sell condition is relatively straightforward in the strategy:
Sell Signal: The sell condition simply checks if the closing price crosses below the 10-period EMA. When this condition is met, it indicates a potential reversal or weakening of the upward price momentum, and a sell signal is generated.
Backtest Outcome:
The strategy was backtested over the period from January 22nd, 1999 to May 3rd, 2023, using daily candlestick charts for the NASDAQ: NVDA. The strategy used an initial capital of 1,000,000 USD, The order quantity is defined as 10% of the equity. The strategy allows for pyramiding with 1 order, and the transaction fee is set at 0.03% per trade. Here are the key outcomes of the backtest:
Net Profit: 539,595.84 USD, representing a return of 53.96%.
Percent Profitable: 48.82%
Total Closed Trades: 127
Profit Factor: 2.331
Max Drawdown: 68,422.70 USD
Average Trade: 4,248.79 USD
Average Number of Bars in Trades: 11, indicating the average duration of the trades.
Conclusion:
In conclusion, the Swing Momentum Strategy is a quantitative trading approach that combines swing trading principles with momentum indicators to identify and capture mid term trading opportunities. The strategy has demonstrated promising results during backtesting, including a significant net profit and a favourable profit factor.
BTC SOPR Momentum: OnchainThis Onchin metric is based on SOPR data
Use this metric on daily and weekly timeframes:
SOPR:
The Spent Output Profit Ratio (SOPR) is computed by dividing the realized value (in USD) divided by the value at creation (USD) of a spent output. Or simply: price sold / price paid. Renato Shirakashi created this metric. When SOPR > 1, it means that the owners of the spent outputs are in profit at the time of the transaction; otherwise, they are at a loss. You can find "SOPR" in tradingview indicators
BTC SOPR Momentum: Onchain
This metric is based on SOPR Momentum. I made some changes to it so that its momentum can be checked.
Interpretation:
If the indicator is above the gray level of resistance/support, bitcoin has an uptrend and Bullish bias
If the indicator is below the resistance/ support level, bitcoin has a downtrend and Bearish Bias
Crossup the gray level is a long signal
Cross-down the gray level is a shorts signal
Entering and exit of the indicator to the overhigh area means creating a top
Entering and leaving the indicator to the overflow area means creating a bottom
MTF Signal XpertMTF Signal Xpert – Detailed Description
Overview:
MTF Signal Xpert is a proprietary, open‑source trading signal indicator that fuses multiple technical analysis methods into one cohesive strategy. Developed after rigorous backtesting and extensive research, this advanced tool is designed to deliver clear BUY and SELL signals by analyzing trend, momentum, and volatility across various timeframes. Its integrated approach not only enhances signal reliability but also incorporates dynamic risk management, helping traders protect their capital while navigating complex market conditions.
Detailed Explanation of How It Works:
Trend Detection via Moving Averages
Dual Moving Averages:
MTF Signal Xpert computes two moving averages—a fast MA and a slow MA—with the flexibility to choose from Simple (SMA), Exponential (EMA), or Hull (HMA) methods. This dual-MA system helps identify the prevailing market trend by contrasting short-term momentum with longer-term trends.
Crossover Logic:
A BUY signal is initiated when the fast MA crosses above the slow MA, coupled with the condition that the current price is above the lower Bollinger Band. This suggests that the market may be emerging from a lower price region. Conversely, a SELL signal is generated when the fast MA crosses below the slow MA and the price is below the upper Bollinger Band, indicating potential bearish pressure.
Recent Crossover Confirmation:
To ensure that signals reflect current market dynamics, the script tracks the number of bars since the moving average crossover event. Only crossovers that occur within a user-defined “candle confirmation” period are considered, which helps filter out outdated signals and improves overall signal accuracy.
Volatility and Price Extremes with Bollinger Bands
Calculation of Bands:
Bollinger Bands are calculated using a 20‑period simple moving average as the central basis, with the upper and lower bands derived from a standard deviation multiplier. This creates dynamic boundaries that adjust according to recent market volatility.
Signal Reinforcement:
For BUY signals, the condition that the price is above the lower Bollinger Band suggests an undervalued market condition, while for SELL signals, the price falling below the upper Bollinger Band reinforces the bearish bias. This volatility context adds depth to the moving average crossover signals.
Momentum Confirmation Using Multiple Oscillators
RSI (Relative Strength Index):
The RSI is computed over 14 periods to determine if the market is in an overbought or oversold state. Only readings within an optimal range (defined by user inputs) validate the signal, ensuring that entries are made during balanced conditions.
MACD (Moving Average Convergence Divergence):
The MACD line is compared with its signal line to assess momentum. A bullish scenario is confirmed when the MACD line is above the signal line, while a bearish scenario is indicated when it is below, thus adding another layer of confirmation.
Awesome Oscillator (AO):
The AO measures the difference between short-term and long-term simple moving averages of the median price. Positive AO values support BUY signals, while negative values back SELL signals, offering additional momentum insight.
ADX (Average Directional Index):
The ADX quantifies trend strength. MTF Signal Xpert only considers signals when the ADX value exceeds a specified threshold, ensuring that trades are taken in strongly trending markets.
Optional Stochastic Oscillator:
An optional stochastic oscillator filter can be enabled to further refine signals. It checks for overbought conditions (supporting SELL signals) or oversold conditions (supporting BUY signals), thus reducing ambiguity.
Multi-Timeframe Verification
Higher Timeframe Filter:
To align short-term signals with broader market trends, the script calculates an EMA on a higher timeframe as specified by the user. This multi-timeframe approach helps ensure that signals on the primary chart are consistent with the overall trend, thereby reducing false signals.
Dynamic Risk Management with ATR
ATR-Based Calculations:
The Average True Range (ATR) is used to measure current market volatility. This value is multiplied by a user-defined factor to dynamically determine stop loss (SL) and take profit (TP) levels, adapting to changing market conditions.
Visual SL/TP Markers:
The calculated SL and TP levels are plotted on the chart as distinct colored dots, enabling traders to quickly identify recommended exit points.
Optional Trailing Stop:
An optional trailing stop feature is available, which adjusts the stop loss as the trade moves favorably, helping to lock in profits while protecting against sudden reversals.
Risk/Reward Ratio Calculation:
MTF Signal Xpert computes a risk/reward ratio based on the dynamic SL and TP levels. This quantitative measure allows traders to assess whether the potential reward justifies the risk associated with a trade.
Condition Weighting and Signal Scoring
Binary Condition Checks:
Each technical condition—ranging from moving average crossovers, Bollinger Band positioning, and RSI range to MACD, AO, ADX, and volume filters—is assigned a binary score (1 if met, 0 if not).
Cumulative Scoring:
These individual scores are summed to generate cumulative bullish and bearish scores, quantifying the overall strength of the signal and providing traders with an objective measure of its viability.
Detailed Signal Explanation:
A comprehensive explanation string is generated, outlining which conditions contributed to the current BUY or SELL signal. This explanation is displayed on an on‑chart dashboard, offering transparency and clarity into the signal generation process.
On-Chart Visualizations and Debug Information
Chart Elements:
The indicator plots all key components—moving averages, Bollinger Bands, SL and TP markers—directly on the chart, providing a clear visual framework for understanding market conditions.
Combined Dashboard:
A dedicated dashboard displays key metrics such as RSI, ADX, and the bullish/bearish scores, alongside a detailed explanation of the current signal. This consolidated view allows traders to quickly grasp the underlying logic.
Debug Table (Optional):
For advanced users, an optional debug table is available. This table breaks down each individual condition, indicating which criteria were met or not met, thus aiding in further analysis and strategy refinement.
Mashup Justification and Originality
MTF Signal Xpert is more than just an aggregation of existing indicators—it is an original synthesis designed to address real-world trading complexities. Here’s how its components work together:
Integrated Trend, Volatility, and Momentum Analysis:
By combining moving averages, Bollinger Bands, and multiple oscillators (RSI, MACD, AO, ADX, and an optional stochastic), the indicator captures diverse market dynamics. Each component reinforces the others, reducing noise and filtering out false signals.
Multi-Timeframe Analysis:
The inclusion of a higher timeframe filter aligns short-term signals with longer-term trends, enhancing overall reliability and reducing the potential for contradictory signals.
Adaptive Risk Management:
Dynamic stop loss and take profit levels, determined using ATR, ensure that the risk management strategy adapts to current market conditions. The optional trailing stop further refines this approach, protecting profits as the market evolves.
Quantitative Signal Scoring:
The condition weighting system provides an objective measure of signal strength, giving traders clear insight into how each technical component contributes to the final decision.
How to Use MTF Signal Xpert:
Input Customization:
Adjust the moving average type and period settings, ATR multipliers, and oscillator thresholds to align with your trading style and the specific market conditions.
Enable or disable the optional stochastic oscillator and trailing stop based on your preference.
Interpreting the Signals:
When a BUY or SELL signal appears, refer to the on‑chart dashboard, which displays key metrics (e.g., RSI, ADX, bullish/bearish scores) along with a detailed breakdown of the conditions that triggered the signal.
Review the SL and TP markers on the chart to understand the associated risk/reward setup.
Risk Management:
Use the dynamically calculated stop loss and take profit levels as guidelines for setting your exit points.
Evaluate the provided risk/reward ratio to ensure that the potential reward justifies the risk before entering a trade.
Debugging and Verification:
Advanced users can enable the debug table to see a condition-by-condition breakdown of the signal generation process, helping refine the strategy and deepen understanding of market dynamics.
Disclaimer:
MTF Signal Xpert is intended for educational and analytical purposes only. Although it is based on robust technical analysis methods and has undergone extensive backtesting, past performance is not indicative of future results. Traders should employ proper risk management and adjust the settings to suit their financial circumstances and risk tolerance.
MTF Signal Xpert represents a comprehensive, original approach to trading signal generation. By blending trend detection, volatility assessment, momentum analysis, multi-timeframe alignment, and adaptive risk management into one integrated system, it provides traders with actionable signals and the transparency needed to understand the logic behind them.
MTF SqzMom [tradeviZion]Credits:
John Carter for creating the TTM Squeeze and TTM Squeeze Pro.
Lazybear for the original interpretation of the TTM Squeeze: Squeeze Momentum Indicator.
Makit0 for evolving Lazybear's script by incorporating TTM Squeeze Pro upgrades – Squeeze PRO Arrows.
MTF SqzMom - Multi-Timeframe Squeeze & Momentum Tool
MTF SqzMom is a tool designed to help traders easily monitor squeeze and momentum signals across multiple timeframes in a simple, organized format. Built using Pine Script 5, it ensures that data remains consistent, even when switching between different time intervals on the chart.
Key Features:
Multi-Timeframe Monitoring: Track squeeze and momentum signals across various timeframes, all in one view. This includes key timeframes like 1-minute, 5-minute, hourly, and daily.
Dynamic Table Display: A color-coded table that automatically adjusts based on the selected timeframes, offering a clear view of market conditions.
Alerts for Key Market Events: Get notifications when a squeeze starts or fires across your chosen timeframes, so you can stay informed without needing to monitor the chart continuously.
Customizable Appearance: Tailor the look of the table by selecting colors for squeeze levels and momentum shifts, and choose the best position on your chart for easy access.
How It Works:
MTF SqzMom is based on the concept of the squeeze, which signals periods of lower volatility where price breakouts may occur. The tool tracks this by monitoring the contraction of Bollinger Bands within Keltner Channels. Along with this, it provides momentum analysis to help you gauge the potential direction of the market after a squeeze.
Squeeze Conditions: The script tracks four levels of squeeze conditions (no squeeze, low, mid, and high), each represented by a different color in the table.
Momentum Analysis: Momentum is visually represented by colors indicating four stages: up increasing, up decreasing, down increasing, and down decreasing. This color coding helps you quickly assess whether the market is gaining or losing momentum.
Using Alerts:
You can enable two types of alerts: when a squeeze starts (indicating consolidation) and when a squeeze fires (indicating a breakout). These alerts cover all timeframes you’ve selected, so you never miss important signals.
How to Set It Up:
1. Enable Alerts in Settings: Turn on "Alert for Squeeze Start" and "Alert for Squeeze Fire" in the settings.
2. Add Alerts to Your Chart:
Click the three dots next to the indicator name.
Select "Add alert on tradeviZion - MTF SqzMom."
3. Customize and Save: Adjust alert options, choose your notification type, and click "Create."
Why Use MTF SqzMom ?
Consistent Data: The tool ensures that squeeze and momentum data remain consistent, even when you switch between chart intervals.
Real-Time Alerts: Stay updated with alerts for squeeze conditions without needing to constantly watch the chart.
Simple to Use, Customizable to Fit: You can easily adjust the table’s look and choose the timeframes and colors that best suit your trading style.
Acknowledgment:
While this tool builds on the TTM Squeeze concept developed by John Carter of Simpler Trading, it offers added flexibility through multi-timeframe analysis, alerts, and customizability to make monitoring market conditions more accessible.
Trend Tide Oscillator [UAlgo]🔶 Description:
The "Trend Tide Oscillator " is a technical analysis tool designed to identify potential trend reversals and overbought/oversold conditions in the market. It calculates an oscillator based on the Commodity Channel Index (CCI) and then applies smoothing techniques to provide a clearer view of market momentum.
🔶 Key Features:
Oscillator Calculation : The indicator calculates an oscillator based on the Commodity Channel Index (CCI), which is a momentum-based oscillator used to identify overbought and oversold conditions.
Smoothing : Smoothing techniques are applied to the oscillator to reduce noise and provide a clearer view of market momentum. This helps traders in identifying trends more effectively.
Support and Resistance Zones : The indicator plots support and resistance zones based on the highest and lowest values of the oscillator over a specified lookback (default 50) period. These zones can help traders identify potential areas of price reversal. The indicator considers volatility when plotting the support and resistance zones. This aims to create more adaptable levels that account for fluctuating market conditions.
Visualization : The indicator visually represents overbought and oversold conditions with shapes (⚠️), aiding traders in quickly identifying potential entry or exit points.
Customization : Users can adjust parameters such as oscillator length, smoothing, and overbought/oversold levels, support and resistance lookbacks according to their trading preferences.
🔶 Disclaimer :
This indicator is provided for informational and educational purposes only and should not be considered as financial advice. Trading in the financial markets involves risk, and users should conduct their own research and analysis before making any investment decisions.
Weighted Oscillator Convergence DivergenceThe Weighted Oscillator Convergence Divergence (WOCD) aims to help traders identify potential trend reversals or momentum shifts in financial markets by calculating and visualizing the difference between a smoothed oscillator (WMA) value and its exponential moving average (EMA) and simple moving average (SMA) counterparts. This indicator is particularly useful for traders who want an alternative perspective on price momentum and divergence.
Key Features:
Inputs:
Length: The user can specify the number of bars to consider for calculations (default is 9).
Smoothing 1: Defines the smoothing factor for the first smoothed value (default is 5).
Smoothing 2: Specifies the smoothing factor for the second smoothed value (default is 7).
Ma Type: There are three types of moving averages you can choose (Wilder, non-lag, Weighted is by default).
Color Settings: Users can customize the indicator's colors for various elements, such as length, smoothing values, and different sections of the histogram.
Calculation:
WOCD calculates the raw oscillator value by subtracting the close price from a 3-period High, Low, Close (HLC3) moving average.
It then applies smoothing to this raw oscillator value using two different methods: exponential moving average (EMA) and simple moving average (SMA) with user-defined smoothing periods.
Histogram Plot:
The indicator plots a histogram based on the difference between the smoothed oscillator and the first smoothed value.
When the histogram is above zero and rising, it is colored according to the "Above Grow" color setting. When it's above zero and falling, it uses the "Fall" color for visualization.
Similarly, when the histogram is below zero and rising, it is colored according to the "Below Grow" color setting, and when it's below zero and falling, it uses the "Fall" color.
Oscillator and Smoothed Values:
The indicator also plots the smoothed oscillator, smoothed value 1 (EMA-based), and smoothed value 2 (SMA-based) on the chart.
Zero Line:
A horizontal line at zero is drawn on the chart for reference.
How to Use the WOCD Indicator:
Trend Identification: Observe the histogram's direction and color. A rising histogram above zero may indicate bullish momentum, while a falling histogram below zero could signal bearish momentum.
Divergence: Look for divergences between price action and the histogram. When the histogram and price move in opposite directions, it can be a potential reversal signal.
Crossovers: Pay attention to crossovers between the smoothed oscillator and its smoothed counterparts (EMA and SMA). These crossovers can indicate changes in trend strength or direction.
Zero Line: The zero line can act as a reference point. Positive histogram values suggest bullish sentiment, while negative values indicate bearish sentiment.
Comparison to MACD Indicator:
The WOCD indicator shares some similarities with the Moving Average Convergence Divergence (MACD) indicator but also has distinct differences:
Similarities:
Both WOCD and MACD are momentum oscillators designed to identify potential trend reversals and divergences.
They use moving averages (EMA in the case of MACD) to smooth the raw oscillator values.
Both indicators provide histogram representations of the difference between the oscillator and its smoothed counterpart.
Differences:
WOCD uses a 3-period High, Low, Close (HLC3) moving average to calculate the raw oscillator value, whereas MACD uses the difference between two exponential moving averages (usually 12-period and 26-period EMAs).
The smoothing in WOCD employs both EMA and SMA, while MACD exclusively uses EMA.
WOCD allows users to customize colors for various elements, enhancing visual clarity.
LNL Squeeze ArrowsIf you struggle with the entries, low % win rate or trading the squeeze setup overall, this indicator is for you!
If you look closely at your losing trades, chances are the losers have one thing in common = inverse momentum. I created this tool after I found out that Stacked EMAs and picture perfect trend is not the only thing you need for a squeeze setup. Squeeze arrows pinpoint the exact moment where the squeeze momentum change happens (momentum change is absolutely crucial for the squeeze setup). These arrows will help you stay out of "everything was aligned but still failed" type of setups.
Squeeze Arrows:
1. Momentum Arrows (cyan blue/red) - Showing the best possible moment for an entry during the squeeze (after you see one, you can expect the squeeze to fire soon).
2. Slingshot Arrows (yellow) - Even though you can trade off of them, these arrows work mostly as a confirmation & caution tool. If an inverse slingshot arrow is plotted during a squeeze that means caution = you should wait because momentum is not on your side thus there there is a quite high probability that the squeeze can fire the other direction.
Squeeze Dots Trigger:
Represents the number of red dots (squeeze) after which the arrows should plot. Default = 5 (only after 5 red dots, arrows will appear), some traders like to set it on 3 or even 1.
Tips & Tricks:
1.Breakout or Bailout Mentality
- The big advantage of the arrows is the fact that they either work straight away or they don't. This is where you can apply the breakout or bailout mentality and really focus exclusively on the breakout part of the whole squeeze move. You can minimize the risk by putting mental stops just a few points below the last low of the candle where the arrows appeared. That way you can be stopped out even during the squeeze = won't hurt as much as when the squeeze fire the opposite direction. Reward may be the same but the risk is lower.
2. Yellow Flags
- Use the slingshot arrows as a caution tool. Even if all your squeeze criteria are met. Yellow inverse arrow = caution (wait for the true momentum change). Once the slingshot arrow appears in the conext of the trend, you are good to go.
3. Last Arrow Rule
- Sometimes you will see a lot of arrows during the longer squeezes. This is where the last arrow rule come in handy. The last arrow you see on chart can be canceled anytime by a new one. The last arrow is the valid one!
Hope you can squeeze from these squeeze arrows as much as there is to squeeze so you can finally trade the squeeze with ease.
Hope it helps.
Cryptogrithm's Secret Momentum and Volatility IndicatorThis indicator is hard-coded for Bitcoin, but you may try it on other asset classes/coins. I have not updated this indicator in over 3 years, but it seems to still work very well for Bitcoin.
This indicator is NOT for beginners and is directed towards intermediate/advanced traders with a sensibility to agree/disagree with what this indicator is signalling (common sense).
This indicator was developed back in 2018 and I has not been maintained since, which is the reason why I am releasing it. (It still works great though! At the time of this writing of May 2022).
How to use:
Terms:
PA (Price Action): Literally the candlestick formations on your chart (and the trend formation). If you don't know how to read and understand price action, I will make a fast-track video/guide on this later (but in the meanwhile, you need to begin by learning Order-Flow Analysis, please google it first before asking).
CG Level (Cryptogrithm Level/Yellow Line): PA level above = bullish, PA level below = bearish
CG Bands (Cryptogrithm Bands): This is similar to how bollingers work, you can use this the same was as bollinger bands. The only difference is that the CG bands are more strict with the upper and lower levels as it uses different calculations to hug the price tighter allowing it to be more reactive to drastic price changes (earlier signals for oversold/overbought).
CG Upper Band (Red Upper Line): Above this upper bound line means overbought.
CG Middle Band (Light Blue Line): If PA trades above this line, the current PA trend is bullish continuing in the uptrend. If PA trades below this line, the current PA trend is bearish continuing in the downtrend. This band should only be used for short-term trends.
CG Lower Band (Green Lower Line): Below this lower bound line means oversold.
What the CG Level (yellow line) tells you:
PA is trading above CG Level = Bullish
PA is trading below CG Level = Bearish
Distance between CG Level and price = Momentum
What this means is that the further away the price is from the CG Level, the greater the momentum of the current PA trend. An increasing gap between the CG Level and PA indicates the price's strength (momentum) towards the current upward/downward trend. Basically when the PA and CG Level diverge, it means that the momentum is increasing in the current trend and when they converge, the current trend is losing momentum and the direction of the PA trend may flip towards the other direction (momentum flip).
PA+CG Level Momentum:
To use the CG Level as a momentum indicator, you need to pay attention to how the price and the CG level are moving away/closer from each other:
PA + CG Level Diverges = Momentum Increasing
PA + CG Level Converges = Momentum Decreasing
Examples (kind of common sense, but just for clarity):
Case 1: Bullish Divergence (Bullish): The PA is ABOVE and trending AWAY above from the CG Level = very bullish, this means that momentum is increasing towards the upside and larger moves will come (increasing gap between the price and CG Level)
Case 2: Bearish Convergence (Bearish): - The PA is ABOVE the CG Level and trending TOWARDS the CG Level = bearish, there is a possibility that the upward trend is ending. Look to start closing off long positions until case 1 (divergence) occurs again.
Case 3: Neutral - The PA is trading on the CG Level (no clear divergence or convergence between the PA and CG Level) = Indicates a back and forth (tug of war) between bears and bulls. Beware of choppy price patterns as the trend is undecisive until either supply/liquidity is dried out and a winner between bull/bear is chosen. This is a no trade zone, but do as you wish.
Case 4: Bearish Divergence (Bearish): The PA is BELOW and trending AWAY BELOW from the CG Level = very bearish, this means that momentum is increasing towards the downside and larger downward moves will come (increasing gap between the price and CG Level).
Case 5: Bullish Convergence (Bullish): - The PA is BELOW the CG Level and trending TOWARDS the CG Level = bullish, there is a possibility that the downward trend is ending and a trend flip is occuring. Look to start closing off short positions until case 4 (divergence) occurs again.
CG Bands + CG Level: You can use the CG bands instead of the PA candles to get a cleaner interpretation of reading the momentum. I won't go into detail as this is pretty self-explanatory. It is the same explanation as PA+CG Level Momentum, but you are replacing the PA candles with the CG Bands for interpretation. So instead of the PA converging/diverging from the CG Level, the Upper and Lower Bound levels are converging/diverging from the CG level instead.
Convergence: CG Level (yellow line) trades inside the CG bands
Divergence: CG Level (yellow line) trades outside the CG bands
Bullish/Bearish depends on whether the CG Band is trading below or above the CG level. If CG Band is above the CG Level, this is bullish. If CG Band is below the CG level, this is bearish.
Crosses (PA or CG Band crosses with CG level): This typically indicates volatility is incoming.
There are MANY MANY MANY other ways to use this indicator that is not explained here and even other undiscovered methods. Use some common sense as to how this indicator works (it is a momentum indicator and volatility predictor). You can get pretty creative and apply your own methods / knowledge to it and look for patterns that occur. Feel free to comment and share what you came up with!
+ WaveTrend OscillatorI'm guessing most of you are familir with LazyBear's adaptation of the Wavetrend Oscillator; it's one of the most popular indicators on TradingView. I know others have done adaptations of it, but I thought I might as well, because that's kind of a thing I like doing.
In this version I've added a second Wavetrend plot. This is a thing I like to do. The longer plot gives you a longer timeframe momentum bias, and the shorter plot gives you entries and/or exits. Here we have one plot with a lookback period of 55, and another with the default set to 6 (change this to 14 if you think you might prefer something slower and that will plot similarly to the default RSI settings). With the traditional Wavetrend Oscillator there is a simple moving average on the WTO that is to help provide entries and exits. I've done away with this as there are already two plots, and I felt more would just clutter the indicator. Instead of plotting the SMA I've plotted the crosses along the bottom and top of the indicator. Also, as is not the case in LazyBear's version, this SMA length is adjustable. By default it is set to 3, which is the default setting on the original indicator.
I've also plotted background colors for when there is what I call a momentum shift. If one or the other oscillators crosses the centerline a colored bar is plotted. By default it is turned on for both WTOs, though in practice you might only want it on for the longer one.
I would say use of the indicator is similar to the original WTO or many other oscillators. Buying oversold and selling overbought, but being mindful of the momentum of the market. If the longer WTO is above the centerline it's best to be looking for dips to the centerline, or for an overbought signal by the faster WTO, and vice versa if the longer WTO is below the centerline. That said, you can also adjust the length of the SMA on the faster WTO to fine tune entries or exits, which is kind of how you would trade LazyBear's version. In this case you have that additional confirmation of market momentum.
You can set colored candles to either of the WTO plots via a dropdown menu.
There are alerts for overbought and oversold situations, centerline crosses, and Wavetrend crosses.
That's about it. Hope you enjoy this particular implementation of LazyBear's well known indicator.
Ah yes, last thing: Original version the source is set to hlc3. I've given you the opportunity to change that, so if you prefer using close you can, or whatever you want.
CDV Momentum WaveDescription:
This indicator visualizes the Cumulative Delta Volume (CDV) as waves, providing traders with insights into the momentum and strength of buying and selling activity. By tracking the cumulative difference between buying and selling pressure, it highlights shifts in market sentiment with color-coded wave patterns.
How to Use:
Spot Momentum:
Green waves signify strong buying pressure, while red waves indicate dominant selling pressure. Blue and orange waves mark transitions or weaker momentum.
Trend Analysis:
Persistent color and direction in waves reflect a strong trend, while frequent shifts may signal reversals or consolidation.
Sensitivity Adjustment:
Use the mul2 setting to fine-tune wave responsiveness for short-term or long-term analysis.
Wave Position Adjustment:
The osx setting adjusts the visual placement of the waves on the chart.
By default (osx = 0), the waves are aligned directly with the candle data they are calculated from.
Increasing osx shifts the waves forward.
Decreasing osx shifts the waves backward.
This tool helps traders detect momentum shifts, confirm trends, and understand volume dynamics in various market conditions.
TTM Waves ABC ATR AO MOM SQZ//All code picked from many indicators, if you recognize your code, pls comment so people can see your awesome work! I only edited and added them all together so people don't use all their indicator slots. Hope this indicator helps as many people as it can. LFG!!!
AO (Awesome Oscillator) Useful to find potential reversals in trend.
MOM (Momentum) An oscillator that measures momentum.
ATR (Average True Range) Measures the upside and downside from the average price movement occuring. 1 ATR is the general measurement. Many traders use 2ATR to set a stop and 4ATR to set take profit from their entry based on current reading from the ATR.
SQZ ( TTM Squeeze) Measures when bollinger bands have left the interior of the Keltner Channel in an attempt to predict volatility thats about to happen to either side. Green = Move is probably about to happen.
TTM Waves ( Waves A, B, and C) Measure the previous candles to determine chop, positive or negative trends. C measures the previous 30 candles or so, B the last 15 or so, and A measures the last 8 or so. You can use all three or just one. You can sneak in a move if the 2 fastest ones have moved into your preferred area. (Positive or Negative) If the wave is not fully positve or negative then that is probably chop.
-Penguincryptic
CoffeeShopCrypto 3pl MAThe CoffeeShopCrypto 3pl MA indicator is a technical analysis tool that uses three different moving averages to identify trends in the price of an asset. The three moving averages have lengths of 12, 26, and 50. If these numbers sound familiar its because they are based off the standard of the MACD indicator, and can be either simple moving averages (SMA) or exponential moving averages (EMA), depending on user preference.
The following is plotted on the chart
The fast EMA/SMA (based on the 12-period length) in yellow.
The mid EMA/SMA (based on the 26-period length) in gray.
The slow EMA/SMA (based on the 50-period length) in either green or red, depending on whether the current close price is above or below the Overall Trend MA.
In addition to the moving averages, the indicator also calculates the MACD (Moving Average Convergence Divergence), and uses it to color the bars based on the momentum of the asset.
The MACD is calculated using two user-defined lengths (fast and slow), as well as a user-defined smoothing length for the signal line. The oscillator and signal line can be either SMA or EMA, and the colors of the MACD bars are based on whether the histogram is growing or falling, and whether it is above or below the zero line.
Overall, this indicator provides traders with a comprehensive tool for understanding the trend of an asset, as well as the momentum behind that trend. The moving averages provide a clear visual representation of the trend, while the MACD bars give insight into the strength of that trend and potential shifts in momentum.
---------------LONG ENTRY----------------
MA1 above MA2 and Overall trend = Green
IF RSI is above its midline you are confirmed for a long entry
-----------Short Entry--------------
MA1 below MA2 and Overall trend = Red
IF RSI is below its midline you are confirmed for a short entry
RSI Potential Divergence - FontiramisuIndicator showing potential momentum divergences on RSI Momentum.
The problem with the classic divergence is that when the signal appears, it is sometimes too late to enter a trade.
The potential divergence corrects this problem by signaling the beginning of a potential divergence.
RSI is a momentum indicator that offers relevant insights with divergences.
Potential divergences are indicated with the letter B and a red color for Bearish Div or Green color for Bullish Div .
Potential divergence is confirmed when the line and the label "Bear"' or "Bull" appear.
Williams %R - SmoothedFrom TradingView's description:
Williams %R (%R) is a momentum-based oscillator used in technical analysis, primarily to identify overbought and oversold conditions. The %R is based on a comparison between the current close and the highest high for a user defined look back period. %R Oscillates between 0 and -100 (note the negative values) with readings closer to zero indicating more overbought conditions and readings closer to -100 indicating oversold. Typically %R can generate set ups based on overbought and oversold conditions as well overall changes in momentum.
What's special?
This indicator adds two additional EMA lines to the original Williams %R indicator. Default EMA lengths are 5 and 13. The result is 2 smoother average lines, which are easier to read.
This indicator includes:
- signals for EMA crosses. EMA crosses can help indicate confirmed trend changes. Default colors are green and red
- signals for trend reversals on the faster EMA line. Default colors are blue and orange
Alerts available for bullish/bearish crossovers and reversals.
Enjoy~~!
+ Rate of ChangeNOTE!* If you were using my previous + Rate of Change (and OBV) indicator, I will not be updating that. OBV was moved to my + Breadth & Volume indicator.
This indicator here is basically and updated version of the old indicator, without OBV.
The Rate of Change, or RoC, is a momentum indicator that measures the percentage change in price between the current period and the price n periods ago.
It oscillates above and below a zeroline, basically showing positive or negative momentum.
I applied the OBV's calculation to it, but without the inclusion of volume (also added a lookback period) to see what would happen. I rather liked the result.
I call this the "Cumulative Rate of Change." I only recently realized that this is actually just the OBV without volume, however the OBV does not have a lookback period, and this indicator does.
Doing some more fiddling, I realized that removing both the signum and the volume from the calculation gets you basically a price chart, but calculated as the change in price over n periods. I'm leaving this in because maybe someone discovers they really like having a line chart with moving averages or some other indicator on it to leave their main chart indicator free (giving a more clear look at price action). Can't hurt, right?
Default lookback is set to 1, but play with longer settings (especially if using the traditional RoC, which is by default in TV set to 10, and is nigh on useless at 1--I like 13).
Default source is set to each candle close, but give ohlc4 a look. It smooths out the indicator a bit, and because it's an average of the open, high, low, and close it should give a better idea of what price in general is doing.
Moving averages, Bollinger Bands, Donchian Channels, candle coloring and alerts are my usual additions.
Below are some comparison images of the different indicators wrapped up in here.
Comparison of Cumulative Rate of Change with two different sources. Lookback set to 1.
Cumulative Rate of Change as a price chart, essentially.
And, lastly, the traditional Rate of Change indicator.
+ Rate of Change (and OBV)The Rate of Change, or RoC, is a momentum indicator that measures the percentage change in price between the current period and the price n periods ago. It oscillates above and below a zeroline, basically showing positive or negative momentum. I applied the OBV's calculation to it, but without the inclusion of volume (also added a lookback period) to see what would happen.
Actually what happened was I was looking at hot-rodding the OBV indicator, but then wondered if I could apply the cumulative calculation to another indicator to see what would happen. Not sure why I chose the Rate of Change, but it seemed a neat idea. And it worked! And so I called it the "Cumulative Rate of Change." I only recently realized that this is actually just the OBV without volume, HOWEVER the OBV does not have a lookback period, and its source is the close of each period. Basically, when you look at the calculation for the OBV you'll notice that it's a cumulative measure of the "change" of the closing price against the previous close times the volume. The Rate of Change is basically that measurement over more than one period, excluding the volume, and is not cumulative. Thus the "Cumulative Rate of Change" is basically an OBV without the volume but with the capability to adjust the lookback period.
Anyway, after days and weeks of playing with the indicator pretty infrequently I did decide that I actually really liked it, especially with the addition of moving averages and bollinger bands. So I decided to play with it a bit more.
I added a drop-down menu to include the standard Rate of Change indicator, and then thought I may as well add the OBV too, in case someone might like to compare that to the C-RoC, or just wants an OBV with myriad moving averages and bollinger bands.
By default I have the indicator set to the "C-RoC" and the lookback is set to 1, but play with longer settings (this is pretty much necessary if using the traditional RoC, which is by default set to 10 in TradingView, and is nigh on useless at 1).
I also recommend playing with the source. 'Close' is nice, but 'ohlc4' provides some very nice signals as well, as it follows the price flow for each period completely, filtering the noisiness of 'close' as source.
Hope you guys like this. With the bollinger bands and your preferred moving average settings this can be a powerful tool for re-entering trades in trend, taking profits, determining momentum swings.
Stochastic CandlesA series of up to 28 stochastics oscillators used to form an average stochastic value, which is then used to colour the candles based on the momentum.
Each candle can be coloured one of ten colours and each one represents a position on the stochastic oscillator.
The indicator helps traders to visualise the momentum and helps trend following.
Inputs:
MA: multiple smoothing methods
Theme: multiple colours
Increment: stochastic length start and increments
End: stochastic length end
Smooth: smooth stochastic
UCS_Top & Bottom CandleThis is an experimental Indicator based on Momentum. Picks the Top & Bottom Candle for most Swing. Please post your opinion or suggestion to improve this indicator.
I have not back tested this completely. This is recently developed Indicator.
Truly Iterative Gaussian ChannelOVERVIEW
The Truly Iterative Gaussian Channel is a robust channeling system that integrates a Gaussian smoothing kernel with a rolling standard deviation to create dynamically adaptive upper and lower boundaries around price. This indicator provides a smooth, yet responsive representation of price movements while minimizing lag and dynamically adjusting channel width to reflect real-time market volatility. Its versatility makes it effective across various timeframes and trading styles, offering significant potential for experimentation and integration into advanced trading systems.
TRADING USES
The Gaussian indicator can be used for multiple trading strategies. Trend following relies on the middle Gaussian line to gauge trend direction: prices above this line indicate bullish momentum, while prices below signal bearish momentum. The upper and lower boundaries act as dynamic support and resistance levels, offering breakout or pullback entry opportunities. Mean reversion focuses on identifying reversal setups when price approaches or breaches the outer boundaries, aiming for a return to the Gaussian centerline. Volatility filtering helps assess market conditions, with narrow channels indicating low volatility or consolidation and suggesting fewer trading opportunities or an impending breakout. Adaptive risk management uses channel width to adjust for market volatility, with wider channels signaling higher risk and tighter channels indicating lower volatility and potentially safer entry points.
THEORY
Gaussian kernel smoothing, derived from the Gaussian normal distribution, is a cornerstone of probability and statistics, valued for its ability to reduce noise while preserving critical signal features. In this indicator, it ensures price movements are smoothed with precision, minimizing distortion while maintaining responsiveness to market dynamics.
The rolling standard deviation complements this by dynamically measuring price dispersion from the mean, enabling the channel to adapt in real time to changing market conditions. This combination leverages the mathematical correctness of both tools to balance smoothness and adaptability.
An iterative framework processes data efficiently, bar by bar, without recalculating historical value to ensure reliability and preventing repainting to create a mathematically grounded channel system suitable for a wide range of market environments.
The Gaussian channel excels at filtering noise while remaining responsive to price action, providing traders with a dependable tool for identifying trends, reversals, and volatility shifts with consistency and precision.
CALIBRATION
Calibration of the Gaussian channel involves adjusting its length to modify sensitivity and adaptability based on trading style. Shorter lengths (e.g., 50-100) are ideal for intraday traders seeking quick responses to price fluctuations. Medium lengths (e.g., 150-200) cater to swing traders aiming to capture broader market trends. Longer lengths (e.g., 250-400+) are better suited for positional traders focusing on long-term price movements and stability.
MARKET USAGE
Stock, Forex, Crypto, Commodities, and Indices.
Supertrend with EMASupertrend + EMA Indicator
This custom indicator combines the popular Supertrend and Exponential Moving Average (EMA) indicators to enhance trend analysis and signal accuracy. The Supertrend tracks price volatility to identify potential trend directions, while the EMA provides a smooth moving average to help refine entries and exits based on trend momentum.
Features:
Supertrend: Detects trend reversals by using price action and volatility, making it effective in trending markets.
Exponential Moving Average (EMA): Smoothens price fluctuations, helping you gauge the trend’s strength and filter out false signals.
Versatile for multiple timeframes and asset classes.
Ideal for traders looking to catch sustained trends and avoid false breakouts, this indicator offers an improved way to follow market momentum and confirm trend strength. Customize the Supertrend ATR multiplier and EMA length to suit your trading style and timeframe.
Intramarket Difference Index StrategyHi Traders !!
The IDI Strategy:
In layman’s terms this strategy compares two indicators across markets and exploits their differences.
note: it is best the two markets are correlated as then we know we are trading a short to long term deviation from both markets' general trend with the assumption both markets will trend again sometime in the future thereby exhausting our trading opportunity.
📍 Import Notes:
This Strategy calculates trade position size independently (i.e. risk per trade is controlled in the user inputs tab), this means that the ‘Order size’ input in the ‘Properties’ tab will have no effect on the strategy. Why ? because this allows us to define custom position size algorithms which we can use to improve our risk management and equity growth over time. Here we have the option to have fixed quantity or fixed percentage of equity ATR (Average True Range) based stops in addition to the turtle trading position size algorithm.
‘Pyramiding’ does not work for this strategy’, similar to the order size input togeling this input will have no effect on the strategy as the strategy explicitly defines the maximum order size to be 1.
This strategy is not perfect, and as of writing of this post I have not traded this algo.
Always take your time to backtests and debug the strategy.
🔷 The IDI Strategy:
By default this strategy pulls data from your current TV chart and then compares it to the base market, be default BINANCE:BTCUSD . The strategy pulls SMA and RSI data from either market (we call this the difference data), standardizes the data (solving the different unit problem across markets) such that it is comparable and then differentiates the data, calling the result of this transformation and difference the Intramarket Difference (ID). The formula for the the ID is
ID = market1_diff_data - market2_diff_data (1)
Where
market(i)_diff_data = diff_data / ATR(j)_market(i)^0.5,
where i = {1, 2} and j = the natural numbers excluding 0
Formula (1) interpretation is the following
When ID > 0: this means the current market outperforms the base market
When ID = 0: Markets are at long run equilibrium
When ID < 0: this means the current market underperforms the base market
To form the strategy we define one of two strategy type’s which are Trend and Mean Revesion respectively.
🔸 Trend Case:
Given the ‘‘Strategy Type’’ is equal to TREND we define a threshold for which if the ID crosses over we go long and if the ID crosses under the negative of the threshold we go short.
The motivating idea is that the ID is an indicator of the two symbols being out of sync, and given we know volatility clustering, momentum and mean reversion of anomalies to be a stylised fact of financial data we can construct a trading premise. Let's first talk more about this premise.
For some markets (cryptocurrency markets - synthetic symbols in TV) the stylised fact of momentum is true, this means that higher momentum is followed by higher momentum, and given we know momentum to be a vector quantity (with magnitude and direction) this momentum can be both positive and negative i.e. when the ID crosses above some threshold we make an assumption it will continue in that direction for some time before executing back to its long run equilibrium of 0 which is a reasonable assumption to make if the market are correlated. For example for the BTCUSD - ETHUSD pair, if the ID > +threshold (inputs for MA and RSI based ID thresholds are found under the ‘‘INTRAMARKET DIFFERENCE INDEX’’ group’), ETHUSD outperforms BTCUSD, we assume the momentum to continue so we go long ETHUSD.
In the standard case we would exit the market when the IDI returns to its long run equilibrium of 0 (for the positive case the ID may return to 0 because ETH’s difference data may have decreased or BTC’s difference data may have increased). However in this strategy we will not define this as our exit condition, why ?
This is because we want to ‘‘let our winners run’’, to achieve this we define a trailing Donchian Channel stop loss (along with a fixed ATR based stop as our volatility proxy). If we were too use the 0 exit the strategy may print a buy signal (ID > +threshold in the simple case, market regimes may be used), return to 0 and then print another buy signal, and this process can loop may times, this high trade frequency means we fail capture the entire market move lowering our profit, furthermore on lower time frames this high trade frequencies mean we pay more transaction costs (due to price slippage, commission and big-ask spread) which means less profit.
By capturing the sum of many momentum moves we are essentially following the trend hence the trend following strategy type.
Here we also print the IDI (with default strategy settings with the MA difference type), we can see that by letting our winners run we may catch many valid momentum moves, that results in a larger final pnl that if we would otherwise exit based on the equilibrium condition(Valid trades are denoted by solid green and red arrows respectively and all other valid trades which occur within the original signal are light green and red small arrows).
another example...
Note: if you would like to plot the IDI separately copy and paste the following code in a new Pine Script indicator template.
indicator("IDI")
// INTRAMARKET INDEX
var string g_idi = "intramarket diffirence index"
ui_index_1 = input.symbol("BINANCE:BTCUSD", title = "Base market", group = g_idi)
// ui_index_2 = input.symbol("BINANCE:ETHUSD", title = "Quote Market", group = g_idi)
type = input.string("MA", title = "Differrencing Series", options = , group = g_idi)
ui_ma_lkb = input.int(24, title = "lookback of ma and volatility scaling constant", group = g_idi)
ui_rsi_lkb = input.int(14, title = "Lookback of RSI", group = g_idi)
ui_atr_lkb = input.int(300, title = "ATR lookback - Normalising value", group = g_idi)
ui_ma_threshold = input.float(5, title = "Threshold of Upward/Downward Trend (MA)", group = g_idi)
ui_rsi_threshold = input.float(20, title = "Threshold of Upward/Downward Trend (RSI)", group = g_idi)
//>>+----------------------------------------------------------------+}
// CUSTOM FUNCTIONS |
//<<+----------------------------------------------------------------+{
// construct UDT (User defined type) containing the IDI (Intramarket Difference Index) source values
// UDT will hold many variables / functions grouped under the UDT
type functions
float Close // close price
float ma // ma of symbol
float rsi // rsi of the asset
float atr // atr of the asset
// the security data
getUDTdata(symbol, malookback, rsilookback, atrlookback) =>
indexHighTF = barstate.isrealtime ? 1 : 0
= request.security(symbol, timeframe = timeframe.period,
expression = [close , // Instentiate UDT variables
ta.sma(close, malookback) ,
ta.rsi(close, rsilookback) ,
ta.atr(atrlookback) ])
data = functions.new(close_, ma_, rsi_, atr_)
data
// Intramerket Difference Index
idi(type, symbol1, malookback, rsilookback, atrlookback, mathreshold, rsithreshold) =>
threshold = float(na)
index1 = getUDTdata(symbol1, malookback, rsilookback, atrlookback)
index2 = getUDTdata(syminfo.tickerid, malookback, rsilookback, atrlookback)
// declare difference variables for both base and quote symbols, conditional on which difference type is selected
var diffindex1 = 0.0, var diffindex2 = 0.0,
// declare Intramarket Difference Index based on series type, note
// if > 0, index 2 outpreforms index 1, buy index 2 (momentum based) until equalibrium
// if < 0, index 2 underpreforms index 1, sell index 1 (momentum based) until equalibrium
// for idi to be valid both series must be stationary and normalised so both series hae he same scale
intramarket_difference = 0.0
if type == "MA"
threshold := mathreshold
diffindex1 := (index1.Close - index1.ma) / math.pow(index1.atr*malookback, 0.5)
diffindex2 := (index2.Close - index2.ma) / math.pow(index2.atr*malookback, 0.5)
intramarket_difference := diffindex2 - diffindex1
else if type == "RSI"
threshold := rsilookback
diffindex1 := index1.rsi
diffindex2 := index2.rsi
intramarket_difference := diffindex2 - diffindex1
//>>+----------------------------------------------------------------+}
// STRATEGY FUNCTIONS CALLS |
//<<+----------------------------------------------------------------+{
// plot the intramarket difference
= idi(type,
ui_index_1,
ui_ma_lkb,
ui_rsi_lkb,
ui_atr_lkb,
ui_ma_threshold,
ui_rsi_threshold)
//>>+----------------------------------------------------------------+}
plot(intramarket_difference, color = color.orange)
hline(type == "MA" ? ui_ma_threshold : ui_rsi_threshold, color = color.green)
hline(type == "MA" ? -ui_ma_threshold : -ui_rsi_threshold, color = color.red)
hline(0)
Note it is possible that after printing a buy the strategy then prints many sell signals before returning to a buy, which again has the same implication (less profit. Potentially because we exit early only for price to continue upwards hence missing the larger "trend"). The image below showcases this cenario and again, by allowing our winner to run we may capture more profit (theoretically).
This should be clear...
🔸 Mean Reversion Case:
We stated prior that mean reversion of anomalies is an standerdies fact of financial data, how can we exploit this ?
We exploit this by normalizing the ID by applying the Ehlers fisher transformation. The transformed data is then assumed to be approximately normally distributed. To form the strategy we employ the same logic as for the z score, if the FT normalized ID > 2.5 (< -2.5) we buy (short). Our exit conditions remain unchanged (fixed ATR stop and trailing Donchian Trailing stop)
🔷 Position Sizing:
If ‘‘Fixed Risk From Initial Balance’’ is toggled true this means we risk a fixed percentage of our initial balance, if false we risk a fixed percentage of our equity (current balance).
Note we also employ a volatility adjusted position sizing formula, the turtle training method which is defined as follows.
Turtle position size = (1/ r * ATR * DV) * C
Where,
r = risk factor coefficient (default is 20)
ATR(j) = risk proxy, over j times steps
DV = Dollar Volatility, where DV = (1/Asset Price) * Capital at Risk
🔷 Risk Management:
Correct money management means we can limit risk and increase reward (theoretically). Here we employ
Max loss and gain per day
Max loss per trade
Max number of consecutive losing trades until trade skip
To read more see the tooltips (info circle).
🔷 Take Profit:
By defualt the script uses a Donchain Channel as a trailing stop and take profit, In addition to this the script defines a fixed ATR stop losses (by defualt, this covers cases where the DC range may be to wide making a fixed ATR stop usefull), ATR take profits however are defined but optional.
ATR SL and TP defined for all trades
🔷 Hurst Regime (Regime Filter):
The Hurst Exponent (H) aims to segment the market into three different states, Trending (H > 0.5), Random Geometric Brownian Motion (H = 0.5) and Mean Reverting / Contrarian (H < 0.5). In my interpretation this can be used as a trend filter that eliminates market noise.
We utilize the trending and mean reverting based states, as extra conditions required for valid trades for both strategy types respectively, in the process increasing our trade entry quality.
🔷 Example model Architecture:
Here is an example of one configuration of this strategy, combining all aspects discussed in this post.
Future Updates
- Automation integration (next update)
Uptrick: DPO Signal & Zone Indicator
## **Uptrick: DPO Signal & Zone Indicator**
### **Introduction:**
The **Uptrick: DPO Signal & Zone Indicator** is a sophisticated technical analysis tool tailored to provide insights into market momentum, identify potential trading signals, and recognize extreme market conditions. It leverages the Detrended Price Oscillator (DPO) to strip out long-term trends from price movements, allowing traders to focus on short-term fluctuations and cyclical behavior. The indicator integrates multiple components, including a Detrended Price Oscillator, a Signal Line, a Histogram, and customizable alert levels, to deliver a robust framework for market analysis and trading decision-making.
### **Detailed Breakdown:**
#### **1. Detrended Price Oscillator (DPO):**
- **Purpose and Functionality:**
- The DPO is designed to filter out long-term trends from the price data, isolating short-term price movements. This helps in understanding the cyclical patterns and momentum of an asset, allowing traders to detect periods of acceleration or deceleration that might be overlooked when focusing solely on long-term trends.
- **Calculation:**
- **Formula:** `dpo = close - ta.sma(close, smaLength)`
- **`close`:** The asset’s closing price for each period in the dataset.
- **`ta.sma(close, smaLength)`:** The Simple Moving Average (SMA) of the closing prices over a period defined by `smaLength`.
- The DPO is derived by subtracting the SMA value from the current closing price. This calculation reveals how much the current price deviates from the moving average, effectively detrending the price data.
- **Interpretation:**
- **Positive DPO Values:** Indicate that the current price is higher than the moving average, suggesting bullish market conditions and a potential upward trend.
- **Negative DPO Values:** Indicate that the current price is lower than the moving average, suggesting bearish market conditions and a potential downward trend.
- **Magnitude of DPO:** Reflects the strength of momentum. Larger positive or negative values suggest stronger momentum in the respective direction.
#### **2. Signal Line:**
- **Purpose and Functionality:**
- The Signal Line is a smoothed average of the DPO, intended to act as a reference point for generating trading signals. It helps to filter out short-term fluctuations and provides a clearer perspective on the prevailing trend.
- **Calculation:**
- **Formula:** `signalLine = ta.sma(dpo, signalLength)`
- **`ta.sma(dpo, signalLength)`:** The SMA of the DPO values over a period defined by `signalLength`.
- The Signal Line is calculated by applying a moving average to the DPO values. This smoothing process reduces noise and highlights the underlying trend direction.
- **Interpretation:**
- **DPO Crossing Above Signal Line:** Generates a buy signal, suggesting that short-term momentum is turning bullish relative to the longer-term trend.
- **DPO Crossing Below Signal Line:** Generates a sell signal, suggesting that short-term momentum is turning bearish relative to the longer-term trend.
- **Signal Line’s Role:** Provides a benchmark for assessing the strength of the DPO. The interaction between the DPO and the Signal Line offers actionable insights into potential entry or exit points.
#### **3. Histogram:**
- **Purpose and Functionality:**
- The Histogram visualizes the difference between the DPO and the Signal Line. It provides a graphical representation of momentum strength and direction, allowing traders to quickly gauge market conditions.
- **Calculation:**
- **Formula:** `histogram = dpo - signalLine`
- The Histogram is computed by subtracting the Signal Line value from the DPO value. Positive values indicate that the DPO is above the Signal Line, while negative values indicate that the DPO is below the Signal Line.
- **Interpretation:**
- **Color Coding:**
- **Green Bars:** Represent positive values, indicating bullish momentum.
- **Red Bars:** Represent negative values, indicating bearish momentum.
- **Width of Bars:** Indicates the strength of momentum. Wider bars signify stronger momentum, while narrower bars suggest weaker momentum.
- **Zero Line:** A horizontal gray line that separates positive and negative histogram values. Crosses of the histogram through this zero line can signal shifts in momentum direction.
#### **4. Alert Levels:**
- **Purpose and Functionality:**
- Alert levels define specific thresholds to identify extreme market conditions, such as overbought and oversold states. These levels help traders recognize potential reversal points and extreme market conditions.
- **Inputs:**
- **`alertLevel1`:** Defines the upper threshold for identifying overbought conditions.
- **Default Value:** 0.5
- **`alertLevel2`:** Defines the lower threshold for identifying oversold conditions.
- **Default Value:** -0.5
- **Interpretation:**
- **Overbought Condition:** When the DPO exceeds `alertLevel1`, indicating that the market may be overbought. This condition suggests that the asset could be due for a correction or reversal.
- **Oversold Condition:** When the DPO falls below `alertLevel2`, indicating that the market may be oversold. This condition suggests that the asset could be poised for a rebound or reversal.
#### **5. Visual Elements:**
- **DPO and Signal Line Plots:**
- **DPO Plot:**
- **Color:** Blue
- **Width:** 2 pixels
- **Purpose:** To visually represent the deviation of the current price from the moving average.
- **Signal Line Plot:**
- **Color:** Red
- **Width:** 1 pixel
- **Purpose:** To provide a smoothed reference for the DPO and generate trading signals.
- **Histogram Plot:**
- **Color Coding:**
- **Green:** For positive values, signaling bullish momentum.
- **Red:** For negative values, signaling bearish momentum.
- **Style:** Histogram bars are displayed with varying width to represent the strength of momentum.
- **Zero Line:** A gray horizontal line separating positive and negative histogram values.
- **Overbought/Oversold Zones:**
- **Background Colors:**
- **Green Shading:** Applied when the DPO exceeds `alertLevel1`, indicating an overbought condition.
- **Red Shading:** Applied when the DPO falls below `alertLevel2`, indicating an oversold condition.
- **Horizontal Lines:**
- **Dotted Green Line:** At `alertLevel1`, marking the upper alert threshold.
- **Dotted Red Line:** At `alertLevel2`, marking the lower alert threshold.
- **Purpose:** To provide clear visual cues for extreme market conditions, aiding in the identification of potential reversal points.
#### **6. Trading Signals and Alerts:**
- **Buy Signal:**
- **Trigger:** When the DPO crosses above the Signal Line.
- **Visual Representation:** A "BUY" label appears below the price bar in the specified buy color.
- **Purpose:** Indicates a potential buying opportunity as short-term momentum turns bullish.
- **Sell Signal:**
- **Trigger:** When the DPO crosses below the Signal Line.
- **Visual Representation:** A "SELL" label appears above the price bar in the specified sell color.
- **Purpose:** Indicates a potential selling opportunity as short-term momentum turns bearish.
- **Overbought/Oversold Alerts:**
- **Overbought Alert:** Triggered when the DPO crosses below `alertLevel1`.
- **Oversold Alert:** Triggered when the DPO crosses above `alertLevel2`.
- **Visual Representation:** Labels "OVERBOUGHT" and "OVERSOLD" appear with distinctive colors and sizes to highlight extreme conditions.
- **Purpose:** To signal potential reversal points and extreme market conditions that may lead to price corrections or trend reversals.
- **Alert Conditions:**
- **DPO Cross Above Signal Line:** Alerts traders when the DPO crosses above the Signal Line, generating a buy signal.
- **DPO Cross Below Signal Line:** Alerts traders when the DPO crosses below the Signal Line, generating a sell signal.
- **DPO Above Upper Alert Level:** Alerts when the DPO is above `alertLevel1`, indicating an overbought condition.
- **DPO Below Lower Alert Level:** Alerts when the DPO is below `alertLevel2`, indicating an oversold condition.
- **Purpose:** To provide real-time notifications of significant market events, enabling traders to make informed decisions promptly.
### **Practical Applications:**
#### **1. Trend Following Strategies:**
- **Objective:**
- To capture and ride the prevailing market trends by entering trades that align with the direction of the momentum.
- **How to Use:**
- Monitor buy and sell signals generated by the DPO crossing the Signal Line. A buy signal suggests a bullish trend and a potential long trade, while a sell signal suggests a bearish trend and a potential short trade.
- Use the Histogram to confirm the strength of the trend. Expanding green bars indicate strong bullish momentum, while expanding red bars indicate strong bearish momentum.
- **Advantages:**
- Helps traders stay aligned with the market trend, increasing the likelihood of capturing substantial price moves.
#### **2. Reversal Trading:**
- **Objective:**
- To identify potential market reversals
by detecting overbought and oversold conditions.
- **How to Use:**
- Look for overbought and oversold signals based on the DPO crossing `alertLevel1` and `alertLevel2`. These conditions suggest that the market may be due for a reversal.
- Confirm reversal signals with the Histogram. A decrease in histogram bars (from green to red or vice versa) may support the reversal hypothesis.
- **Advantages:**
- Provides early warnings of potential market reversals, allowing traders to position themselves before significant price changes occur.
#### **3. Momentum Analysis:**
- **Objective:**
- To gauge the strength and direction of market momentum for making informed trading decisions.
- **How to Use:**
- Analyze the Histogram to assess momentum strength. Positive and expanding histogram bars indicate increasing bullish momentum, while negative and expanding bars suggest increasing bearish momentum.
- Use momentum insights to validate or question existing trading positions and strategies.
- **Advantages:**
- Offers valuable information about the market's momentum, helping traders confirm the validity of trends and trading signals.
### **Customization and Flexibility:**
The **Uptrick: DPO Signal & Zone Indicator** offers extensive customization options to accommodate diverse trading preferences and market conditions:
- **SMA Length and Signal Line Length:**
- Adjust the `smaLength` and `signalLength` parameters to control the sensitivity and responsiveness of the DPO and Signal Line. Shorter lengths make the indicator more responsive to price changes, while longer lengths provide smoother, less volatile signals.
- **Alert Levels:**
- Modify `alertLevel1` and `alertLevel2` to fit varying market conditions and volatility. Setting these levels appropriately helps tailor the indicator to different asset classes and trading strategies.
- **Color and Shape Customization:**
- Customize the colors and sizes of buy/sell signals, histogram bars, and alert levels to enhance visual clarity and align with personal preferences. This customization helps ensure that the indicator integrates seamlessly with a trader's charting setup.
### **Conclusion:**
The **Uptrick: DPO Signal & Zone Indicator** is a multifaceted analytical tool that combines the power of the Detrended Price Oscillator with customizable visual elements and alert levels to deliver a comprehensive approach to market analysis. By offering insights into momentum strength, trend direction, and potential reversal points, this indicator equips traders with valuable information to make informed decisions and enhance their trading strategies. Its flexibility and customization options ensure that it can be adapted to various trading styles and market conditions, making it a versatile addition to any trader's toolkit.
