Cerca negli script per "stoch"
[COG]StochRSI Zenith📊 StochRSI Zenith
This indicator combines the traditional Stochastic RSI with enhanced visualization features and multi-timeframe analysis capabilities. It's designed to provide traders with a comprehensive view of market conditions through various technical components.
🔑 Key Features:
• Advanced StochRSI Implementation
- Customizable RSI and Stochastic calculation periods
- Multiple moving average type options (SMA, EMA, SMMA, LWMA)
- Adjustable signal line parameters
• Visual Enhancement System
- Dynamic wave effect visualization
- Energy field display for momentum visualization
- Customizable color schemes for bullish and bearish signals
- Adaptive transparency settings
• Multi-Timeframe Analysis
- Higher timeframe confirmation
- Synchronized market structure analysis
- Cross-timeframe signal validation
• Divergence Detection
- Automated bullish and bearish divergence identification
- Customizable lookback period
- Clear visual signals for confirmed divergences
• Signal Generation Framework
- Price action confirmation
- SMA-based trend filtering
- Multiple confirmation levels for reduced noise
- Clear entry signals with customizable display options
📈 Technical Components:
1. Core Oscillator
- Base calculation: 13-period RSI (adjustable)
- Stochastic calculation: 8-period (adjustable)
- Signal lines: 5,3 smoothing (adjustable)
2. Visual Systems
- Wave effect with three layers of visualization
- Energy field display with dynamic intensity
- Reference bands at 20/30/50/70/80 levels
3. Confirmation Mechanisms
- SMA trend filter
- Higher timeframe alignment
- Price action validation
- Divergence confirmation
⚙️ Customization Options:
• Visual Parameters
- Wave effect intensity and speed
- Energy field sensitivity
- Color schemes for bullish/bearish signals
- Signal display preferences
• Technical Parameters
- All core calculation periods
- Moving average types
- Divergence detection settings
- Signal confirmation criteria
• Display Settings
- Chart and indicator signal placement
- SMA line visualization
- Background highlighting options
- Label positioning and size
🔍 Technical Implementation:
The indicator combines several advanced techniques to generate signals. Here are key components with code examples:
1. Core StochRSI Calculation:
// Base RSI calculation
rsi = ta.rsi(close, rsi_length)
// StochRSI transformation
stochRSI = ((ta.highest(rsi, stoch_length) - ta.lowest(rsi, stoch_length)) != 0) ?
(100 * (rsi - ta.lowest(rsi, stoch_length))) /
(ta.highest(rsi, stoch_length) - ta.lowest(rsi, stoch_length)) : 0
2. Signal Generation System:
// Core signal conditions
crossover_buy = crossOver(sk, sd, cross_threshold)
valid_buy_zone = sk < 30 and sd < 30
price_within_sma_bands = close <= sma_high and close >= sma_low
// Enhanced signal generation
if crossover_buy and valid_buy_zone and price_within_sma_bands and htf_allows_long
if is_bullish_candle
long_signal := true
else
awaiting_bull_confirmation := true
3. Multi-Timeframe Analysis:
= request.security(syminfo.tickerid, mtf_period,
)
The HTF filter looks at a higher timeframe (default: 4H) to confirm the trend
It only allows:
Long trades when the higher timeframe is bullish
Short trades when the higher timeframe is bearish
📈 Trading Application Guide:
1. Signal Identification
• Oversold Opportunities (< 30 level)
- Look for bullish crosses of K-line above D-line
- Confirm with higher timeframe alignment
- Wait for price action confirmation (bullish candle)
• Overbought Conditions (> 70 level)
- Watch for bearish crosses of K-line below D-line
- Verify higher timeframe condition
- Confirm with bearish price action
2. Divergence Trading
• Bullish Divergence
- Price makes lower lows while indicator makes higher lows
- Most effective when occurring in oversold territory
- Use with support levels for entry timing
• Bearish Divergence
- Price makes higher highs while indicator shows lower highs
- Most reliable in overbought conditions
- Combine with resistance levels
3. Wave Effect Analysis
• Strong Waves
- Multiple wave lines moving in same direction indicate momentum
- Wider wave spread suggests increased volatility
- Use for trend strength confirmation
• Energy Field
- Higher intensity in trading zones suggests stronger moves
- Use for momentum confirmation
- Watch for energy field convergence with price action
The energy field is like a heat map that shows momentum strength
It gets stronger (more visible) when:
Price is in oversold (<30) or overbought (>70) zones
The indicator lines are moving apart quickly
A strong signal is forming
Think of it as a "strength meter" - the more visible the energy field, the stronger the potential move
4. Risk Management Integration
• Entry Confirmation
- Wait for all signal components to align
- Use higher timeframe for trend direction
- Confirm with price action and SMA positions
• Stop Loss Placement
- Consider placing stops beyond recent swing points
- Use ATR for dynamic stop calculation
- Account for market volatility
5. Position Management
• Partial Profit Taking
- Consider scaling out at overbought/oversold levels
- Use wave effect intensity for exit timing
- Monitor energy field for momentum shifts
• Trade Duration
- Short-term: Use primary signals in trading zones
- Swing trades: Focus on divergence signals
- Position trades: Utilize higher timeframe signals
⚠️ Important Usage Notes:
• Avoid:
- Trading against strong trends
- Relying solely on single signals
- Ignoring higher timeframe context
- Over-leveraging based on signals
Remember: This tool is designed to assist in analysis but should never be used as the sole decision-maker for trades. Always maintain proper risk management and combine with other forms of analysis.
mystochrsirsi + stochrsi
Indicator where rsi and stoch rsi are both together. Please adjust the color etc settings from the style tab.
Guth_3X_ConfirmThis indicator has three built in indicators based on the SMA of HIGH, SMA of LOW, and Stochastic. The baseline indicator is the retreats after departures from SMA of HIGH and LOW.
The first time a HIGH that is above the SMA HIGH has a lower HIGH but it still above the SMA HIGH, a (-) will appear at the bottom. This signals an aggressive entry point for potential coming downtrend. The second time the HIGH produces a lower high but is still above the SMA HIGH, a (S) will appear at the bottom which signals a more conservative entry point for potential coming downtrend. All of the opposite information is true of reversals beyond the SMA LOW.
When these reversals appear the same time the Stochastic is overbought or oversold, a red bar (overbought and potentially coming down) or a green bar (oversold and potentially coming up) will appear. NOTE: Aggressive symbols occur more often and will always occur when a conservative symbol appears. When a conservative indicator and respective overbought/oversold level occur at the same time, the bar is darker in color.
You can enter positions at any one of the indicators, however, the darker bars are what I look for. This has a high success rate but cannot guarantee results every time. I recommend adjusting the SMA, and Stoch parameters as well as time periods. I have had success with this indicator while day trading the 5, 10, 15, 30, 65 minute periods as well as daily and weekly periods. Every symbol traded can provide differing results based on the parameters used.
Please feel free to leave feedback and I know this can work well for you!
BB Running Away CandleHello,
here is an indicator that can be helpful for your trading that is simple and easy to use.
Our culprit here is a candle that opens and closes below the lower band of Bollinger Band, Black and red lines are put on the high and low of that candle.
Green Arrows are happening when:
1- When candle closes above the black line and Stochastic RSI is in the oversold area >> "Confirmed B"
2- When candle closes above the black line >> "B"
Note that you can choose from the settings whether you want it confirmed or not.
Red Arrows are happening when:
1- Price reached the higher band of Bollinger Bands >> "BB High"
2- Stochastic crosses down from above 80 level >> "Stoch Crossdown"
3- RSI reached above 70 levle >> "RSI Oversold"
Note that you can choose to turn these on or off from the settings.
Settings of indicators are set to default.
NOTE: Alerts are put there however i didn't get the chance to test them, so would like to hear your feedback about them.
THE USE OF THIS INDICATOR IS YOUR OWN RESPONSIBILITY.
wishing you the best.
+ JMA KDJ with RSI OB/OS SignalsSo, what is the KDJ indicator? If you're familiar with the Stochastic, then you'll know that the two oscillating lines are called the 'K' and 'D' lines. Now you know that this is some sort of implementation of the Stochastic. But, then, what is the J? The 'J' is simply the measure of convergence/divergence of the 'K' and 'D' lines, and the 'J' crossing the 'K' and 'D' lines is representational of the 'K' and 'D' lines themselves crossing. Is this an improvement over simply using the Stochastic as it is? Beats me. I don't use the Stochastic. I stumbled upon the KDJ while surfing around the web, and it sounded cool, so I thought I'd look at it. I do like it a bit more as the 'J' line being far overextended from the other two (usually into overbought/sold territory) does give a clear visual representation of the divergence of the 'K' and 'D' lines, which you might not notice otherwise. So, from that perspective I suppose it is nicer.
But let's get to the good stuff now, shall we? What did I do here?
Well, first thing you're wondering is why there are only two lines when based on my explanation (or your previous experience with the indicator) there should be three. I found this script here on TV, by x4random, who took the 'K' and 'D' lines and made an average of them, so there is only one line instead of the two. So, fewer lines on the indicator, but still the same usefulness. It was in older TV code, so I took it to version4 and cleaned up the code slightly. His indicator included the RSI ob/os plots, and I thought this was neat (even though the RSI being os/ob doesn't tell you much except that the trend is strong, and you should be buying pullback or selling rallies) so I kept them in. His indicator was also the most visually appealing one that I saw on here, so that attracted me too. Credit to x4random for the indicator, though.
Aside from code cleanup and adding the usual bells and whistles (which I will get to) the big thing I did here was change is RMA that he was using for the 'K' and 'D' lines to a Jurik MA's, which smooth a lot of the noise of other moving averages while maintaining responsiveness. This eliminates noise (false signals) while keeping the signals of significance. It took me a while to figure out how to substitute the JMA for the RMA, but thanks to QuantTherapy's "Jurik PPO" indicator I was able to nail down the implementation. One thing you might notice is that there is no input to change signal length. I fiddled with this for a time before sticking to using the period, instead of the signal (thus eliminating the use of the signal input altogether), length to generate the 'K' and 'D' calculations. To make any adjustments other than the period length use the Jurik Power input. You can use the phase input as well, but it has much less of an effect.
Everything else I changed is pretty much cosmetic.
Candle coloring with the option to color candles based on either the 'J' line or the 'KD' line.
color.from_gradients with color inputs to make it beautiful (this is probably my best looking indicator, imo)
plots for when crosses occur (really wish there was a way to plot these over candlesticks! If anyone has any suggestions I'd love to see!)
I think that's about it. Alerts of course.
Enjoy!
Below is a comparison chart of my JMA implementation to the original RMA script.
You can see how much smoother the JMA version is. Both of these had the default period of 55 set, and the JMA version is using the default settings, while the original version is using a length of 3 for the signal line.
[Coingrats]RSI Divergence + StochRSIThis indicator shows the RSI and StochRSI. RSI divergence will also be marked.
- Bullish divergence - green triangle,
- Hidden bullish divergence - gray triangle
- Bearish divergence = red triangle
- Hidden bearish divergence - gray triangle
Credits to BabyWhale83 for the code to spotting divergence
WANNA TIP ME? BUY ME SOME BEERS!
BTC: 3BMEXX5JrX94ziUSoQMLEmi51WcYwphAg3
ETH: 0x541e504bb461aa141de6ddce09dc89eb16f58f9c
LTC: LPBJXzUZJksCuCK27AY2qAVYGGGiUfejok
DON'T FORGET TO LOOK AT OUR SITE MYCRYPTODARAR.COM
Multi-Timeframe Stochs by Tom L.I find it really usefull. Can put 4 different timeframes.
Thanks again to Tom !
PMA4LIFE
RAF3x
Dual Stochastic with Trend FilterThe "Dual Stochastic with Trend Filter" is an oscillator indicator designed to provide clearer, trend-aligned trading signals. It uses two distinct stochastic oscillators to identify potential entry points and incorporates an optional EMA-based trend filter to ensure that you are trading in the direction of the broader market momentum.
How It Works and How to Use It
This indicator combines two key technical analysis concepts: momentum (via stochastics) and trend (via moving averages).
Core Components:
Dual Stochastic Oscillators:
Signal Line 1 (Blue): A standard stochastic oscillator.
Signal Line 2 (Red): A second stochastic oscillator, often using a different source (like hlcc4) to provide a smoother, more reliable signal.
A buy signal is generated when the Blue Line (d1) crosses above the Red Line (d2).
A sell signal is generated when the Blue Line (d1) crosses below the Red Line (d2).
Trend Filter (Optional):
This feature uses a fast and a slow Exponential Moving Average (EMA) to determine the overall market trend.
When the fast EMA is above the slow EMA, the background will turn green, indicating an uptrend.
When the fast EMA is below the slow EMA, the background will turn red, indicating a downtrend.
This filter can be toggled on or off in the indicator settings.
How to Use:
With Trend Filter Enabled (Recommended):
Long (Buy) Entry: Look for a green triangle buy signal (▲). This signal only appears when:
The Blue Signal Line crosses above the Red Signal Line.
The market is in a confirmed uptrend (green background).
Short (Sell) Entry: Look for a red triangle sell signal (▼). This signal only appears when:
The Blue Signal Line crosses below the Red Signal Line.
The market is in a confirmed downtrend (red background).
Exit Signal:
A yellow circle (●) appears to suggest closing an open trade. This signal is triggered for a long position if either the stochastics have a bearish cross or the trend flips to a downtrend. Conversely, for a short position, it's triggered by a bullish stochastic cross or a trend flip to an uptrend.
With Trend Filter Disabled:
If you turn off the "Use Trend Filter" option, the indicator will function as a simple dual stochastic crossover system.
A green triangle (▲) will appear every time the Blue Line crosses above the Red Line.
A red triangle (▼) will appear every time the Blue Line crosses below the Red Line.
The background coloring and exit signals based on trend flips will be deactivated. This mode is more sensitive but may produce more false signals in choppy markets.
Key Visuals:
Blue Line: The primary signal line.
Red Line: The secondary, often smoother, signal line.
Green Triangle (▲): Bullish entry signal.
Red Triangle (▼): Bearish entry signal.
Yellow Circle (●): Suggested trade exit/stop.
Green/Red Background: Visual confirmation of the current uptrend or downtrend.
By filtering stochastic signals with the dominant trend, this indicator helps traders avoid common pitfalls like entering short positions during a strong uptrend or buying into a bearish market. This alignment of momentum and trend is key to improving signal quality.
Disclaimer
This indicator is provided for educational and informational purposes only and should not be considered as financial advice or a recommendation to buy or sell any asset. All trading and investment decisions are your own sole responsibility.
Trading financial markets involves a high level of risk, and you may lose more than your initial investment. Past performance is not indicative of future results. The signals generated by this indicator are not guaranteed to be accurate, and you should always use this tool in conjunction with other forms of analysis and sound risk management practices.
Before using this indicator in a live trading environment, it is strongly recommended that you backtest it thoroughly and practice with it on a demo account. The author is not responsible for any financial losses you may incur from using this script.
Trigonometric StochasticTrigonometric Stochastic - Mathematical Smoothing Oscillator
Overview
A revolutionary approach to stochastic oscillation using sine wave mathematical smoothing. This indicator transforms traditional stochastic calculations through trigonometric functions, creating an ultra-smooth oscillator that reduces noise while maintaining sensitivity to price changes.
Mathematical Foundation
Unlike standard stochastic oscillators, this version applies sine wave smoothing:
• Raw Stochastic: (close - lowest_low) / (highest_high - lowest_low) × 100
• Trigonometric Smoothing: 50 + 50 × sin(2π × raw_stochastic / 100)
• Result: Naturally smooth oscillator with mathematical precision
Key Features
Advanced Smoothing Technology
• Sine Wave Filter: Eliminates choppy movements while preserving signal integrity
• Natural Boundaries: Mathematically constrained between 0-100
• Reduced False Signals: Trigonometric smoothing filters market noise effectively
Traditional Stochastic Levels
• Overbought Zone: 80 level (dashed line)
• Oversold Zone: 20 level (dashed line)
• Midline: 50 level (dotted line) - equilibrium point
• Visual Clarity: Clean oscillator panel with clear level markings
Smart Signal Generation
• Anti-Repaint Logic: Uses confirmed previous bar values
• Buy Signals: Generated when crossing above 30 from oversold territory
• Sell Signals: Generated when crossing below 70 from overbought territory
• Crossover Detection: Precise entry/exit timing
Professional Presentation
• Separate Panel: Dedicated oscillator window (overlay=false)
• Price Format: Formatted as price indicator with 2-decimal precision
• Theme Adaptive: Automatically matches your chart color scheme
Parameters
• Cycle Length (5-200): Period for highest/lowest calculations
- Shorter periods = more sensitive, more signals
- Longer periods = smoother, fewer but stronger signals
Trading Applications
Momentum Analysis
• Overbought/Oversold: Clear visual identification of extreme levels
• Momentum Shifts: Early detection of momentum changes
• Trend Strength: Monitor oscillator position relative to midline
Signal Trading
• Long Entries: Buy when crossing above 30 (oversold bounce)
• Short Entries: Sell when crossing below 70 (overbought rejection)
• Confirmation Tool: Use with trend indicators for higher probability trades
Divergence Detection
• Bullish Divergence: Price makes lower lows, oscillator makes higher lows
• Bearish Divergence: Price makes higher highs, oscillator makes lower highs
• Early Warning: Spot potential trend reversals before they occur
Trading Strategies
Scalping (5-15min timeframes)
• Use cycle length 10-14 for quick signals
• Focus on 20/80 level bounces
• Combine with price action confirmation
Swing Trading (1H-4H timeframes)
• Use cycle length 20-30 for reliable signals
• Wait for clear crossovers with momentum
• Monitor divergences for reversal setups
Position Trading (Daily+ timeframes)
• Use cycle length 50+ for major signals
• Focus on extreme readings (below 10, above 90)
• Combine with fundamental analysis
Advantages Over Standard Stochastic
1. Smoother Action: Sine wave smoothing reduces whipsaws
2. Mathematical Precision: Trigonometric functions provide consistent behavior
3. Maintained Sensitivity: Smoothing doesn't compromise signal quality
4. Reduced Noise: Cleaner signals in volatile markets
5. Visual Appeal: More aesthetically pleasing oscillator movement
Best Practices
• Market Context: Consider overall trend direction
• Multiple Timeframe: Confirm signals on higher timeframes
• Risk Management: Always use proper position sizing
• Backtesting: Test parameters on your preferred instruments
• Combination: Works excellently with trend-following indicators
Built-in Alerts
• Buy Alert: Trigonometric stochastic oversold crossover
• Sell Alert: Trigonometric stochastic overbought crossunder
Technical Specifications
• Pine Script Version: v6
• Panel: Separate oscillator window
• Format: Price indicator with 2-decimal precision
• Performance: Optimized for all timeframes
• Compatibility: Works with all instruments
Free and open-source indicator. Modify, improve, and share with the community!
Educational Value: Perfect for traders wanting to understand how mathematical smoothing improves oscillators and trigonometric applications in technical analysis.
Momentum + Keltner Stochastic Combo)The Momentum-Keltner-Stochastic Combination Strategy: A Technical Analysis and Empirical Validation
This study presents an advanced algorithmic trading strategy that implements a hybrid approach between momentum-based price dynamics and relative positioning within a volatility-adjusted Keltner Channel framework. The strategy utilizes an innovative "Keltner Stochastic" concept as its primary decision-making factor for market entries and exits, while implementing a dynamic capital allocation model with risk-based stop-loss mechanisms. Empirical testing demonstrates the strategy's potential for generating alpha in various market conditions through the combination of trend-following momentum principles and mean-reversion elements within defined volatility thresholds.
1. Introduction
Financial market trading increasingly relies on the integration of various technical indicators for identifying optimal trading opportunities (Lo et al., 2000). While individual indicators are often compromised by market noise, combinations of complementary approaches have shown superior performance in detecting significant market movements (Murphy, 1999; Kaufman, 2013). This research introduces a novel algorithmic strategy that synthesizes momentum principles with volatility-adjusted envelope analysis through Keltner Channels.
2. Theoretical Foundation
2.1 Momentum Component
The momentum component of the strategy builds upon the seminal work of Jegadeesh and Titman (1993), who demonstrated that stocks which performed well (poorly) over a 3 to 12-month period continue to perform well (poorly) over subsequent months. As Moskowitz et al. (2012) further established, this time-series momentum effect persists across various asset classes and time frames. The present strategy implements a short-term momentum lookback period (7 bars) to identify the prevailing price direction, consistent with findings by Chan et al. (2000) that shorter-term momentum signals can be effective in algorithmic trading systems.
2.2 Keltner Channels
Keltner Channels, as formalized by Chester Keltner (1960) and later modified by Linda Bradford Raschke, represent a volatility-based envelope system that plots bands at a specified distance from a central exponential moving average (Keltner, 1960; Raschke & Connors, 1996). Unlike traditional Bollinger Bands that use standard deviation, Keltner Channels typically employ Average True Range (ATR) to establish the bands' distance from the central line, providing a smoother volatility measure as established by Wilder (1978).
2.3 Stochastic Oscillator Principles
The strategy incorporates a modified stochastic oscillator approach, conceptually similar to Lane's Stochastic (Lane, 1984), but applied to a price's position within Keltner Channels rather than standard price ranges. This creates what we term "Keltner Stochastic," measuring the relative position of price within the volatility-adjusted channel as a percentage value.
3. Strategy Methodology
3.1 Entry and Exit Conditions
The strategy employs a contrarian approach within the channel framework:
Long Entry Condition:
Close price > Close price periods ago (momentum filter)
KeltnerStochastic < threshold (oversold within channel)
Short Entry Condition:
Close price < Close price periods ago (momentum filter)
KeltnerStochastic > threshold (overbought within channel)
Exit Conditions:
Exit long positions when KeltnerStochastic > threshold
Exit short positions when KeltnerStochastic < threshold
This methodology aligns with research by Brock et al. (1992) on the effectiveness of trading range breakouts with confirmation filters.
3.2 Risk Management
Stop-loss mechanisms are implemented using fixed price movements (1185 index points), providing definitive risk boundaries per trade. This approach is consistent with findings by Sweeney (1988) that fixed stop-loss systems can enhance risk-adjusted returns when properly calibrated.
3.3 Dynamic Position Sizing
The strategy implements an equity-based position sizing algorithm that increases or decreases contract size based on cumulative performance:
$ContractSize = \min(baseContracts + \lfloor\frac{\max(profitLoss, 0)}{equityStep}\rfloor - \lfloor\frac{|\min(profitLoss, 0)|}{equityStep}\rfloor, maxContracts)$
This adaptive approach follows modern portfolio theory principles (Markowitz, 1952) and Kelly criterion concepts (Kelly, 1956), scaling exposure proportionally to account equity.
4. Empirical Performance Analysis
Using historical data across multiple market regimes, the strategy demonstrates several key performance characteristics:
Enhanced performance during trending markets with moderate volatility
Reduced drawdowns during choppy market conditions through the dual-filter approach
Optimal performance when the threshold parameter is calibrated to market-specific characteristics (Pardo, 2008)
5. Strategy Limitations and Future Research
While effective in many market conditions, this strategy faces challenges during:
Rapid volatility expansion events where stop-loss mechanisms may be inadequate
Prolonged sideways markets with insufficient momentum
Markets with structural changes in volatility profiles
Future research should explore:
Adaptive threshold parameters based on regime detection
Integration with additional confirmatory indicators
Machine learning approaches to optimize parameter selection across different market environments (Cavalcante et al., 2016)
References
Brock, W., Lakonishok, J., & LeBaron, B. (1992). Simple technical trading rules and the stochastic properties of stock returns. The Journal of Finance, 47(5), 1731-1764.
Cavalcante, R. C., Brasileiro, R. C., Souza, V. L., Nobrega, J. P., & Oliveira, A. L. (2016). Computational intelligence and financial markets: A survey and future directions. Expert Systems with Applications, 55, 194-211.
Chan, L. K. C., Jegadeesh, N., & Lakonishok, J. (2000). Momentum strategies. The Journal of Finance, 51(5), 1681-1713.
Jegadeesh, N., & Titman, S. (1993). Returns to buying winners and selling losers: Implications for stock market efficiency. The Journal of Finance, 48(1), 65-91.
Kaufman, P. J. (2013). Trading systems and methods (5th ed.). John Wiley & Sons.
Kelly, J. L. (1956). A new interpretation of information rate. The Bell System Technical Journal, 35(4), 917-926.
Keltner, C. W. (1960). How to make money in commodities. The Keltner Statistical Service.
Lane, G. C. (1984). Lane's stochastics. Technical Analysis of Stocks & Commodities, 2(3), 87-90.
Lo, A. W., Mamaysky, H., & Wang, J. (2000). Foundations of technical analysis: Computational algorithms, statistical inference, and empirical implementation. The Journal of Finance, 55(4), 1705-1765.
Markowitz, H. (1952). Portfolio selection. The Journal of Finance, 7(1), 77-91.
Moskowitz, T. J., Ooi, Y. H., & Pedersen, L. H. (2012). Time series momentum. Journal of Financial Economics, 104(2), 228-250.
Murphy, J. J. (1999). Technical analysis of the financial markets: A comprehensive guide to trading methods and applications. New York Institute of Finance.
Pardo, R. (2008). The evaluation and optimization of trading strategies (2nd ed.). John Wiley & Sons.
Raschke, L. B., & Connors, L. A. (1996). Street smarts: High probability short-term trading strategies. M. Gordon Publishing Group.
Sweeney, R. J. (1988). Some new filter rule tests: Methods and results. Journal of Financial and Quantitative Analysis, 23(3), 285-300.
Wilder, J. W. (1978). New concepts in technical trading systems. Trend Research.
Christmas Toolkit [LuxAlgo]It's that time of the year... and what would be more appropriate than displaying Christmas-themed elements on your chart?
The Christmas Toolkit displays a tree containing elements affected by various technical indicators. If you're lucky, you just might also find a precious reindeer trotting toward the tree, how fancy!
🔶 USAGE
Each of the 7 X-mas balls is associated with a specific condition.
Each ball has a color indicating:
lime: very bullish
green: bullish
blue: holding the same position or sideline
red: bearish
darkRed: very bearish
From top to bottom:
🔹 RSI (length 14)
rsi < 20 - lime (+2 points)
rsi < 30 - green (+1 point)
rsi > 80 - darkRed (-2 points)
rsi > 70 - red (-1 point)
else - blue
🔹 Stoch (length 14)
stoch < 20 - lime (+2 points)
stoch < 30 - green (+1 point)
stoch > 80 - darkRed (-2 points)
stoch > 70 - red (-1 point)
else - blue
🔹 close vs. ema (length 20)
close > ema 20 - green (+1 point)
else - red (-1 point)
🔹 ema (length 20)
ema 20 rises - green (+1 point)
else - red (-1 point)
🔹 ema (length 50)
ema 50 rises - green (+1 point)
else - red (-1 point)
🔹 ema (length 100)
ema 100 rises - green (+1 point)
else - red (-1 point)
🔹 ema (length 200)
ema 200 rises - green (+1 point)
else - red (-1 point)
The above information can also be found on the right side of the tree.
You'll see the conditions associated with the specific X-mas ball and the meaning of color changes. This can also be visualized by hovering over the labels.
All values are added together, this result is used to color the star at the top of the tree, with a specific color indicating:
lime: very bullish (> 6 points)
green: bullish (6 points)
blue: holding the same position or sideline
red: bearish (-6 points)
darkRed: very bearish (< -6 points)
Switches to green/lime or red/dark red can be seen by the fallen stars at the bottom.
The Last Switch indicates the latest green/lime or red/dark red color (not blue)
🔶 ANIMATION
Randomly moving snowflakes are added to give it a wintry character.
There are also randomly moving stars in the tree.
Garland rotations, style, and color can be adjusted, together with the width and offset of the tree, put your tree anywhere on your chart!
Disabling the "static tree" setting will make the needles 'move'.
Have you happened to see the precious reindeer on the right? This proud reindeer moves towards the most recent candle. Who knows what this reindeer might be bringing to the tree?
🔶 SETTINGS
Width: Width of tree.
Offset: Offset of the tree.
Garland rotations: Amount of rotations, a high number gives other styles.
Color/Style: sets the color & style of garland stars.
Needles: sets the needle color.
Static Tree: Allows the tree needles to 'move' with each tick.
Reindeer Speed: Controls how fast the deer moves toward the most recent bar.
🔶 MESSAGE FROM THE LUXALGO TEAM
It has been an honor to contribute to the TradingView community and we are always so happy to see your supportive messages on our scripts.
We have posted a total of 78 script publications this year, which is no small feat & was only possible thanks to our team of Wizard developers @alexgrover + @dgtrd + @fikira , the development team behind Pine Script, and of course to the support of our legendary community.
Happy Holidays to you all, and we'll see ya next year! ☃️
VCC SmtmWorks better for Cryptos (1W and greater than) timeframes.
This strategy incorporates multiple indicators to make informed trading signals. It leverages the Stochastic indicator to assess price momentum, utilizes the Bollinger Band to identify potential oversold and overbought conditions, and closely monitors Moving Averages to gauge the trend's bullish or bearish nature.
A long signal will be displayed if the following conditions are met:
The Stochastic D and Stochastic K both indicate an oversold condition, with Stochastic K being lower than Stochastic D.
The current Price Low is below the Bollinger Lower Band.
The Price Close is currently below all Moving Averages.
A Death Cross pattern has formed among the Moving Averages.
A short signal will be displayed if the opposite of the long conditions are true:
The Stochastic D and Stochastic K both indicate an overbought condition, with Stochastic K being higher than Stochastic D.
The current Price High is above the Bollinger Upper Band.
The Price Close is currently above all Moving Averages.
A Golden Cross pattern has formed among the Moving Averages.
User Defined Momentum Change with Swing VisualsThis script is a groundbreaking, math-centric technical analysis tool that blends two well-established indicators, the Stochastic Oscillator and the Exponential Moving Average (EMA), to deliver a unique and visually engaging way of identifying momentum swings and stochastic indicators. Unlike mashups, this script is tailored to accommodate a wide range of trading strategies, providing traders with a distinctive perspective on market trends.
The innovation in this script lies in its mathematically-driven ability to effectively combine the Stochastic Oscillator and EMA, setting it apart from other available tools that simply offer a rehash of old ideas or slight modifications to popular indicators. The EMA is employed instead of a Simple Moving Average (SMA), enhancing the uniqueness of the calculations. This novel approach creates a new dimension for traders to evaluate potential momentum swings and visualize them on the chart, proving it to be more than just a mere mashup of existing indicators.
Central to the script's utility is its extensive customization options, which allow traders to adjust various inputs to suit their preferences and trading strategies. Users can modify the EMA length, swing range signal offsets, and smoothing factors for both the fast and slow components of the Stochastic Oscillator. Additionally, the script offers the ability to personalize the color thresholds, transparency, and line properties for the Stochastic Oscillator and swing range signal.
This script's visually dynamic representation of momentum swings empowers traders to make more informed trading decisions, particularly on the 6-hour timeframe. The swing range signal, represented by vertical lines on the chart, acts as a valuable visual aid for identifying potential entry or exit points. Furthermore, the Stochastic Oscillator provides insights into the strength and direction of momentum, which is beneficial for confirming potential trade signals.
To conclude, this script is not just another combination of MAs or a slightly modified version of a popular indicator. Instead, it offers traders a comprehensive, visually appealing, and customizable tool for technical analysis, which is both original and useful. By uniquely combining the EMA and the Stochastic Oscillator with a strong mathematical foundation, and allowing traders to adjust a variety of settings, this script adds value to the TradingView community and enhances the body of knowledge available for traders. It is designed to support traders in tailoring their analysis based on their own strategies and preferences, enabling them to make well-informed decisions in the financial markets.
RSI and Stochastic Probability Based Price Target IndicatorHello,
Releasing this beta indicator. It is somewhat experimental but I have had some good success with it so I figured I would share it!
What is it?
This is an indicator that combines RSI and Stochastics with probability levels.
How it works?
This works by applying a regression based analysis on both Stochastics and RSI to attempt to predict a likely close price of the stock.
It also assess the normal distribution range the stock is trading in. With this information it does the following:
2 lines are plotted:
Yellow line: This is the stochastic line. This represents the smoothed version of the stochastic price prediction of the most likely close price.
White Line: This is the RSI line. It represents the smoothed version of the RSI price prediction of the most likely close price.
When the Yellow Line (Stochastic Line) crosses over the White Line (the RSI line), this is a bearish indication. It will signal a bearish cross (red arrow) to signal that some selling or pullback may follow.
IF this bearish cross happens while the stock is trading in a low probability upper zone (anything 13% or less), it will trigger a label to print with a pullback price. The pullback price is the "regression to the mean" assumption price. Its the current mean at the time of the bearish cross.
The inverse is true if it is a bullish cross. If the stock has a bullish cross and is trading in a low probability bearish range, it will print the price target for a regression back to the upward mean.
Additional information:
The indicator also provides a data table. This data table provides you with the current probability range (i.e. whether the stock is trading in the 68% probability zone or the outer 13, 2.1 or 0.1 probability zones), as well as the overall probability of a move up or down.
It also provides the next bull and bear targets. These are calculated based on the next probability zone located immediately above and below the current trading zone of the stock.
Smoothing vs Non-smoothed data:
For those who like to assess RSI and Stochastic for divergences, there is an option in the indicator to un-smooth the stochastic and RSI lines. Doing so looks like this:
Un-smoothing the RSI and stochastic will not affect the analysis or price targets. However it does add some noise to the chart and makes it slightly difficult to check for crosses. But whatever your preference is you can use.
Cross Indicators :
A bearish cross (stochastic crosses above RSI line) is signalled with a red arrow down shape.
A bullish cross (RSI crosses above stochastic line) is signalled with a green arrow up shape.
Labels vs Arrows:
The arrows are lax in their signalling. They will signal at any cross. Thus you are inclined to get false signals.
The labels are programmed to only trigger on high probability setups.
Please keep this in mind when using the indicator!
Warning and disclaimer:
As with all indicators, no indicator is 100% perfect.
This will not replace the need for solid analysis, risk management and planning.
This is also kind of beta in its approach. As such, there are no real rules on how it should be or can be applied rigorously. Thus, its important to exercise caution and not rely on this alone. Do your due diligence before using or applying this indicator to your trading regimen.
As it is kind of different, I am interested in hearing your feedback and experience using it. Let me know your feedback, experiences and suggestions below.
Also, because it does have a lot of moving parts, I have done a tutorial video on its use linked below:
Thanks for checking it out, safe trades everyone and take care!
DSS of Advanced Kaufman AMA [Loxx]DSS of Advanced Kaufman AMA is a double smoothed stochastic oscillator using a Kaufman adaptive moving average with the option of using the Jurik Fractal Dimension Adaptive calculation. This helps smooth the stochastic oscillator thereby making it easier to identify reversals and trends.
What is the double smoothed stochastic?
The Double Smoothed Stochastic indicator was created by William Blau. It applies Exponential Moving Averages (EMAs) of two different periods to a standard Stochastic %K. The components that construct the Stochastic Oscillator are first smoothed with the two EMAs. Then, the smoothed components are plugged into the standard Stochastic formula to calculate the indicator.
What is KAMA?
Developed by Perry Kaufman, Kaufman's Adaptive Moving Average (KAMA) is a moving average designed to account for market noise or volatility . KAMA will closely follow prices when the price swings are relatively small and the noise is low. KAMA will adjust when the price swings widen and follow prices from a greater distance. This trend-following indicator can be used to identify the overall trend, time turning points and filter price movements.
What is the efficiency ratio?
In statistical terms, the Efficiency Ratio tells us the fractal efficiency of price changes. ER fluctuates between 1 and 0, but these extremes are the exception, not the norm. ER would be 1 if prices moved up 10 consecutive periods or down 10 consecutive periods. ER would be zero if price is unchanged over the 10 periods.
What is Jurik Fractal Dimension?
There is a weak and a strong way to measure the random quality of a time series.
The weak way is to use the random walk index ( RWI ). You can download it from the Omega web site. It makes the assumption that the market is moving randomly with an average distance D per move and proposes an amount the market should have changed over N bars of time. If the market has traveled less, then the action is considered random, otherwise it's considered trending.
The problem with this method is that taking the average distance is valid for a Normal (Gaussian) distribution of price activity. However, price action is rarely Normal, with large price jumps occuring much more frequently than a Normal distribution would expect. Consequently, big jumps throw the RWI way off, producing invalid results.
The strong way is to not make any assumption regarding the distribution of price changes and, instead, measure the fractal dimension of the time series. Fractal Dimension requires a lot of data to be accurate. If you are trading 30 minute bars, use a multi-chart where this indicator is running on 5 minute bars and you are trading on 30 minute bars.
Included
-Toggle bar colors on/offf
High and Low Checker
GBPUSD / 3m
BTCUSD / 5m
This is an indicator used to know the tops and bottoms of the market.
The logic is simple.
1. find out whether the current price is above or below the past by a very slow stoch.
2. Find out if the RSI is overbought or oversold.
3. Combine these two conditions and find out if the current price is tops or bottoms than it was in the past.
Appropriate settings will vary depending on the market and the time frame. Try changing various settings!
It is also not useful in markets that are experiencing a very strong trend.
For this case, we have chosen to display overshoot.
日本語
これは相場の天井と底をスナイプするために作ったインジケーターです。
ロジックはいたってシンプルです。
1. 非常に期間の長いStochを使い現在の価格が、過去から見て上か下に位置するのかを判断します。
2. RSIの買われすぎ、売られ過ぎを判断します。
3. この2つを組み合わせます。価格帯が上に位置する場合買われ過ぎが有効になり、価格帯が下に位置する場合売られ過ぎが有効になります。
銘柄や時間軸によって適切な設定値が変わると思うので、色々と試してみて下さい。
また、非常に強いトレンドが発生している相場では基本的に役に立ちません。
その場合のために、オーバーシュート(×マーク)を表示するようにしているので、参考にして下さい。
[blackcat] L2 Ehlers SwamiCharts StochasticLevel: 2
Background
John F. Ehlers introuced SwamiCharts Stochastic Indicator in Mar, 2012.
Function
In the late 1950s, George Lane developed stochastics, an indicator that measures the relationship between an issue's closing price and its price range over a predetermined period of time. To this day, stochastics is a favored technical indicator because it is easy to understand and has a high degree of accuracy in indicating whether it's time to buy or sell a security. In “Introducing SwamiCharts” in Mar, 2012, authors John Ehlers & Ric Way presented the use of SwamiCharts to better visualize market activity using an indicator that presents a heatmap visualization. The authors provided descriptions for the construction of SwamiCharts using Stochastic indicator.
Key Signal
Stochastic ---> Stochastic array
Plot2~48 ---> SwamiCharts Stochastic Heat Map
Pros and Cons
100% John F. Ehlers definition translation, even variable names are the same. This help readers who would like to use pine to read his book.
Remarks
The 78th script for Blackcat1402 John F. Ehlers Week publication.
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.
[blackcat] L2 Ehlers Adaptive StochasticLevel: 2
Background
John F. Ehlers introuced Adaptive Stochastic in his "Rocket Science for Traders" chapter 21 on 2001.
Function
The Stochastic measures the current closing price relative to the lowest low over the observation period. It then normalizes this to the range between the highest high and the lowest low over the observation period. If the current closing price is equal to the highest high over the observation period, then the Stochastic has a value of 1. If the current closing price is equal to the lowest low over the observation period, then the Stochastic has a value of zero. These are the limits over which the Stochastic can range. To optimize the Stochastic for the measured cycle, the correct fraction of the cycle to use is one-half, as the Stochastic can
range from its minimum to its maximum on each half cycle of the period. As before, the code for the optimized Stochastic measures the cycle period using the Homodyne Discriminator algorithm and then uses that period as the basis for finding HH and LL and computing the Stochastic. Since half the cycle period may not be the universal answer, we include a CycPart input as a modifier. This input allows you to optimize the observation period for each particular situation. The optimized Stochastic tends to be in phase with the original price data. This suggests a way to turn a good indicator into a great one. If we subtract 50 from the optimized Stochastic, we would get a zero mean and thus tend to have Poisson-like statistics on the Stochastic’s zero crossings. If that were the case, we could smooth the optimized Stochastic and make an Optimum Predictive filter from it. That way we could anticipate signals rather than wait for signals to cross the 20 percent and 80 percent marks for confirmation as is done with the standard indicator. I will leave it to you to decide which method best suits your needs and purposes.
Key Signal
Stochastic ---> Stochastic fast line
Stochastic ---> Stochastic slow line
Pros and Cons
100% John F. Ehlers definition translation of original work, even variable names are the same. This help readers who would like to use pine to read his book. If you had read his works, then you will be quite familiar with my code style.
Remarks
The 19th script for Blackcat1402 John F. Ehlers Week publication.
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.
Advanced Directional Stoch RSIAdvanced Directional Stochastic RSI
Overview
The Advanced Directional Stochastic RSI (Adv Stoch RSI Dir) is a powerful oscillator that combines the classic Stochastic RSI with John Ehlers' SuperSmoother filter for ultra-smooth signals and reduced noise. Unlike traditional Stoch RSI, this indicator incorporates directional coloring based on price action relative to a smoothed trend line, helping traders quickly spot bullish or bearish momentum. It's designed for swing traders and scalpers looking for clearer overbought/oversold conditions in volatile markets.
Key Features
Directional Coloring: %K line turns green when price is above the trend MA (bullish) and red when below (bearish), providing instant visual bias.
Multi-Pass SuperSmoothing: Apply Ehlers' SuperSmoother filter up to 5 times for customizable noise reduction—dial in passes (default: 2) to balance responsiveness and smoothness.
Trend-Aware Baseline: Uses a cascaded smoothed moving average (default length: 20) to gauge overall direction, making the oscillator more context-aware.
Classic Stoch RSI Core: Built on RSI (default: 14) and Stochastic (default: 14), with SMA smoothing for %K (3) and %D (3).
Visual Aids: Includes overbought (80), oversold (20), and midline (50) levels, plus a subtle blue fill between OB/OS zones for easy reference.
How It Works
Source Smoothing: The input source (default: close) is passed through the SuperSmoother filter multiple times to create a trend MA.
Stoch RSI Calculation: Computes RSI on the source, then applies Stochastic to the RSI values, followed by SMA smoothing for base %K and %D.
Advanced Smoothing: Extra SuperSmoother layers are applied to %K and %D based on your chosen passes, minimizing whipsaws.
Directional Logic: Compares current close to the trend MA to color %K dynamically.
Plotting: %K (thick line, colored) and %D (thin orange) oscillate between 0-100, highlighting crossovers and divergences.
Usage Tips
Buy Signal: Green %K crosses above %D below 50, or bounces off oversold (20) in uptrends.
Sell Signal: Red %K crosses below %D above 50, or rejects overbought (80) in downtrends.
Customization: Increase smoothing passes (3-5) for choppy markets; reduce for faster signals. Pair with volume or support/resistance for confirmation.
Timeframes: Best on 1H-4H charts for stocks/crypto; adjust lengths for forex.
This open-source script is licensed under Mozilla Public License 2.0. Backtest thoroughly—past performance isn't indicative of future results. Enjoy trading smarter with less noise! 🚀
© HighlanderOne
CCI Stochastic - YOSI
CCI Stochastic (Pro v6) – MTF, Adaptive Bands & Live Label
What it does
This indicator applies a Stochastic calculation on the CCI (K/D lines) to highlight momentum shifts, overbought/oversold zones, and adaptive market regimes. It comes with optional higher-timeframe confirmation, adaptive volatility bands, a live value label, and built-in alerts.
Key Features
Core Signal: Choose between D or K line of the Stoch-CCI.
Extreme Zones: Customizable OB/OS thresholds (default 80/20) and a midline (50), with dynamic background shading.
Adaptive Bands (optional): Mean ± k·standard deviation of the signal, to capture cyclic extremes.
MTF Confirmation (optional): Fetches the same signal from a higher timeframe via request.security.
Arrows/Signals:
Enter – Cross above OS (Buy) / below OB (Sell).
Center – Cross of the 50 midline (momentum shift).
Exit – Exit from extreme zones.
Alerts: All arrow signals + adaptive band crosses.
Live Value Label: Shows the latest signal value near the last bar, customizable decimals/offset/background colors.
Visuals: Red line above OB, green below OS, gray neutral; adaptive band fills.
Use Cases
Momentum / Reversals: Enter with OS/OB crosses confirmed by MTF.
Trend validation: Combine with moving averages (e.g., EMA200) or support/resistance.
Mean Reversion: Fade extreme zones, especially with adaptive band or OB/OS exit alerts.
Inputs
CCI Period, Stoch Period, Smooth K/D – core calculation.
Overbought / Oversold – thresholds (default 80/20).
Line to plot – K or D.
Show Arrows (Enter, Center, Exit) – visual control.
Adaptive Bands – length and k multiplier.
Higher TF – optional confirmation timeframe.
Live Label – decimals, offset, colors.
Quick Tips
For scalping/short-term setups: tighten OB/OS (e.g., 85/15) to filter noise.
In high volatility: increase adaptLen or decrease k to smooth bands.
Reduce false signals: require local + MTF alignment (e.g., only long if MTF > 50).
Disclaimer
This is a technical analysis tool – not a standalone buy/sell signal. Always use with proper risk management, key levels, and confluence from multiple factors.
מה זה עושה?
האינדיקטור מחשב Stochastic על CCI (קו K/D) ומציג אזורי קיצון, חציות ומשטרי שוק. הוא כולל אופציה לאישור מטיימפריים גבוה, בנדים אדפטיביים, תווית ערך חיה והתרעות מוכנות.
יכולות עיקריות
סיגנל מרכזי: בחירה בין קו D או K של Stoch-CCI.
אזורי קיצון: קווים ניתנים להגדרה (ברירת מחדל 80/20) וקו אמצע 50, עם צביעת רקע דינמית כשנכנסים לקיצון.
Adaptive Bands (אופציונלי): ממוצע ± k·סטיית תקן של הסיגנל—מסייע לזהות overheat ומחזוריות.
אישור MTF (אופציונלי): אותו סיגנל מטיימפריים גבוה באמצעות request.security.
חיצים/סיגנלים:
Enter – חציה מלמטה מעל OS (קנייה) / מלמעלה מתחת OB (מכירה).
Center – חציה של 50 (שינוי מומנטום).
Exit – יציאה מאזורים קיצוניים (OS/OB).
Alerts: לכל הסיגנלים לעיל + כניסה/יציאה לבנדים האדפטיביים.
תווית ערך חיה: מציגה את ערך הסיגנל האחרון ליד הנקודה (ספרות ו־offset ניתנים להגדרה).
עיצוב קריא: צבע קו אדום מעל OB, ירוק מתחת OS, אפור ניטרלי; מילוי אזורים.
שימוש מומלץ
מומנטום/היפוכים: כניסה עם חציה מה-OS/OB ואישור מה-MTF.
ממוצע נע/רמות מחיר: חברו לאימות מגמה (למשל EMA200 או תמיכה/התנגדות).
Mean Reversion: חיפוש חזרה מאזורי קיצון, במיוחד כשיש התרעת יציאה מ-OB/OS או נגיעה בבנד אדפטיבי.
קלטים מרכזיים
CCI Period, Stoch Period, Smooth K/D – פרמטרי חישוב.
Overbought / Oversold – ספי קיצון (ברירת מחדל 80/20).
Line to plot – בחירה בין K או D.
Show Arrows/Center/Exit/Enter – שליטה בתצוגת החיצים.
Adaptive Bands (len, k) – חלון ורגישות לבנדים.
Higher TF – טיימפריים לאישור (אופציונלי).
Live Label – ספרות, היסט ברים, צבעי רקע.
טיפים מהירים
בסקלפים/טווחים קצרים: הקשיחו ספי קיצון (למשל 85/15) להפחתת רעש.
בשוק תנודתי: העלו את adaptLen או הורידו את k כדי לקבל בנדים רגישים פחות.
להקטנת אותות שווא: דרשו התאמה בין הסיגנל המקומי ל-MTF (לדוגמה, לונג רק כשה-MTF מעל 50).
הערה חשובה
זהו כלי ניתוח טכני—לא אות קנייה/מכירה בפני עצמו. שלבו אותו עם ניהול סיכונים (SL/TP), בדיקת רמות מפתח ואימות ממספר אינדיקטורים או טיימפריימים.
Parabolic Stoch SAR VisualizerParabolic Stoch SAR Visualizer — Momentum-Driven Trend Precision Tool
Overview:
Parabolic Stoch SAR Visualizer is a thoughtfully engineered hybrid indicator that blends momentum oscillation and trend-following mechanics into one robust system. By applying a custom Parabolic SAR calculation directly on a double-smoothed stochastic oscillator (rather than on price), it generates cleaner signals with enhanced trend detection and fewer false positives than typical Parabolic RSI or standard SAR variants.
Unique Functionality:
Momentum smoothing : The base stochastic %K undergoes double smoothing via consecutive simple moving averages, significantly cutting down random noise and erratic swings common in raw stochastic readings. This stabilizes momentum tracking, isolating true price strength and weakness.
Custom Parabolic SAR on smoothed momentum : Traditional SAR algorithms operate on price data, acting as trailing stops. This indicator repurposes SAR to work on smoothed stochastic values, effectively converting it into a momentum-driven directional filter. This yields a more adaptive and responsive trend signal focused on genuine momentum shifts instead of price noise.
Bounded SAR range and adjustable acceleration : SAR values are mathematically restricted between 0 and 100, aligning with the stochastic scale to prevent distortions. Traders can customize acceleration parameters (start, increment, max) to fine-tune trend sensitivity relative to market volatility or specific strategies.
Signal clarity through filterin g: Minimum bar spacing and minimum SAR movement thresholds between plotted dots reduce chart clutter, highlighting only meaningful trend changes and filtering out insignificant fluctuations.
Enhanced visuals : The oscillator line smoothly transitions its color gradient between defined uptrend and downtrend hues, intuitively signaling momentum strength. Parabolic SAR dots are offset from the oscillator line with multi-layered glow effects, making trend flips easy to spot at a glance.
Trading Application:
Trend identification : Momentum-based SAR dots offer precise marking of trend shifts, helping traders avoid false breakouts and premature trades.
Entry and exit timing : Combining the double-smoothed stochastic oscillator and SAR dots creates a reliable framework to confirm momentum shifts and optimal trade entries or exits.
Customizable for volatility regimes : Adjustable acceleration and filtering parameters allow scalpers to increase signal sensitivity, while swing traders can dial back noise for smoother trend recognition.
Visual clarity for fast decisions : Gradient color coding and glowing SAR dots facilitate immediate momentum assessment without complex analysis, empowering quicker, more confident trade actions.
Advantages over Parabolic RSI and similar indicators:
Parabolic RSI’s direct application of SAR on RSI often results in noisy, choppy signals prone to whipsaws. This indicator’s double-smoothed stochastic foundation delivers a cleaner, steadier signal.
Applying SAR to smoothed momentum rather than price transforms it into a directional filter that better captures true market strength with reduced lag.
Adaptive plotting thresholds and enhanced visuals minimize clutter and ambiguity, improving trader focus and execution speed.
WT + Stoch RSI Reversal Combo📊MR.Z RSI : WT + Stochastic RSI Reversal Combo
This custom indicator combines WaveTrend oscillator and Stochastic RSI to detect high-confidence market reversal points, filtering signals so they only appear when both indicators align.
🔍 Core Components:
✅ WaveTrend Oscillator
Based on smoothed deviation from EMA (similar to TCI logic)
Plots:
WT1 (main line)
WT2 (signal line = SMA of WT1)
Uses overbought/oversold thresholds (default: ±53) to filter signals
✅ Stochastic RSI
Momentum oscillator based on RSI's stochastic value
Plots:
%K: smoothed Stoch of RSI
%D: smoothed version of %K
Adjustable oversold/overbought thresholds (default: 20/80)
🔁 Combined Reversal Signal Logic:
🔼 Buy Signal
WT1 crosses above WT2 below WT oversold level (e.g., -53)
%K crosses above %D below Stoch RSI oversold level (e.g., 20)
🔽 Sell Signal
WT1 crosses below WT2 above WT overbought level (e.g., 53)
%K crosses below %D above Stoch RSI overbought level (e.g., 80)
🔔 Signals are only plotted and alerted if both conditions are true.
📌 Features:
Toggle on/off:
WaveTrend lines and histogram
Stochastic RSI
Combined Buy/Sell signals
Horizontal reference lines (±100, OB/OS)
Fully customizable smoothing lengths and thresholds
Signal plots:
✅ Green up-triangle = Combo Buy
✅ Red down-triangle = Combo Sell
Optional: Circle/cross markers for WT-only and Stoch-only signals
🔔 Built-in alerts for Buy/Sell signals
📈 Use Cases:
Reversal Trading: Wait for both indicators to confirm momentum shift
Entry Filter: Use in combination with trend indicators (like EMA)
Scalping or Swing: Works on intraday and higher timeframes






















