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Alligator Signals by RickAlligator Signals by Rick Alligator Signals by Rick is a clean overlay indicator built to deliver simple directional outputs without cluttering the chart. Under the hood, it combines Williams Alligator structure with Zero Lag confirmation logic to generate filtered LONG and SHORT signals. What this script does Uses Williams Alligator logic to detect bullish, bearish, and sleeping market structure Uses Zero Lag confirmation to validate directional triggers Displays only clean LONG and SHORT labels on the chart Optionally shows the Alligator lines if you want to inspect the underlying structure Includes a configurable anti-repeat signal cooldown Why this version is different This script is designed to stay simple on the chart while doing the heavier filtering in the background. Instead of forcing the user to interpret Jaw, Teeth, Lips, and extra confirmation conditions manually, the script reduces everything to a direct trading signal. Clean chart output with simple LONG and SHORT labels Alligator trend structure is used as the main directional engine Zero Lag acts as a confirmation layer rather than the primary visual output Sleeping market filter helps reduce low-quality signals in choppy conditions Optional price agreement filter requires price to be aligned with the Alligator structure Signal cooldown can block repeated longs until a short happens, and vice versa How to use it Use LONG and SHORT labels as the final output of the combined Alligator + Zero Lag logic Enable Show Alligator Lines only if you want to inspect the underlying structure Keep the sleeping filter enabled if you want fewer low-quality signals during sideways conditions Use the cooldown mode if you want a cleaner chart with fewer repeated signals in the same direction Switch Signal Mode to Entry Only for a stricter trigger style Inputs overview Alligator Settings: source, Jaw, Teeth, Lips, offsets, optional line display, and line colors Trend Filter: sleeping filter, ATR-based minimum line separation, and price agreement filter Zero Lag Confirmation: Zero Lag length, band multiplier, signal mode, and signal cooldown Signal Style: long and short label colors and text colors Alerts included Long Signal Short Signal Alligator Turned Bullish Alligator Turned Bearish Alligator Turned Sleeping Notes The Alligator line offsets are used only for optional visual display. Signal logic is based on the underlying non-shifted calculations so alerts and chart signals remain logically consistent. Credits This script is inspired by the Williams Alligator concept and uses Zero Lag confirmation logic adapted from AlgoAlpha. Modified and integrated by Rick. This indicator is for educational and analytical use only. It does not provide financial advice or guarantee performance.
Pine Script® göstergesi
rickugo tarafından
2
EMA + Zero Lag Signals by RickEMA + Zero Lag Signals by Rick EMA + Zero Lag Signals by Rick is an overlay indicator that combines a customizable Exponential Moving Average with a Zero Lag trend engine to help traders read trend direction, momentum shifts, and filtered long/short opportunities from one tool. What this script does Plots a configurable EMA directly on the chart Plots the Zero Lag basis and dynamic deviation bands Displays bullish and bearish trend labels Displays entry markers for continuation setups Shows a multi-timeframe trend table for 5 additional timeframes Adds custom EMA-filtered long and short alerts Why this version is different This script is not just a standard EMA or a basic repackaging of Zero Lag signals. It combines both tools into one workflow and adds practical chart controls for filtering, styling, and alerting. EMA length and source are configurable EMA line style can be adjusted directly from the script inputs Long and short marker colors can be customized Label text colors can be customized Plotted signals can optionally be filtered by the EMA EMA combo alerts can react to either any Zero Lag signal or entry signals only How to use it Use the EMA as a higher-level directional filter Watch the Zero Lag basis and deviation bands for trend state changes Use Bullish Trend and Bearish Trend labels to identify directional flips Use entry markers for continuation opportunities within the active trend Enable EMA filtering if you only want to display chart signals aligned with the EMA Alerts included Bullish Entry Signal Bearish Entry Signal Bullish Trend Bearish Trend (Bullish or Bearish) Trend Bullish and bearish trend alerts for 5 extra timeframes EMA + Zero Lag Long EMA + Zero Lag Short Inputs overview EMA Settings: length, source, line style, and EMA color Zero Lag Settings: calculation length and band multiplier Extra Timeframes: 5 configurable timeframe trend checks Appearance and Style: bullish and bearish colors, long and short signal colors, and label text colors Signal Filters: plotted signal filtering by EMA and EMA alert mode Credits Portions of the Zero Lag logic are adapted from AlgoAlpha. This version adds EMA integration, customizable styling, optional EMA-based signal filtering, and custom alert logic. This indicator is for educational and analytical use only. It does not provide financial advice or guarantee performance.
Pine Script® göstergesi
rickugo tarafından
2
Zero Lag Kalman Structure [BOSWaves]Zero Lag Kalman Structure - Adaptive Trend Filtering with Deviation-Based Structure Detection Overview Zero Lag Kalman Structure is a precision trend identification system that tracks directional price movement through a zero-lag-compensated Kalman filter ribbon, where deviation-based structural levels dynamically form at volatility-normalized extremes and persist as active support and resistance zones until price invalidates them. Instead of relying on fixed moving average crossovers or static support/resistance lookbacks, trend state, level formation, and break detection are determined through Kalman velocity tracking, ATR-normalized deviation measurement, and swing-based structure identification. This creates adaptive trend boundaries and structural zones that reflect actual price conviction rather than arbitrary historical levels - contracting the ribbon during trending conditions when directional certainty is high, forming fresh levels during deviation extremes when price has meaningfully separated from the Kalman baseline, and incorporating BOS/CHoCH detection to reveal whether market structure is continuing or reversing. Price is therefore evaluated relative to a filter that adapts to momentum velocity rather than conventional lagging averages. Conceptual Framework Zero Lag Kalman Structure is founded on the principle that meaningful structural zones emerge when price deviates from its statistically optimal estimated path by a volatility-significant margin, and that trend context is best captured by a filter engineered to eliminate the lag inherent to traditional smoothing methods. Conventional support/resistance tools identify levels through historical pivot lookbacks, which ignore the dynamic nature of price conviction and the statistical state of the current trend. This framework replaces static pivot logic with Kalman-anchored deviation measurement informed by actual filter velocity and error covariance state. Three core principles guide the design: Trend direction should be captured by a velocity-aware Kalman filter with active lag compensation, not by lagging moving averages. Structural levels must form at statistically significant deviation extremes, normalized to current volatility rather than fixed price distances. Market structure breaks and character changes should be identified through swing-based logic tied to the same price data the filter operates on. This shifts trend and structure analysis from static indicator crossovers into adaptive, filter-anchored confidence zones. Theoretical Foundation The indicator combines Kalman filter estimation theory, zero-lag error compensation, ATR-normalized deviation measurement, deviation zone persistence modeling, and swing pivot structure detection. A Kalman filter baseline provides statistically optimal price estimation by balancing process noise and measurement noise parameters, while a velocity tracker within the filter captures directional momentum. Zero-lag compensation applies the residual error between current price and the filter estimate back onto the output, reducing phase delay. Deviation measurement identifies when price has separated from the filter by an ATR-scaled threshold, triggering level creation at the extreme point once price snaps back. BOS/CHoCH detection uses pivot highs and lows to identify structural breaks and character changes. Four internal systems operate in tandem: Kalman Filter Engine : Computes error-covariance-weighted price estimates with integrated velocity tracking, Kalman gain adaptation, and zero-lag correction applied to each bar. Ribbon Construction System : Runs six parallel Kalman instances with incrementally increasing process noise to produce a multi-layered trend ribbon whose spread and color reflect directional strength. Deviation Level Formation Logic : Monitors ATR-normalized distance from the Kalman estimate, records extreme highs and lows during deviation events, and creates persistent zone boxes upon mean reversion. Market Structure Detection : Tracks swing pivot highs and lows using configurable lookback, identifies crossovers of those pivots, and classifies each break as either a BOS continuation or a CHoCH reversal depending on prior structural trend. This design allows the trend filter, structural zones, and structure labels to operate as a unified system rather than independent overlapping indicators. How It Works Zero Lag Kalman Structure evaluates price through a sequence of filter-aware and deviation-driven processes: Kalman State Initialization : On the first bar, filter state initializes with estimate equal to source price, zero velocity, and unit error covariance to establish a clean starting condition. Prediction Step : Each bar predicts the next estimate by advancing the prior estimate by the velocity component weighted by the velocity weight parameter. Velocity Tracking : A separate exponential tracker computes price-change velocity using a 95/5 blend of decayed prior velocity and current bar price change. Kalman Gain Calculation : Gain is computed from current error covariance and measurement noise, controlling the balance between trusting the filter model versus reacting to new price data. Estimate Update : The filtered estimate updates using the Kalman gain applied to the innovation - the difference between current price and the predicted estimate. Zero-Lag Correction : Residual lag error between price and estimate is computed, then multiplied by the zero lag factor and current Kalman gain, and added back to the estimate to compress phase delay. Ribbon Smoothing : The zero-lag estimate passes through a 0.8/0.2 exponential blend each bar to produce the final ribbon line, providing continuity without reintroducing significant lag. Ribbon Color Gradient : The spread between the fastest and slowest ribbon lines is normalized by ATR to produce a ribbon strength value, which drives a color gradient between the configured bullish and bearish colors. Deviation Monitoring : Each bar, the distance between close and the main Kalman line is measured in ATR units. When this exceeds the deviation threshold, the system begins tracking the extreme high or low of that deviation event. Level Creation on Snap-Back : Once price returns inside 50% of the deviation threshold after an extended move, a new zone box is created centered on the tracked extreme, with width scaled to the level width ATR parameter. Level Management : Active levels extend forward each bar. Broken levels - where price closes beyond the zone boundary - are deleted. When the level count reaches the configured maximum, the oldest level is removed to make space. Retest Detection : Depending on the selected retest method, the system either monitors price interaction with zone boundaries or price proximity to the main Kalman line, applying cooldown periods to prevent signal clustering. BOS/CHoCH Detection : Pivot highs and lows are tracked using the swing lookback parameter. Crossovers of the most recent pivot high trigger bullish structural breaks, and crossunders of the most recent pivot low trigger bearish structural breaks. The prior structural trend determines whether each break is classified as continuation (BOS) or reversal (CHoCH). Together, these elements form a continuously updating trend and structure framework anchored in Kalman estimation theory. Interpretation Zero Lag Kalman Structure should be interpreted as a filter-anchored trend state with deviation-driven structural memory: Ribbon Direction : The relative positioning and color of the six-line ribbon communicates directional trend bias. Bullish gradient color with spread above zero reflects upward trend conviction; bearish gradient with inverted spread reflects downward conviction. Ribbon Spread Width : A widening spread between the fastest and slowest Kalman lines indicates strong directional momentum. A compressing spread suggests trend deceleration or potential transition. Resistance Zones (Red) : Created at extreme highs where price deviated significantly above the Kalman line before snapping back, marking areas where price showed unsustainable separation to the upside. Support Zones (Green) : Created at extreme lows where price deviated significantly below the Kalman line before recovering, marking areas where price showed unsustainable separation to the downside. Zone Persistence : Active zones extend forward until broken by a close beyond the zone boundary, treating them as live structural reference until price demonstrably invalidates them. BOS Labels : Dashed lines with "BOS" text mark continuation breaks of prior swing structure in the direction of the established trend. CHoCH Labels : Dotted lines with "CHoCH" text mark counter-trend breaks of prior swing structure, signaling potential trend character changes. ▲ / ▼ Retest Signals : Small directional arrows identify price retesting either a deviation zone boundary or the main Kalman line, depending on the selected retest method. Colored Candles : Bar coloring reflects the current ribbon gradient state for immediate directional reference across the entire chart history. Note: The original chart candles must be disabled in chart settings for the trend-colored candles to display properly. Ribbon gradient strength, zone validity, and structural trend classification outweigh isolated price movements or individual bar reactions. Signal Logic & Visual Cues Zero Lag Kalman Structure presents two categories of structural interaction signals: BOS / CHoCH Events : Labeled lines appear when price crosses a tracked swing pivot. BOS signals continuation of existing structure; CHoCH signals the first counter-trend structural break, indicating potential trend change. Retest Signals (▲ / ▼) : Arrows appear when price interacts with an active deviation zone boundary (Levels mode) or touches the main Kalman line after sufficient separation (Kalman Line mode), confirmed by cooldown period to prevent rapid repeat signals. Alert generation covers deviation level creation, BOS and CHoCH events, Kalman line retests, and support/resistance level retests for systematic monitoring across instruments and timeframes. Strategy Integration Zero Lag Kalman Structure fits within structure-aware and trend-following analytical frameworks: Filter-Confirmed Directional Bias : Use ribbon color and spread direction as the primary trend filter before evaluating entries, favoring positions aligned with ribbon gradient. Deviation Zone Re-entries : Use active support and resistance zones as high-probability re-entry reference areas when price returns to a level from the correct side. BOS/CHoCH Context Alignment : Treat BOS events as continuation confirmation within established trends; treat CHoCH events as early warning of structural regime change requiring reassessment. Retest-Based Entries : Use Kalman line or zone retests as lower-risk entry points within an established trend after initial separation has confirmed directional conviction. Zone Invalidation as Exit Logic : Use level deletion events - where price closes beyond a zone boundary - as structural evidence that the prior support or resistance thesis is no longer valid. Multi-Timeframe Structure Layering : Apply higher-timeframe deviation zones and BOS/CHoCH context to filter lower-timeframe entry signals for improved precision. Technical Implementation Details Core Engine : Kalman filter with error covariance tracking, Kalman gain adaptation, and integrated velocity model Lag Correction : Zero-lag factor applied multiplicatively with current Kalman gain to preserve filter responsiveness at the correction stage Ribbon System : Six parallel Kalman instances with linearly incremented process noise, blended via gradient fill Level Formation : ATR-normalized deviation threshold with extreme tracking, snap-back detection, and box-based zone persistence Structure Detection : Pivot high/low crossover logic with trend state tracking for BOS/CHoCH classification Retest Logic : Dual-mode detection supporting zone boundary interaction and Kalman proximity, each with configurable cooldown Visualization : Gradient ribbon fills, persistent zone boxes, labeled structure lines, and signal arrows Performance Profile : Optimized for real-time execution with per-bar level management across all timeframes Optimal Application Parameters Timeframe Guidance: 1 - 5 min : Short-term structure tracking with responsive deviation settings for intraday scalping 15 - 60 min : Intraday trend context with balanced deviation threshold and level persistence 4H - Daily : Swing-level structure identification with ATR-normalized zones carrying multi-session significance Suggested Baseline Configuration: Process Noise (Q) : 0.01 Measurement Noise (R) : 0.5 Zero Lag Factor : 1.0 Velocity Weight : 0.5 Ribbon Spread : 0.003 Deviation Threshold (ATR) : 1.5 Level Width (ATR) : 0.25 Maximum Levels : 6 Level Extend Bars : 50 Swing Lookback : 5 Retest Method : Kalman Line Retest Cooldown : 50 Show Ribbon : Enabled Show Deviation Levels : Enabled Show BOS / CHoCH : Enabled These suggested parameters should be used as a baseline; their effectiveness depends on the asset's volatility profile, structural characteristics, and preferred signal frequency, so fine-tuning is expected for optimal performance. Parameter Calibration Notes Use the following adjustments to refine behavior without altering the core logic: Filter too reactive to noise : Increase Measurement Noise (R) to make the Kalman gain more conservative and smooth the estimate more aggressively. Filter too slow to respond : Increase Process Noise (Q) to allow faster adaptation to genuine price movements, or increase Zero Lag Factor to strengthen lag correction. Levels forming too frequently : Increase Deviation Threshold to require greater ATR-normalized separation before a level is created. Levels forming too rarely : Decrease Deviation Threshold to trigger level creation at more moderate deviations. Zones too wide or too narrow : Adjust Level Width multiplier to scale zone thickness proportionally to current ATR. Too many active levels cluttering the chart : Reduce Maximum Levels so older zones are removed sooner, keeping only the most recent structural reference. BOS/CHoCH signals too frequent : Increase Swing Lookback to require more significant pivot formations before a structural break is recognized. BOS/CHoCH signals too infrequent : Decrease Swing Lookback for faster swing detection and more responsive structural classification. Retest signals clustering : Increase Retest Cooldown to enforce greater bar separation between consecutive retest events. Adjustments should be incremental and evaluated across multiple session types rather than isolated market conditions. Performance Characteristics High Effectiveness: Trending markets with clear directional phases where Kalman velocity remains consistently signed Instruments with regular mean-reversion behavior where deviation extremes produce reliable structural zones Swing and position trading approaches where BOS/CHoCH context informs multi-bar directional bias Structure-based strategies that benefit from ATR-normalized level placement over fixed-point lookback methods Reduced Effectiveness: Choppy, range-bound markets with frequent shallow deviations that trigger premature level creation Extremely low volatility environments where ATR normalization compresses zones to negligible significance News-driven or gapped markets with discontinuous price behavior that bypasses zone boundaries without interaction Markets with highly irregular volatility profiles where ATR scaling produces inconsistently sized zones Consolidation and sideways price action where trend-following and structure-based methodologies inherently struggle due to lack of sustained directional conviction Integration Guidelines Confluence : Combine with volume analysis, higher-timeframe trend context, or momentum oscillators to confirm deviation zone significance Ribbon Alignment : Trust structural breaks and retest signals occurring in the direction of the current ribbon color gradient Zone Side Discipline : Treat deviation zones as directional only - approach support zones from above for bullish entries, resistance zones from below for bearish entries CHoCH Awareness : Reduce directional exposure when CHoCH events occur against the prior established structural trend until a confirming BOS in the new direction appears Velocity Respect : During periods of high Kalman velocity as reflected by wide ribbon spread, expect price to sustain moves further from the filter before meaningful retests occur Level Invalidation Response : When a zone is broken, treat the break as structural confirmation of the new directional move rather than a retest opportunity Disclaimer Zero Lag Kalman Structure is a professional-grade trend filtering and structure analysis tool. It uses Kalman estimation theory with zero-lag compensation and ATR-normalized deviation measurement but does not predict future price movements. Results depend on market conditions, volatility characteristics, parameter selection, and disciplined execution. BOSWaves recommends deploying this indicator within a broader analytical framework that incorporates volume context, higher-timeframe bias, and comprehensive risk management.
Pine Script® göstergesi
BOSWaves tarafından
6
Zero-Lag ATR Trend [BackQuant]Zero-Lag ATR Trend Overview Zero-Lag ATR Trend is a volatility-adaptive trend-following overlay designed to identify directional market regimes with minimal delay while preserving structural clarity. The indicator combines a zero-lag moving average framework with a zero-lag volatility model to produce a trailing trend line that reacts quickly to meaningful price changes without becoming unstable or overly sensitive. Unlike conventional ATR-based trend tools that rely on lagging averages and delayed volatility estimates, this indicator applies zero-lag logic to both the trend centerline and the volatility calculation. The result is a trend structure that aligns more closely with real-time price action while still maintaining the discipline required for trend continuation trading. Core design philosophy The core idea behind Zero-Lag ATR Trend is simple: Reduce signal delay without sacrificing trend integrity. Adapt dynamically to changing volatility regimes. Provide a single, clean structure that defines trend direction, continuation, and invalidation. Instead of stacking multiple indicators, the script builds a complete trend framework from two tightly integrated components: a zero-lag trend spine and a zero-lag ATR trailing mechanism. Zero-lag trend spine The trend spine is constructed using a zero-lag moving average (ZLMA). This is achieved by applying a corrective step to a traditional moving average, effectively compensating for smoothing delay. Conceptually, the process works as follows: A base moving average is calculated from the selected price source. That moving average is then passed through a zero-lag correction. The correction pulls the line closer to current price without introducing noise. This produces a trend line that reacts faster than standard EMA, SMA, or HMA signals, particularly during early trend acceleration phases. Multiple moving-average types can be used inside the zero-lag framework, allowing traders to fine-tune responsiveness based on asset behavior and timeframe. Zero-lag volatility model Volatility is measured using True Range, but instead of applying classic ATR smoothing, the indicator uses a zero-lag smoothing pass on the True Range itself. This approach offers several advantages: Volatility expands more quickly during impulse moves. Volatility contracts faster during consolidations. Band width adjusts in near real-time to changing conditions. The smoothed zero-lag ATR is multiplied by a user-defined factor to create adaptive upper and lower boundaries around the trend spine. These boundaries define how much counter-movement price is allowed before the trend structure is invalidated. Volatility-aware trailing structure The trailing output is the defining feature of the indicator. It behaves as a one-directional trailing structure: In bullish conditions, the trailing line can only move upward. In bearish conditions, the trailing line can only move downward. Minor pullbacks inside the volatility envelope do not flip the trend. This logic prevents the indicator from reacting to shallow retracements and focuses instead on structural trend changes. Because the trailing behavior is volatility-scaled, the indicator remains stable during high volatility while still responding promptly during regime shifts. Trend flips and regime transitions Trend direction is determined by changes in the trailing structure itself rather than raw price crosses. A trend flip occurs only when price movement is strong enough, relative to current volatility, to force the trailing line to reverse direction. This means: Bullish flips represent genuine transitions into upward regimes. Bearish flips represent genuine transitions into downward regimes. Sideways noise is largely filtered out. As a result, the indicator is well suited for identifying medium-to-long trend phases rather than short-term oscillations. Visual structure and chart clarity The visual design is intentionally minimal and functional: The main trailing line is color-coded by trend direction. An optional ribbon or cloud reinforces directional bias. Optional candle coloring aligns price bars with the active trend. These elements allow traders to assess trend state instantly without interpreting multiple signals or overlays. How to use for trend following Trend bias Maintain a bullish bias while price holds above the trailing line. Maintain a bearish bias while price holds below the trailing line. Entries Trend flips can be used as initial directional entries. Pullbacks toward the trailing line often act as continuation opportunities. Momentum confirmation can be layered on top for additional confluence. Trend management The trailing line naturally functions as a dynamic stop reference. As long as price respects the trailing structure, the trend remains valid. A flip in direction signals a full regime transition rather than a minor correction. Why zero-lag matters for trend trading Traditional trend indicators often react late, especially during fast expansions, resulting in delayed entries and early exits. By reducing lag in both the trend calculation and the volatility model, Zero-Lag ATR Trend aims to capture a larger portion of directional moves while maintaining consistency and discipline. This makes it particularly effective for momentum-based trend following, breakout continuation strategies, and traders who prioritize staying aligned with dominant market structure rather than predicting reversals. Summary Zero-Lag ATR Trend is a complete trend-following framework built around responsiveness, adaptability, and clarity. Its zero-lag architecture allows it to respond earlier to meaningful price changes, while its volatility-aware trailing logic ensures that trends are only invalidated when structure truly breaks. The result is a clean, intuitive tool that supports disciplined trend participation across assets and timeframes.
Pine Script® göstergesi
BackQuant tarafından
5
Zero Lag Trend Signals (MTF) [AlgoAlpha]Zero Lag Trend Signals 🚀📈 Ready to take your trend-following strategy to the next level? Say hello to Zero Lag Trend Signals , a precision-engineered Pine Script™ indicator designed to eliminate lag and provide rapid trend insights across multiple timeframes. 💡 This tool blends zero-lag EMA (ZLEMA) logic with volatility bands, trend-shift markers, and dynamic alerts. The result? Timely signals with minimal noise for clearer decision-making, whether you're trading intraday or on longer horizons. 🔄 🟢 Zero-Lag Trend Detection : Uses a zero-lag EMA (ZLEMA) to smooth price data while minimizing delay. ⚡ Multi-Timeframe Signals : Displays trends across up to 5 timeframes (from 5 minutes to daily) on a sleek table. 📊 Volatility-Based Bands : Adaptive upper and lower bands, helping you identify trend reversals with reduced false signals. 🔔 Custom Alerts : Get notified of key trend changes instantly with built-in alert conditions. 🎨 Color-Coded Visualization : Bullish and bearish signals pop with clear color coding, ensuring easy chart reading. ⚙️ Fully Configurable : Modify EMA length, band multiplier, colors, and timeframe settings to suit your strategy. How to Use 📚 ⭐ Add the Indicator : Add the indicator to favorites by pressing the star icon. Set your preferred EMA length and band multiplier. Choose your desired timeframes for multi-frame trend monitoring. 💻 Watch the Table & Chart : The top-right table dynamically updates with bullish or bearish signals across multiple timeframes. Colored arrows on the chart indicate potential entry points when the price crosses the ZLEMA with confirmation from volatility bands. 🔔 Enable Alerts : Configure alerts for real-time notifications when trends shift—no need to monitor charts constantly. How It Works 🧠 The script calculates the zero-lag EMA (ZLEMA) by compensating for data lag, giving traders more responsive moving averages. It checks for volatility shifts using the Average True Range (ATR), multiplied to create upper and lower deviation bands. If the price crosses above or below these bands, it marks the start of new trends. Additionally, the indicator aggregates trend data from up to five configurable timeframes and displays them in a neat summary table. This helps you confirm trends across different intervals—ideal for multi-timeframe analysis. The visual signals include upward and downward arrows on the chart, denoting potential entries or exits when trends align across timeframes. Traders can use these cues to make well-timed trades and avoid lag-related pitfalls.
Pine Script® göstergesi
AlgoAlpha tarafından
101
Nasan Moving AverageNasan Moving Average belong to the group of moving average which provides a high degree of smoothness with very low lag. The calculation process involves several steps to analyze the typical price of a financial asset over specific periods. It starts by computing a simple moving average and standard deviation of the typical price. Then, it standardizes (differencing TP - Average Typical price over previous n periods) the price and applies an inverse hyperbolic sine transformation to the standardized value. The transformed values are summed cumulatively, and various weighted moving averages are calculated to adjust and smooth the data. The final output is a smoothed signal with reduced lag. Input Parameters: len: Differencing length (default 21, Use a minimum of 5 and for lower time frames less than 15 min use values between 300 -3000) len1: Correction Factor Length 1 (default 21, this determines the length of the MA you want , eg. 10 MA, 50 MA, 100 MA, ) len2: Correction Factor Length 2 (default 9, this works best if it is ~ </=1/2 of len1 ) len3: Smoothing Length (default 5, I would not change this and only use if I want to introduce lag where you want to use it for cross over strategies). Differencing and Standardization: The code calculates the standardized price a by differencing the typical price and normalizing it using the mean and standard deviation. This step standardizes the price changes. Transformation: The transformation using logarithms and square roots (b) aim to stabilize the variance and make the distribution more normal-like, improving the robustness of the cumulative sum c. Cumulative Sum: The cumulative sum c of the transformed series helps in integrating the series over time, capturing the overall trend and movement. Correction Factors: Correction factors c1 and c4 adjust the cumulative sum based on weighted averages, to correct any biases or to align it with the typical price. Smoothing: The final result c6 is smoothed using a weighted moving average, reducing noise and making it easier to interpret trends.
Pine Script® göstergesi
federalTacos5392b tarafından
Nonlinear Regression, Zero-lag Moving Average [Loxx]Nonlinear Regression and Zero-lag Moving Average Technical indicators are widely used in financial markets to analyze price data and make informed trading decisions. This indicator presents an implementation of two popular indicators: Nonlinear Regression and Zero-lag Moving Average (ZLMA). Let's explore the functioning of these indicators and discuss their significance in technical analysis. Nonlinear Regression The Nonlinear Regression indicator aims to fit a nonlinear curve to a given set of data points. It calculates the best-fit curve by minimizing the sum of squared errors between the actual data points and the predicted values on the curve. The curve is determined by solving a system of equations derived from the data points. We define a function "nonLinearRegression" that takes two parameters: "src" (the input data series) and "per" (the period over which the regression is calculated). It calculates the coefficients of the nonlinear curve using the least squares method and returns the predicted value for the current period. The nonlinear regression curve provides insights into the overall trend and potential reversals in the price data. Zero-lag Moving Average (ZLMA) Moving averages are widely used to smoothen price data and identify trend directions. However, traditional moving averages introduce a lag due to the inclusion of past data. The Zero-lag Moving Average (ZLMA) overcomes this lag by dynamically adjusting the weights of past values, resulting in a more responsive moving average. We create a function named "zlma" that calculates the ZLMA. It takes two parameters: "src" (the input data series) and "per" (the period over which the ZLMA is calculated). The ZLMA is computed by first calculating a weighted moving average (LWMA) using a linearly decreasing weight scheme. The LWMA is then used to calculate the ZLMA by applying the same weight scheme again. The ZLMA provides a smoother representation of the price data while reducing lag. Combining Nonlinear Regression and ZLMA The ZLMA is applied to the input data series using the function "zlma(src, zlmaper)". The ZLMA values are then passed as input to the "nonLinearRegression" function, along with the specified period for nonlinear regression. The output of the nonlinear regression is stored in the variable "out". To enhance the visual representation of the indicator, colors are assigned based on the relationship between the nonlinear regression value and a signal value (sig) calculated from the previous period's nonlinear regression value. If the current "out" value is greater than the previous "sig" value, the color is set to green; otherwise, it is set to red. The indicator also includes optional features such as coloring the bars based on the indicator's values and displaying signals for potential long and short positions. The signals are generated based on the crossover and crossunder of the "out" and "sig" values. Wrapping Up This indicator combines two important concepts: Nonlinear Regression and Zero-lag Moving Average indicators, which are valuable tools for technical analysis in financial markets. These indicators help traders identify trends, potential reversals, and generate trading signals. By combining the nonlinear regression curve with the zero-lag moving average, this indicator provides a comprehensive view of the price dynamics. Traders can customize the indicator's settings and use it in conjunction with other analysis techniques to make well-informed trading decisions.
Pine Script® göstergesi
loxx tarafından
1
RedK DIY ZLMA: Customizable Zero-Lag MA (Educational / Utility)This script is more of an educational / utility piece rather than a fully-fledged indicator - It provides an easy way to customize and produce a zero-lag Moving average that can then be used in various scenarios What is DIY_ZLMA? ------------------------ The DIY ZLMA is for fans and enthusiasts of researching Moving Averages (like me) - the script enables the user to play around with one of the common approaches used to reduce lag in moving averages - which was explained in this old post below Suggested uses of the DIY_ZLMA --------------------------------------- * The Zero-lag approach here applies 3 moving average passes to a source data series - I'll refer to these 3 passes as Base MA Pass , De-lagging Pass, and Smoothing Pass - these "passes" can be customized from the indicator settings in terms of MA Length and type. The first pass allows the choice of a "source", and the second pass allows additional fine tuning by playing around with the magnification factor. The 3rd pass (smoothing) is optional and can be skipped altogether when needed. (as noted in the script, HMA and TEMA, which are very common low-lag MA's use slightly different approach in the calculation than the one used here .. so we can't get an equivalent of either of these MA's with the customization of DIY_ZLMA parameters) * After the user experiments with the various settings for the 3 passes, and finds a "preferred combination", the script not only plots the resulting My_ZLMA - it also produces the "1-line Pine script formula" that the user can then use in any other script, maybe to smoothen some data series, or to combine with other types of moving averages to create multi-MA cross-over trading signals... and so on. * The DIY_ZLMA can also be added to another indicator as a signal line using the Indicator-on-Indicator feature of TradingView (review this post for step-by-step --> ) * the script also showcases couple of recent (and very neat) Pine features: the use of User-defined Types (UDT) and User-defined Methods - which are awesome and a lot of fun to work with :) Since this is more of a utility piece, I added as many comments as possible to the script to explain the way it works - so it's more valuable if someone finds it by searching the "Add Indicator" feature in TradingView charts Please feel free to play around with this new toy :) and share comments and feedback below if you find this useful. I truly hope you do.
Pine Script® göstergesi
RedKTrader tarafından
11
Zero-lag, 3-Pole Super Smoother [Loxx]Zero-lag, 3-Pole Super Smoother is an Ehlers 3-pole smoother with lag reduction What is 3-pole Super Smoother? A SuperSmoother filter is used anytime a moving average of any type would otherwise be used, with the result that the SuperSmoother filter output would have substantially less lag for an equivalent amount of smoothing produced by the moving average. For example, a five-bar SMA has a cutoff period of approximately 10 bars and has two bars of lag. A SuperSmoother filter with a cutoff period of 10 bars has a lag a half bar larger than the two-pole modified Butterworth filter. Therefore, such a SuperSmoother filter has a maximum lag of approximately 1.5 bars and even less lag into the attenuation band of the filter. The differential in lag between moving average and SuperSmoother filter outputs becomes even larger when the cutoff periods are larger. Included: -Color bars -Loxx's Expanded Source Types
Pine Script® göstergesi
loxx tarafından
1
Zero Lag Detrended Price Oscillator (ZL DPO)This indicator attempts to create a zero lag Detrended price oscillator using 2 different scripts. I actually really like the results so far. I hope you all find it useful too. Green>Red = long Red>Green = short The lines on the example chart are some of the signals that the indicator gave on default settings. The greens are wins, reds are outright losses, and blues are "scratch" trades(signal for other side before hitting stop loss). All of the signals tested were using NNFX money management to see if they are wins or losses(1.5x atr for SL and 1 Atr for TP).
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Zen_Forex_ tarafından
6
Hybrid, Zero lag, Adaptive cycle MACD [Loxx]TASC's March 2008 edition Traders' Tips includes an article by John ​Ehlers titled "Measuring Cycle Periods," and describes the use of bandpass filters to estimate the length, in bars, of the currently dominant price cycle. What are Dominant Cycles and Why should we use them? Even the most casual chart reader will be able to spot times when the market is cycling and other times when longer-term trends are in play. Cycling markets are ideal for swing trading however attempting to “trade the swing” in a trending market can be a recipe for disaster. Similarly, applying trend trading techniques during a cycling market can equally wreak havoc in your account. Cycle or trend modes can readily be identified in hindsight. But it would be useful to have an objective scientific approach to guide you as to the current market mode. There are a number of tools already available to differentiate between cycle and trend modes. For example, measuring the trend slope over the cycle period to the amplitude of the cyclic swing is one possibility. We begin by thinking of cycle mode in terms of frequency or its inverse, periodicity. Since the markets are fractal; daily, weekly, and intraday charts are pretty much indistinguishable when time scales are removed. Thus it is useful to think of the cycle period in terms of its bar count. For example, a 20 bar cycle using daily data corresponds to a cycle period of approximately one month. When viewed as a waveform, slow-varying price trends constitute the waveform's low frequency components and day-to-day fluctuations (noise) constitute the high frequency components. The objective in cycle mode is to filter out the unwanted components--both low frequency trends and the high frequency noise--and retain only the range of frequencies over the desired swing period. A filter for doing this is called a bandpass filter and the range of frequencies passed is the filter's bandwidth . Indicator Features -Zero lag or Regular MACD/signal calculation - Fixed or Band-pass Dominant Cycle for MACD and Signal MA period inputs -10 different moving average options for both MACD and Signal MA calculations -Separate Band-pass Dominant Cycle calculations for both MACD and Signal MA calculations - Slow-to-Fast Band-pass Dominant Cycle input to tweak the ratio of MACD MA input periods as they relate to each other
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loxx tarafından
3
Supertrend Ext1st it exactly looks like the original Supertrend indicator. But if you see the options, you can see it is totally different: It uses my other indicator inside: Zero Lag Keltner Channels, so you can use smoothed ATR bands for calculation instead of the raw ATR. By default it's length is 1 so it works like the original Supertrend. You can choose different sources and moving averages for Keltner Channel calculation It can filter outliers in ATR calculation The indicator code is in my TAExt library, so it can easily be used in custom strategies.
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TheBacktestGuy tarafından
3
Ehlers Average Error Filter [CC]The Average Error Filter was created by John Ehlers and this is a variation of a Zero Lag Exponential Moving Average that uses a Super Smoother to filter out the noise and then uses a second Super Smoother of the difference between the current price and the filtered data. This works well as a trendline and does give out a few false signals like all indicators inevitably do but most signals do a good job of keeping up with the trend and providing clear entries and exits when the trend changes. I have included strong buy and sell signals in addition to normal ones so like always darker colors are strong signals and lighter colors are normal ones. Buy when the line turns green and sell when it turns red. Let me know if there are any other scripts you would like to see me publish!
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cheatcountry tarafından
1
RedK Dual-Color Zero-Lag Moving Average (RedK ZLMA v1)Here's my Dual-color Zero-Lag Moving Average indicator - with alerts - as a separate study This is published in response to couple of requests i received. Please refer to previous posts on TA Basics on creating zero-lag MAs for more background. This version adds couple of extras --------------------------------------------- - the ability to choose the price being used (close vs hl2, hlc3..etc) - ability to change resolution the example chart below on the right uses a weekly resolution for the ZLMA on top of a daily chart - the left chart shows the same view but with the ZLMA resolution set to "same as chart" - Alerts-enabled for when trend change is detected - optional smoothing - keep the smoothing low (3 or 4) else it introduces lagging again i hope some will find this useful - the code is light and can easily be integrated into other indicators of your own - or you can add this ZLMA to your charts in combination with other MA's you use to easily identify trends and swings. let me know your feedback. Good luck!
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RedKTrader tarafından
13
AM_ZLWMA Crossover_xDear All, Please find updated version of Zero lag WMA crossover. In addition to this added 20/50 EMA to get better results. Settings: ZLWMA = 8 identified by Blue line Fast WMA = 21 identified by Red line EMA Period 20/50 How to Trade: Buy: Wait for positive crossover (Blue cross above Red) to happen trade can be taken there but to get better results post crossover once price move above EMA 20 then buy can be initiated. Sell: Wait for negative crossover (Blue cross below Red) to happen trade can be taken there but to get better results post crossover once price move below EMA 20 then sell can be initiated. Reason to wait for confirmation of price action above / Below moving average is most of the time it happens that even after crossover happens sometimes it was just a pull back and from there it could be a possibility for reversal. Once price action confirms moving above / below EMA20 then trade will be initiated. Please comment and ask for any doubt
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happyTacos tarafından
3
[blackcat] L2 Ehlers Zero-lag EMACircumstance Remarks: Because of my carelessness, the script of the same name that I posted before was banned and hidden because the description contained content that violated the TradingView House Rule. After communicating with the MOD, I corrected the description and obtained permission to publish it again. I hereby declare. Sorry for the inconvenience! Level: 2 Background John F. Ehlers introuced Zero-lag EMA Indicator in Nov, 2010. Function In “Zero Lag (Well, Almost)” article, authors John Ehlers and Ric Way presented their zero-lag exponential moving average indicator and strategy. They have adapted their zero-lag EMA by extending the functionality in an additional chart indicator named “Zero-Lag EMA”. Labels were added so that the user can be alerted when a crossing of the averages occurs. The authors created an error-correcting filter for an exponential moving average ( EMA ) that seeks to minimize the lag effect of increasing periods. Increasing the gain parameter from zero changes the filter from an EMA with lag to effectively zero lag (albeit with zero smoothing also). The crossover of these lines can be used to form a trading strategy, with the addition of some threshold value for the difference between the Price and error-correcting line. Key Signal ZLEMA ---> Zero-lag EMA fast line Trigger ---> Zero-lag EMA slow line 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 76th 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.
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blackcat1402 tarafından
5
[blackcat] L2 Ehlers Zero-lag SmootherLevel: 2 Background John F. Ehlers introuced Zero-Lag Data Smoothers in Jul, 2002. Function John Ehlers introduced "Zero-Lag Data Smoothers", the infinite impulse response (IIR) filter and finite impulse response (FIR) filter. In his article this issue on zero-lag smoothing, John Ehlers notes that his favorite filter is the symmetrically weighted six-bar finite impulse response (FIR) filter. This is also known as a triangular moving average, and can be conveniently implemented as a double-smoothed simple moving average. Per Ehlers, since this filter has six elements, its lag is 2.5 bars. Via further processing, this lag can be reduced to zero, but this produces too much overshoot. As a compromise, Ehlers suggests reducing the lag to one bar. To enable a user to adjust the lag easily, I provide the pine v4 code for an Adjustable Lag Filter indicator below. The first input, Price, should typically be set to OHLC, hl2, hl3, ohlc4 etc. The second input, LagReduction, should be set to a value in the zero-to-2.5 range. Setting it to zero will result in no adjustment, and the output will match that of the raw triangular average. Setting it to 2.5 will reduce the lag to zero. Setting it to 1.5 will reduce the lag to one bar. Key Signal Filter--> Zero-Lag Data Smoother fast line Trigger--> Zero-Lag Data Smoother slow line 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 67th 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.
Pine Script® göstergesi
blackcat1402 tarafından
[blackcat] L3 Ehlers ZeroLag Intraday Trading SystemLevel: 3 Background John F. Ehlers introuced ZeroLag Intraday Trading System in his "Rocket Science for Traders" chapter 16. Function blackcat L3 EhlersZeroLag Intraday Trading System is used to find proper long and short entries. Dr. Ehlers developed a completely automatic ZeroLag Intraday Trading System. The concepts of the Instantaneous Trendline and the ZeroLag EMA are very powerful. To demonstrate just how profound these concepts are, Dr. Ehlers designed an intraday trading system. An intraday trade is defined as any active trade that is traded and then closed at the end of the day. Key Signal Smooth --> 4 bar WMA w/ 1 bar lag Detrender --> The amplitude response of a minimum-length HT can be improved by adjusting the filter coefficients by trial and error. HT does not allow DC component at zero frequency for transformation. So, Detrender is used to remove DC component/ trend component. Q1 --> Quadrature phase signal I1 --> In-phase signal Period --> Dominant Cycle in bars SmoothPeriod --> Period with complex averaging DCPeriod ---> Dominant Cycle Period Trendline ---> IT fast line ZeroLag ---> Zero Lag Filter long ---> long entry signal short ---> short entry signal 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. NOTE: This version of Trading System has better preformance than "Automatic SineTrend Trading System". Remarks The 12th 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.
Pine Script® göstergesi
blackcat1402 tarafından
3
Forward Backward EMA [Repaint]Perform forward-backward filtering using exponential averaging, thus providing a zero-phase exponential moving average. The output repaint and cannot be used as input for other indicators. Settings Length : moving average period Src : data input of the moving average Plot Color : the color of the displayed plot Line Width : width of the plotted line Usages The main usage of moving averages is to provide an estimate of the underlying trend in the price by removing higher term variations from it. Non-causal (repainting) indicators are limited to offline applications, as such, they are most useful for summary analyses, note that it is still possible to infer from the output of repainting indicators, however since past outputs are subject to changes, it is extremely difficult to track the effectiveness of such indicators, and in online applications they only track the price, making them equally useful for predictive applications than following the direction of an individual candle. Non-causal filters can be useful in order to have a better view of symbols with a relatively uninformative evolution. Details Causal filters have lag, this is the cost of using past observations as inputs, the more past observations you use, the more lag you will obtain (assuming these past observations have non-zero weights). There are various solutions to reduce the lag of a moving average, the most simple one relying on giving higher weights to more recent observations, another one relies on introducing gain in the filter passband, that is amplifying certain variations in the input signal while attenuating/removing higher term ones, finally, we can use adaptive moving averages to avoid excessive lag. All these previous solutions can be used causally, but they are far from being perfect, as the lag reduction is often done at the cost of smoothness, if we were to keep the original smoothness of the filter while having no lag we would need to use non-causal solutions. The most common solution is to directly use future values as inputs, such moving averages are called "two-sided" moving averages since they use past values as input (left side) as well as future input values (right side), this is equivalent to shifting the results of a moving average backward. The advantages of two-sided moving averages is that they conserve the original amplitude response of the moving average, however, it won't be possible to compute the most recent values of the moving average (since we won't have access to future values at a certain point), an alternative method heavily used in digital signal processing is forward-backward filtering. The method consists of applying a filter forward in time, then we apply it once again backward. In order for you to have an easier understanding of this process think about applying a moving average normally starting at time t = 0 , then apply that moving average once again using the previous results as input but start from t = N-1 , that is from the most recent point, and proceed backward, plotting the result from left to right until you get back to t = 0 . From this, it follows that forward-backward filtering applies a filter twice, the resulting filter is thus a two-passes filter, this results in an even smoother output (more precisely the filter amplitude response is squared). Forward-backward filtering can be done in Pinescript by using the function "line.new" inside a loop, an exponential moving average is applied forward first, then once again backward inside the loop, "line.new" is used to plot the results backward. Notes It is important to note that forward-backward filtering is a repainting process, all the results of the indicator you see on the chart are subject to change over time. Since the method make use of line.new you will have around only 54 visible observations, with the impossibility of using them as input for other indicators. If you see indicators in the future with the same characteristics be aware that they will repaint. Never purchase/rent filters that appear as having no lag, they are either repainting or the results are coming from a lucky shot or from an overfitted model, it is impossible to make both zero-lag and causal moving averages with pinescript, if you have doubt don't test your luck, better safe than sorry.
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alexgrover tarafından
5
Trendflex - Another new Ehlers indicatorSource: Stocks and Commodities V38 Hooray! Another new John Ehlers indicator! John claims this indicator is lag-less and uses the SPY on the Daily as an example. This indicator is a slight modification of Reflex, which I have posted here I think it's better for Stocks and ETFs than Reflex since it factors in long trends. It tends to keep you in winning trades for a long time. I believe this indicator can be used for entries or exits, potentially both. Entry 1. Entering Long positions at the pivot low points (Stocks and ETFs) 2. Entering Long when the Reflex crosses above the zero lines (Stocks, ETFs, Commodities ) Exit 1. Exiting Long positions at a new pivot high point (Stocks and ETFs) 2. Exiting Long when the Reflex crosses below the zero lines (Stocks, ETFs, Commodities ) In this example, I place a Long order on the SPY every time the Reflex crosses above the zero level and exit when it crosses below or pops my stop loss, set at 1.5 * Daily ATR. 2/3 Wins +16.05% Let me know in the comment section if you're able to use this in a strategy.
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DasanC tarafından
10
Reflex - A new Ehlers indicatorSource: Stocks and Commodities V38 Hooray! A new John Ehlers indicator! John claims this indicator is lag-less and uses the SPY on the Daily as an example. He states that drawing a line from peak to peak (or trough to trough) will correspond perfectly with the Asset. I have to say I agree! There is typically one bar of lag or no lag at all! I believe this indicator can be used for either entries or exits, but not both. Entry 1. Entering Long positions at the pivot low points (Stocks and ETFs) 2. Entering Long when the Reflex crosses above the zero lines (Stocks, ETFs, Commodities) Exit 1. Exiting Long positions at a new pivot high point (Stocks and ETFs) 2. Exiting Long when the Reflex crosses below the zero lines (Stocks, ETFs, Commodities) In this example, I place a Long order on the SPY every time the Reflex crosses above the zero level and exit when it crosses below or pops my stop loss, set at 1.5 * Daily ATR. 4/6 Wins +10.76% For me, that's good enough to create a strategy and backtest on several Indices and ETFs, which is what I have a hunch this will work on. I think there is a lot of promise from a single Indicator! Let me know in the comment section if you're able to use this in a strategy.
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DasanC tarafından
8