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lib/momentum/asi/Asi.md
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# ASI: Accumulation Swing Index
# ASI: Accumulation Swing Index
| Property | Value |
| ---------------- | -------------------------------- |
| **Category** | Momentum |
| **Inputs** | OHLCV bar (TBar) |
| **Parameters** | `limitMove` (default 3.0) |
| **Outputs** | Single series (Asi) |
| **Output range** | Varies (see docs) |
| **Warmup** | `> 2` bars |
### TL;DR
- The Accumulation Swing Index is Wilder's method for separating genuine breakouts from whipsaw noise.
- Parameterized by `limitmove` (default 3.0).
- Output range: Varies (see docs).
- Requires `> 2` bars of warmup before first valid output (IsHot = true).
- Validated against TA-Lib, Skender, and Tulip reference implementations where available.
> "Price tells us what is happening. The Accumulation Swing Index tells us whether to believe it." — J. Welles Wilder Jr.
lib/momentum/bias/Bias.md
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# BIAS: Price Deviation from Moving Average (also known as Disparity Index)
| Property | Value |
| ---------------- | -------------------------------- |
| **Category** | Momentum |
| **Inputs** | Source (close) |
| **Parameters** | `period` |
| **Outputs** | Single series (Bias) |
| **Output range** | Varies (see docs) |
| **Warmup** | `period` bars |
### TL;DR
- The Bias indicator measures the percentage difference between the current price and its Simple Moving Average (SMA).
- Parameterized by `period`.
- Output range: Varies (see docs).
- Requires `period` bars of warmup before first valid output (IsHot = true).
- Validated against TA-Lib, Skender, and Tulip reference implementations where available.
> "When traders ask 'how overbought is it?', they're really asking how far price has strayed from its anchor. Bias answers that question in percentage terms, telling you whether the current price is 5% above or 10% below its moving average. It's the market's stretch marks made visible."
The Bias indicator measures the percentage difference between the current price and its Simple Moving Average (SMA). A positive bias indicates price is above the average (potentially overbought), while negative bias suggests price is below average (potentially oversold). This is one of the simplest yet most effective tools for identifying mean-reversion opportunities.
lib/momentum/bop/Bop.md
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# BOP: Balance of Power
| Property | Value |
| ---------------- | -------------------------------- |
| **Category** | Momentum |
| **Inputs** | OHLCV bar (TBar) |
| **Parameters** | None |
| **Outputs** | Single series (BOP) |
| **Output range** | Varies (see docs) |
| **Warmup** | `> 0` bars |
### TL;DR
- The Balance of Power measures buying versus selling pressure by comparing the body (Close minus Open) to the range (High minus Low).
- No configurable parameters; computation is stateless per bar.
- Output range: Varies (see docs).
- Requires `> 0` bars of warmup before first valid output (IsHot = true).
- Validated against TA-Lib, Skender, and Tulip reference implementations where available.
> "The market is a tug of war between buyers and sellers. BOP tells you who's pulling harder."
The Balance of Power measures buying versus selling pressure by comparing the body (Close minus Open) to the range (High minus Low). Created by Igor Livshin in 2001, this ratio oscillates between -1 and +1, providing instantaneous momentum readings with zero lag. A stateless indicator: each bar evaluated independently, no memory of previous values required.
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- Livshin, I. (2001). "Balance of Power." *Technical Analysis of Stocks & Commodities*, August 2001.
- Investopedia. "Balance of Power (BOP) Indicator." https://www.investopedia.com/terms/b/bop.asp
- Achelis, S. (2000). *Technical Analysis from A to Z*. McGraw-Hill. (General indicator theory)
- Achelis, S. (2000). *Technical Analysis from A to Z*. McGraw-Hill. (General indicator theory)
lib/momentum/cci/Cci.md
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# CCI - Commodity Channel Index
# CCI - Commodity Channel Index
| Property | Value |
| ---------------- | -------------------------------- |
| **Category** | Momentum |
| **Inputs** | OHLCV bar (TBar) |
| **Parameters** | `period` (default DefaultPeriod) |
| **Outputs** | Single series (CCI) |
| **Output range** | Varies (see docs) |
| **Warmup** | `> period` bars |
### TL;DR
- The Commodity Channel Index (CCI) is a versatile momentum-based oscillator developed by Donald Lambert in 1980.
- Parameterized by `period` (default defaultperiod).
- Output range: Varies (see docs).
- Requires `> period` bars of warmup before first valid output (IsHot = true).
- Validated against TA-Lib, Skender, and Tulip reference implementations where available.
## Overview
lib/momentum/cfb/Cfb.md
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# CFB: Jurik Composite Fractal Behavior
| Property | Value |
| ---------------- | -------------------------------- |
| **Category** | Momentum |
| **Inputs** | Source (close) |
| **Parameters** | int[]? lengths = null |
| **Outputs** | Single series (CFB) |
| **Output range** | Varies (see docs) |
| **Warmup** | 1 bar |
### TL;DR
- The Composite Fractal Behavior index measures trend duration by analyzing fractal efficiency across 96 simultaneous lookback periods (2 to 192 bars...
- Parameterized by int[]? lengths = null.
- Output range: Varies (see docs).
- Requires 1 bar of warmup before first valid output (IsHot = true).
- Validated against TA-Lib, Skender, and Tulip reference implementations where available.
> "Mark Jurik's CFB is not a momentum indicator. It is a stopwatch for chaos."
The Composite Fractal Behavior index measures trend duration by analyzing fractal efficiency across 96 simultaneous lookback periods (2 to 192 bars by default). Rather than asking "how strong is the trend," CFB asks "how long has the market been moving efficiently." The answer: a single integer representing the dominant trending timeframe. Use CFB to dynamically tune other indicators: instead of RSI(14), use RSI(CFB).
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- Jurik Research. "Composite Fractal Behavior." http://jurikres.com/
- Mandelbrot, B. (1997). *Fractals and Scaling in Finance*. Springer. (Theoretical foundation)
- Peters, E. (1994). *Fractal Market Analysis*. Wiley. (Fractal efficiency concepts)
- Peters, E. (1994). *Fractal Market Analysis*. Wiley. (Fractal efficiency concepts)
lib/momentum/cmo/Cmo.md
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# CMO (Chande Momentum Oscillator)
# CMO (Chande Momentum Oscillator)
| Property | Value |
| ---------------- | -------------------------------- |
| **Category** | Momentum |
| **Inputs** | Source (close) |
| **Parameters** | `period` (default DefaultPeriod) |
| **Outputs** | Single series (Cmo) |
| **Output range** | $-100$ to $+100$ |
| **Warmup** | `period + 1` bars |
### TL;DR
- The Chande Momentum Oscillator (CMO) is a momentum indicator developed by Tushar Chande.
- Parameterized by `period` (default defaultperiod).
- Output range: $-100$ to $+100$.
- Requires `period + 1` bars of warmup before first valid output (IsHot = true).
- Validated against TA-Lib, Skender, and Tulip reference implementations where available.
The Chande Momentum Oscillator (CMO) is a momentum indicator developed by Tushar Chande. Unlike RSI which uses smoothed averages of gains and losses, CMO uses raw sums of up and down movements, making it more responsive to price changes. The indicator oscillates between -100 and +100.
lib/momentum/macd/Macd.md
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# MACD: Moving Average Convergence Divergence
| Property | Value |
| ---------------- | -------------------------------- |
| **Category** | Momentum |
| **Inputs** | Source (close) |
| **Parameters** | `fastPeriod` (default 12), `slowPeriod` (default 26), `signalPeriod` (default 9) |
| **Outputs** | Multiple series (Signal, Histogram) |
| **Output range** | Varies (see docs) |
| **Warmup** | 1 bar |
### TL;DR
- The Moving Average Convergence Divergence measures momentum through the relationship between two exponential moving averages.
- Parameterized by `fastperiod` (default 12), `slowperiod` (default 26), `signalperiod` (default 9).
- Output range: Varies (see docs).
- Requires 1 bar of warmup before first valid output (IsHot = true).
- Validated against TA-Lib, Skender, and Tulip reference implementations where available.
> "The trend is your friend, until it bends." — Ed Seykota
The Moving Average Convergence Divergence measures momentum through the relationship between two exponential moving averages. Created by Gerald Appel in 1979, the indicator transforms price into a bounded oscillator that reveals trend strength, direction, and potential reversals. Standard parameters (12, 26, 9) detect monthly and biweekly cycles: the 26-period represents roughly one trading month, the 12-period half that duration.
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- Aspray, T. (1986). "MACD Histogram." *Technical Analysis of Stocks & Commodities*.
- Murphy, J. (1999). *Technical Analysis of the Financial Markets*. New York Institute of Finance.
- Pring, M. (2002). *Technical Analysis Explained*. McGraw-Hill.
- Elder, A. (1993). *Trading for a Living*. Wiley. (Discussion of MACD histogram interpretation)
- Elder, A. (1993). *Trading for a Living*. Wiley. (Discussion of MACD histogram interpretation)
lib/momentum/mom/Mom.md
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# MOM: Momentum (Absolute Price Change)
| Property | Value |
| ---------------- | -------------------------------- |
| **Category** | Momentum |
| **Inputs** | Source (close) |
| **Parameters** | `period` (default 10) |
| **Outputs** | Single series (Mom) |
| **Output range** | Varies (see docs) |
| **Warmup** | `period + 1` bars |
### TL;DR
- MOM (Momentum) calculates the absolute price difference between the current value and the value N periods ago.
- Parameterized by `period` (default 10).
- Output range: Varies (see docs).
- Requires `period + 1` bars of warmup before first valid output (IsHot = true).
- Validated against TA-Lib, Skender, and Tulip reference implementations where available.
> "The market's simplest question answered: how much has price moved in N bars? No ratios, no percentages. Just the raw delta."
MOM (Momentum) calculates the absolute price difference between the current value and the value N periods ago. It is the purest expression of directional price movement, returning a signed value in the same units as the input. Positive MOM indicates rising prices; negative indicates falling. This is functionally identical to ROC but with a configurable lookback period (default 10 vs ROC's convention), and maps directly to TA-Lib's `MOM` function.
lib/momentum/pmo/Pmo.md
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# PMO: Price Momentum Oscillator
| Property | Value |
| ---------------- | -------------------------------- |
| **Category** | Momentum |
| **Inputs** | Source (close) |
| **Parameters** | `timePeriods` (default DefaultTimePeriods), `smoothPeriods` (default DefaultSmoothPeriods), `signalPeriods` (default DefaultSignalPeriods) |
| **Outputs** | Single series (Pmo) |
| **Output range** | Varies (see docs) |
| **Warmup** | `timePeriods + smoothPeriods` bars |
### TL;DR
- PMO (Price Momentum Oscillator), developed by Carl Swenlin at DecisionPoint, is a double-smoothed 1-bar rate of change.
- Parameterized by `timeperiods` (default defaulttimeperiods), `smoothperiods` (default defaultsmoothperiods), `signalperiods` (default defaultsignalperiods).
- Output range: Varies (see docs).
- Requires `timePeriods + smoothPeriods` bars of warmup before first valid output (IsHot = true).
- Validated against TA-Lib, Skender, and Tulip reference implementations where available.
> "Double-smooth the rate of change and you get something that actually tells you where momentum is headed, not where it was five bars ago."
PMO (Price Momentum Oscillator), developed by Carl Swenlin at DecisionPoint, is a double-smoothed 1-bar rate of change. It applies two custom EMA passes to a percentage ROC, producing a momentum oscillator that is smoother than raw ROC yet more responsive than triple-smoothed alternatives like TRIX. The custom EMA uses $\alpha = 2/N$ rather than the standard $2/(N+1)$, and seeds with the SMA of the first N values. PMO oscillates around zero: positive values indicate upward momentum, negative values indicate downward momentum.
lib/momentum/ppo/Ppo.md
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# PPO: Percentage Price Oscillator
| Property | Value |
| ---------------- | -------------------------------- |
| **Category** | Momentum |
| **Inputs** | Source (close) |
| **Parameters** | `fastPeriod` (default DefaultFastPeriod), `slowPeriod` (default DefaultSlowPeriod), `signalPeriod` (default DefaultSignalPeriod) |
| **Outputs** | Multiple series (Signal, Histogram) |
| **Output range** | Varies (see docs) |
| **Warmup** | 1 bar |
### TL;DR
- PPO (Percentage Price Oscillator) measures the percentage difference between a fast EMA and a slow EMA.
- Parameterized by `fastperiod` (default defaultfastperiod), `slowperiod` (default defaultslowperiod), `signalperiod` (default defaultsignalperiod).
- Output range: Varies (see docs).
- Requires 1 bar of warmup before first valid output (IsHot = true).
- Validated against TA-Lib, Skender, and Tulip reference implementations where available.
> "MACD told you the spread in dollars. PPO tells you the spread in percent. One of those actually works across instruments."
PPO (Percentage Price Oscillator) measures the percentage difference between a fast EMA and a slow EMA. It is functionally equivalent to MACD normalized by the slow EMA, producing values that are comparable across instruments with different price levels. The implementation outputs three components: the PPO line, a signal line (EMA of PPO), and a histogram (PPO minus Signal).
lib/momentum/prs/Prs.md
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# PRS: Price Relative Strength
# PRS: Price Relative Strength
| Property | Value |
| ---------------- | -------------------------------- |
| **Category** | Momentum |
| **Inputs** | Source (close) |
| **Parameters** | `smoothPeriod` (default 1) |
| **Outputs** | Single series (PRS) |
| **Output range** | Varies (see docs) |
| **Warmup** | `smoothPeriod` bars |
### TL;DR
- **Category:** Momentum **Also known as:** Relative Strength Comparison, Price Ratio, Performance Ratio
- Parameterized by `smoothperiod` (default 1).
- Output range: Varies (see docs).
- Requires `smoothPeriod` bars of warmup before first valid output (IsHot = true).
- Validated against TA-Lib, Skender, and Tulip reference implementations where available.
**Category:** Momentum
**Also known as:** Relative Strength Comparison, Price Ratio, Performance Ratio
lib/momentum/roc/Roc.md
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# ROC: Rate of Change (Absolute)
| Property | Value |
| ---------------- | -------------------------------- |
| **Category** | Momentum |
| **Inputs** | Source (close) |
| **Parameters** | `period` (default 9) |
| **Outputs** | Single series (Roc) |
| **Output range** | Varies (see docs) |
| **Warmup** | `period + 1` bars |
### TL;DR
- ROC (Rate of Change) calculates the absolute price difference between the current value and the value N periods ago.
- Parameterized by `period` (default 9).
- Output range: Varies (see docs).
- Requires `period + 1` bars of warmup before first valid output (IsHot = true).
- Validated against TA-Lib, Skender, and Tulip reference implementations where available.
> "The simplest momentum measure: how far has price moved? Not percentage, not ratio - just the raw difference."
ROC (Rate of Change) calculates the absolute price difference between the current value and the value N periods ago. This is the most basic form of momentum measurement, returning the raw price change in the same units as the input data. Unlike ROCP (percentage) or ROCR (ratio), ROC preserves the original scale, making it directly interpretable in dollar/point terms.
lib/momentum/rocp/Rocp.md
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# ROCP: Rate of Change Percentage
| Property | Value |
| ---------------- | -------------------------------- |
| **Category** | Momentum |
| **Inputs** | Source (close) |
| **Parameters** | `period` (default 9) |
| **Outputs** | Single series (Rocp) |
| **Output range** | Varies (see docs) |
| **Warmup** | `period + 1` bars |
### TL;DR
- ROCP (Rate of Change Percentage) calculates the percentage change between the current value and the value N periods ago.
- Parameterized by `period` (default 9).
- Output range: Varies (see docs).
- Requires `period + 1` bars of warmup before first valid output (IsHot = true).
- Validated against TA-Lib, Skender, and Tulip reference implementations where available.
> "The percentage form of momentum: by what percent has price changed? The most intuitive momentum measure."
ROCP (Rate of Change Percentage) calculates the percentage change between the current value and the value N periods ago. This is the most commonly used form of rate of change, expressing change in percentage terms that are directly interpretable (e.g., 5.0 = 5% increase).
lib/momentum/rocr/Rocr.md
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# ROCR: Rate of Change Ratio
| Property | Value |
| ---------------- | -------------------------------- |
| **Category** | Momentum |
| **Inputs** | Source (close) |
| **Parameters** | `period` (default 9) |
| **Outputs** | Single series (Rocr) |
| **Output range** | Varies (see docs) |
| **Warmup** | `period + 1` bars |
### TL;DR
- ROCR (Rate of Change Ratio) calculates the ratio between the current value and the value N periods ago.
- Parameterized by `period` (default 9).
- Output range: Varies (see docs).
- Requires `period + 1` bars of warmup before first valid output (IsHot = true).
- Validated against TA-Lib, Skender, and Tulip reference implementations where available.
> "The ratio form of momentum: how many times larger is the current price compared to the past? A multiplier view of market movement."
ROCR (Rate of Change Ratio) calculates the ratio between the current value and the value N periods ago. Values hover around 1.0, with values above 1.0 indicating price increase and values below 1.0 indicating price decrease. Unlike ROC (absolute) or ROCP (percentage), ROCR provides a dimensionless multiplier that directly shows the price ratio.
lib/momentum/rsi/Rsi.md
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# RSI: Relative Strength Index
| Property | Value |
| ---------------- | -------------------------------- |
| **Category** | Momentum |
| **Inputs** | Source (close) |
| **Parameters** | `period` (default 14) |
| **Outputs** | Single series (Rsi) |
| **Output range** | Varies (see docs) |
| **Warmup** | `period + 1` bars |
### TL;DR
- The Relative Strength Index measures the speed and magnitude of price changes.
- Parameterized by `period` (default 14).
- Output range: Varies (see docs).
- Requires `period + 1` bars of warmup before first valid output (IsHot = true).
- Validated against TA-Lib, Skender, and Tulip reference implementations where available.
> "Momentum is the premier anomaly." — Clifford Asness, AQR Capital (who actually said it, and meant it)
The Relative Strength Index measures the speed and magnitude of price changes. Introduced by J. Welles Wilder Jr. in 1978, it oscillates between 0 and 100, identifying overbought and oversold conditions. The "Relative Strength" name is misleading: RSI measures internal strength (price versus itself) not relative strength (asset versus benchmark). Wilder knew this. He kept the name anyway. Marketing, perhaps.
@@ -303,4 +320,4 @@ finally
- Wilder, J. W. (1978). *New Concepts in Technical Trading Systems*. Trend Research. Chapter: Relative Strength Index.
- Constance Brown. (1999). *Technical Analysis for the Trading Professional*. McGraw-Hill. (RSI divergence patterns)
- Cutler, David. (1991). "RSI Revisited." *Technical Analysis of Stocks & Commodities*. (Smoothed RSI variants)
- Cutler, David. (1991). "RSI Revisited." *Technical Analysis of Stocks & Commodities*. (Smoothed RSI variants)
lib/momentum/rsx/Rsx.md
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# RSX: Relative Strength Quality Index
| Property | Value |
| ---------------- | -------------------------------- |
| **Category** | Momentum |
| **Inputs** | Source (close) |
| **Parameters** | `period` |
| **Outputs** | Single series (Rsx) |
| **Output range** | Varies (see docs) |
| **Warmup** | `period` bars |
### TL;DR
- Mark Jurik's RSX represents the pinnacle of bounded momentum oscillator design.
- Parameterized by `period`.
- Output range: Varies (see docs).
- Requires `period` bars of warmup before first valid output (IsHot = true).
- Validated against TA-Lib, Skender, and Tulip reference implementations where available.
> "RSX is to RSI what a Tesla is to a horse-drawn carriage: same basic concept, vastly superior engineering."
Mark Jurik's RSX represents the pinnacle of bounded momentum oscillator design. Standard RSI suffers from a fundamental paradox: raw RSI produces jagged noise triggering false signals at overbought/oversold boundaries, but smoothing introduces unacceptable lag that delays turning points. RSX solves this through cascaded IIR filter topology that eliminates high-frequency noise while preserving linear phase response. The result: output so smooth it resembles a sine wave, yet turns precisely at market extrema with zero effective lag.
@@ -358,4 +375,4 @@ Epsilon threshold prevents division by zero while maintaining meaningful output
- Jurik, M. (1990s). "RSX: Relative Strength Quality Index." Jurik Research. Proprietary documentation.
- Ehlers, J. F. (2001). *Rocket Science for Traders*. Wiley. IIR filter design principles.
- ProRealCode. "Jurik RSX Implementation." https://www.prorealcode.com/prorealtime-indicators/jurik-rsx/
- Scribd. "Jurik RSX Algorithm Reference." https://scribd.com/document/253633684/Jurik-RSX
- Scribd. "Jurik RSX Algorithm Reference." https://scribd.com/document/253633684/Jurik-RSX
lib/momentum/sam/Sam.md
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# SAM: Smoothed Adaptive Momentum
# SAM: Smoothed Adaptive Momentum
| Property | Value |
| ---------------- | -------------------------------- |
| **Category** | Momentum |
| **Inputs** | Source (close) |
| **Parameters** | `alpha` (default 0.07), `cutoff` (default 8) |
| **Outputs** | Single series (Sam) |
| **Output range** | Varies (see docs) |
| **Warmup** | `MaxCyclePeriod * 2` bars |
### TL;DR
- The Smoothed Adaptive Momentum oscillator measures price momentum over an adaptively determined lookback period equal to the dominant cycle length,...
- Parameterized by `alpha` (default 0.07), `cutoff` (default 8).
- Output range: Varies (see docs).
- Requires `MaxCyclePeriod * 2` bars of warmup before first valid output (IsHot = true).
- Validated against TA-Lib, Skender, and Tulip reference implementations where available.
The Smoothed Adaptive Momentum oscillator measures price momentum over an adaptively determined lookback period equal to the dominant cycle length, then smooths the result with a 2-pole Super Smoother filter. Unlike fixed-period momentum indicators (ROC, TRIX) that use an arbitrary lookback, SAM measures the dominant cycle via Ehlers' Homodyne Discriminator and uses that cycle length as the momentum window, ensuring that the momentum measurement always spans exactly one full cycle. This eliminates the half-cycle phase distortion that plagues fixed-period momentum, producing a zero-lag momentum oscillator that naturally adapts to changing market rhythm.
lib/momentum/tsi/Tsi.md
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# TSI: True Strength Index
# TSI: True Strength Index
| Property | Value |
| ---------------- | -------------------------------- |
| **Category** | Momentum |
| **Inputs** | Source (close) |
| **Parameters** | `longPeriod` (default DefaultLongPeriod), `shortPeriod` (default DefaultShortPeriod), `signalPeriod` (default DefaultSignalPeriod) |
| **Outputs** | Single series (Tsi) |
| **Output range** | $-1$ to $+1$ |
| **Warmup** | 1 bar |
### TL;DR
- The True Strength Index (TSI) is a momentum oscillator developed by William Blau that uses double-smoothed exponential moving averages of price mom...
- Parameterized by `longperiod` (default defaultlongperiod), `shortperiod` (default defaultshortperiod), `signalperiod` (default defaultsignalperiod).
- Output range: $-1$ to $+1$.
- Requires 1 bar of warmup before first valid output (IsHot = true).
- Validated against TA-Lib, Skender, and Tulip reference implementations where available.
The True Strength Index (TSI) is a momentum oscillator developed by William Blau that uses double-smoothed exponential moving averages of price momentum to reduce noise and identify trend strength and direction.
lib/momentum/vel/Vel.md
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# VEL: Jurik Velocity
| Property | Value |
| ---------------- | -------------------------------- |
| **Category** | Momentum |
| **Inputs** | Source (close) |
| **Parameters** | `period` |
| **Outputs** | Single series (Vel) |
| **Output range** | Varies (see docs) |
| **Warmup** | `period` bars |
### TL;DR
- Jurik Velocity (VEL) measures price rate-of-change through the differential between two weighted moving averages with distinct inertia profiles.
- Parameterized by `period`.
- Output range: Varies (see docs).
- Requires `period` bars of warmup before first valid output (IsHot = true).
- Validated against TA-Lib, Skender, and Tulip reference implementations where available.
> "Momentum is easy. Smooth momentum without lag is hard. Jurik Velocity is the answer."
Jurik Velocity (VEL) measures price rate-of-change through the differential between two weighted moving averages with distinct inertia profiles. Standard momentum ($P_t - P_{t-n}$) amplifies noise: single outlier bars create false signals. VEL exploits the different convergence speeds of Parabolic Weighted Moving Average (PWMA) and linear Weighted Moving Average (WMA) to isolate clean velocity information. The quadratic weighting of PWMA responds faster than linear WMA; their difference captures acceleration without bar-to-bar noise.
@@ -363,4 +380,4 @@ Reset propagates to composed indicators, ensuring clean state.
- Jurik, M. (1990s). "Jurik Velocity (VEL)." Jurik Research. Proprietary documentation.
- Kaufman, P. J. (2013). *Trading Systems and Methods*. 5th ed. Wiley. Chapter on weighted moving averages.
- Ehlers, J. F. (2001). *Rocket Science for Traders*. Wiley. Filter design principles.
- Ehlers, J. F. (2001). *Rocket Science for Traders*. Wiley. Filter design principles.