AP IFTCCIv2/IFTStoch/IFTRSI Multi-Timeframe

10 May

Multi-Timeframe IFT-CCI/Stoch/RSI Composite

This enhanced indicator combines three powerful oscillators—Inverse Fisher Transform (IFT) versions of the Commodity Channel Index (CCI), Stochastic, and Relative Strength Index (RSI)—into a unified multi-timeframe analysis tool. Originally developed by John Ehlers (pioneer of cyclical analysis and signal processing in trading systems) and adapted by KIVANC (fr3762), this version adds dual-timeframe capability to compare indicator values across different chart resolutions.

Key Features:
Triple Oscillator Composite

IFT-CCI: Smoothed CCI values transformed via Ehlers' Inverse Fisher Transform (blue-gold)

IFT-Stochastic: Classic stochastic oscillator processed through IFT (blue)

IFT-RSI: RSI oscillator converted to IFT format (magenta)

Composite Average Line: Combined average of all three indicators (green)

Multi-Timeframe Analysis

Compare primary and secondary timeframes (e.g., 1H vs. 4H, daily vs. weekly)

Primary timeframe plots use solid lines with 80% opacity

Secondary timeframe (optional) uses dashed/circle markers with 40% opacity

Key Levels

Overbought (+0.75) and oversold (-0.75) reference lines

Zero-centerline for momentum direction bias

Applications:
Trend Confirmation: Align higher timeframe signals with lower timeframe entries

Divergence Detection: Spot inter-timeframe discrepancies in momentum

Regime Filter: Use higher timeframe composite values to filter trades

Technical Basis:
Inverse Fisher Transform: Compresses oscillator values into bounded (-1 to +1) range while emphasizing extreme moves

Dual WMA Smoothing: Combines initial calculation smoothing (WMA1) with final output smoothing (WMA2)

Exponential Scaling: (e^2x - 1)/(e^2x + 1) formula converts Gaussian-like distributions to bounded outputs

Credits:
Original Concept: John Ehlers (IFT methodology, cyclical analysis foundations)

Initial Implementation: KIVANC (fr3762 on Twitter) for the base IFT-CCI/Stoch/RSI script

Multi-Timeframe Adaptation: [Your Name/Handle] for cross-resolution analysis capabilities

This tool is particularly effective for traders seeking to align multiple timeframes while using Ehlers' noise-reduction techniques. The composite average line provides a consensus view, while the individual oscillators help identify component strength/weakness.

21 May

Sürüm Notları

Multi-Timeframe IFT-CCI/Stoch/RSI Composite

(edit: updated screenshot/chart which had daily pivots applied, which was causing it to cramp the chart)
This enhanced indicator combines three powerful oscillators—Inverse Fisher Transform (IFT) versions of the Commodity Channel Index (CCI), Stochastic, and Relative Strength Index (RSI)—into a unified multi-timeframe analysis tool. Originally developed by John Ehlers (pioneer of cyclical analysis and signal processing in trading systems) and adapted by KIVANC (fr3762), this version adds dual-timeframe capability to compare indicator values across different chart resolutions.

Key Features:
Triple Oscillator Composite

IFT-CCI: Smoothed CCI values transformed via Ehlers' Inverse Fisher Transform (blue-gold)

IFT-Stochastic: Classic stochastic oscillator processed through IFT (blue)

IFT-RSI: RSI oscillator converted to IFT format (magenta)

Composite Average Line: Combined average of all three indicators (green)

Multi-Timeframe Analysis

Compare primary and secondary timeframes (e.g., 1H vs. 4H, daily vs. weekly)

Primary timeframe plots use solid lines with 80% opacity

Secondary timeframe (optional) uses dashed/circle markers with 40% opacity

Key Levels

Overbought (+0.75) and oversold (-0.75) reference lines

Zero-centerline for momentum direction bias

Applications:
Trend Confirmation: Align higher timeframe signals with lower timeframe entries

Divergence Detection: Spot inter-timeframe discrepancies in momentum

Regime Filter: Use higher timeframe composite values to filter trades

Technical Basis:
Inverse Fisher Transform: Compresses oscillator values into bounded (-1 to +1) range while emphasizing extreme moves

Dual WMA Smoothing: Combines initial calculation smoothing (WMA1) with final output smoothing (WMA2)

Exponential Scaling: (e^2x - 1)/(e^2x + 1) formula converts Gaussian-like distributions to bounded outputs

Credits:
Original Concept: John Ehlers (IFT methodology, cyclical analysis foundations)

Initial Implementation: KIVANC (fr3762 on Twitter) for the base IFT-CCI/Stoch/RSI script

Multi-Timeframe Adaptation: [Your Name/Handle] for cross-resolution analysis capabilities

This tool is particularly effective for traders seeking to align multiple timeframes while using Ehlers' noise-reduction techniques. The composite average line provides a consensus view, while the individual oscillators help identify component strength/weakness.