Range Filtered Trend Signals indicator

1. Introduction

The Range Filtered Trend Signals indicator (by AlgoAlpha) is a composite tool designed to help traders identify both tentative “in-range” price movements and decisive trend changes. By combining three powerful elements

1. a Kalman filter to smooth price noise,
2. a SuperTrend algorithm to gauge directional bias on the filtered line, and
3. a volatility-based range filter to spot mild breakouts—
   this indicator offers clear visual cues for entries and exits on any market or timeframe.

Why combine these components?

• Noise reduction: The Kalman filter adaptively smooths price data, preserving real movements while suppressing random fluctuations.
• Trend bias: SuperTrend applied to the smoothed line defines when the market is trending up or down.
• Range filtering: Dynamic bands based on recent volatility highlight genuine momentum moves without overreacting to micro-noise.

Together, they produce two distinct signal types:

• “In-range” breakouts (dots when price crosses a volatility band but trend has not yet shifted), and
• Trend-change alerts (colored fills when the filtered line flips relative to the SuperTrend).

2. Input Parameters

Tip: Start with the default values, then tweak one group at a time (Kalman vs. SuperTrend vs. range factor) to match your preferred balance of responsiveness vs. noise suppression.

3. Internal Logic

3.1 Kalman Filter Smoothing

The Kalman filter produces a smoothed price line K by iteratively updating:

1. Estimate update:
   – v3 = kalmanAlpha * kalmanPeriod
   – gain = v2 / (v2 + v3)
   – v1 = v1_prev + gain * (close – v1_prev)
2. Error covariance update:
   – v2 = (1 – gain) * v2 + kalmanBeta / kalmanPeriod

Here, v1 is the estimated true price, and v2 is its error variance. Smaller kalmanAlpha/larger kalmanPeriod yield heavier smoothing; a higher kalmanBeta adapts variance faster when volatility changes.

3.2 SuperTrend on the Filtered Line

Using the smoothed series K as the “price,” a standard SuperTrend computation defines two bands:

• UpperBand = K + supertrendFactor × ATR(supertrendAtrPeriod)
• LowerBand = K – supertrendFactor × ATR(supertrendAtrPeriod)

Logic ensures each band only moves in a favorable direction (Upper never decreases unless broken, Lower never increases unless broken). The SuperTrend line itself alternates between the latest Upper and Lower band depending on whether K is above or below the prior band—yielding a clean up/down bias on the Kalman-filtered price.

3.3 Volatility-Based Range Filter

A Weighted Average of the daily range (high – low) over 200 bars defines vola—a smoothed measure of recent volatility. Two dynamic range bands are then set:

• UpperRange = K + dev × vola
• LowerRange = K – dev × vola

These bands capture typical short-term swings around the Kalman line.

3.4 Signal Generation

The indicator produces two types of visual signals:

1. In-Range Breakouts:
   • When the current close crosses above UpperRange or below LowerRange, and the SuperTrend line has not just flipped (isupertrend = isupertrend[1]), a small dot is plotted at the breakout point. This flags a potential pullback or continuation within the prevailing trend.
2. Trend-Change Alerts:
   • When the SuperTrend line flips (i.e., its value differs from the prior bar) and K has crossed through the old band, the chart background (or the Kalman line) is filled in green for an up-flip or red for a down-flip. This highlights a more decisive shift in market direction.

4. Interpretation of Signals

1. In-Range Breakouts (Dots):
   • Purpose: Catch smaller, intra-trend opportunities without waiting for a full trend flip.
   • How to trade: Look for price retests of the breakout level or close-of-bar confirmation before entering in the direction of the predominant trend.
2. Trend-Change Alerts (Fills):
   • Purpose: Identify robust reversals when noise has been removed and volatility bands confirm momentum beyond typical ranges.
   • How to trade: Consider these as primary entry/exit points—enter on the next bar after the fill appears, or wait for a retest of the SuperTrend line for a more conservative approach.

Example Scenario: On an hourly chart of EUR/USD, price may cross the upper range band (dot signal) three times, indicating small pullbacks within an uptrend. Eventually, the Kalman-filtered line pierces the SuperTrend band and the background turns green—a high-conviction signal to establish a new long position.

5. Configuration and Advanced Adjustments

• Adapting to Timeframes:
  • Shorter timeframes (e.g., 5 min) often require a smaller kalmanPeriod (e.g., 50) and slightly higher dev (e.g., 1.5) to avoid false dots.
  • Longer charts (daily/weekly) benefit from a larger kalmanPeriod (100–150) and modest supertrendFactor (1.5–2.0) for stable swings.
• Optimizing Kalman vs. SuperTrend:
  • Increase kalmanBeta if the filter is too sluggish to adapt after sudden volatility spikes.
  • Raise supertrendAtrPeriod if you want the trend filter to ignore small whipsaws.
• Volatility Regime Tuning:
  • In trending, low-volatility markets, reduce dev toward 1.0 to tighten bands and capture earlier in-range moves.
  • In choppy/high-volatility periods, raise dev toward 2.0 to avoid over-signaling.
• Combining with Other Tools:
  • Use higher-timeframe Simple Moving Averages or RSI to confirm the direction flagged by this indicator.
  • Overlay support/resistance zones to validate Swing entries on dot signals.

6. Full ProBuilder Code

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