Novel Indicator: Power Assisted Trend Following – Charts – 20 March 2025

Energy Assisted Development Following Indicator 

How are you going to measure the energy of a chart? We have now developed a novel indicator primarily based on ideas from digital sign processing (energy & vitality).

Overview

The PowerIndicator is an implementation of the “Energy Assisted Development Following” methodology developed by Dr. Andreas A. Aigner and Walter Schrabmair. This indicator builds upon and improves J. Welles Wilder’s pattern following ideas by making use of ideas from sign evaluation to monetary markets.

The core perception of this indicator is that profitable pattern following requires value actions to exceed a sure threshold (usually a a number of of the Common True Vary). By measuring the “energy” of each sign and noise elements in value actions, this indicator helps merchants determine when a market is in a powerful sufficient pattern to commerce profitably.

The total analysis report on this system is out there at no cost on ResearchGate: Energy Assisted Development Following.

Theoretical Background

The Drawback with Conventional Development Following

J. Welles Wilder’s “Volatility System” (printed in his 1978 ebook “New Ideas in Technical Buying and selling Techniques”) makes use of a trailing stop-loss primarily based on the Common True Vary (ATR). The system follows new highs/lows with a trailing cease and reverses course when the cease is triggered.

Nevertheless, as demonstrated within the analysis, this method solely works profitably when the pattern’s amplitude exceeds a sure a number of of the stop-loss vary:

• When value fluctuations are equal to or smaller than the stop-loss (1× ATR), the system continually will get stopped out and loses cash
• At 2× ATR, the system nonetheless loses cash however lower than at 1× ATR
• At 3× ATR, the system breaks even
• At 4× ATR or increased, the system turns into worthwhile

This creates the necessity for a technique to measure when a market is trending strongly sufficient to commerce.

The Energy Idea

The PowerIndicator applies ideas from sign evaluation, particularly the notion of “energy” in alerts. In physics, energy for periodic alerts is outlined as the typical vitality over a interval. The researchers tailored this idea to monetary markets by:

1. Calculating the “energy” of value actions
2. Separating this energy into “sign” (pattern) and “noise” (deviation from pattern) elements
3. Evaluating these energy measurements to a threshold primarily based on the ATR

This method supplies a extra correct method to determine tradable traits than Wilder’s Directional Motion indicators (DX, ADX, ADXR).

Mathematical Basis

The indicator calculates a number of key metrics:

1. Energy of a Worth Collection

For a window of N intervals, the facility at time j is calculated as:

Energy(j,N) = (1/N) * Σ(|P(j-n)/P(j-N+1)|²)

The place:

• P(j-n) is the value n intervals in the past
• P(j-N+1) is the value firstly of the N-period window
• The sum runs from n=0 to N-1

2. Energy of Sign and Noise

The worth collection is decomposed into:

• Sign: The N-period transferring common (MA)
• Noise: The deviation of value from the transferring common

The ability of every part is calculated as:

Energy of Sign:

PowerOfSignal(j,N) = (1/N) * Σ(|MA(j-n,N)/P(j-N+1)|²)

Energy of Noise:

PowerOfNoise(j,N) = (1/N) * Σ(|(P(j-n) – MA(j-n,N))/P(j-N+1)|²)

3. Energy Threshold

The ability threshold is predicated on the ATR normalized by the Customary Instrument Fixed (SIC):

PowerThreshold(j) = |ATR(j)/SIC(j)|²

The place SIC is outlined as 1% of the present value.

4. Energy Ratios

The ultimate metrics used for buying and selling selections are:

Sign Energy Ratio:

R(Sign) = √((PowerOfSignal(j,N) – 1)/PowerThreshold(j))

Noise Energy Ratio:

R(Noise) = √(PowerOfNoise(j,N)/PowerThreshold(j))

These ratios characterize what number of multiples of the ATR the sign and noise elements are, respectively.

Elements of the PowerIndicator

The PowerIndicator.mq5 implementation calculates and shows 5 units of metrics, every for 5 completely different time intervals (10, 20, 50, 100, and 200):

1. Worth Shifting Averages (PMA)

Easy transferring averages of value for various intervals. These function the premise for the sign part.

2. Sum Power (SE)

Measures the normalized squared deviations of value from its transferring common. This represents the uncooked vitality of value actions relative to the beginning value of every window.

3. Sum Power Shifting Common (SEMA)

Measures the squared ratio of transferring common to cost from interval days in the past. This represents the vitality of the pattern part.

4. Energy Ratio Noise

The sq. root of the ratio between Sum Power and the facility threshold. This reveals what number of multiples of the ATR the noise part is.

5. Energy Ratio Sign

The sq. root of the ratio between absolutely the distinction of Sum Power MA from 1 and the facility threshold. This reveals what number of multiples of the ATR the sign part is.

Interpretation and Buying and selling Functions

When to Use the Indicator

The analysis reveals that the Energy Ratio of Noise has a stronger relationship to profitability than the Sign Energy Ratio, with the 50-day calculation displaying the strongest correlation (R² = 0.37).

Based mostly on the analysis findings:

1. Development Power Evaluation: Larger Energy Ratio values (particularly above 4) point out stronger traits which might be extra prone to be worthwhile for pattern following methods.
2. Market Choice: Use the Energy Ratios to rank completely different markets or securities, specializing in these with the very best values.
3. Entry Timing: Think about getting into pattern following trades when:
   • The Energy Ratio Noise exceeds 4
   • The pattern course is evident (value above/beneath transferring common)
4. Exit Concerns: Monitor for reducing Energy Ratios as potential early warning of pattern weak spot.

Optimum Settings

The analysis discovered:

• A multiplier of 4× ATR for stop-loss placement supplies one of the best outcomes
• The 50-day calculation interval reveals the strongest correlation with profitability
• Each 30-day and 100-day intervals additionally present vital correlations

Configuration Choices

The PowerIndicator.mq5 implementation supplies a number of configuration choices:

enter int ATR_Period = 14; // ATR Interval enter bool Show_PMA = false; // Present Worth Shifting Averages enter bool Show_SumEnergy = false; // Present Sum Power enter bool Show_SumEnergyMA = false; // Present Sum Power MA enter bool Show_PowerRatioNoise = true; // Present Energy Ratio Noise enter bool Show_PowerRatioSignal = true; // Present Energy Ratio Sign

By default, solely the Energy Ratio Noise and Energy Ratio Sign elements are displayed, as these are probably the most immediately helpful for buying and selling selections.

Visible Illustration

The indicator makes use of colour coding to differentiate between completely different time intervals:

• Blue colour scheme for Worth Shifting Averages (PMA)
• Pink colour scheme for Sum Power
• Inexperienced colour scheme for Sum Power MA
• Purple/Magenta colour scheme for Energy Ratio Noise
• Orange/Yellow colour scheme for Energy Ratio Sign

For every metric, darker colours characterize shorter time intervals (10, 20) whereas lighter colours characterize longer time intervals (100, 200).

Benefits Over Conventional Indicators

The analysis demonstrates that the Energy Ratio metrics outperform Wilder’s conventional pattern indicators:

• Energy Ratio Noise (50-day): R² = 0.37
• ADX: R² = 0.06
• ADXR: R² = 0.07
• DX: R² = 0.05

This means that the Energy Assisted Development Following method supplies a extra correct evaluation of pattern energy and profitability potential.

Conclusion

The PowerIndicator implements a complicated method to pattern following that addresses a elementary limitation of conventional strategies: figuring out when a pattern is powerful sufficient to commerce profitably.

By making use of ideas from sign evaluation, the indicator supplies a extra strong framework for:

1. Assessing pattern energy
2. Deciding on markets with the strongest traits
3. Timing entries into pattern following methods
4. Setting acceptable stop-loss ranges

The empirical testing reveals that this method outperforms conventional pattern indicators, making it a helpful device for merchants who depend on pattern following methods.

References

1. Aigner, A. A., & Schrabmair, W. (2020). Energy Assisted Development Following. ResearchGate. DOI: 10.13140/RG.2.2.20898.17605/1
2. Wilder, J. W. (1978). New ideas in technical buying and selling programs. Development Analysis.

The total analysis paper on Energy Assisted Development Following is out there at no cost obtain on ResearchGate.