Intelligent Moving

📈 Intelligent Moving — Self-Adjusting Trend Bands with Neural Optimization

Description

Intelligent Moving is a closed-source indicator for trend analysis and breakout detection. It uses a central moving average, ATR-based deviation bands, and a self-optimizing algorithm powered by virtual trade simulation and a simple neural network (perceptron). The tool adjusts its core parameters in real time, allowing it to dynamically adapt to evolving market conditions without manual intervention.

🧩 Structure and Visual Elements

The indicator displays:
- 📍 Central Moving Average Line: The trend baseline.
- 📊 ATR-Based Deviation Bands: Upper and lower lines offset from the MA using an adaptive multiplier.
- 📈 Trend Coloring: All three lines change color based on whether the price is trending above or below the MA.
- 🔼🔽 Signal Arrows: Buy/sell arrows appear when the price reverts from an overextended zone.

🔍 Detailed Logic of Calculations

1. Moving Average

The center line is a moving average whose period is dynamically optimized based on historical performance. It reflects the current trend direction and is used for band calculations and signal logic.

2. ATR-Based Deviation Bands

Deviation bands are calculated as:
- Upper Band = MA + ATR × UpperDeviation
- Lower Band = MA − ATR × LowerDeviation

These bands do not use standard deviation. Instead, the ATR (with the same period as the MA) is multiplied by deviation coefficients, which are optimized in real time.

3. Trend Coloring

The indicator colors the bands based on the relative position of price closes:
- Bullish Trend (e.g., Blue): Recent closes are above the MA.
- Bearish Trend (e.g., Red): Recent closes are below the MA.

This helps traders visually identify the dominant trend at a glance.

🎯 Signal Generation Logic

🔼 Buy Signal:
- Price closes below the lower band for one or more bars.
- Then, a bar closes back above the lower band.

🔽 Sell Signal:
- Price closes above the upper band for one or more bars.
- Then, a bar closes back below the upper band.

Signals are reversion-based, not triggered by classical crossovers or oscillators. They aim to detect price exhaustion followed by reversal.

🧠 Neural Optimization Engine

The key innovation in Intelligent Moving is a lightweight neural self-optimization system.

🧪 Virtual Trade Simulation

At regular intervals (e.g., every 100 bars), the indicator performs simulations:
- Virtual Buy Entry: When price closes below the lower band and then closes above.
- Virtual Sell Entry: When price closes above the upper band and then closes below.
- Virtual Stop-Losses:
- - For longs: one pip below the lowest low during the signal zone.
- - For shorts: one pip above the highest high during the signal zone.
- Virtual Take-Profit Conditions:
- - Longs close when price closes above the MA.
- - Shorts close when price closes below the MA.

Simulated profits are calculated for each combination of parameters.

🔄 Neural Optimization Process

Using the results of these virtual trades, the built-in perceptron neural network evaluates:
- A range of moving average periods
- A range of upper and lower deviation coefficients

You define the optimization boundaries through:
- Base value
- Step size
- Number of passes
- Whether to base the search on the original value or the last-best result

The perceptron selects the best-performing combination, which is then used until the next optimization cycle.

This enables the indicator to continuously adapt to changing market dynamics.

🚀 Why Use Intelligent Moving?

- ✅ Dynamic self-optimization using neural logic
- ✅ Reversion-based signal system
- ✅ Visual trend clarity through adaptive coloring
- ✅ No manual tuning required
- ✅ Customizable visuals and alerts

⚠️ Additional Notes

- This script is closed-source, but the description provides sufficient transparency about its logic and mechanisms as required by TradingView rules.
- It does not repaint signals.
- The built-in training is purely historical, and parameters are only updated between intervals — not retroactively.
- Due to the complexity of the internal training and optimization logic, the script may take longer to load, especially when deep simulation depth or a large number of passes is selected.
- In rare cases, TradingView may show a “Script execution timeout” error if the combined loop workload exceeds platform limits. If that happens, try reducing:
- - Neurolearning Rates Depth
- - Neurolearning Periods Passes
- - Neurolearning Deviations Passes