Settings & Parameters

1. Type Parameter – Adaptive Cycle Selection

The Type parameter acts as the core selection switch, determining which of the following model is activated:

• Volatility Cycle → Ideal for stable market environments with consistent price movements, focusing on volatility-driven entry/exit zones.

• Elliott Wave Cycle → Best suited for trending markets, where wave pattern recognition enables traders to capitalize on structural price movements.

• Strength Cycle → Optimized for highly volatile conditions, allowing traders to identify aggressive momentum shifts and potential trend reversals.

Our adaptive cycle selection feature allows you to implement a strategic cycle selection approach to seamlessly adjust strategy according to the evolving market conditions.

Here are a few optimization strategies you can use to switch the type parameter:

• Market-Regime Detection – Dynamic cycle switching based on trend strength, volatility clusters, or fundamental macro shifts.

• Automated Type Selection – Implementing adaptive filters to shift between cycle models in real time.

• Combining Multiple Cycle Types – Overlaying different cycles to cross-validate trend signals, ensuring high-probability trades.

2. ShortWave Parameter – Sensitivity Tuning

The ShortWave parameter determines the responsiveness of wave cycle calculations, balancing between immediate market reactions and long-term stability.

• Lower values (1-3) → Provide high-frequency, real-time responsiveness, ideal for fast-moving, momentum-driven markets.

• Medium values (5-10) → Capture balanced retracements and wave continuations, filtering short-term fluctuations.

• Higher values (10-20) → Focus on macro-trend stability, reducing noise and false reversals.

A precision-calibrated wave length selection can maximize signal reliability while reducing trade lag. There are three strategies that can be employed here to adjust the ShortWave_len parameter properly.

• Volatility-Based Wave Scaling – Adjust wave length dynamically based on ATR or standard deviation analysis.

• Context-Aware Sensitivity Modulation – Employ higher smoothing in choppy markets and lower smoothing during breakouts.

• Multi-Length Wave Fusion – Utilizing short and long wave combinations for trend-phase classification.

3. Trendlinecolor Parameter – Enhanced Visual Interpretation

While primarily a visual feature, trendline color selection plays a pivotal role in chart efficiency and rapid market interpretation. Here’s how it works:

• High-contrast colors ensure immediate recognition of directional trends.

• Gradient-based coloring enables momentum strength visualization within trend cycles.

• Dynamic color modulation (e.g., based on RSI or volume intensity) provides additional trade confirmations.

To optimize your TA, you can adjust trendline colors based on price action intensity, divergence zones, or cycle state. OR use separate colors for short, medium, and long-term cycle alignments.

Some of the pro traders in our community also employ faded colors in weak trends and amplified brightness in strong momentum phases. This small yet impactful optimization enhances your reaction speed and charting efficiency.

4. alert_combine Parameter – High-Fidelity Trade Alerting

The alert_combine parameter introduces a multi-tier alerting system, reducing false-positive trade signals while increasing execution precision.

• Single Condition Alerts → Provide fast trade triggers, but with a higher chance of noise.

• Multi-Condition Alerts → Require confluence from multiple indicators, resulting in fewer but higher-confidence trade signals.

5. DOs and DONTs with Trend & Pullback Toolkit

Here’s how you should use our Trend & Pullback toolkit with TradingView:

• Maintain a balanced parameter configuration by prioritizing robust performance over absolute precision.

• If possible, run side-by-side strategy variations to optimize real-time execution logic on your end.

• Test how each parameter reacts to volatility shifts to make sure you adapt to changing markets.

• Ensure that separate converging cycle signals align before high-risk trades.

Here’s what you should absolutely avoid doing:

• DO NOT overfit historical data. Excessive tuning creates fragile models, unable to adapt to real-time changes.

• DO NOT ignore execution costs and slippage. Over-trading small signals reduces net profitability due to trading costs.

• DO NOT overcomplicate or misinterpret trend color variations. It would be incorrect to assume every color change implies immediate trend reversal.