Control Panel

The Control Panel  allows users to configure  indicators and settings.

Variance Pulse

Enables the Variance Pulse indicator, designed to highlight variations in market pulse or momentum, providing visual cues on charts for potential volatility shifts.

Core Turning Points

Displays Core Turning Points, focusing on fundamental or core-level turning points in market data for more reliable pivot identification.

Pulse Turning Points

Activates the Pulse Turning Points feature, which identifies key turning points in pulse-based trends, helping users spot potential changes in direction.

Probable Reversal/Exit

Displays probable reversal or exit signals, based on algorithmic predictions of trend reversals or optimal exit points.

Price-Volume Confluence

Toggles the Price-Volume Confluence indicator, which highlights areas where price movements align with volume activity for stronger confluence signals. Best for spotting strong reversals.

Expand Panels

Expands and enables all indicator panels.

Instrument

A dropdown selector for choosing the financial instrument, currently set to ES (E-mini S&P 500 futures). Users can select other instruments from the list to update the data focus.

The Variance Pulse panel allows fine-tuning the Pulse and Core Pulse indicators, which  visualize variations in market momentum or "pulses" through adaptive algorithms. It includes numerical inputs for algorithmic parameters and subsections for specific components (Pulse and Core). These controls directly influence the underlying code's computations, such as optimization loops and batch processing, allowing users to adjust sensitivity and performance. The panel is organized vertically with labels, input fields (editable via arrows or direct entry), and icons for customization.

PULSE

Learning Rate

Set to 0.01 by default, this numerical input controls the step size in the gradient-based optimization algorithm within the Variance Pulse code. A lower value (e.g., closer to 0) results in slower, more stable convergence during the adaptive learning process that calculates variance shifts, while higher values speed up adaptation but may introduce instability in detecting pulse variations.

Adapt Interval

Defaulting to 10, this input defines the frequency (in data points or bars) at which the algorithm re-adapts its model in the code's loop. Shorter intervals make the indicator more responsive to recent market data for real-time variance detection, tying into the periodic update functions that recalibrate pulse metrics.

Max Iterations

Set to 20, this limits the maximum number of iterations in the optimization routine of the code. It prevents excessive computation by capping the loop cycles used to refine variance pulse estimates, balancing accuracy with processing efficiency.

Mini-batch Size

Default of 50, this determines the batch size for mini-batch gradient descent in the code's training or adaptation phase. Larger batches provide smoother updates to the pulse variance model but require more data, affecting how the algorithm processes historical price inputs for variance calculations.

CORE

Learning Rate

Defaulting to 0.002, this input specifically adjusts the learning rate for the Pulse component's sub-algorithm in the code. It fine-tunes the adaptation speed for pulse turning detection, often using a smaller value than the top-level to focus on finer momentum details without overfitting.

Adapt Interval

Set to 50, this controls the adaptation frequency for the Pulse sub-model in the code's segmented loops. Longer intervals here emphasize broader trends in pulse variance, integrating with functions that handle subset data for turning point identification.

Max Iterations

Default 20, this caps iterations for the Pulse optimization in the code, ensuring efficient computation for real-time pulse analysis without extending beyond necessary cycles.

Mini-batch Size

At 50 by default, this sets the batch processing size for the Pulse code segment, influencing how mini-batches of data are used to update pulse-specific variance models for accuracy in dynamic markets.

The Core Turning Points panel customizes the Core Turning Points indicator, focusing on core-level market pivots through extrema and regime analysis (R4 resistance and S4 support). Controls influence the code's core detection algorithms, which filter for fundamental turns, similar to Pulse Turning Points but capturing a higher timeframe.

Extrema Lookback

Default 0, this input specifies the historical lookback for extrema in the code's core analysis loop. Zero may enable dynamic or infinite lookback, impacting how deeply the algorithm scans for turning points.

Min Change Threshold

Set to 0.25, this threshold in the code determines the minimum change needed for a core turn, integrated into validation functions to ignore noise.

The Pulse Turning Points panel configures the Pulse Turning Points indicator, which identifies potential turning points in market pulses using regime-gated analysis. It focuses on extrema detection and line styling for different regimes (R6 and S6). These controls tie into the code's algorithms for scanning historical data and plotting regime-specific points, allowing adjustments for sensitivity and visual distinction. The panel is organized vertically with labels, input fields (editable via arrows or direct entry), dropdowns, and color pickers, noted as "Pulse (regime-gated)" at the bottom.

Extrema Lookback

Set to 0 by default, this numerical input defines the lookback period (in bars or data points) for detecting local extrema in the code's pulse analysis function. A value of 0 may imply automatic or no fixed lookback, relying on real-time data; higher values extend the historical scan for more context in identifying turning points.

Min Change Threshold

Defaulting to 0.25, this input sets the minimum price or percentage change required to qualify as a turning point in the code's threshold filtering logic. It prevents minor fluctuations from being marked, tying into conditional checks that validate pulse shifts.

The Price-Volume Confluence panel configures the indicator for aligning price and volume data, highlighting confluence zones. It emphasizes line styling for CVD (Cumulative Volume Delta) and Price, tying into code that computes and plots these alignments. 

The Probable Reversal/Exit Zones panel provides controls for customizing the behavior of the R2 resistance and S2 support zones, which highlight high-probability reversal or exit areas based on AI-optimized swing detection. These zones are regime-aware, adapting dynamically to market conditions via entropy-based tuning when enabled.

AI Adaptive Mode

Toggles self-optimization behavior. When enabled the AI dynamically adjusts the lookback period (in ticks), bandwidth, and decay rate in real-time using the MDKE entropy engine—no manual input needed. When disabled, it falls back to the look back set in Seed swing loopback (ticks).