Signal Analyzer

Signal Analyzer evaluates indicator values against a target asset's future outcome such as return, win rate, or volatility. Use it to test a signal before turning it into a strategy rule.

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When To Use It

Use Signal Analyzer when the open question is whether an indicator has a stable relationship with a later outcome.
Use Strategy Gallery when you already know the rule and want to test it inside a portfolio.
Use Strategy Builder when the next step is a signal-driven switching rule.

Modes

Mode	Primary Inputs	Primary Results
Single	One indicator, one target ticker, explicit price mode, one forward metric, and one horizon.	Scatter and fit view, bin summaries, split coverage, and diagnostics.
Dual	Two indicators measured jointly against shared forward outcomes.	Metric heatmap, populated-cell diagnostics, bin table, and cell-level save-to-library selection.
Multi	Feature set, tree controls, and train/test validation settings.	Tree summary, feature importance, leaf-level reporting metrics, and validation diagnostics.

Core Inputs

Indicator: the predictor being tested, such as price, SMA, EMA, RSI, trailing return, volatility, or drawdown.
Signal asset: the asset used to compute each indicator.
Transform: optional subtract or divide operation against a second indicator.
Target ticker: the asset whose future behavior is being measured by the forward metric.
Price mode: whether returns are computed from raw prices or total-return series.
Forward metric: the future outcome, such as forward return, win rate, or volatility.
Horizon: the number of trading days between the signal observation and the measured outcome.

Research Controls

Sampling frequency: how often observations are taken from the daily history.
Signal lag: shifts the sampling schedule so the same analysis can be checked against nearby alignments.
Splits: divides the sample into time slices for stability checks.
Fit method and bins: single-mode controls for polynomial fit or regressogram summaries.
Metric selection: dual mode lets you switch the displayed heatmap metric while keeping the same sample.
Tree controls: multi-mode settings such as train/test split, depth, minimum leaf size, and validation folds.

Read The Results

Single mode: start with scatter and fit, then check diagnostics for horizon, sampling assumptions, correlation, and split coverage before reading bin means.
Dual mode: use populated-cell coverage and best/worst cell diagnostics to separate broad effects from sparse outliers before saving a cell to the Library.
Multi mode: compare train/test and cross-validation diagnostics, then inspect leaf-level means and rule paths before creating a signal from a leaf.

Signal Analyzer does not turn a relationship into a trading rule by itself. It isolates the relationship so it can be checked before it is embedded in a strategy.

Save To Library

Save a run when you want reproducible inputs and diagnostics for later review. Use the mode-specific selection control (single setup, dual cell, or multi leaf) to turn a validated pattern into a reusable Library signal for strategies or Strategy Builder.