> ## Documentation Index
> Fetch the complete documentation index at: https://docs.openstrat.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Task & Technical Signals

> Principles, types, grading and best practices for technical signals.

## Principles

Signals are derived from historical prices, volumes, and indicators via pattern recognition and ML models.
Core steps: data analysis → pattern recognition → probability estimation, with multi-timeframe, volatility,
and volume-price confirmations.

## Types

* Intraday/Weekly bottoms and tops
* Price/Options alerts

## Grading & performance

* <span class="text-secondary">50%–65%: mild</span>; <span class="highlight-blue">65%–80%: moderate</span>; <span class="positive">80%–100%: strong</span>
* Historical: <span class="highlight-blue">bottoms \~68% avg</span>, <span class="highlight-orange">tops \~65%</span> (lower during high volatility)
* Personalized stats by symbol/type/timeframe

## Best practices

* Combine with fundamentals and events; avoid single-signal decisions
* Prefer indicator resonance and cross-timeframe consistency
* Diversify watched symbols; review and tune regularly

## Risk management

* Scale in; pyramid adds (with cap)
* Fixed/technical/time-based stop loss
* Adjust position dynamically based on follow-up signals