strategy-workflow

# Strategy Workflow

Comprehensive strategy development workflow for quantitative trading, from hypothesis to validated production deployment.

## Overview

This skill provides a complete framework for developing, testing, and validating trading strategies. It supports:

- Hypothesis-driven strategy development
- Multi-GPU backtesting on Vast.ai
- Bayesian hyperparameter optimization with Optuna
- Walk-forward validation and out-of-sample testing
- Automated tearsheet generation

## Entry Points

### Control Plane (Swarm Orchestration)

Always-on watchdog loops that manage hardware utilization and self-healing:

```bash
bash scripts/start_swarm_watchdogs.sh
```

For local environments, set explicit paths:

```bash
VENV_PATH=/path/to/.venv/bin/activate \
RESULTS_ROOT=/path/to/backtests \
STATE_ROOT=/path/to/backtests/state \
LOGS_ROOT=/path/to/backtests/logs \
bash scripts/start_swarm_watchdogs.sh
```

### Work Plane (Parallel Execution)

Unified wrapper that starts control plane and launches parallel work:

```bash
scripts/backtest-optimize --parallel
```

Multi-GPU, multi-symbol execution:

```bash
cd WORKFLOW && ./launch_parallel.sh
```

### Single-Symbol Pipeline

For focused optimization on a single asset:

```bash
scripts/backtest-optimize --single --symbol SYMBOL --engine native --prescreen 50000 --paths 1000 --by-regime
```

## Strategy Development

### 1. Hypothesis Formulation

Define your strategy hypothesis in measurable terms:

- What market inefficiency are you exploiting?
- What is the expected holding period?
- What are the entry/exit conditions?
- What is the target risk-adjusted return?

### 2. Feature Selection

Identify relevant features for signal generation:

- Price-based (OHLCV, returns, volatility)
- Technical indicators (EMA, RSI, Bollinger Bands)
- Multi-timeframe features (MTF resampling)
- Volume analysis (PVSRA, VWAP)
- Market microstructure (order flow, spread)

### 3. Signal Generation

Convert features into actionable signals:

- Dire...