Tutorial · 5 Steps

Strategy Backtesting

Test trading strategies against historical data before risking real capital. Compare strategies, analyze results, and refine your approach using AI.

The Problem

Deploying an untested strategy is gambling. But setting up backtests manually requires coding, data sourcing, and statistical analysis that most traders lack time for.

Workflow

1

Browse available strategies

list_strategies

Explore the strategy marketplace to find strategies that match your market preference and risk tolerance.

“Show me all available futures strategies”
2

Understand a strategy

explain_strategy

Get a plain-English explanation of how a strategy works, when it enters and exits trades, and what market conditions suit it best.

“Explain how GhostRider works in simple terms”
3

Run a backtest

what_if_backtest

Test the strategy against historical data for any pair, timeframe, and date range. See P&L, win rate, drawdown, and every individual trade.

“Backtest GhostRider on BTC/USDT for the last 30 days”
4

Review detailed results

get_backtest_results

Dig into the backtest report: equity curve, trade-by-trade breakdown, Sharpe ratio, and risk-adjusted returns.

“Show me the detailed results of that backtest”
5

Compare alternatives

compare_strategies

Run the same test on multiple strategies and compare them side by side to find the best performer.

“Compare GhostRider vs Momentum Rider on the same pair”

Example Prompts

Try asking your AI assistant any of these:

“Backtest GhostRider on BTC/USDT for the last 30 days”
“Which strategy has the best Sharpe ratio?”
“Test Momentum Rider on ETH with 4-hour candles”
“Compare three strategies on SOL/USDT”
“What is the max drawdown for this strategy?”

Tools Used in This Workflow

list_strategies

Browse all available trading strategies in the TradeStaq marketplace. Filter by market type (spot/fu

get_strategy

Get detailed information about a specific trading strategy including its logic, indicators used, ris

explain_strategy

Get a plain-English explanation of how a strategy works, when it enters and exits trades, what marke

what_if_backtest

Run a quick "what-if" backtest to see how a strategy would have performed on historical data. Specif

get_backtest_results

Retrieve the results of a previously run backtest. Returns detailed metrics including total return,

compare_strategies

Compare two or more strategies side by side on key metrics: win rate, Sharpe ratio, max drawdown, av

Other Use Cases

Portfolio Monitoring

Track your crypto portfolio across multiple exchanges in real time using AI. Get balance summaries, position updates, and performance metrics through natural language.

5 steps·5 tools

Copy Trading Setup

Find top-performing traders on the leaderboard and automatically mirror their trades on your exchange account using AI.

5 steps·5 tools

AI Strategy Creation

Generate complete trading strategies from natural language descriptions using FORGE AI. Describe your idea, let AI write the code, then backtest and deploy.

5 steps·5 tools

Bot Deployment

Deploy, monitor, and manage automated trading bots across multiple exchanges using natural language commands.

6 steps·7 tools

Start Strategy Backtesting with AI

Set up the TradeStaq MCP server and try this workflow in under a minute.

Get Started Free All Tools