Tutorial · 5 Steps

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.

The Problem

Turning a trading idea into executable code requires programming skills, quantitative knowledge, and hours of debugging. Most traders have the intuition but lack the tools.

Workflow

1

Describe your strategy

generate_strategy

Tell the AI what you want in plain English. FORGE AI will write the strategy code, set parameters, and prepare it for testing.

“Create a strategy that buys ETH when RSI crosses below 30 and sells when it crosses above 70”
2

Review the logic

explain_strategy

Get a clear explanation of what the AI built, including entry/exit conditions, indicators used, and risk parameters.

“Explain the strategy you just created”
3

Backtest it

what_if_backtest

Run the generated strategy against historical data to validate performance before deploying with real capital.

“Backtest this strategy on ETH/USDT for the last 60 days”
4

Analyze results

get_backtest_results

Review the backtest metrics. If performance is not satisfactory, refine the description and regenerate.

“Show me the full backtest report with trade details”
5

Deploy to live trading

deploy_bot

Once satisfied with backtest results, deploy the strategy as a live trading bot on your preferred exchange.

“Deploy this strategy on Bybit with $300 and 3x leverage”

Example Prompts

Try asking your AI assistant any of these:

“Generate a scalping strategy using Bollinger Bands”
“Build a trend-following strategy for BTC futures”
“Create a mean reversion strategy for altcoins”
“Make a momentum strategy that uses MACD and volume”
“Design a conservative DCA strategy for ETH”

Tools Used in This Workflow

generate_strategy

Use AI to generate a complete trading strategy from a natural language description. Describe your tr

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,

deploy_bot

Deploy a new trading bot with a strategy on your connected exchange. Configure the trading pair, pos

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.

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Strategy Backtesting

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

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Copy Trading Setup

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

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Bot Deployment

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

6 steps·7 tools

Start AI Strategy Creation with AI

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

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