Build Your Own Bot
Skip to content Lesson 7 — Risk management, hedging & deployment Final crypto lesson: implement hedging/green‑up, enforce risk limits and circuit breakers, make order flows idempotent and observable, and package/deploy your bot safely (Docker / VPS) with monitoring and runbooks.…
Skip to content Lesson 6 — Backtesting & simulation (Jupyter) Simulate strategies in Jupyter: load historical ticks/candles, replay data, simulate executions with slippage & partial fills, and compute performance metrics. Estimated time: 60–90 minutes • Skill level: Intermediate Download .env…
Skip to content Lesson 5 — Webhooks & Pine alerts Build a secure webhook receiver for TradingView Pine alerts, validate HMAC signatures, map alert symbols to exchange testnet markets, and forward idempotent order instructions to the trading layer. Estimated time:…
Skip to content Lesson 4 — Order placement & fills (testnet) Place limit and market orders on exchange testnets, handle partial fills and cancellations, account for slippage and fees, and persist order state for reconciliation. Estimated time: 60 minutes •…
Skip to content Lesson 3 — Market data (REST & WebSocket) Implement reliable REST polling and WebSocket subscriptions, normalize different exchange payloads, merge snapshot + delta orderbooks, and respect rate limits. Estimated time: 45–60 minutes • Skill level: Beginner →…
Skip to content Lesson 2 — Authentication & HMAC Implement HMAC signing and secure API key handling for exchange testnets. Build a signed request helper, add replay protection and safe key storage best practices. Estimated time: 45–60 minutes • Skill…
Skip to content Lesson 1 — Crypto: Environment & testnet setup Prepare your Python environment, create exchange testnet API keys, and run quick REST and WebSocket smoke tests. This lesson gets you ready for the Crypto track. Estimated time: 30–45…
Skip to content Lesson 7 — Risk, hedging & deployment Final lesson: implement green-up hedges and risk controls, ensure idempotent and observable order flows, and deploy your bot safely using Docker or a VPS with proper monitoring and runbooks. Estimated…
Skip to content Lesson 6 — Backtesting & analysis (Jupyter) Use Jupyter to replay historical market data, simulate order execution and compute P/L and performance metrics. We’ll build small, testable backtest components you can evolve into more advanced systems. Estimated…
Skip to content Lesson 5 — Webhooks & alerts Receive TradingView alerts via a secure webhook, verify the HMAC signature, map the alert to a Betfair market/selection and trigger an idempotent order placement in the sandbox. Estimated time: 45–60 minutes…
