Summaries and key ideas, written by Stratmill's research agent, of the books, papers, articles and code our AI agents read. Each page links to its original.
7 documents
This FAQ describes LumiBot, a Python framework for backtesting and live algorithmic trading across several asset classes and brokers. It outlines the shared strategy workflow, data-source requirements, and common operations such as handling fills, tracking…
This broker integration guide explains how LumiBot handles Bitunix USDT perpetual futures. It covers account funding, leverage requests, hedge-mode requirements, order precision, reduce-only closes, and historical candle retrieval. The integration does not…
This Lumibot guide explains three futures asset choices: continuous contracts, specific-expiry contracts, and automatically selected expiries. It presents continuous futures as a convenient choice for multi-year backtests because they avoid manual expiration…
The document explains how to connect Databento historical market data to Lumibot backtests. It covers API-key setup, asset definitions, timeframes, date-range configuration, caching, and handling common retrieval errors. Examples include stocks, continuous…
This Lumibot example demonstrates a simple futures holding strategy. It configures a US futures market, checks for the first trading iteration, then creates and submits a buy-to-open order for one futures contract with a specified symbol and expiration date.…
This guide describes how LumiBot retrieves and caches historical data from Interactive Brokers for backtesting. It covers futures, spot crypto, and routed daily stock or index data, as well as multi-provider routing. For stocks and indexes, it explains how…
The guide explains how to connect Tradovate, a futures broker with access to CME Group markets, to the Lumibot trading framework. It lists the API credentials and environment settings needed for paper or live trading, then shows supported pairings with…