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.
9,660 documents
This document explains a workflow for collecting live market data for selected instruments. After connecting to a market interface and starting the recorder, a user adds tick or bar recording tasks. The recorder subscribes to the required instruments, stores…
This guide explains execution algorithms that divide large orders, react to market prices, and adjust positions on a grid or across a spread. It describes time-weighted execution, iceberg orders, a tick-driven sniper approach, conditional orders, and…
This lesson explains how Python functions return values and how that differs from printing output. It covers explicit returns, the implicit None result when no value is returned, how a return ends the current function, and how multiple returned elements are…
The document describes an options volatility trading module built around live pricing, portfolio risk tracking, and execution. It outlines three pricing models for different exercise styles and underlyings, with routines to calculate theoretical prices and…
This document explains the structure of a historical trading strategy backtester. It loads bar or tick records over a selected date range, initializes a strategy with a warm-up period, then replays the remaining data. The engine tracks simulated orders and…
This document describes a graphical interface for defining and monitoring spread trades. Users can create standard or flexible spreads, specify leg instruments and directions, set a pricing formula, identify an active leg, and enter minimum trade volume. The…
The document explains utilities for turning incoming trades into one-minute OHLCV bars and combining minute bars into larger time windows. It tracks price extremes, closing price, volume changes, and open interest, then sends completed bars through…
This code tracks long and short holdings, separating each side into today’s and prior-day positions. It updates those amounts from position snapshots and trades, and it keeps active orders so that quantities committed to closing positions are treated as…
The document explains a local simulator that routes orders and cancellations to a paper-trading engine instead of sending them to an external trading server. It supports limit, market, and stop orders, and uses quote-triggered matching: for example, a buy…
This document describes a framework for building trading strategies around market-data and order-event callbacks. A strategy can receive tick, bar, trade, order, and stop-order updates; load historical bars or ticks during initialization; and query or…
This document describes a position reconciliation process that compares a strategy’s intended direction and size with the account’s actual holdings. The intended position is read from stored records, while the account position and current market price are…
This guide explains two ways to schedule asynchronous work in an event-driven trading application. A loop-run task registers an asynchronous callback at a specified interval, measured in seconds, and returns an identifier that can later be used to unregister…
This strategy builds Keltner-style bands from a simple moving average of closing prices and a simple moving average of true range. On five-minute bars, when flat, it places linked stop orders above and below the bands so that a move beyond either boundary…
This application example connects a trading engine to a crypto exchange, loads a channel-based CTA strategy, and starts it. Separately, it requests recent hourly bars for a symbol through a market-data endpoint, converts the response to a tabular format,…
This guide explains how a Python script engine can connect to trading gateways, subscribe to market data, query account and instrument records, and submit or cancel orders. It describes both an interactive notebook workflow and a continuously running script…
This document describes a wrapper for trading delivery futures. It places buy and sell orders, checks their status, and can respond to unfilled or partially filled orders using price-based cancellation, timed cancellation, or automatic cancellation. When an…
This guide explains spread trading across related instruments, contrasting it with single-instrument trend strategies. It presents several approaches: latency-sensitive arbitrage between equivalent markets, threshold or Bollinger Band mean-reversion trades…
The document explains how a trading application can use a remote procedure call (RPC) service to share events and handle requests across separate processes. It frames RPC as a way to work around Python’s global interpreter lock limiting CPU-bound work in a…
The document sketches a scheduled accumulation strategy for a crypto trading pair. A broker object stores an exchange connection, symbol, investment amount, latest bid and ask, and most recent order identifier. A scheduler periodically refreshes quotes,…
This guide explains a market-data recorder that subscribes to selected instruments and saves live tick or one-minute bar data to a database. The stored history can then be reviewed in a data-management interface, used in historical backtests, or loaded to…
This document describes a workflow for importing historical bar data from a CSV file into a trading database. The operator configures the input file, instrument symbol, exchange, bar interval, and the column names corresponding to timestamps and OHLCV…
This HTTP client code illustrates basic operations for an exchange trading API: request signing, server-time retrieval, order creation and cancellation, open-order and position retrieval, and historical candle loading. Private requests add a timestamp and…
This code describes an exchange-trading wrapper that submits orders, checks their status, and optionally manages unfilled quantities. Its order workflow can cancel and reissue an order after a price move or a configured wait, using the remaining amount after…
This implementation describes a two-sided spot grid. It tracks buy and sell limit orders, checks their exchange status, and, when one fills, places a replacement order on the other side at a configured percentage gap. It rounds prices and quantities to…