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 platform guide explains how FMZ defines live trading: a strategy instance connected either to an exchange’s production environment or to its simulation environment. Starting an instance requires a saved strategy, a deployed platform host, and at least…
The document explains why similarly named strategy handlers can receive bars of different durations. In an event-driven trading framework, a callback such as a five-minute handler or a ten-minute handler is called when the corresponding timeframe bar is…
The post answers why a community-edition backtest can work while simulated trading produces no orders. It distinguishes imported historical data, which can be replayed during a backtest and used to initialize indicators, from simulated trading, where…
The discussion explains why a strategy can run in a historical backtest yet place no trades in simulated trading. Imported historical bars support backtests and indicator initialization, while a live simulation generally depends on real-time tick or bar…
This document describes a MetaTrader 5 utility for estimating the costs of a prospective trade. It combines spread, commission, and swap charges using symbol data and trader inputs such as position size, direction, commission per lot, and expected holding…
The document explains how self-custody trading bots automate strategies while keeping exchange API keys or wallet credentials under the user's control. It compares three ways to automate centralized-exchange trading: exchange-hosted bots, third-party…
This brief forum exchange explains how VeighNa handles strategy updates after the application has started. For backtesting, users can use the strategy reload control to rescan strategies. For a live trading instance, the reply says that changing instance…
This client code illustrates order handling for coin-margined futures. It configures position mode, margin mode, and leverage, submits buy and sell orders, checks order status, and exposes account, position, contract, depth, and funding-rate queries. Limit…
The document describes a software framework for executing spread trades across multiple instruments. It tracks each leg’s orders, fills, costs, and positions, then estimates the spread’s completed volume and average fill price. For inverse contracts, it…
This implementation models a spread as a collection of instrument legs, with separate multipliers for calculating its quoted price and translating spread quantities into leg quantities. It combines leg bid and ask prices, reversing which side is used for…
This document describes a software interface for spot trading. It provides methods for placing limit and market buy or sell orders, checking balances and order status, canceling orders, and retrieving ticker, candle, and order book data. The order wrapper…
This introduction explains Python modules as reusable files, distinguishes modules from packages and libraries, and shows how to import whole modules, selected names, or aliases. It also covers installing third-party packages and using the main-module guard…
This document describes an order-routing adapter that connects algorithmic parent orders and exchange-facing child orders through FIX messages. It maps exchanges, order types, directions, and statuses between two systems. A parent order carries the…
This strategy starts by placing buy and sell limit orders around the best bid, then follows whichever side fills. After a fill, it cancels opposing and profit-taking orders and adds another same-direction order at a wider, position-dependent grid interval.…
The material explains how an order-management component adapts close orders to futures position rules. It maintains separate long and short holdings, splitting each into positions opened today and positions carried from earlier sessions. Incoming position…
The strategy compares the current marked value of its position with a stored balance amount on each new bar. When the relative difference reaches a configurable threshold, it trades toward balance: it buys when the stored amount exceeds position value and…
This code provides a client wrapper for trading and querying USDT margined perpetual futures. It configures position mode, margin mode, and leverage, then supports buy and sell orders with limit, market, or other order types. After submission, it checks…
The document defines common records used to represent ticks, bars, orders, fills, positions, accounts, contracts, and trading requests. Fields capture instrument identity, exchange, time, prices, volumes, order state, and selected contract properties.…
This document describes a live monitoring system in which users define named formulas over instrument prices. The system subscribes to the instruments referenced by each rule, reads their latest available prices when market updates arrive, evaluates the…
This document implements a directional crossover strategy using fast and slow exponential moving averages on hourly bars. It calculates the averages from closing prices, discards the latest bar if it has not yet closed, and signals a long position when the…
The document outlines an event-driven trading system designed for cryptocurrency strategies, including market making and higher-frequency activity. It describes an asynchronous event loop for processing work and a message queue that connects separate market…
This document explains how to build a multi-contract strategy using synchronized bar data, per-leg targets, and order management. Its example computes the spread between two weighted contract prices, updates a rolling window, and uses Bollinger Bands to…
The document describes a two-leg spread strategy built around Bollinger Bands. It calculates a weighted price difference between two contracts, samples the spread on a five-minute schedule, and compares it with a rolling mean and standard deviation. A move…
This guide explains how to use a Python wrapper around multiple cryptocurrency exchanges through a mostly consistent interface. It shows initialization with an exchange name and credentials, then describes calls for market status, candlesticks, order books,…