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.
13 documents
This guide explains a formula tool for rapidly calculating and checking trading ideas using expressions based on publicly available WorldQuant Alpha101 methods. It lists arithmetic and conditional syntax, cross-sectional ranking, lagging, moving averages,…
This guide surveys the languages and visual tools available for building trading strategies on FMZ, including JavaScript, TypeScript, Python, Rust, C++, My language, Pine, Blockly, and Workflow. It describes selected platform features: JavaScript…
This guide explains FMZ’s simulated-tick and real-tick backtesting modes. Simulated ticks are generated from candlestick data, while real-tick mode replays recorded tick data and can include depth and trade records. The guide describes the trade-off between…
This reference describes the fields used by FMZ trading data structures, including market trades, tickers, candlestick records, orders, and conditional-order configurations. It covers identifiers, timestamps, prices, quantities, volume, open interest, order…
The guide outlines a basic structure for automated strategies in JavaScript, Python, Rust, and C++. A main loop repeatedly runs strategy logic, while a sleep interval controls polling frequency in live trading and playback speed in backtests. Its examples…
This guide explains how FMZ evaluates trading strategies on historical market data. It contrasts simulated Tick backtests, which construct intrabar price events from candles, with live-data Tick backtests, which replay collected tick, depth, and trade…
This guide describes an FMZ tool for evaluating trading ideas with time-series expressions modeled partly on publicly available Alpha101 calculations. It lists arithmetic and logical operators, transformations such as moving averages and differences,…
This platform guide surveys the ways to build trading strategies in FMZ, including JavaScript, TypeScript, Python, Rust, C++, Pine, a domain-specific language, Blockly, and visual workflows. It explains selected development features: JavaScript asynchronous…
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…
This guide explains how interface parameters are defined and used by strategies on the FMZ platform. It describes numeric, boolean, string, dropdown, and encrypted-string values, noting language-specific behavior such as Python’s need for the global keyword…
This guide describes common causes of failures and abnormal exits in live automated trading. It separates errors detectable before launch, such as static syntax problems, from runtime failures, including unchecked function return values, excessive memory…
This FMZ guide explains the lifecycle functions available to strategies written in JavaScript, Python, Rust, and C++. The main function is the strategy entry point; init runs first for initialization; onexit handles cleanup after normal termination; and…
This guide explains how FMZ strategy interface parameters are defined and used in code. It covers numeric, Boolean, string, dropdown, and encrypted string values, including how language support differs. For example, Python functions need a global declaration…