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.
320 documents
This tutorial introduces block based visual programming as an entry point to quantitative trading and demonstrates its use with a simple moving average rule. The example opens a long position when the previous candle closes above a 50 period average, opens…
This tutorial shows how to adapt FMZ’s futures-oriented interface for basic cryptocurrency options operations on Deribit. It introduces expiration, strike, premium, and call versus put concepts, and notes that options may have wider bid–ask spreads and…
This introduction explains how FMZ’s visual editor assembles trading logic from connected blocks. It covers snapping blocks together, configuring inputs, using defaults, copying and arranging modules, and saving a strategy. The examples show utility blocks…
This account of an automated liquidity provision strategy focuses on the practical risks that emerged while moving from simulation to live trading on V3 and V4 pools. Early trades encountered tokens that could not be sold or pools whose liquidity disappeared…
This guide describes the FMZ mobile trading terminal, which connects to exchange APIs through a deployed Docker process. It covers exchange and market selection, order controls, depth and asset views, and compact or expanded candlestick charts. Developers…
This implementation guide describes connecting FMZ’s Web3 Tron exchange object to SunSwap V3. It outlines address format conversion, batching contract reads, enumerating pools, querying pool prices and token balances, estimating swap output through routing,…
The guide explains how strategy interface parameters are defined and displayed alongside code. It covers numeric, string, dropdown, Boolean, and encrypted string fields, including how their selected or entered values are exposed to the strategy. Encrypted…
The document distinguishes conventional market making, which seeks spread income by quoting different bid and ask prices, from a volume-boosting self-matching approach. In the latter, buy and sell orders are posted at the same price to generate trading…
The document explains how to adapt a market data collector so a backtesting system can read user supplied price data from a CSV file. A configuration flag selects CSV input, and a file path identifies the data file on the collector’s server. The service…
The article proposes an automated grid strategy for traditional-asset perpetual contracts listed on crypto exchanges. It ranks instruments by average daily high-low range, rejects those whose range is too small relative to grid spacing, then runs buy-low,…
This article describes an AI-assisted crypto trading workflow that combines scheduled market analysis with human approval before routine purchases. Its demonstration strategy is dollar-cost averaging: a base amount is adjusted between zero and twice that…
This guide walks through programmatic access to Hyperliquid spot and perpetual markets through the FMZ platform. It covers connecting a wallet, configuring a proxy wallet, distinguishing mainnet from testnet settings, and querying market metadata, order…
This document shows how to encapsulate time-based triggers in reusable alarm-clock objects for trading strategies. Each object stores a trigger hour and minute, checks the current clock, and returns true once the scheduled minute has arrived. A per-day flag…
This brief note examines how trading fees affect the spread available to a triangular hedging strategy. It points readers to two research notebooks: one using the default fee setting and another adjusted for a different fee rate. Its central lesson is that…
This beginner tutorial outlines how to build a simple spot grid strategy for a cryptocurrency pair. It begins by defining the intended behavior: use equally spaced price levels around a starting point, allow the grid to extend in both directions, and place…
The article describes a taker-style spot arbitrage method for capturing temporary price gaps across crypto exchanges. It proposes fetching order books concurrently, combining eligible ask and bid levels, and ranking them after adjusting prices for exchange…
The document outlines a Python framework for running a strategy across several crypto perpetual contracts. It organizes account, position, order, precision, timing, and ticker data in shared structures, then describes functions for retrieving exchange…
This tutorial outlines a data-mining approach to machine-learning signals, contrasting it with strategies that begin from an explicit market inefficiency such as trend following or mean reversion. It recommends defining the prediction target and evaluation…
The article compares conventional candlestick backtests with more detailed approaches for high-frequency and multi-instrument strategies. It explains that bars omit the timing of intrabar extremes, bid and ask quotes, and queue priority, which can distort…
This tutorial shows how to transfer a simple MyLanguage trend strategy into JavaScript using a reusable event loop and order-management framework. The example computes two moving averages from market bars, compares their recent completed values, and treats…
This guide explains how to connect to dYdX v4, use its test network, inspect market and account data, place and cancel orders, manage subaccounts, and query transaction details. It describes the exchange’s two-part architecture: an indexer for market and…
This article explains the design of a C++ strategy for hedging the calendar spread between near and deferred cryptocurrency futures contracts. It outlines the basic position logic: when the spread is positive, it sells the deferred contract and buys the…
This article describes two simulated workflows connecting AI-Trader, a cloud agent runtime, and FMZ. In one direction, an agent reads a live FMZ strategy’s output through MCP and publishes a corresponding signal to the signal platform. In the other, it…
This article argues that a trading strategy should explain both the source of its expected return and the risks that could prevent it from earning that return. It uses a hypothetical short-horizon crypto signal based on reconstructing how one exchange…