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.
157 documents
This spot strategy generates signals from a fast and a slow moving average. It identifies a bullish crossover using completed bar values rather than the current bar, which is intended to avoid signals that flicker while a bar is forming. A bullish cross…
This strategy uses Bollinger-style price bands to enter long or short positions when a bar reaches beyond the upper or lower band. It adds a directional filter based on the difference between the latest close and a close from an earlier lookback: positive…
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 strategy builds 15-minute bars from incoming ticks and updates a rolling indicator manager. After the indicator window is initialized, it calculates Bollinger Bands and a simple moving average midline. When flat, it places stop entries above the upper…
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…
This guide describes configuring and running an automated cryptocurrency grid trader for spot or futures markets. Its settings include the trading pair, percentage spacing between grid levels, per-order quantity, price and quantity precision constraints, and…
This strategy combines Bollinger Bands, MACD, and ATR to trade breakouts in either direction. It opens a long position when price reaches the upper band while MACD and its histogram are positive; it opens a short position when price reaches the lower band…
This document describes an execution wrapper for futures orders. It submits an order, checks its status, and can respond to an unfilled or partially filled order in several ways: cancel and reissue when the market price moves beyond a configured threshold,…
The strategy uses a fast and slow moving average to trade both directions in a USD margined futures contract. It checks completed bars for a bullish or bearish crossover, entering a position when flat and reversing an existing position when the signal points…
This document describes a client for futures exchange HTTP endpoints. It covers public market data requests for exchange specifications, order books, candlesticks across several intervals, recent prices, and best bid and ask quotes. It also defines common…
The document introduces Python's built-in functions, explaining that they are available without importing a module and highlighting common conversion and arithmetic tools. Examples include converting values to numbers or sequences, finding minima and maxima,…
The document surveys several ways to seek returns in cryptocurrency markets: lending assets through deposit products, supplying liquidity to earn fees, collecting perpetual-futures funding, trading price differences between contracts with different…
The document explains design choices for a cryptocurrency trading framework, focusing on Python, asyncio, and RabbitMQ. It presents Python as a practical language for quickly changing strategies and argues that asynchronous I/O can handle many network…
This program wires a double exponential moving average strategy to a Bitcoin perpetual futures market. It creates an authenticated HTTP client, subscribes to websocket market data, and passes incoming ticks to the strategy. A background scheduler…
This example shows a workflow for backtesting an ATR-RSI strategy on one-minute futures data. The setup specifies the contract, date range, transaction costs, slippage, contract size, tick size, and starting capital, then loads data, runs the simulation,…
This introductory lesson explains how to install and use Python through Anaconda. It describes Anaconda’s package and environment management features, including creating separate environments so projects can use different Python versions and dependencies. It…
This example describes a directional strategy that uses two exponential moving averages on hourly bars. It compares a 15-period average with a 50-period average and treats a crossover between the latest and prior readings as a change in direction. When flat,…
The strategy compares a synthetic futures price, calculated from a call price minus a put price plus the strike, with the traded futures price. It measures the difference and opens a three-leg position when the spread crosses a configurable entry level: one…
The document describes a funding-rate trade that pairs a short perpetual futures position with a long spot position of equal size. It proposes opening the hedge when both the funding rate and quoted spread meet configured thresholds, collecting funding…
This example shows how to run a double exponential moving average strategy through an event-driven trading system. It creates an event engine, subscribes to tick updates, and sends those updates to a strategy callback. A websocket supplies live market data,…