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.
1,747 documents
This long-only averaging strategy uses a low RSI reading on a higher timeframe to arm an initial entry. If price falls further from the base entry, it places up to five additional orders at preset percentage distances, with each order sized twice as large as…
This short-only strategy is designed for SOL perpetual futures. It opens a short when a three-minute RSI with a nine-period setting crosses down through an overbought threshold. If price rises after entry, it can add up to three averaging orders at fixed…
The strategy seeks funding payments by holding long spot and an offsetting short perpetual futures position. When perpetual contracts trade at a premium and funding is positive, longs pay shorts; the paired positions are intended to reduce exposure to the…
This document describes a monitoring script for price alerts across several Binance trading pairs. The user supplies a symbol list and a corresponding upper and lower threshold for each pair. The script polls each market, reads its latest price, and logs an…
This Hummingbot controller example opens a market position in a configured direction, sizing the order from a quote-currency amount and the current mid-price. It records when the opening action is submitted, then waits for a configurable delay before placing…
This Bybit perpetual-futures strategy uses fast and slow moving averages, closing prices, and recent candle direction to manage a single long or short position. A long setup requires the close to be above both averages and the fast average to be rising; the…
This source describes a long-only grid strategy for FIL perpetual futures. It places a set of price levels between user-defined upper and lower bounds, with either geometric or arithmetic spacing. The comments describe buying as price crosses grid levels…
This FMEX perpetual futures bot repeatedly calculates bid and ask prices from order book depth, places orders of a configured size on both sides, and cancels and replaces them when its calculated prices change. It periodically cancels all open orders to…
This document outlines a Python framework for managing several perpetual futures markets. Its modules cover market data, exchange-specific contract precision, positions, orders, account metrics, and a live status display. The main loop polls these components…
This document presents an automated Bitcoin USDT perpetual futures setup that operates across two exchange accounts. It configures both accounts for the same contract, sets leverage and margin mode, retrieves exchange and position data, and tracks account…
This script describes a long-only grid approach for a Bitcoin perpetual futures market. It divides a fixed price range into levels, using either geometric or arithmetic spacing. The stated default configuration uses geometric spacing, with buys triggered as…
This short-term reversal approach combines the Money Flow Index (MFI) with a simple moving average (MA). Its stated logic looks for MFI readings at overbought or oversold extremes and uses the close relative to the MA as a directional filter. The…
This Hummingbot strategy is a data-only screener that compares volatility across configured trading pairs using three-minute candles. Once candle histories are ready, it periodically reports a ranked table of markets. Its selected measures are Bollinger Band…
This long-only dollar-cost-averaging strategy for a crypto perpetual contract uses a four-hour RSI reading below 28 to arm a base entry. If price declines from that entry, it places as many as five additional orders at fixed percentage offsets, with order…
The document describes how to convert between coin quantities and contract counts for OKX swap instruments. It uses the exchange’s public contract conversion endpoint, supplying an instrument identifier, conversion price, quantity, and—when converting…
This strategy seeks reversals when price is far from a weighted moving-average reference and volume-based momentum is at an extreme. It calculates a 60-period weighted moving average and bands two standard deviations above and below it. A 14-period RSI…
This strategy compares selected altcoins’ prices relative to Bitcoin with a shared index. It aims to short coins trading above that reference and buy coins below it, with position values scaled to the size of each deviation. The updated approach uses an…
This demo outlines an always-on crypto trading loop connected to Alpaca’s USD spot market. It maps a perpetual-futures case-study universe to the venue’s supported spot pairs, making clear that only a subset can be traded there. The example signal is a…
This notebook demonstrates covariate-drift monitoring for ETF momentum features and crypto perpetual futures features across contrasting market windows. It compares Population Stability Index, which measures changes in individual feature distributions, with…
This notebook turns model rankings into simple crypto perpetual-futures portfolios so later experiments can measure the effect of changing sizing, costs, or risk controls. It applies entry rules such as selecting the highest-scored contracts for longs and…
This notebook develops a simulated market-making task in which a PPO agent chooses quote skew and spread width. Fill probability declines as quotes move farther from the mid price, while order imbalance affects both fills and subsequent price moves. A…
This notebook trains a PPO agent to schedule a parent sell order across hourly perpetual-futures bars. It augments price and volume history with the perpetual premium and time to the next funding settlement, while lagging information that would not yet be…
This notebook introduces vectorized backtesting with VectorBT through a long-only RSI mean-reversion rule on Bitcoin perpetual market data. It calculates a close-based RSI, enters when the prior day’s reading is below a lower threshold, and exits when it is…
This notebook compares six allocation methods on crypto perpetual strategies that have already passed a baseline selection funnel. It keeps each strategy’s predictions and entry rules fixed, then changes how capital is assigned: one allocator uses model…