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.
549 documents
The document presents an FMZ teaching strategy that adds positions at successive price levels spaced by multiples of ATR. It builds short positions when price rises through upper levels and long positions when price falls through lower levels, increasing the…
The article proposes a long-only grid strategy for crypto contracts, motivated by the view that a long position has a bounded loss if the asset falls to zero while potential gains are not similarly capped. It places successive buy orders at intervals below…
This personal account traces the author’s path from hardware development into cryptocurrency mining and automated trading. It describes early Litecoin mining, holding coins through a severe decline, and later selling during a recovery. The trading discussion…
This teaching example describes a spot strategy that aims to keep the account’s balance currency and valuation currency equal in value. It calculates paired buy and sell limit orders around the current account holdings, using a configurable distance from the…
This overview sketches several automated crypto strategies. Its main examples are funding-rate arbitrage, which pairs a short perpetual futures position with a spot long to seek funding income, and spot grid trading, which places paired buy and sell levels…
The document explains why candle-based backtests can mislead, especially for high-frequency and multi-instrument strategies. Candles omit the timing of trades and bid-ask quotes, making it hard to reconstruct simultaneous prices or realistic fills. They also…
The article presents a simple long-only strategy for crypto perpetual contracts. Starting from the current price, it places buy orders at fixed intervals below that level, increasing order size by a configured ratio as price falls. When a long position…
This article explains how to expand a single-pair cryptocurrency grid strategy into a multi-asset spot system. It outlines practical design needs: retrieving aggregated market data and account balances, assigning different grid intervals and order sizes to…
This tutorial shows how to connect Claude Pro to FMZ through the Model Context Protocol (MCP), then use the AI assistant to inspect and operate configured trading accounts. Examples include placing a grid of futures orders, comparing prices across exchanges,…
This tutorial develops a multi-contract spread monitor and a grid-based hedge for crypto futures. It matches near and far contracts for the same underlying, calculates spread values from executable bid and ask quotes, and creates price levels around an…
This tutorial explains how to implement an extendable price grid and trigger trades when market prices cross its levels. It begins with a finite set of grid prices, then adds levels above or below the existing range as the market moves, while preventing new…
The article describes a rebalancing approach for perpetual futures: maintain a target position value, sell as price rises, and buy as it falls. An adjustment threshold determines how much price movement triggers a rebalance. It contrasts this with a grid…
This beginner guide surveys common programmed trading approaches, including arbitrage, trend following, grid or regression methods, and high-frequency trading. It also distinguishes strategies by implementation scope, such as single-asset, multi-asset,…
The article presents an automated strategy for Binance perpetual contracts after a delisting signal. It detects contracts whose delivery date changes from a distant placeholder to a scheduled settlement time, then opens a base short and runs a separate short…
The document walks through a long, short, or two-sided grid strategy written in Pine for use with FMZ. Users set grid spacing, order size, grid count, and take-profit distance. When the live bar begins, the strategy records a starting price, plots grid…
The document explains a perpetual futures balance strategy that maintains a target position value by selling after price rises and buying after declines. Its adjustment ratio determines how much the position changes for a given price move. The author…
This article explains two ways to seek gains when a crypto price fluctuates around a stable level. A balancing strategy maintains a target value split between cash and coin, trading when the allocation drifts beyond a chosen adjustment band. A grid strategy…
This tutorial outlines a simple martingale-style strategy for cryptocurrency perpetual futures. It places long and short entry orders around the current price, cancels the remaining order after one fills, then sets a closing order relative to the open…
This first-person account traces a programmer’s path into cryptocurrency trading, from mining Litecoin to cross-exchange arbitrage, grid strategies, market making, and taking liquidity. It describes how apparent opportunities changed as prices moved,…
This research note develops a three-leg hedge across perpetual, near-dated, and deferred delivery futures. It defines a butterfly spread as the deferred contract price plus the perpetual price minus twice the near-dated contract price. A long spread position…
The document explains a simple grid strategy written in Pine and describes how to run it in an FMZ environment. It anchors grid levels to the first live price, then places limit orders at fixed intervals above or below that level according to a long, short,…
This tutorial describes a Python grid strategy for a cryptocurrency price range. It divides the range into fixed price levels, places a buy order when the market is between adjacent levels, and, after a buy fills, places a sell order above the entry to seek…
The document describes a percentage-based grid strategy for a volatile Pre-IPO derivative. It divides a price range into levels, placing buys below and sells above, and proposes moving the range after a breakout. The described implementation can trade long,…
This article explains a simple spot-market grid strategy implemented in Python. It divides a chosen price interval into fixed-spaced nodes, places buy orders when the market is between adjacent levels, and submits a sell order at a predefined profit offset…