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.
23 documents
This case study recounts a team’s experience entering crypto trading in 2021, when they viewed the market’s fragmented and developing structure as a source of inefficiencies. It describes several approaches: futures basis arbitrage, exploiting delays between…
This article argues that traders should begin with a workable strategy and build technology in response to problems encountered in live trading. Elaborate systems designed before trading can consume time without generating market feedback, and the imagined…
This article demonstrates a convex optimisation workflow for a crypto perpetual futures portfolio. It combines expected returns estimated from cross-sectional momentum and carry features with a breakout signal, then uses a covariance estimate to represent…
This article explains statistical arbitrage by contrasting it with cross-exchange arbitrage. Pure arbitrage seeks to buy and sell the same asset at different prices, but transfers, costs, and price changes make the apparent opportunity difficult to capture.…
This article brainstorms possible inputs for a crypto statistical arbitrage model. It covers relative price moves between similar assets, short and long horizon trends, crowded spreads that may unwind with momentum, lead-lag effects across markets, and…
The article advises new trading businesses to begin trading with available skills and tools, then build operational capabilities in response to real market experience. It argues that constructing a large technology stack before trading can waste effort…
The article demonstrates a spreadsheet-based permutation test for assessing whether an observed market pattern could arise by chance. Its example examines whether Bitcoin returns are unusually high on Tuesdays: daily returns are randomly shuffled, grouped by…
This tutorial demonstrates a workflow for obtaining cryptocurrency listings, market capitalization, trading volume, and daily historical prices through the CryptoCompare API. It batches coin queries, ranks assets by reported market capitalization, removes…
The article explains why market making is demanding for beginners. A market maker posts bids and asks around an estimate of fair value, seeking to earn the spread while providing liquidity. The example shows how a mistaken estimate can attract trades on the…
This article demonstrates a practical way to reduce trading costs in a crypto statistical-arbitrage portfolio: keep existing positions until they drift sufficiently far from their target weights. The example uses perpetual futures, excludes stablecoins, and…
This note applies lessons from gambling to strategy selection. It recommends looking for comparatively tractable opportunities, including harvesting risk premia and predicting relative returns across assets rather than forecasting the absolute direction of…
This course description presents a practical framework for evaluating trading ideas with spreadsheet analysis and freely available market data. Its proposed research process is to formulate a hypothesis, collect and clean relevant observations, explore the…
The article outlines three practical sources of trading hypotheses. Traders can learn from other market participants who appear to have profitable approaches, while adapting ideas to smaller niches or constraints that may not suit large asset managers. It…
The document argues that binary rules, such as taking a position based only on whether price is above a moving average, discard information and conceal how signal strength relates to future returns. For a crypto trend example, it replaces the on/off…
This course page presents a framework for systematic trading centered on identifying a plausible edge before building and evaluating a strategy. It argues that a strong backtest alone does not establish that a strategy is sound, and recommends formulating a…
This article uses simulated cryptocurrency price paths to explore how often a leveraged trend strategy might need rebalancing to manage drawdowns. The author builds a geometric Brownian motion simulator with autocorrelated returns and random jumps, using a…
The document argues that mean reversion, momentum, and trend describe observed price behavior but do not by themselves establish a tradable edge. A credible hypothesis should pair supportive data with a plausible mechanism explaining who trades, why the flow…
The article presents a workflow for studying and combining signals on Binance crypto perpetual futures. It examines carry from funding rates and cross-sectional momentum alongside a breakout measure based on closeness to recent highs. The author first…
Carry is a position expected to earn a return as time passes, provided prices and other conditions remain stable. The document explains this through currency yield differentials, rolling bond and stock futures, and selling options, then describes perpetual…
The article explains how to express trading signals as expected returns, giving a common scale for comparing features and combining them with risk estimates and trading costs. Its example uses Binance perpetual futures and considers carry, short-term…
The article argues that a trading business needs a plausible, explainable source of returns rather than relying on discretionary chart reading or feeding features into a machine-learning model without a clear rationale. It frames durable edges as…
This short essay argues that independent traders should learn from the ideas behind institutional strategies without copying their implementations. It points to statistical arbitrage opportunities that can arise when supply and demand are uneven or when…
The article discusses two proposed crypto trading signals. The retail-flow factor uses order-book data to distinguish retail from institutional activity and treats unusually strong retail participation as a contrarian signal. The author reports a near-linear…