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.
16 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 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 examines practical limits of traditional market-neutral pairs trading. Each trade consumes capital on two legs, incurs spreads and commissions on both, and may use capital on a fairly valued leg even when the opportunity is concentrated in the…
This review surveys research on selecting and trading equity pairs, comparing distance-based matching, cointegration, correlation, and other selection criteria. A common design forms candidate pairs over one period and trades them during a subsequent,…
This article explains how to combine overlapping pair spread signals to infer which individual stocks appear rich or cheap relative to peers. Each spread acts as a relative vote; aggregating votes across a network can help distinguish a likely outlier from a…
The article groups systematic strategies into three broad types, ordered by increasing turnover. Risk-premia harvesting seeks compensation for bearing risks that investors tend to avoid, using diversified exposure and sensible risk control; examples include…
The document frames consistent participation in markets as a way to grow capital over time. It points to the time value of money and the no-arbitrage principle as the main ideas for understanding how investments can earn more than a baseline return, though…
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…
This short note lists ways traders can lose money: excessive trading increases fees and market impact, oversized positions can impair compounding or cause ruin, and shorting positive drift or risk premia can create persistent losses. It also cautions against…
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 installment proposes converting signals from overlapping pairs into security-level signals. For each spread, its z-score becomes two opposing votes: the relatively rich ticker receives a positive signal and the relatively cheap ticker a negative one.…
The document presents statistical arbitrage as a broader portfolio problem than trading matched pairs. It ranks assets by expected cheapness or expensiveness, then builds long and short positions intended to capture relative value convergence while…
The article explains why an upward expected drift does not, by itself, make a call more valuable than a put with the same strike and expiry. It uses a toy probability example to distinguish the chance of finishing above the strike from option value, then…
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 describes a three-part approach to equity statistical arbitrage for independent traders. First, rank related stock pairs using measures of historical mean-reversion returns and consistency of convergence, then retain economically sensible…