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.
765 documents
The document introduces interactive tear sheets for examining candidate trading pairs. It explains why selection requires more than a single cointegration result: Engle–Granger analysis is sensitive to which asset is treated as dependent, while Johansen…
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 walks through implementing a price-spread pairs trade in Zorro using GDX and GLD as an example. It defines the spread as one asset’s price minus a hedge-ratio-adjusted price of the other, then standardises the spread with a rolling z-score. The…
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.…
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 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…
This tutorial builds an adaptive pairs trading example with gold and gold-mining ETF prices. A Kalman filter estimates a changing hedge ratio and intercept as new observations arrive. The prediction error is compared with its estimated standard deviation to…
The article explains how to assess candidate equity pairs and estimate a spread for mean-reversion trading. Using XOM and CVX as an example, it fits an ordinary least squares hedge ratio, forms a residual spread, and applies an Augmented Dickey-Fuller test.…
This article focuses on selecting stock pairs for statistical arbitrage. It argues that finding pairs whose prices reliably diverge and reconverge matters more than the details of hedge-ratio estimation or other implementation models. Historical correlation…
The article presents pairs trading as taking opposite positions in correlated assets when their relative prices diverge, with the expectation that the relationship will move back toward its mean. It questions the routine use of price regression to estimate a…
The article introduces parameter optimization for systematic strategies, using a moving average window as a simple example. It describes choosing a default value, search range, and step size, then comparing approaches such as sequential ascent, brute force,…
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 article treats trading as an operating business that must allocate limited capital, time, and skills across strategy research, infrastructure, reporting, accounting, and ongoing learning. Its guiding question is how to improve the trading setup in ways…
The Hurst exponent is presented as a way to characterize whether a time series tends to behave like a random walk, persist in its direction, or revert toward an average. The article connects this classification to the search for mean-reverting financial…
The document explores whether currency prices can form stationary spreads suitable for mean-reversion analysis. It estimates a two-currency spread using ordinary least squares, then tests the residual with an augmented Dickey-Fuller procedure. It also…
This tutorial combines a Kalman filter written in R with a simple pairs trading system in Zorro. The filter updates a hedge ratio as new prices arrive, estimates the spread prediction error, and calculates its uncertainty. The trading logic uses that…
The article describes practical TradingView workflows for discretionary and early-stage trading research. The author uses watchlists to monitor macro instruments and track a basket of factor ETFs through a synthetic instrument weighted by units held. A…
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…
The article introduces serial correlation, also called autocorrelation, as dependence between observations at different times. It reviews expectation, variance, covariance, and correlation, then explains why correlation is a normalized measure of linear…
This June 2020 update reports several releases of the QSTrader backtesting engine. Its main technical change was an overhaul of portfolio, position, transaction, and simulated broker components to support short selling. The platform moved from long-only…