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
This work studies optimal control when a model contains latent factors and the decision maker chooses a distribution over actions rather than selecting a single action directly. It introduces Tsallis entropy as a reward for exploration of the state space, in…
This study evaluates whether widely used pairs trading rules remain effective in modern US equity markets. It applies both distance-based and cointegration-based methods to equities over the period from 1990 to 2020, including the Covid-19 crisis. The…
The paper frames pairs trading as a choice among three positions: staying flat, holding one asset long and the other short, or reversing those positions. The spread between two correlated assets follows a mean-reverting process with stochastic volatility,…
This study evaluates an automated pairs trading method across stocks listed on the first section of the Tokyo Stock Exchange. It examines pairs of highly correlated stocks and tracks the spread between their prices. Three thresholds define when a position…
This paper formulates pairs trading as an optimal stopping problem. It considers two historically correlated securities whose price difference is modeled as a mean-reverting process. When their relative prices diverge, the strategy shorts the outperforming…
This study extends a single-stock execution framework to trades in two stocks, accounting for cross-impact: trading one stock can move the price of the other. It represents a strategy through the stocks’ trading rates and the ratio of their execution…
The document introduces a cointegrated autoregressive model for time series whose observations are matrices. Its cointegrating relationships are bilinear, representing structure across both rows and columns. This formulation is intended to retain matrix…
MARKET-BENCH evaluates whether large language models can turn natural-language strategy descriptions and market assumptions into executable backtesters. Its tasks cover scheduled trading in Microsoft, pairs trading in Coca-Cola and Pepsi, and delta hedging…
This paper presents a general pairs-trading algorithm framed as a feedback-control problem. It allows the trader to choose a broad class of spread functions and adjusts investment levels dynamically as that spread changes. Rather than relying on restrictive…
This study uses random walks to simulate two coupled limit order books and examine how correlation develops between them. Its model represents order arrivals, cancellations, and diffusion, while a pairs trader links the books by trading on mean reversion. It…
The document describes a mean-reversion approach that begins with yield-curve trading strategies and extends the idea to a multi-pair strategy involving major currency pairs. To refine its trading signals, the strategy incorporates machine-learning forecasts…
This study proposes a multi-pair statistical arbitrage framework for U.S. equities that uses graph clustering to identify relationships among stocks. It combines quantitative methods with machine-learning classifiers and the Kelly criterion, aiming to…
This study formulates pairs trading as a portfolio optimization problem for two cointegrated stock log-prices. A singular stochastic control model jointly determines when to trade and how many shares to adjust, while incorporating proportional transaction…
This paper studies Bertram’s optimal strategy for a pair of cointegrated assets whose price difference follows an Ornstein–Uhlenbeck process. The baseline objective is to maximize expected profit per unit time. The authors generalize the setup by…
The study proposes a stock-pair selection distance measure that accounts for lead-lag relationships between the two stocks. It starts from the observation that correlated securities may not move simultaneously: one can tend to respond before the other.…
The document describes a pairs trading strategy using 22 international country ETFs. It normalizes dividend-inclusive total return series, selects the five pairs with the smallest cumulative price distance over a 120-day formation period, then trades them…
The document describes a futures spread strategy based on the price difference between WTI and Brent crude oil. It explains that the oils differ in composition and production and transport characteristics, while temporary shocks may cause their price spread…
The document explains a relative value strategy that pairs stocks with similar historical price paths. It normalizes total return series, selects close matches using the sum of squared price differences, and trades the selected pairs in a later period. When…
This event announcement outlines two educational topics: futures and cash-futures spread trading, and machine-learning methods for developing CTA signals. The spread section describes analyzing related contracts through their price difference, looking for…
The document examines what the coefficient in a log-price cointegrating relation means for a pairs trade. It contrasts interpreting the coefficient as a share ratio with interpreting it as a ratio of market values, and explains why those interpretations lead…
This spread strategy uses Bollinger Bands to enter and exit positions. After building spread bars and waiting for its array manager to initialize, it calculates the moving average and upper and lower bands over a configurable window. When flat, it opens a…