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.
5,922 documents
This document summarizes a research approach that uses Google Trends search activity to inform equity portfolio weights. It treats search volume as a measure of how popular a stock is and assumes that popularity is related to risk. The portfolio therefore…
The report outlines a framework for timing equity factors whose performance has become less stable. It first examines indicators such as valuation spreads and pairwise correlations, testing their relationship with future factor returns. It then uses a random…
This meetup Q&A contrasts futures CTA strategies, often framed around trend following, with equity multi-factor strategies that combine signals such as value, momentum, quality, and size. It outlines a Bollinger Band example for futures: calculate a…
This research summary examines quantitative stock selection among Chinese technology companies. It highlights research and development spending as a candidate signal and also discusses profitability, earnings growth, valuation, company size, turnover, and…
This example builds a simple portfolio analysis workflow that generates a daily value series for several allocation weights and plots the paths together. A configuration object holds the tested weights, chart dimensions, and date range. The demonstration's…
This project explores combining strategies associated with different market styles. The author says market styles can persist over a period, so a strategy that fits a clearly expressed style may adapt better to prevailing conditions. They changed a provided…
The document describes a beginner’s question about passing results from earlier BigQuant modules into a backtest. The proposed strategy uses a fixed universe of ten stocks, ranks them daily by five-day return in ascending order, buys the five lowest-ranked…
This summary describes a method for constructing broad stock factor exposures and checking factor usefulness in a multifactor model. It presents returns as a linear combination of factor contributions plus an unexplained residual, and emphasizes examining…
This beginner-oriented guide recommends planning trades in advance, researching assets before buying, and avoiding impulsive decisions driven by hype or fear of missing out. It advocates diversification across crypto assets, monitoring Bitcoin as a possible…
This tutorial demonstrates a graph convolutional policy, GPM, inside a reinforcement-learning portfolio workflow. It loads historical stock features and a sector and industry graph, then reduces the graph to nodes within two hops of the selected portfolio…
This article summary presents a quantitative framework for combining conventional alpha factors with ESG-related signals in equity portfolios. It distinguishes exclusion screens, ESG integration, and impact investing, then focuses on integration: investors…
This introductory guide surveys active and passive approaches to cryptocurrency trading. Its active strategies include day trading, swing trading, trend trading, and scalping. It distinguishes them by holding period, monitoring demands, and the kinds of…
This tutorial explains how to combine daily stock-price observations with less frequent dividend records using an ASOF JOIN. The example pairs records by instrument and date, allowing each daily price row to be associated with a nearby dividend record even…
This research summary examines how sell-side analyst reports may inform stock selection. It argues that report counts and recommendation strength alone provide limited differentiation, while target-price upside and changes in analyst views may be more…
This article surveys six implementation choices that shape equity factor strategies: selecting proxy measures, constructing portfolios, combining factors, allocating among them, trading, and managing risk. It argues that one factor can be represented by…
The document presents daily portfolio rebalancing as a Markov decision process. An agent selects nonnegative weights for Dow 30 stocks, normalized to sum to one, using a state that combines a rolling covariance matrix with MACD, RSI, CCI, and ADX indicators.…
The document raises a portfolio-construction question about using a stock-ranking model to select both ends of its predictions: stocks with the highest factor scores and stocks with the lowest scores. The proposed idea is to hold the two groups together as a…
This article introduces support vector machines for classification and regression, then applies them to A-share stock selection. It explains the maximum-margin principle for linear SVMs, slack variables for imperfectly separable observations, and kernel…
This tutorial explains how support vector machines classify data by finding a boundary with a wide margin, and how slack variables allow some classification errors in noisy data. It introduces kernel methods as a way to handle nonlinear boundaries by…
The document outlines a factor attribution framework for evaluating active equity funds within a fund of funds (FOF). It separates returns into broad risk exposures, such as market, style, and industry effects; alpha-factor contributions from technical and…
This review summarizes research comparing highly rated ESG stocks with other stocks in US and developed international markets. It examines individual securities and randomly formed portfolios using MSCI ESG classifications and a Fama-French five-factor model…
This configuration describes a Qlib experiment using a graph attention model, GATs, with an LSTM base model to predict near-term returns for CSI 300 constituents. It sets Chinese market data, defines a close-to-close forward return label, normalizes features…
This tutorial explains applying principal component analysis to stock returns to identify dominant co-movement patterns. It standardizes historical returns, estimates a rolling correlation matrix, and decomposes it into eigenvalues and eigenvectors. The…
This algorithm implements a January barometer rule using a broad equity ETF and a Treasury bill ETF as alternatives. At the start of January, it liquidates the bill holding and invests in equities, recording the equity price as a reference. In February, it…