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.
4,194 documents
This code module supplies plotting and summary routines for quantitative factor research. It formats tables for factor returns, turnover, rank autocorrelation, quantile statistics, and information coefficients. Its chart functions visualize information…
This research summary presents a framework for classifying industry and thematic funds and using the resulting categories to form candidate investment pools. Fund contracts’ investment requirements serve as a core eligibility basis. The framework begins with…
This analysis proposes six dimensions for assessing Chinese brokerage firms’ monthly stock recommendations: absolute returns, return relative to volatility, sector selection, stock-level excess returns, ability to identify emerging winners, and selection…
This review of Asness and Frazzini examines how price timing affects the book-to-price measure used to form the HML value factor. The standard Fama–French approach pairs accounting book value with a prior fiscal year-end price, then updates portfolios…
The article proposes a Chinese stock screen combining daily price amplitude, a change in controlling shareholders’ holdings, and a fundamental-data condition meant to reflect an investor’s preferences. It offers a formula-style sketch and Python-like…
The article proposes screening mainland Chinese main-board stocks for turnover between 3% and 12%, a robot-related theme, and circulating market value below 10 billion yuan. Its initial version uses a 2019 dividend payout threshold above 25%; the revised…
This brief platform support exchange answers where to find the dividend_yield_ratio field after a user cannot locate it in the dividend information table. The response points to a precomputed stock factors table, explaining that the requested field is…
This article develops two monthly equity factors from Chinese market flow data. The first, called institutional-versus-retail harvesting, adds the cross-sectional ranks of large-order net buying and small-order net buying. The author interprets the factor as…
This proposed equity screen combines a share price below 12 yuan, market capitalization under 10 billion yuan, companies described as having no losses, and at least five overlapping moving averages. The article frames the price and size limits as a way to…
This Chinese stock screen selects Shenzhen Main Board companies with RSI below 65, positive price-to-earnings ratios below 29.01, price-to-book ratios below 3.11, and a gain under 6% at 9:25. The accompanying code reference also filters for circulating…
This summary of a securities research report examines alternative data, focusing on company job postings. It describes a hiring-count factor tested over 2017–2021, reporting that preprocessing and filtering job listings improved its backtest performance. The…
The article compares two Chinese equity approaches built around market capitalization. The traditional strategy selects the smallest-cap stocks for a portfolio. The AI version uses a StockRanker ranking model with market capitalization as its sole feature.…
This excerpt introduces a framework for assessing whether stock-selection factors may deliver persistent returns beyond broad market exposure. It distinguishes market-related beta from alpha and presents factor effectiveness as a question of both return…
The document outlines a basic workflow for studying whether investors favor value or growth stocks during crises. It suggests obtaining constituent stock prices from market data sources, using an established equity research classification to separate value…
The document discusses practical uses of equity return factors such as the Fama–French factors, momentum, and liquidity or tail-risk measures. It describes factor investing as a portfolio construction approach and notes that predicting factor returns, often…
The document asks how to interpret common sell-side analyst ratings on a five-point scale in quantitative terms. It uses a score associated with market-average performance as an example and asks whether ratings above that level correspond to defined ranges…
The document considers how to build a fundamental scoring model for a defined stock universe using metrics for size, growth, valuation, quality, and risk. It describes the practical challenge of collecting current, historical, and estimated Bloomberg fields,…
The discussion distinguishes forecasting the aggregate equity premium for the next month from ranking individual stocks by expected return. It points to characteristic-based cross-sectional models, using rolling Fama–MacBeth slopes and multiple firm…
The document asks how factor exposures differ from the factor returns themselves in the Fama–French three-factor model. It contrasts a Fama–MacBeth second-stage regression using estimated asset betas with a proposed regression using the factor series…
The document asks whether Sharpe-style portfolio style analysis can explain equity fund performance using indices grouped by high, medium, and low ESG characteristics. It identifies suitable data as the central practical challenge and points to ESG scoring…
The discussion distinguishes contemporaneous factor models from forecasting models for portfolio optimization. In the Fama–French three-factor setup described, an asset’s return is related to factor returns from the same period. That relationship can help…
The document explains a standard regression approach for estimating a portfolio’s CAPM alpha. It recommends calculating monthly excess returns for the portfolio and market, then regressing portfolio excess returns on market excess returns. The regression…
The document compares two CAPM regression forms: one uses the asset's return in excess of the risk-free rate, while the other regresses the raw asset return on the market's excess return. It explains that, when the same observations and regressors are used,…
The note asks whether traditional factor models become less adequate as markets grow more complex and new return patterns emerge. It cites the Fama-French three-factor model, which captures broad cross-sectional return patterns in the mid-1990s but does not…