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 document summarizes a study of whether slow updating of beliefs about future earnings can account for the profitability anomaly: the tendency for more profitable stocks to outperform. In its model, expectations combine prior beliefs with rational…
This research summary presents a model in which investors update beliefs about future profits too slowly. When earnings signals are persistent, that sluggish updating can leave information out of stock prices, helping explain why more profitable firms and…
This research examines whether large and small order money flows predict cross-sectional stock returns. It standardizes net inflow by trading value to form separate factors, then compares stocks grouped by factor strength. The reported results show a…
The study tests whether hedge funds can time returns in particular industries and whether measured timing ability predicts later fund outcomes. It first removes market exposure from industry returns, then estimates each fund’s industry timing coefficient…
This note outlines a Chinese equity selection approach that first limits candidates to companies with market capitalization below 10 billion yuan and no losses, then ranks them by capital strength and selects the top five by the day’s auction amount. The…
The proposed stock screen combines an RSI below 65 with greater displayed buy-side than sell-side volume, and limits candidates to Shenzhen Main Board stocks with positive price-to-earnings and price-to-book ratios below specified ceilings. The article also…
This document summarizes a method for evaluating mutual fund managers while accounting for both factor exposures and the characteristics of the stocks held. Its premise is that standard factor models, including the Carhart four-factor model, may leave return…
This meetup summary collects questions and answers on quantitative research, strategy development, and live trading. It points readers toward factor analysis, information coefficient interpretation, portfolio performance assessment, and resampling data to…
This research summary describes a Chinese equity approach that first screens stocks within broad industry groups using selected fundamental indicators, then combines the resulting preferred-stock universe with a multi-factor framework. It discusses a…
This overview explains feature engineering as the work of turning raw market and company data into useful inputs for quantitative strategies and machine-learning models. It uses a dual moving-average crossover to show that a trading rule can be understood…
The document explains how small-cap and value premiums in China’s A-share market may vary over time. It frames stock valuation as depending on expected future cash flows and the discount rates applied to them. A two-beta model separates a stock’s sensitivity…
This proposed A-share screen filters for stocks with turnover between 3% and 12%, market value below 10 billion yuan, no reported losses, and a listing history beyond a stated minimum such as three years. The stated rationale is that an established trading…
This document presents a stock screen that combines an industry filter for beverage and alcohol businesses, a turnover-rate range of 3% to 12%, and a bullish KDJ crossover. The accompanying explanation describes KDJ as a technical signal and notes that the…
This stock-selection approach ranks shares using two measures: net capital flow and net large-order flow. Each measure is calculated over a period by taking net inflows less outflows and dividing by free-float market capitalization. Higher values are…
The document presents a brief summary of a research report on identifying the investment style of equity funds. It argues that fund style is closely related to fund returns and should be assessed before selecting a fund. The proposed approach is to identify…
The post describes constructing a broad Chinese A-share stock universe by retrieving and combining constituents of the Shanghai Composite and Shenzhen Component indices. It recommends obtaining the constituent lists dynamically rather than fixing them once,…
The document describes a Chinese A-share screen that selects stocks associated with the metaverse theme, applies a morning price-change ceiling, and requires market capitalization of at least 200 million. It also gives an example implementation that…
This post describes a daily stock selection screen for Shenzhen main-board shares. It combines a ranking by capital inflows, keeping the top 100, with price-to-earnings ratios between 0 and 29.01 and price-to-book ratios between 0 and 3.11. The author…
This July 2020 market note attributes the bull market to falling risk-free rates and increased allocations to equities. It argues that a more diverse investor base may reduce the chance of a sudden collapse, while rising participation and short-term…
This Chinese stock selection example combines turnover, earnings growth, and recent money flow. It screens for stocks with turnover between 3% and 12%, year-over-year growth in net profit attributable to shareholders between 20% and 100%, and positive…
This A-share stock selection strategy buys the ten smallest companies by market capitalization each day and rebalances daily. Its universe is drawn from the CSI 1000 and excludes ST and delisted stocks. Additional filters require a positive trailing…
This article proposes interpreting value, momentum, quality, and low-volatility returns through a recurring factor cycle inferred from factor performance itself. It describes normal periods, episodes when value suffers a major drawdown due to growth stocks…
This Chinese-language summary reviews a quantitative research team’s 2017 results across four areas: multi-asset allocation, index enhancement, factor timing, and commodity trading adviser strategies. It reports that an equity-and-bond active risk-parity…
This Chinese stock screen combines three filters: at least five moving averages overlap, the prior day’s exchange leaderboard shows participation by large institutions or funds, and the company’s 2019 payout ratio exceeds 25%. The article interprets the…