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 Chinese-language post outlines a stock selection screen for the Shenzhen main board. It combines a ranking by capital inflows, retaining the top 100 names, with valuation filters that require price-to-earnings ratios from 0 to 29.01 and price-to-book…
The document describes research that extracts information from high-frequency order-book data and turns it into two groups of factors. It says the researchers aggregate these measures into monthly signals and evaluate their stock-selection performance in…
This report reviews Chinese equity index enhancement portfolios and single-factor results for the week of March 14–18, 2022. Its portfolio construction process is described as combining return forecasts, risk controls, and portfolio optimization, with the…
The post presents a Chinese-equity screening idea that combines a relative strength index filter with a range for tradable market capitalization and dividend-related criteria. Its initial description refers to a historical dividend proportion, while its…
This report describes three Chinese equity portfolio approaches designed to compete with active mutual funds rather than broad market indices. The fund-enhancement portfolio selects funds by performance layers, uses their holdings as a universe, and applies…
This note describes a stock-selection and rotation approach built around buying shares judged to be at relatively low price levels. A scoring system ranks candidates; the strategy buys higher-ranked stocks and holds five positions. As a holding rises, its…
The document describes a buy-sentiment factor built by distinguishing aggressive purchases, which execute against sell orders already on the book, from passive purchases, which wait as limit orders for incoming sells. It argues that finer-grained market data…
This research review describes a dynamic, out-of-sample process for selecting US active equity mutual funds from observable fund characteristics. It compares elastic net, random forests, gradient boosting, and linear regression. Each year, models are trained…
The post argues that factor research can use information from later minutes within the same trading day when constructing a daily-frequency factor, provided the factor does not use data from the following day. It proposes examining relationships between…
This study tests whether investors can improve a diversified global equity factor portfolio by adjusting factor weights with time-series signals or cross-sectional characteristics. It applies parameterized portfolio policies to twenty long-short equity…
This research summary compares seven ways to identify active mutual funds with positive, negative, or zero risk-adjusted performance. It explains a factor-model benchmark and methods that adjust for multiple testing, including bootstrap and false discovery…
This article reviews seven methods for classifying active mutual funds as skilled, unskilled, or zero-alpha, with emphasis on how their accuracy changes when return histories are short. It describes a four-factor alpha benchmark, multiple-testing…
The post describes a stock-screening rule that combines a positive MACD reading with a share price below 12 yuan, market capitalization no greater than 10 billion yuan, and positive net income. Its stated rationale is to combine technical strength with…
This Chinese-language post describes an equity screen combining three conditions: price amplitude above a threshold, a dividend payout ratio above a threshold for 2019, and a MACD value below zero two trading days earlier. The rationale is to combine a…
This post outlines a Chinese stock screen using a 2019 dividend-ratio threshold above 25%, an RSI below 65, and a rule excluding stocks that hit the daily price limit on the prior day. Its stated final selection logic adds price-to-earnings below 50 and…
This proposed A-share screen combines capital-strength ranking, the five stocks with the highest auction amount for the day, and a dividend ratio above 25% in 2019. Its expanded final logic adds price-to-earnings below 30, price-to-book above 1, a bullish…
This post outlines a Chinese A-share screen using turnover between 3% and 12%, at least one limit-up event in the prior 25 days, and a revenue comparison requiring 2021 revenue to exceed 2018 revenue by more than ten percent. It also describes ranking…
This brief summary of a multi-factor stock-selection report describes three ways to refine traditional factors using high-frequency returns. High-frequency return variance is presented as a closer measure of volatility than variance calculated from daily…
This tutorial presents a workflow for evaluating a factor on Chinese equities, using the lower Bollinger Band as an example. It introduces factor analysis as a way to summarize variables and derive composite scores, then describes building daily factor data,…
The document proposes a Chinese equity screen combining metaverse industry membership, a rounded price pattern, market capitalization below a stated ceiling, and positive return on equity as a proxy for avoiding loss-making companies. It frames the…
The document outlines a Chinese equity screen combining a high 2019 dividend payout ratio, a recent increase in holdings, and a requirement that the previous session was not limit-up. It later adds price-to-earnings and price-to-book thresholds and a minimum…
This research summary tests whether splitting stock volatility into components yields useful selection signals from high-frequency returns. The reported system-versus-idiosyncratic volatility split performs poorly at the one-minute sampling interval; its…
This research digest summarizes two studies. The first revisits the claim that small-cap stocks earn higher average returns than large-cap stocks, reviewing competing views about the size effect and describing simple tests with public data intended to…
This research summary examines valuation factors for industry allocation and explains why raw valuation measures can be difficult to compare across sectors. It reviews five common measures, including earnings, book, sales, and operating-cash-flow based…