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 proposed equity screen selects shares using three conditions: daily price amplitude above a threshold, a closing price of 18.5 yuan, and return on equity above 15% for five consecutive years. The article presents sustained ROE as a signal of long-term…
This strategy ranks stocks in the MSCI World universe by the change in their ESG rating deciles over a roughly twelve-month interval. It goes long the strongest ESG improvers and short the weakest, rebalancing monthly. The implementation selects about 700…
This user proposal for a quantitative trading platform focuses on making research and strategy evaluation more credible. Suggestions include allowing users to schedule live strategy runs, screening factors using their information coefficients over prior…
This assignment describes two Chinese equity ranking approaches focused on micro-cap stocks. Both screen for positive trailing earnings, the smallest market-cap segment, and exclude special-treatment, suspended, and recently listed shares. The XGBoost model…
This document summarizes a Chinese research report on a standardized growth factor based on trailing-twelve-month operating profit. It reports results after removing correlations with other factors, including an information coefficient of 2.2%, an…
This Chinese stock-screening example combines a price-range condition, exclusion of stocks that hit the upper price limit on the previous day, and revenue growth between 2018 and 2021. The stated screen requires the later revenue figure to exceed the earlier…
This research note constructs a stock-selection factor from intraday volume surges and the price response around them. A surge is a minute when volume has risen from the prior minute by more than the stock-day average increase plus one standard deviation,…
This strategy description proposes rebalancing on a weekly schedule, excluding suspended stocks, and investing equal amounts in selected shares. Its selection function queries stocks with market capitalization between 20 and 30 units in the platform’s…
This overview explains quantitative stock selection as a data-driven way to rank or choose equities using historical prices, trading volume, financial statements, macroeconomic measures, and sentiment data. It outlines a workflow: clean and standardize…
This summary of a 2017 Chinese broker report examines active mutual-fund holdings as potential signals for sector and stock selection. It argues that changes in sector positioning may matter more than the level of over- or underweighting: sectors that remain…
This study examines whether equity factor performance varies with institutional ownership in Chinese A-shares. It estimates each company’s institutional holdings as a share of tradable market value, combining reported fund and asset-management positions,…
The strategy selects Chinese equities whose MACD is above zero and whose symbols begin with the code prefix associated with Shanghai listings. Its rationale is that positive MACD may indicate upward price momentum, while the listing filter focuses the screen…
This note describes a method for splitting a stock’s recent trading days by average transaction value, calculated as daily traded value divided by trade count. Over an even-length lookback window, it ranks days by this measure, sums returns for the…
This study examines whether U.S. equity mutual fund managers adjust market exposure when stock misvaluation is unusually high. It measures common misvaluation with a financing-based factor that buys repurchasing firms and sells issuing firms, then removes…
This stock-selection screen combines three filters: prior-session price amplitude above 1%, free float no greater than 5.5 billion shares, and more than one year since listing. The accompanying explanation treats amplitude as a way to find active, volatile…
This support post reports a KeyError during a Chinese equities factor analysis. The example defines an operating cash flow growth factor, selects the CSI 300 universe and benchmark, and requests ten portfolio groups. The failure occurs when the analysis…
This report compares machine-learning stock-selection models trained with conventional return labels against models using information ratio or Calmar ratio labels. The alternative labels incorporate aspects of the path within the evaluation period, including…
This brief outlines a stock-selection approach that first looks for shares with recent market activity, checks for changes in capital flows, and applies multiple factors. It presents these as broad screening ideas rather than a fully specified trading…
This explanation describes a factor evaluation score derived from rolling Elastic Net regressions that include all submitted factors together. The model predicts each stock’s next-day return after cross-sectional standardization, fits on rolling windows, and…
This research note classifies Chinese listed companies according to whether institutional investors appear in periodic ownership disclosures, then compares portfolios formed from the two groups. It reports that portfolios without institutional holdings…
This review summarizes research comparing the returns of published stock market anomalies before and after academic publication. The study examines 241 anomalies across the United States and 38 international markets, constructing long-short returns and…
This research summary examines residual momentum, also called idiosyncratic momentum: a stock’s return after removing shared market influences. It reports that, in China’s A-share market, stronger residual returns in the prior period are associated with…
The screen selects equities using three criteria: turnover between 3% and 12%, circulating market value between 5 billion and 10 billion yuan, and 2021 revenue divided by 2018 revenue above 1.1. The stated rationale is to combine trading activity and company…
This strategy ranks a universe of commodity futures by the skewness of their daily returns over a trailing 12-month window. At each monthly rebalance, it goes long the quintile with the lowest skewness and short the quintile with the highest, with equal…