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
The document introduces the task of developing a complete strategy from daily factors extracted with a high-frequency expression engine. It identifies strategy development as the topic of a meetup presentation and points readers to a related recording, but…
This report examines listed companies’ interest-bearing debt as a quantitative stock-selection and risk-screening measure. It defines the debt measure around short-term and long-term borrowings and bonds, and observes that debt ratios tend to reflect…
This Chinese language post describes a stock selection screen combining technical and fundamental filters. It selects stocks with RSI below 65, circulating market capitalization between 5 billion and 10 billion yuan, and a weekly five period moving average…
The article describes a stock selection screen that combines daily price amplitude above 1, a controlling-shareholder measure whose absolute daily change exceeds 21, and operating revenue in 2021 divided by 2018 revenue above 1.1. It presents the conditions…
This overview explains how factor models can identify portfolio risk drivers and how factor strategies can target their associated return premia. It describes equity factors such as value, size, momentum, volatility, quality, yield, growth, and liquidity,…
The document explains the price-to-earnings ratio (P/E) as a way to relate a stock’s price to the company’s earnings per share. Comparing two stocks at the same price but with different earnings shows how the ratio distinguishes their valuations: the stock…
This document describes an A-share stock screen that combines an RSI threshold below 65 with parent-company net profit growth above 20% and up to 100%, while excluding ST-designated stocks. It also invokes a five-step limit-up method intended to identify…
The document describes a Chinese A-share screening rule focused on metaverse companies listed on the Shenzhen main board. It selects stocks with a circulating share count no greater than 5.5 billion and filters for price-to-earnings ratios from zero to 29.01…
This research note introduces propensity-score methods as a way to estimate causal effects from observational data, where treated and comparison groups may differ in confounding characteristics. Its workflow is to estimate scores and treatment effects,…
This Chinese stock selection method looks for shares with a daily price range above 1%, prior-day trading activity above 60 million, and return on equity above 15% in each of the preceding five years. It combines a short-term price and liquidity filter with…
The report builds a composite trading-heat signal from stock-specificity and market-cap-adjusted turnover, using these trading-behavior measures as proxies for speculative activity. It argues that the two inputs capture most of the useful information in a…
The screen selects Chinese A-shares whose daily high-low range exceeds one percent, excludes Beijing-listed stocks, and requires at least one limit-up event in the prior month. The accompanying explanation interprets range as a measure of activity and a…
This overview explains how quantitative strategies use factors to express hypotheses about future returns. It describes candidate signal sources such as prices, fundamentals, macroeconomic data, and text, then outlines a research process: translate an…
A VeighNa community discussion considers how to adapt a daily-bar backtest so a multi-factor stock portfolio is held for a week and rebalanced less often. The practical suggestion is to inspect each bar’s date inside the strategy’s bar handler and permit…
This meetup outline raises questions about constructing sector or industry factors, measuring correlations among industries, and choosing industry classifications that reflect granularity and supply-chain relationships. It identifies these as topics for…
This report explains the risk-prediction component of a multi-factor investment framework. It describes estimating a structured risk matrix from factor covariance and specific-risk components, with adjustments intended to improve consistency and accuracy.…
This report introduces quantitative funds in China and distinguishes three operating models. Active quantitative funds use models to select stocks in search of returns above a benchmark. Index-enhanced funds combine index exposure with model-based stock…
This research constructs a stock-selection factor from the short-term correlation between trading volume and price movement. It uses that relationship to distinguish stocks whose volume and price move together from those that diverge, then ranks stocks for a…
This research summary describes a corporate-governance factor for Chinese equities, built from 58 measures across board structure, ownership and shareholders, financial governance, compensation and incentives, governance conduct, and external oversight. It…
This research summary measures listed companies’ earnings quality by the relative size of accruals in reported profits, then tests accruals as a stock selection factor in China’s A-share market. Its regression findings describe operating profit as…
This tutorial shows how to evaluate a stock factor with Alphalens and then examine a portfolio built from its strongest and weakest ranked groups with Pyfolio. Its example defines a mean-reversion signal from the negative five-day change in opening prices,…
The post proposes screening A-share companies using daily turnover, market capitalization, profitability, and metaverse-related business exposure. Its stated criteria are turnover between 3% and 12%, market value below 10 billion yuan, and no losses, with…
This account develops an equity-selection process that compares equal-weighted factor rankings with weights that adapt to each factor’s recent Rank IC information ratio. It describes screening a large factor pool for missing data, outliers, redundancy,…
This Chinese equities research reproduction develops a cross-sectional factor from minute-level volume surges. A surge is defined when the minute-to-minute volume increase exceeds that stock’s daily average increase by one standard deviation. For each surge,…