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 stock-selection recipe filters Shenzhen main-board listings using turnover between 3% and 12%, year-over-year growth in net profit attributable to parent-company shareholders above 20% and up to 100%, price-to-earnings ratios from 0 to 29.01, and…
This Chinese research note examines the common practice of relating price-to-earnings ratios to expected earnings growth, including the assumption that a PEG ratio of one indicates fair value. Its hypothetical comparison shows that companies with PE and…
This Chinese equity-screening note selects stocks with MACD above zero, positive price-to-earnings ratio, and turnover between three and twelve percent. It interprets the MACD condition as an upward trend filter, positive PE as a basic valuation sanity…
This research summary describes using machine learning to predict equity returns from alpha factors. It compares LASSO, support vector machines, boosted decision trees, and random forests, selecting random forests for their relatively simple structure,…
This research summary describes equity signals built from timestamped order submissions and cancellations, which can reveal more of the trading process than completed trades alone. It focuses mainly on Shenzhen exchange data because that venue had a longer…
This Chinese equity screening method selects stocks with turnover between 3% and 12%, year-over-year growth in net profit attributable to parent-company shareholders above 20% and no higher than 100%, and a daily increase-in-holdings ratio above 5%. The…
This code implements a collection of cross-sectional and time-series equity alpha factors, mainly using close, open, high, low, volume, returns, and VWAP data. The factors combine operations such as rolling ranks, correlations, moving averages, extrema, and…
This research summary proposes combining price-to-book ratio (PB) with return on equity (ROE) to find companies with stronger fundamentals and lower valuations in China’s A-share market. It treats ROE and other operating measures as indicators of value…
This student submission translates a Chinese “dragon returning” trading approach into a factor-based stock strategy. It first identifies strong sectors with sector momentum, then selects leading stocks within them using stock momentum and price-volume…
The document summarizes a study of dividend-focused Smart Beta strategies in Chinese equities. It argues that dividend factors show a consistent ranking pattern across the CSI 300, CSI 500, and broader market universe, with higher-dividend portfolios…
The document surveys a Chinese securities research team’s work on applying artificial intelligence to quantitative investing. It organizes that research around model evaluation, factor discovery, overfitting controls, synthetic data, and methods intended to…
The document introduces two approaches to factor exposure in multi-factor models: using factor values directly, or estimating exposures through time-series regression. It distinguishes regression-based models, which aim to explain returns, from ranking…
This document summarizes a securities research report on constructing factors from high-frequency data, with a focus on combining intraday and day-level information. It frames the choice of calculation method around whether price and volume signals retain…
This report tests the ratio of research and development spending to revenue as an equity-selection factor across industries. Single-factor tests find some effectiveness in technology-oriented sectors, including pharmaceuticals, electronics, communications,…
This article describes a Chinese equity screening idea for companies associated with the metaverse. It selects stocks that recorded at least one limit-up session during the preceding 25 days, have market capitalization below 10 billion yuan, and show…
This Chinese stock-screening proposal selects companies associated with the metaverse theme, with circulating market capitalization above a stated threshold, and an institutional buying or bottom-fishing signal. The accompanying discussion treats…
The note answers whether factors shown in BigQuant’s factor dashboard can be referenced directly. It says they cannot be called directly from the dashboard; users need to open a factor’s detail page and extract its expression. When available, the displayed…
This stock-selection approach combines a price-movement filter, a weekly moving-average crossover, and valuation bounds. It screens Shenzhen Main Board stocks for amplitude above 1, a weekly five-period moving average crossing above the ten-period average, a…
The document describes a market neutral stock factor strategy that estimates each stock’s beta against a broad US equity index using roughly one year of daily prices. At monthly formation, stocks are ranked by beta; the lowest beta group is held long and the…
The article describes a Chinese A-share screening rule that combines a technical filter with company earnings growth. It selects stocks with RSI below 65 and year-over-year growth in net profit attributable to the parent company above 20% and no more than…
This reference describes several candidate fitness objectives for genetic programming that produces equity factors. It defines IC information ratio as the mean information coefficient divided by its standard deviation, with the information coefficient…
This 2017 review compares commodity trading adviser factors and explores ways to combine them. It covers time-series and return-signal momentum, roll yield, basis momentum, and changes in warehouse receipts and inventories. The report says standalone…
This report examines shortcomings in the Henriksson–Merton (HM) and Treynor–Mazuy (TM) models for assessing fund managers’ market and style timing. TM represents beta adjustment as a gradual quadratic pattern, while HM assumes a two-state exposure shift;…
This report overview defines smart beta as a systematic, rules based way to obtain exposure to selected investment factors. It compares the United States and China through their ETF markets, describing differences in product scale, factor coverage, and index…