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 article argues that greater differences among stocks can improve the opportunity set for systematic equity strategies. When company returns, sectors, and factors diverge, models can rank securities using valuation, momentum, quality, earnings revisions,…
This A-share stock selection example screens for companies meeting three stated criteria: profit growth above 15%, return on equity above 15% for three consecutive years, and a price-to-earnings ratio below 35. The implementation treats profit growth, return…
This research summary reviews stock-selection factors derived from tick-by-tick trade data, including large-buy share, buy-order concentration, intraday aggressive buying, and informed buying or selling measures. After orthogonalization, the factors…
The document describes a study of four MSCI smart beta equity indexes and a market weighted benchmark. It uses principal component analysis (PCA) to separate shared market movements from strategy specific components, then regresses those components on Fama…
This research note explores whether patent data can reveal links between companies that are missed by industry or supply-chain groupings. It uses shared International Patent Classification information to estimate technological similarity, then tests whether…
This Chinese-language example describes a value-oriented stock selection strategy that refreshes its portfolio every 30 trading days. It selects stocks with positive price-to-book ratios below 1.5 and positive price-to-earnings ratios below 15, provided they…
This Chinese equity screen selects stocks with turnover between 3% and 12%, year-over-year net profit growth attributable to parent-company shareholders above 20% and up to 100%, and revenue in 2021 more than 1.1 times its 2018 level. The document supplies…
This stock screen combines four conditions: amplitude above a stated threshold, a change in an institutional trading-volume measure, a negative price change relative to the previous close during the auction-related condition, and large aggregate buy volume…
This Chinese-language post collects questions about factor research and strategy implementation, but does not provide answers. Topics include adding data factors, scheduling entries and exits, evaluating and combining factors, handling collinearity,…
This Chinese-language post outlines a simple mainland China stock screen using turnover, circulating share count or market value, and a specified share price. Its initial description gives a turnover range of 3% to 12%, a circulating share cap, and a price…
The article introduces the Fama-French five-factor model as an extension of the three-factor framework. It describes market, size, book-to-market, profitability, and investment factors, and explains that multiple regression estimates a stock’s exposure to…
The document reviews quality investing as a composite of company characteristics, including profitability, growth, stability, capital structure, accounting quality, and investment. It compares reported findings for U.S. equities with cross-sectional results…
The document describes a style allocation approach that uses an illiquidity measure, called ILLIQ, to represent how much information is associated with each unit of trading value. It divides the stock universe into safer and riskier groups, then infers…
This Chinese stock-screening post proposes selecting companies below a stated market-cap ceiling that have not reported losses, excluding stocks that hit the daily upper price limit on the previous session, and ranking candidates by trading-volume strength.…
This stock-selection approach screens for companies associated with robotics, with turnover between 3% and 12%, floating market capitalization below 10 billion yuan, and year-over-year growth in net profit attributable to parent-company shareholders above…
This research summary examines whether factor crowding measures can help time factor returns or adjust multi-factor portfolio weights in Chinese equities. It constructs eight relative crowding indicators across valuation spreads, pairwise correlations,…
This practice report compares a DeepAlpha deep neural network with LightGBM in a daily A-share stock-selection strategy. Both models use the same 32 short-term price and volume factors and five-year training sample. The portfolio buys the ten highest-ranked…
This proposed screen targets Shenzhen main-board stocks with a price-to-earnings ratio from 0 to 29.01 and a price-to-book ratio from 0 to 3.11, alongside a 9:25 a.m. gain below 6% and a reported increase in holdings above 5%. The article interprets the flow…
This research summary describes two equity factors, jump beta and continuous beta, constructed from five-minute market data over the prior year. It reports that both factors showed stock-selection power across sample universes, including after industry…
This Chinese-language article describes a workflow for turning intraday trading data into daily stock-selection factors and using those factors in analysis and strategy development. Its example is a large-order-driven price-rise factor, alongside other…
This research summary argues that conventional momentum is a weak alpha signal in the Chinese stock market and proposes rebuilding it from intraday returns. The approach divides each trading day’s price change into five time segments, then recombines the…
This research summary outlines a monthly tactical framework for rotating among Chinese A-share industries. It combines two approaches: time-series timing based on industry classification, business-cycle indicators, fundamental forecasts, valuation…
The document proposes a Chinese equities screen for companies classified in the metaverse sector. Its initial conditions combine positive recent price change with year-over-year growth in net profit attributable to parent-company shareholders above 20% and…
This Chinese-language research note analyzes recent trading value as a liquidity factor for stock selection. It describes changing the evaluation horizon to five-day returns, excluding stocks at their daily upper price limit to reflect execution difficulty…