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 post describes a stock screen combining a daily price condition with a profitability filter: select stocks whose intraday high-to-low range exceeds a stated threshold, whose current low is below the previous day’s low, and whose return on equity has…
This A-share screening proposal selects companies with market capitalization no greater than 10 billion yuan and no reported losses, then ranks them by capital-flow strength. The article frames the small-cap filter as a way to reduce the influence of market…
This post describes a simple stock selection screen combining a technical condition with valuation and recent price movement. It selects stocks with RSI below 65, positive price-to-earnings ratios, and a 10-day gain greater than zero but below 35%. The…
This report reviews equity factor performance, emphasizing a February 2018 snapshot and trends over a longer historical period. It compares factor information coefficients, which measure association with subsequent returns, and market neutral long-short…
This note presents an A-share stock screen that combines daily price amplitude, a specified closing price, and year-over-year growth in net profit attributable to parent-company shareholders. The stated selection criteria are amplitude above 1%, a closing…
The document summarizes research that derives two liquidity factors from high-frequency order-book data, one associated with buy orders and one with sell orders. The factors are then aggregated to monthly frequency for use in stock selection. It reports that…
This edited seminar transcript surveys a Chinese quantitative research program on deep learning, then focuses on AlphaNet, a neural approach to stock factor discovery. It frames a multi-factor process as factor generation, factor combination, and portfolio…
This research summary compares Naive Bayes, linear discriminant analysis (LDA), and quadratic discriminant analysis (QDA) as supervised methods for multi-factor stock selection. The described process extracts and preprocesses features and labels, retrains…
This screening rule selects equities with turnover between 3% and 12%, a flag indicating appearance on the prior day's exchange activity list, and a price-to-earnings ratio below 20. The stated rationale is to combine a moderate level of trading activity…
This stock selection idea combines a price range condition, sustained profitability, and a recent price high. It seeks shares whose high-to-low movement exceeds a volatility threshold, whose return on equity stayed above 15% for five consecutive years, and…
The document proposes separating sector allocation from industry selection because broad sector shifts are linked more closely to economic conditions, while industry performance depends on factors such as earnings, valuation, and capital flows. It argues…
The document summarizes research using public Northbound investor holdings and trading-flow data to build 12 factors for Chinese equities. It reports testing those factors from December 2016 through December 2019 across Northbound-held stocks, the CSI 800,…
This Chinese-language post outlines an equity screening idea that combines stocks with amplitude above a stated threshold, the five highest opening-auction amounts for the day, and a proxy for institutional buying. It gives a corresponding indicator-formula…
The document presents a proposed screen for Chinese equities that combines a daily-range condition, a dividend payout ratio above 25% for 2019, and alignment among multiple moving averages. It explains the intended rationale as combining price volatility,…
This stock screening approach combines daily price movement, recent performance, and momentum with valuation and revenue growth filters. It selects shares whose daily high-low range exceeds one percent, whose ten-day return is positive but below 35%, and…
This research summary argues that bond fund rankings based on a single historical performance measure can be distorted by differences in market style, objectives, holdings, manager skill, fund size, and risk controls. Its proposed approach narrows the…
This note argues that quantitative strategy results depend on the combination of input factors and predictive models. It says that different factors can produce substantially different backtests when paired with the same model, and that a given factor can…
This study examines whether U.S. equity mutual fund managers adjust market exposure when broad stock mispricing changes. It builds a market mispricing measure from a financing-based long-short factor, then orthogonalizes it against macroeconomic variables. A…
This note outlines a Chinese equity screen based on a price-amplitude threshold of at least 1, circulating market value of at least 10 billion yuan, and a company-type classification labeled as a high-quality enterprise. It presents the combination as a way…
The post describes a Chinese equity screen for companies classified in the metaverse theme, with a minimum stated circulating market value and average share concentration below a stated threshold. It frames the size filter as a way to focus on larger…
This factor study examines whether the share of a stock’s trading volume occurring in the opening call auction contains information useful for equity selection. It builds an opening call-auction volume proportion factor from relative volume and moving…
This research summary describes a model for estimating whether a company will meet or exceed analyst expectations in its next reporting period. Its premise is that earnings delivery has persistence: stocks that beat expectations in one period are more likely…
The report applies a modified Grinold-style decomposition to attribute equity index returns to dividend yield, nominal earnings growth, and changes in the price-to-earnings multiple. It compares major Chinese broad-market indexes and selected industry…
This brief Chinese-language post describes a stock-selection submission that adds price-to-sales and dividend-yield filters, then increases the weight assigned to dividend yield. The author says the results improved, but provides no performance figures, test…