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 report examines whether analyst expectations data can help rank industries for rotation. It groups signals into analyst coverage and forecast disagreement, the direction of earnings revisions, and the size of forecast changes. Coverage and disagreement…
This proposed A-share stock screen combines daily trading activity, market capitalization, profitability, and price change. It selects main-board companies with turnover between 3% and 12%, circulating market value below 10 billion yuan, positive earnings…
This competition update reports diagnostics for the ten highest-ranked anonymous factors and tracks a CSI 1000 enhancement portfolio. Factor profiles include average Barra style exposures and sector-level average Rank ICs, calculated from cross-sectional…
This stock-selection approach combines three filters: daily price amplitude above 1, exclusion of stocks that closed at the upper price limit on the previous day, and a 2019 dividend ratio above 25%. The accompanying explanation treats amplitude as a measure…
This study proposes adding daily risk monitoring to a traditional monthly rebalancing schedule for multi-factor equity portfolios. It tracks the portfolio’s exposure to the size factor during the month and rebalances on the next trading day when that…
This community post outlines a Chinese stock selection idea that ranks stocks by a measure called capital strength, excludes specially treated risk-warning shares, and combines recent limit-up behavior with a historical dividend payout condition. It presents…
This post outlines a Chinese stock screening idea that combines recent price amplitude, institutional participation, and circulating market value, restricted to main-board stocks. Its final stated criteria use a 15-day amplitude threshold above one,…
This example tests whether market capitalization is associated with next-day stock returns using repeated cross-sectional ordinary least squares regressions. It joins Chinese stock factor data to daily bars, calculates forward returns from the next close,…
This research summary examines the validity of mainland China Stock Connect ownership data and describes portfolio strategies built from investor holdings, sector allocations, style exposures, leading trades, and net capital flows. It reports persistent…
This post proposes a rules-based screen for Shenzhen-listed stocks. It combines an intraday amplitude threshold with an exact closing-price condition, and filters for positive trailing price-to-earnings and price-to-book ratios below specified upper bounds.…
This study builds a monthly Chinese equity factor from stock returns and volatility around intraday volume surges. It defines a surge as a minute when the increase in trading volume exceeds that stock’s daily average increase by more than one standard…
This stock screen combines a technical condition with size and company classification. It selects equities with RSI below a stated threshold and circulating market capitalization in a specified band, then considers enterprise type as an additional…
The article summarizes research on whether active mutual fund managers adjust trading to anticipated stock-picking opportunities. It defines stock-selection timing as trading more when opportunities to hold positive-alpha stocks are greater and less when…
This study compares conventional return labels with alternative labels based on information ratio and Calmar ratio for AI stock selection models. It argues that labels incorporating returns, volatility, and drawdowns across a period may convey more…
This document presents a stock-selection rule that combines turnover, year-over-year growth in net profit attributable to parent-company shareholders, and the Relative Strength Index. It keeps stocks with turnover between 3% and 12%, profit growth above 20%…
This document describes a Chinese stock screen for Shenzhen main-board listings. It combines daily turnover between 3% and 12%, an appearance on the previous day’s 龙虎榜 (a disclosure list of notable trading activity), positive price-to-earnings values up to…
The document describes a stock selection rule combining daily price range with profitability and earnings growth. It first screens for a high-low range of at least one unit, then requires return on equity to exceed 15% for five consecutive years, and finally…
This document describes a Chinese equity screening rule that combines turnover, parent-company net profit growth, and a rising 30-day moving average. It selects stocks with turnover between 3% and 12%, year-over-year profit growth above 20% and at or below…
The document describes APB, a family of cross-sectional stock factors intended to estimate buying and selling pressure from the relationship between price and trading volume. Its premise is that buying concentrated at lower prices and selling concentrated at…
This article describes a Chinese stock screen combining three conditions: price amplitude above one, rising lows, and a 2019 dividend ratio above 25%. It presents the idea as a mix of price behavior and a historical dividend measure, then gives example…
This brief Chinese-language post describes a single-factor timing experiment based on a volatility-difference approach. The author says the test was inspired by a Guosen Securities study on timing with directional volatility differences. The post provides no…
This weekly market note responds to weakening Chinese equity sentiment and increased uncertainty by reducing A-share exposure, adding interest-rate bonds and secondary bond funds, and increasing exposure to low-valuation and dividend factors. Its rationale…
This Chinese-language note outlines an equity selection screen combining price amplitude, return on equity, and a concentration measure. The initial rule calls for amplitude above one, ROE above 15% for five consecutive years, and concentration below 20%.…
This report summarizes three active Chinese equity portfolio approaches. The fund enhancement strategy uses holdings of successful active funds as a starting point, then applies quantitative selection to seek improvement over the active equity fund…