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 note describes a Chinese equity screen using an intraday range above 1%, current volume above 10,000 lots, a higher open, and a 2019 dividend ratio above 25%. It frames the rules as a combination of market activity, liquidity, opening sentiment, and…
This note describes a Chinese equity screen that selects stocks with an intraday range above 1% and a stated 2019 dividend ratio above 25%, then orders them by individual-stock heat. It presents range as a measure of price activity, the dividend condition as…
This document outlines a machine learning workflow built around feature engineering, model training, and model combination. Feature engineering includes creating, extracting, and selecting variables. It contrasts linear models, which capture linear…
The document presents price resiliency (RES), a covariance-based measure intended to capture both the price impact of liquidity shocks and how long those shocks persist. It compares returns in the first half-hour of trading with returns over the rest of the…
This brief project note reports a modification to an existing quantitative strategy: market capitalization was added to the scoring process and return on equity was removed. The author says the backtest improved after the change, but provides no performance…
This Chinese equities screen combines a turnover rate between 3% and 12%, year-over-year growth in net profit attributable to parent-company shareholders above 20% and no more than 100%, and a weekly MACD condition above zero. It presents the combination as…
This document describes a Chinese stock-selection screen combining turnover with year-over-year growth in net profit attributable to parent-company shareholders. It specifies turnover between 3% and 12%, profit growth above 20% and no more than 100%, and an…
The report introduces a Barra-style multi-factor risk and return attribution model for Chinese equities. Its central idea is to explain the returns and risks of many stocks through a smaller set of style factors, making portfolio exposures easier to analyze.…
This note describes a Chinese equity screen that combines amplitude above 1, a prior-day proxy for main-investor control, and return on equity above 15% in each of five consecutive years. The proposed logic aims to pair active price movement and recent…
This note describes a Chinese equity screen combining turnover, year-over-year net profit growth attributable to parent-company shareholders, and the ratio of external to internal trading volume. It selects stocks with turnover between 3% and 12%, profit…
This short BigQuant discussion asks whether factor analysis of a custom stock universe requires manually importing a data table. The response says custom feature data can instead be passed into the factor-analysis module, enabling analysis for a user-defined…
The document describes a China-market stock screen that selects companies in the metaverse theme, with circulating market capitalization above 10 billion yuan and a 2019 dividend payout ratio above 25%. It defines payout ratio as dividends per share relative…
This brief community post proposes adding two filters to a small-cap stock strategy: rank companies from lower to higher debt ratio and require five-year average return on equity to exceed 10%. The title advertises an annualized return of 41% and a win rate…
This explanation defines an asset’s exposure to a factor as its sensitivity to that factor’s returns. It illustrates the idea with a value factor: filter a broad A-share universe, sort stocks by price-to-earnings ratio, and form a long-short portfolio from…
This note presents a proposed screen for Shenzhen main-board shares that excludes Beijing-listed A-shares. Its initial conditions limit price-to-earnings and price-to-book ratios to stated ranges and require daily high-low amplitude above a threshold. An…
The author describes a monthly stock-selection approach that buys the ten lowest price-to-book stocks in the CSI 300 universe, then combines it with a market-timing signal based on a hidden Markov model. The starting idea is a single-factor value strategy,…
This stock-selection proposal combines three filters: a large high-low range, at least one daily gain of 10% or more in the preceding 25 trading days, and a ranking by capital or fund-flow strength. The intended effect is to find volatile stocks that have…
This research summary outlines a strategic allocation model that maps Chinese equities and bonds to underlying macroeconomic risks. It uses principal component analysis to define five factors: economic growth, interest rates, credit, term spread, and…
The document summarizes research on the disposition effect among actively managed U.S. equity mutual funds: managers may sell winning stocks too readily while holding losing stocks. It describes a measurement based on quarterly changes in reported holdings…
The document distinguishes temporary factor decay from permanent factor failure. It attributes much of the decline in a signal’s excess returns to competition: as more capital uses a factor, its alpha can shrink, while changing market styles may later…
This document outlines a screen for Shenzhen main-board stocks combining a technical condition with valuation, size, and profitability filters. Candidates must have RSI below 65, a price-to-earnings ratio between zero and 29.01, a price-to-book ratio between…
The post proposes a Chinese stock screening idea combining three conditions: reported institutional buying above five percent of volume on the latest trading day, seven consecutive declining sessions, and a 20-day moving average above the 120-day average. It…
This Chinese stock screening rule combines turnover between 3% and 12%, year-over-year growth in net profit attributable to parent shareholders above 20% and no more than 100%, and a bullish weekly MACD condition. The document treats turnover as a trading…
This Chinese-equity screening proposal combines three conditions: daily price range above 1%, a short-term moving-average relationship intended to indicate upward movement, and revenue in 2021 more than 1.1 times revenue in 2018. The stated rationale is to…