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 document presents two factor-based approaches to managed futures (CTA) investing. The first aims to time exposure to CTA strategies across changing market and macroeconomic conditions, using indicators from both technical and fundamental perspectives.…
This note describes a simple Chinese equity screen for companies classified in the metaverse industry. It selects stocks with a positive recent return and circulating market capitalization above 10 billion yuan, favoring larger companies by size. It sketches…
This research summary compares industry-level signals built from risk-adjusted returns and moving averages. It reports tests of Jensen’s alpha, Sharpe, Treynor, and Calmar measures across different lookback periods. The six-month Jensen measure behaved as a…
This note describes several equity factors built from the distribution of individual trade values within minute bars. It uses distribution statistics such as quantiles, dispersion, skewness, and kurtosis, and examines correlations between trade value and…
The article describes a Chinese equity screen combining a reported daily increase in investor holdings above 5%, free-float market capitalization between 5 billion and 10 billion yuan, total market capitalization below 10 billion yuan, and a requirement that…
This research summary describes stock-selection factors built from Chinese public mutual-fund holdings. Because quarterly reports disclose only the largest positions and holdings data arrive infrequently, the study fills out recent quarterly holdings using…
This forum post raises a replication problem involving a high-frequency stock return-variance factor described in a Haitong research report. The author says they implemented the report's first two calculation methods in SQL, but obtained results on a very…
This proposed equity screen combines capital-flow ranking, recent limit-up activity, and revenue growth. It looks for stocks with strong fund inflows, more than two limit-up days within ten days, and 2021 revenue exceeding 2018 revenue by a stated multiple.…
This stock screen combines three filters: market capitalization below 10 billion yuan, no reported losses, and a 2019 dividend payout ratio above 25%. It ranks candidates by capital inflow, initially proposing the top 100; its optimization section suggests…
This stock selection idea combines a trading range filter with a profitability screen and a MACD condition. It seeks shares whose high-to-low price range exceeds one, whose return on equity has stayed above 15% for five years, and whose MACD reading from two…
The document presents factor-category weighting as a simple neural-network problem. Gradient-based optimization can learn both the weights within categories and the weights across categories from cross-sectional observations. Under certain conditions,…
This report analyzes Chinese active equity funds using Fama-French and Treynor-Mazuy models to separate market timing, stock selection, and style allocation. It reports that positive stock-selection ability was more common than persistent market-timing…
The article introduces factor investing as portfolio construction based on characteristics associated with differences in risk and return. It outlines the development from the CAPM to the Fama–French three-factor and five-factor models, then distinguishes…
This stock screen combines three conditions for Chinese A-shares: a 14-period RSI below 65, parent-company net profit growth between 20% and 100%, and a 20-day moving average above the 120-day average. The intended selection is profitable-growth companies…
This report summary reviews stock-selection factors derived from individual trade records, including large-buy value share, buy-order concentration, intraday aggressive-buy activity, and informed trading near the close. It reports that orthogonalized factors…
This Chinese stock screen combines liquidity, earnings growth, and price-trend conditions. It selects shares with turnover between 3% and 12%, parent-company net profit growth above 20% and no more than 100%, and at least five moving averages meeting the…
This Chinese stock-screening note selects shares using turnover, tradable share count, and tradable market value. Its stated screen requires turnover between 3% and 12%, a circulating share count no greater than 5.5 billion, and circulating market value…
This post outlines a Chinese equity screen requiring daily price amplitude above a threshold, circulating market capitalization above a stated floor, and a 2019 dividend ratio above a specified level. It frames the filters as a way to combine trading…
This proposed equity screen selects stocks with an intraday high-low range above 1% of the opening price, a dividend yield above 25% attributed to 2019, and a positive measure of institutional or main-fund direction. The accompanying examples calculate range…
The post proposes a Chinese equity screen combining a daily price range threshold, a one-day decline bounded between roughly four and five percent, and revenue growth: 2021 revenue must exceed 2018 revenue by more than a stated ratio. Its example Python code…
This proposed A-share screen combines turnover between 3% and 12%, market capitalization below 10 billion yuan, positive income, and a price-to-book ratio below one. The article frames the idea around selecting profitable, smaller companies with low book…
This research note examines whether order book data can add stock selection information beyond factors derived from executed trades. It proposes three measures based on changes in net buy orders: the average rate of change, its volatility, and its skewness.…
This overview describes a commodity futures CTA strategy that ranks contracts using a combined score. It considers technical signals—cross-sectional momentum, volatility, open-interest changes, and term structure—alongside macroeconomic measures including…
This excerpt summarizes a two-week review of fundamental quantitative sector allocation and ETF rotation recommendations in China. It compares recommended overweight, benchmark-weight, and underweight industries with the broad Wind All A index, reporting…