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 Chinese-language research summary describes a stock-selection factor built from quarterly profitability data. It defines a trend measure as the sensitivity of profitability to time in a linear regression, with separate versions based on…
The document presents a Chinese equity screen combining a turnover ratio from 3% to 12%, appearance on the prior day’s 龙虎榜 (a public ranking of notable trading activity), and a dividend ratio above 25% for 2019. It interprets turnover as a liquidity measure,…
The post outlines a Chinese stock screening idea combining a large price amplitude, a three-session limit-up sequence on the prior day, a market capitalization ceiling, and positive earnings. It proposes tightening the amplitude threshold and checking…
The article outlines an A-share stock selection screen combining turnover, company size, profitability, and past price-limit events. It selects shares with turnover between 3% and 12%, market capitalization below 10 billion yuan, no reported loss, and at…
This post describes a Chinese equity screen combining daily price amplitude, dividend yield, and a large-order net-flow ranking. It presents the factors as signals for volatility, company profitability, and market interest, then shows example implementations…
This article examines whether financial factors such as value, size, profitability, investment, and momentum can be timed using predictive signals. It groups candidate signals into financial conditions, economic conditions, investor sentiment, factor…
The post proposes a stock screen that combines a recent increase in institutional buying, weekly MACD above its zero line, and a high historical dividend payout ratio. It interprets the buying measure as evidence of institutional interest, weekly MACD as a…
This overview surveys recurring problems in quantitative trading, including unreliable or incomplete data, model risk, slippage and fees, parameter selection, real-time monitoring, and processing speed. It also discusses choosing machine-learning methods and…
This post describes a stock screen pairing a minimum daily trading range with return on equity above a threshold for five consecutive years and at least one large one-day gain during a recent trading window. The intended combination seeks companies with…
This April 2020 market note combines valuation, trading activity, sentiment, sector flows, and style factor monitoring to assess Chinese equities. It describes subdued market turnover and relatively low overall valuations, while agriculture-related stocks…
This review of factor performance during the 2018–2020 quant crisis examines why diversified equity strategies struggled. It analyzes standard size, value, investment, profitability, and momentum factors, alongside portfolios formed by sorting stocks on size…
This report presents a three-layer fundamental quant framework: macro indicators and scenario analysis, sector-level earnings and valuation measures, and portfolio strategies. Its macro view combines growth, monetary and credit conditions, and inventory…
This post describes a stock screen that combines at least five overlapping moving averages, a share price below a stated ceiling, and revenue growth between two fiscal years. The intended rationale is to find stocks with clustered trend measures and a…
The post proposes a Chinese equity screen using turnover between 3% and 12%, a positive return over ten days below 35%, and a dividend payout ratio above 25% for 2019. It says to select stocks before 10 a.m. and presents the dividend filter as a way to…
This report excerpt reviews several Chinese equity strategies for the week ending around July 19, 2020. It says valuation and quality factors performed relatively well while momentum weakened. The CSI 300 and CSI 500 enhanced portfolios both declined for the…
This post outlines a Chinese A-share screen combining membership in a metaverse-related category with a turnover-based condition, a technical signal, market-cap ranking, and a valuation filter using PEG. It also sketches a Python workflow that retrieves…
The document describes a framework for deciding whether a candidate multifactor strategy adds value alongside a portfolio of smart beta exposures. It models each advanced beta as a combination of exposures to a small set of investable “elementary” factors,…
The post proposes a Chinese equity screen for beverage and alcohol import-export companies, selecting stocks with turnover between 3% and 12% and shareholder equity above 200 million. It gives example platform formulas and Python references, including…
This study examines how stock volatility relates to reversal and other factor returns in China’s A-share market, controlling for market capitalization and industry effects. It reports that stocks with weaker past returns tended to outperform later across…
The article reviews research linking firms’ incentives to manage investor expectations with earnings announcement premiums and seasonal stock returns. It builds an ex ante expectation management incentive score from analyst coverage and institutional…
This proposed A-share stock screen combines a 14-period RSI below 65 with parent-company net profit growth above 20% and at most 100%, plus a daily price change between -5% and 2.6%. It presents the filters as a mix of technical, fundamental, and market…
This study builds a convertible-bond strategy that separates bonds into equity-like, balanced, and bond-like groups using parity premium relative to bond value. It models each bond as a floor component plus option time value, then examines where factor…
This research proposes treating convertible bonds differently according to whether they are bond-like, balanced, or equity-like, classified by the premium of parity value over bond value. It explains a valuation decomposition in which a bond floor or…
This document outlines a two-stage workflow for calculating Alpha101 factors. First, it reads daily stock data, derives base series such as returns and VWAP, and computes time-series intermediate variables for storage. Later, factor construction retrieves…