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 event page outlines a presentation on moving from discovering individual factors to designing their portfolio weights. It identifies linear and nonlinear combinations and ICIR-based weighting as methods, with attention to their underlying rationale and…
These release notes describe changes across versions of the VeighNa trading framework. For quantitative research, notable updates include a cross-sectional percentile ranking function, revised factor and signal performance analysis, an added VWAP matching…
This summary compares two research reports on protecting portfolios during market stress: one published before a major volatility episode and another written afterward. It frames their comparison around how investors assess defensive strategies before a…
The report describes applying OpenFE, an enumerate-and-filter framework, to discover interpretable fundamental factors from Chinese companies’ balance sheets, income statements, and cash-flow statements. It first removes fields with substantial missing data,…
This research summary describes a multi-factor approach to selecting Chinese convertible bonds. It treats each bond’s value as a combination of straight-bond value and embedded option value, and examines how bond returns relate to the underlying stock. The…
This overview defines factors as common drivers of security returns and distinguishes systematic factor exposure from asset-specific risk. It traces the move from the market-only CAPM to multi-factor explanations such as the Fama–French market, size, and…
This proposed equity screen combines a price-range threshold, a reversal or engulfing-style pattern, and a company-quality filter. The document suggests assessing company quality through market position, management, industry outlook, and financial condition,…
The document offers a short framework for researching technology companies. It suggests looking for businesses with structural growth opportunities, financial resilience, and models that can scale. It also identifies revenue growth, customer concentration,…
This Chinese stock-selection post combines three filters: daily amplitude above 1, large-order net volume above 0.05 for at least three consecutive days, and return on equity above 15% for five consecutive years. It presents the combination as a way to pair…
This Chinese equity screening proposal combines three criteria: at least five moving averages converging, a high rank for net large-order volume, and a dividend payout ratio above 25% in 2019. The post frames moving-average convergence as a possible…
This strategy ranks country exchange-traded funds by estimated market beta, measured against a U.S. equity index using a rolling year of daily prices. Each month, it divides the available funds around the median beta, going long the lower-beta group and…
This research summary examines whether inventory cycle phases can help time broad sectors and the Shanghai Composite. It describes four phases—active restocking, passive restocking, active destocking, and passive destocking—and compares qualitative phase…
This post outlines a Chinese stock-selection approach that ranks stocks by a capital-strength measure, favors opening prices near the 10-day moving average, and filters for a 2019 dividend payout ratio above 25%. It suggests using measures such as turnover…
This Chinese stock screening post describes a rules-based selection method using turnover between 3% and 12%, an opening price near the 10-day moving average, and a historical dividend payout ratio above 25%. The headline instead mentions a threshold above…
This stock-screening idea ranks shares by a fund-strength measure, then filters for a dividend ratio above the stated threshold for 2019 and a 20-day moving average above the 120-day average. The page describes fund strength as potentially drawing on…
This Chinese Q&A discusses basic factor research and strategy refinement. It recommends using a correlation calculation to compare factors and gives rough absolute-correlation bands for weak and strong relationships. It also suggests tracking factor…
This research note develops an equity factor from intraday changes in volatility, which it treats as uncertainty about volatility. Using rolling five-minute windows of returns and volatility, it identifies periods when this uncertainty is elevated. It then…
This note proposes screening stocks by a price-range condition, a price below a stated threshold, and positive institutional participation. Its narrative describes the range and price as technical filters and institutional activity as a sentiment signal. It…
This note describes an A-share stock screen combining technical, trading-activity, and valuation conditions. It selects stocks with RSI below 65, an external-to-internal trading volume ratio above 1.3, and specified price-to-earnings and price-to-book…
This post proposes screening Chinese stocks with a 14-period RSI below 65, membership in a beverage and alcohol import-export industry category, a robot-related concept classification, and circulating market capitalization below 10 billion yuan. It presents…
This Chinese stock-screening note combines three ranked or threshold-based characteristics: capital inflow strength, tradable market capitalization above 2 billion, and a dividend ratio above 25% for 2019. Its described ranking rules select stocks near the…
This short quantitative research answer describes a volume-based factor built from two choices: the number of days used to average volume and the number of observations used to measure volatility. Its notation indicates applying a standard deviation to…
This study examines six smart beta factors in Chinese equities: size, value, low volatility, momentum, quality, and dividends. Its reported sample runs from July 2006 through November 2018. The summary finds differing absolute and risk-adjusted performance…
This research summary explores technical factors built from turnover, illiquidity, and combined price-volume information in the CSI 500 universe. It considers turnover stability, turnover variation, abnormal turnover, several illiquidity measures, On-Balance…