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 research summary discusses how the balance between upward and downward stock volatility may help explain differences in future returns across stocks. It defines Relative Signed Jump Variation (RSJ) by taking the difference between upside and downside…
This overview introduces common stock-selection factors and gives formulas for valuation, momentum, quality, company size, and volatility. It describes price-to-earnings and price-to-book ratios, a twelve-month price comparison, return on equity, market…
This factor research note proposes a general method for designing trading factors by dividing a target variable into informative parts and recombining or transforming them. It identifies three elements: an additive object to split, a discriminating variable…
This overview explains how a stock-selection model can combine several signals to rank securities or construct a portfolio. It surveys market and systematic-risk measures, valuation ratios, growth and profitability metrics, momentum or reversal, trading…
This Chinese strategy note describes turning discretionary stock-screening rules into Boolean model features for a CNN classifier. The proposed universe favors companies with positive profitability and valuation measures, short-term strength, positive…
This brief presentation listing outlines a toolkit for high-frequency factor research. Its workflow covers fast calculation of historical factor values and storage, routine batch updates, adding factors to a research database, factor analysis, and rapid…
The document examines how the relationship between price-to-book valuation and expected return on equity can help assess expected earnings revision factors. A mathematical derivation motivates a linear relationship between log price-to-book and expected ROE;…
This research note describes a stock-selection factor built from the relationship between intraday changes in net buy orders and high-frequency returns. Net buy-order changes serve as a proxy for shifts in investor buying intent, while returns represent…
This Chinese A-share research summary examines airline stocks against the CSI 300 and proposes a fundamental timing and stock-selection model. It characterizes the sector as high beta and reports that relative performance has tended to vary by quarter, with…
This report proposes using public mutual-fund holdings in Chinese equities to build portfolios in two stages. First, it selects funds by Sharpe ratio and rebalances the selected group quarterly. Next, within those funds' ten largest holdings, it identifies…
This document outlines a Chinese equity screen combining daily price movement, company size, and earnings growth. It selects stocks with an intraday range of at least 1%, a circulating market value above 10 billion yuan, and year-over-year growth in net…
This short-term stock screen combines a technical condition, a fundamental growth filter, and a buying-pressure measure. It selects shares with an RSI below 65, year-over-year growth in net profit attributable to parent-company shareholders above 20% and no…
The article examines whether alternative equity weighting strategies outperform market capitalization weighting because of factor tilts or because they capture diversification return. It defines diversification return as the difference between a portfolio’s…
This notebook creates a small synthetic price panel and a date-indexed factor with missing observations, then prepares them for Alphalens. It assigns assets to groups and uses a utility function to combine factor values with forward returns over selected…
This research review examines why the traditional book-to-price value factor underperformed growth stocks over an extended period. It argues that book value misses internally developed intangibles such as software, brands, research, and customer…
The document describes a stock screen for beverage and alcohol companies. It combines a turnover range, an industry classification, a market-cap limit, and positive profitability. The accompanying examples show indicator-style conditions and a Python…
The document shows a stock-ranking workflow that derives 30-day and 90-day returns, ranks securities cross-sectionally, filters the universe, and creates a forward-return label for model training. A StockRanker module trains on historical data and predicts…
This discussion presents a daily Chinese A-share small-cap strategy that filters stocks by listing age, valuation, and turnover rank, sorts the candidates by market capitalization, and targets a basket of twenty names. Its rebalance handler identifies…
The article describes a stock selection experiment in which a machine learning model used only days since listing. Its reported backtest showed positive returns, though with high volatility. The authors attribute performance partly to a rising market during…
This Chinese-language article outlines a six-step process for developing stock selection rules: find an idea, define its logic, run an initial backtest, tune parameters, check for overfitting, and select strategies for combination. Its example setups look…
This study summary examines active-trading (ACT) factors in Chinese equities, which distinguish aggressive from passive executions and group activity by trade size. It argues that the undivided ACT factor has weak stock-selection power, then splits…
The report studies how equity factors behave across groups of A-share stocks sorted by price amplitude, using ten groups from lower to higher amplitude. It reports that price and volume factor effectiveness rises as amplitude increases, while fundamental…
This research summary explores stock-selection signals built from Level 2, trade-by-trade data. It classifies trades by order size and direction, then constructs measures such as the share of trading represented by different order categories and net buying…
This report summary presents a factor model for ranking managers of Chinese public equity and equity-oriented hybrid funds. It builds a manager-level investment index by weighting the funds each manager oversees by fund size, then evaluates candidate…