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 note proposes a two-stage way to use public mutual-fund holdings. First, it selects funds by Sharpe ratio and rebalances the fund basket quarterly. Next, within those funds’ ten largest holdings, it selects stocks with the highest relative…
The document proposes screening Chinese A shares for stocks with a price amplitude above 1, a 2019 dividend payout ratio above 25%, a robotics industry classification, and circulating market capitalization below 10 billion yuan. It frames the criteria as a…
The document presents a monthly long-short residual-momentum strategy for U.S. equities. It describes ranking stocks by risk-adjusted residual returns over the prior 12 months, skipping the latest month, and buying the strongest decile while shorting the…
This article introduces dense neural networks and backpropagation, then outlines an A-share stock selection experiment. A DNN uses connected layers of neurons; training sends predictions forward and propagates errors backward to update weights. The example…
This note describes an A-share screening rule for stocks in the metaverse theme. Its stated final criteria combine prior-day turnover above 8%, a price change from −5% to 2.6%, and trailing price-to-earnings below 50. It also gives a sample implementation…
This report studies whether active-buying measures derived from high-frequency trading data can help rank industries for rotation. It constructs buy-share, buy-intensity, net-buy-share, and net-buy-intensity factors using volume and turnover data from the…
This brief note identifies two errors in the conditions used by a stock strategy example. The first concerns a year-over-year net profit growth factor: the intended filter selects positive growth rather than negative growth. The second concerns position…
This 2020 research summary compares valuations and return drivers across large- and small-cap Chinese equity indexes. It reports that small-cap valuations were near historical medians while large-cap indexes, including the SSE 50 and CSI 100, were near…
This Chinese equity screen looks for non-ST main-board stocks with turnover between 3% and 12%, a daily gain greater than 1%, and a positive price-to-earnings ratio. The activity and price conditions aim to identify shares with market participation and…
This research summary reviews academic momentum-factor development and reports empirical findings for China’s A-share market. It says traditional momentum measures there exhibit reversal, with stronger reversal over shorter formation windows, and that…
This report excerpt discusses forecasting equity factor returns as commonly used stock-selection factors fluctuate. It proposes improving and simplifying an earlier conditional-expectation timing model by framing factor timing as a regression-based…
This research note studies post-earnings-announcement drift in Chinese A-shares: stocks reporting results above expectations may continue to earn positive abnormal returns, while those below expectations may lag. It estimates expected net profit and revenue…
The report adapts William O’Neil’s base-pattern and CANSLIM ideas to the Chinese A-share market. It combines price formations such as cup-with-handle and double bottoms with company growth measures, relative price strength, trading activity, and…
This research summary discusses stock-selection factors built from analyst consensus estimates for Chinese A-shares. It notes that analyst estimates provide information beyond company financial statements and trading data, while also warning that estimates…
The document explains how performance attribution can reveal the sources of a portfolio’s returns, even when portfolios have similar styles and overall results. It outlines three approaches: style analysis, which uses portfolio and benchmark returns to infer…
This Chinese stock-selection post proposes screening for stocks with MACD above zero, favorable company characteristics, and a closing price above the prior day's low. Its explanation frames positive MACD and the price condition as technical signs of…
This article presents a quantitative interpretation of Benjamin Graham’s enterprise-owner investment approach and a version adjusted for Chinese stocks. The original criteria focus on liquidity relative to current liabilities, limits on debt, a history of…
The document translates Benjamin Graham’s enterprise-owner approach into quantitative tests and then proposes a version adapted to Chinese equities. The original framework emphasizes liquidity, manageable debt, a record of profits and cash dividends,…
This Chinese-language research summary studies stock-selection signals from large and small investor order flows. It reports that the two flows are negatively related and that normalized net flows have opposite associations with subsequent returns:…
This Chinese-language post describes a stock screen for companies classified in the metaverse industry. Its stated selection criteria require a volume ratio above 1.5 and below 6, alongside a turnover rate above 2% and below 9%. The rationale is to seek…
The study estimates a fund’s factor exposure from its net asset value returns and factor return series, aiming to provide more timely exposure tracking than holdings-based estimates from delayed periodic reports. It trains an LSTM on features describing the…
This strategy ranks the mainland China A-share universe using company size and a price momentum measure. It removes suspended and specially treated shares, calculates a market-cap rank and the ratio of 20-day to 60-day average closing prices, and adds the…
The strategy ranks a multi asset universe using two momentum horizons and a valuation measure. It assigns equal portions of the combined score to 12 month and one month momentum, and a larger portion to value. Stock valuation is represented by earnings…
This report outlines five high frequency stock factors based on intraday price behavior, price and volume changes, returns, relationships with the market, and sequences of trades. Its main method identifies stocks whose intraday returns relative to the…