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.
22,592 documents
This Chinese stock-selection proposal filters for turnover between 3% and 12%, a rising DEA signal, and at least one daily gain of 10% or more during the previous 25 trading sessions. The article presents these conditions as a combination of trading…
This proposed Chinese equity screen combines three conditions: at least five moving averages clustered near the closing price, floating market capitalization above 200 million, and more than two limit-up sessions within ten trading days. The article…
This stock screen combines daily price amplitude and a controlling-shareholder measure with valuation limits for Shenzhen main-board shares. It selects stocks with amplitude above 1, a stated control measure above 21, price-to-earnings ratios from 0 to…
This stock-selection rule screens for main-board shares with turnover between 3% and 12%, a daily gain above 1%, and a reversal-style candle condition. The stated pattern requires the current open to exceed the prior close while the current close falls below…
This documentation explains formulaic alpha factors: signals represented as mathematical expressions that can be computed from market data. It uses MACD as an example, defining the signal from the difference between short- and long-period exponential moving…
This strategy ranks U.S. stocks by return on assets (ROA) separately within larger- and smaller-capitalization groups. ROA is defined using quarterly income before extraordinary items divided by assets from the prior quarter. Within each size group, it buys…
This brief response addresses preprocessing for deep-learning models applied to stock data, including Boolean values and infinite observations. Its direct recommendation for infinities is to remove them. For broader feature preparation, it lists outlier…
The post describes a Chinese equity screening rule combining a 14-period RSI below 65, a specified range for tradable market capitalization, and a share price below 12. When at least five stocks meet the filters, the example selection function sorts…
This report compares AdaBoost, gradient boosting decision trees, and XGBoost as tools for selecting Chinese equities from factor data. Its workflow covers feature and label preparation, preprocessing, in-sample fitting, cross-validation, and out-of-sample…
This note shows how to construct a simple stock relative-return factor using a precomputed Chinese equity dataset. It identifies one field as each stock’s daily return and another as the CSI 300 index return, then defines relative return as the stock return…
This Chinese A-share screening idea combines three filters: daily price amplitude above a threshold, a minimum time since listing, and a MACD condition above the indicator’s zero axis. The article explains that amplitude is calculated from the day’s high and…
This post outlines a Chinese stock screen for companies classified in the metaverse sector. It limits eligible stocks to those with circulating shares at or below 5.5 billion and excludes stocks that reached the upper price limit on the prior trading day. It…
This note describes a Chinese A-share screening rule for Shenzhen Main Board stocks. It combines daily amplitude above 1%, a reversal or engulfing-style signal, and positive price-to-earnings and price-to-book ratios below 29.01 and 3.11, respectively. The…
This study applies a factor-timing framework from a 2019 paper to China A-share data. It parameterizes factor weights using external variables and compares two approaches based on where the information enters: a time-series model and a cross-sectional model.…
This post describes a Chinese equity selection screen with three filters: price amplitude above 1%, a ten-day price gain greater than zero but below 35%, and circulating market capitalization between 5 billion and 10 billion yuan. Its accompanying Python…
This post describes a stock screen requiring a daily price range greater than 1%, a trading date in 2021, and float market capitalization above 10 billion yuan. It presents these conditions as a way to identify higher-volatility shares while limiting the…
This Chinese-language post describes an equity screening rule using RSI below 65, a three-candle pattern described as three consecutive down candles, and prior-day turnover above 8%. It frames RSI and the candle sequence as signs of weakness, while high…
This Chinese equity selection rule filters stocks by trading activity, prior-day leaderboard appearance, and the latest daily price change. It seeks names with turnover between 3% and 12%, a positive leaderboard flag on the preceding day, and a daily return…
This report evaluates the Shanghai 180 index and the Hua An Shanghai 180 ETF. It describes an index weighted heavily toward financial companies and food and beverage firms, with large, liquid constituents. The report characterizes its recent one-, three-,…
This Chinese stock-screening post describes a three-part selection rule: rank stocks by volume ratio and keep the top 100, require weekly MACD to be above zero, and exclude stocks whose gain at 9:25 is 6% or more. The author interprets the filters as…
This brief strategy description selects the 30 stocks with the smallest market capitalizations and allocates equal weights to them. It rebalances on the first trading day of each month and excludes ST-designated shares, the STAR Market, and the Beijing Stock…
This post outlines a Chinese A-share selection rule combining a technical indicator, earnings growth, and a measure described as previous-day major-holder control. Candidates must have a 14-period RSI below 65 and parent-company net profit growth above 20%…
This Chinese-language post describes a stock screen for companies classified in the metaverse sector. It selects shares trading above their five-day moving average and with a volume ratio above 1.5 but below 6. The post defines the ratio as current volume…
This strategy ranks the full Chinese A-share universe using two cross-sectional signals: circulating market capitalization and five-day price momentum. It ranks each factor, adds the scores, and selects the highest-ranked 50 stocks. The portfolio assigns…