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 post describes a Chinese equity selection rule that screens for companies classified in the metaverse sector, with prior-day actual turnover between 3% and 28%, and a nonempty name for an outstanding convertible bond. The stated interpretation is that…
The article describes a Chinese equity screen for robot-concept stocks. It selects shares with turnover between 3% and 12%, a circulating market value below the stated threshold, and more than two limit-up sessions within a ten-day window. It then proposes…
This stock-selection proposal combines three filters: turnover between 3% and 12%, year-over-year growth in net profit attributable to the parent company above 20% and no more than 100%, and shareholder ownership concentration above 70%. The document…
This proposed A-share screen combines a daily price-move condition, the presence of a nonempty name for an outstanding convertible bond, and turnover between 3% and 12%. The article presents the combination as a way to find stocks with movement and moderate…
This document outlines a Chinese A-share screening idea focused on companies in the metaverse sector. It combines a circulating-share limit of no more than 5.5 billion shares with a “rising bottom” price pattern: after a rise and pullback, the stock forms a…
This proposed Chinese stock screen combines a turnover range of three to twelve percent, a reversal pattern described as a rebound after a decline, and at least five overlapping moving averages. The rationale is that clustered averages may indicate a…
This stock screen focuses on companies classified in the metaverse theme that recorded at least one limit-up day within the previous twenty-five days and have a positive return on the current day. The stated rationale is to identify recent strength and…
The document shows a workflow for calculating daily industry-level average price-to-earnings ratios for Chinese stocks. It queries industry membership and valuation data, groups constituents by date and industry, filters valuation records to each group,…
The proposed A-share selection rule filters for stocks with turnover between 3% and 12%, market capitalization below 10 billion yuan, and no reported losses. It then selects stocks using the previous day's turnover multiplied by the ratio of current auction…
This post outlines a stock selection screen that ranks shares by trading activity and market attention, while requiring the 30-day moving average to trend upward. It suggests using turnover or trading value to gauge capital activity, and market…
The document summarizes a study of stock price movement prediction in China’s A-share market. It describes combining five data types: historical trading data, technical indicators, company announcements, news, and Baidu search activity. The researchers…
The screening idea selects stocks priced below 12 yuan whose 30-day moving average is rising and whose price is near at least five moving averages. It frames the overlap of averages as a possible sign of support and upside potential. The stated selection…
The report presents a Chinese equity timing approach that combines a prior model based on limit-move breadth with a price-volume confirmation model. Its premise is that the two systems capture different long-entry periods: the combined model aims to retain…
This document describes a Chinese equities screen using a daily turnover rate between 3% and 12%, a positive product of price change and large-order net flow, and return on equity above 15% in each of the prior five years. It presents the rule as a…
This post describes an equity screen for stocks in the metaverse theme. It selects names whose latest price is above the 250-day moving average and whose 20-day moving average is above the 120-day moving average. The first condition places price above a…
The document presents a Chinese equities screening rule combining daily price range, a low KDJ reading, and a recent three-session limit-up streak. Its stated aim is to find volatile stocks whose indicator reading is low while they remain active short-term…
This post proposes screening equities for a daily price range of at least one unit, strong return on equity across five years, and a three-candle morning star pattern. The described pattern consists of an advancing candle, a small indecisive or lower candle,…
This Chinese-language post outlines an equity screen that combines daily price movement with company profitability and a short-term price trend. Its initial rules require a price range of at least one unit, return on equity above 15% for five consecutive…
This Chinese stock-screening post combines a price-amplitude filter with a measure based on the prior day’s turnover and the ratio of current auction volume to prior volume. It selects stocks where that combined measure falls between 0.5 and 2, and which…
The document describes research that turns intraday stock volume data into factors for stock selection. It presents seven conventional volume distribution factors and six specialized ones. The methods include measuring minute volume through bucket entropy…
This overview introduces several machine learning approaches used in stock strategies: deep neural networks, convolutional networks, LSTMs, gradient-boosted trees, and a ranking model built around GBDT. It briefly describes what each model can learn or…
The document presents a Chinese equity screening rule that combines trading activity, short-term price location, and a multi-year profitability filter. It selects stocks with turnover between 3% and 12%, an opening price within 5% of the 10-day moving…
This proposed stock screen selects main-board Chinese shares with RSI below 65, a daily gain above 1%, and at least two limit-up moves during the prior 500 days. The article interprets the RSI condition as indicating potential rebound room, the positive…
This review summarizes research on how company news coverage relates to investment efficiency in US firms. The study measures inefficient investment as the difference between actual investment and an expected level based on sales growth, separating…