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
The document proposes a stock screen combining three criteria: recent price amplitude above a stated threshold, circulating market capitalization above a stated level, and a stock code beginning with 60. It frames the screen as a way to find larger,…
This A-share stock-selection proposal combines three conditions: RSI below 65, year-over-year growth in net profit attributable to parent-company shareholders within a stated positive range, and a recent two-day high condition. It presents the combination as…
This research report proposes improving a conventional stock reversal signal by splitting each stock’s recent daily returns according to average trade size. For each lookback window, it ranks days by daily turnover divided by trade count, compounds returns…
This Chinese A-share screening proposal combines a technical filter, a trading-flow condition, and a turnover range. It selects stocks with RSI below 65, positive multiplication of price change by net flow from very large orders, and turnover above 2% but…
This proposed Chinese equity screen combines three conditions: the stock's intraday high-low range exceeds one percent of its closing price, the prior session was not limit-up, and the article's external-to-internal trading measure exceeds 1.3. The author…
This A-share screening rule combines a daily high-low range greater than 1%, a newly formed KDJ crossover, and positive main-fund net inflow on the prior day. The post presents the range condition as a way to find volatile stocks, the crossover as a possible…
This A-share screening concept selects stocks with at least five converging moving averages, ranks them by individual-stock “heat,” and requires at least two limit-up sessions within the prior 500 days. The accompanying explanation interprets the…
This proposed A-share screen combines three conditions: at least five moving averages converge, the opening price is near the 10-day average, and the stock has hit the daily limit at least twice in the past 500 days. The accompanying rationale treats average…
This tutorial demonstrates a graph convolutional policy, GPM, inside a reinforcement-learning portfolio workflow. It loads historical stock features and a sector and industry graph, then reduces the graph to nodes within two hops of the selected portfolio…
This stock-selection note describes a Chinese equities screen that combines three signals: membership in the metaverse theme, positive net buying by major participants during the opening auction, and an increase in the KDJ K value. It interprets these as a…
The document outlines a Chinese A-share stock screen centered on a metaverse industry classification, elevated recent turnover, share prices above a stated threshold, larger market capitalization, and return on equity. It first presents a simpler theme,…
This post outlines a Chinese equity selection idea that ranks stocks by capital-flow strength, choosing the top 100, and filters for an opening-stage price rise below 6% at 9:25. It associates strong flow rankings with market attention and treats a limited…
This post describes a short-term Chinese equity screen using RSI below 65, an outside-volume to inside-volume ratio above 1.3, and a share-price filter. Although the headline mentions a specific price, the body shifts to a range: its example uses prices from…
This post proposes screening Chinese equities for daily price amplitude above 1, return on equity above 15% for five consecutive years, and a rounded price pattern. It presents the combination as a way to pair a volatility condition with sustained…
This Chinese-language post outlines a stock selection rule using price amplitude, relative trading volume, and return on equity. It specifies amplitude above 1%, a volume ratio between 1.5 and 6, and ROE above 15% in each of the past five years. The intended…
This Chinese-language post describes an A-share stock screen combining price amplitude, a 2019 dividend yield threshold, and a range for floating market capitalization. The intended logic selects stocks with amplitude above 1, dividend yield above 25%, and…
This BigQuant platform report investigates Beijing Stock Exchange records in the Chinese stock factors table and how they interact with a basic stock-selection query. The author queries instruments with the Beijing suffix for a single date and reports 249…
This Chinese stock-screening note combines a large-order net-flow ranking with a moving-average trend filter. It proposes ranking stocks by large-order net volume, treated as a measure of buying pressure, and keeping those whose 20-day moving average is…
This indicator description explains pivot-point analysis as a way to derive potential support and resistance levels from the prior period’s high, low, and pivot. The first support and resistance levels use the distance between the pivot and the corresponding…
This factor-monitoring summary compares Chinese equity signals over weekly, monthly, year-to-date, and one-year windows. It reports rankings for long-only absolute returns, long-short returns, information ratios, and relative strength. The factors discussed…
This post describes a stock screen for main-board shares that combines a daily turnover-rate band of 3% to 12%, a circulating market value between 5 billion and 10 billion yuan, and an additional company-type criterion chosen by the user. It gives equivalent…
This factor note defines a volume-weighted measure of a stock’s intraday relative price range. For each instrument and date, it calculates the high-low range divided by the opening price, weights that value by volume, and divides the summed weighted values…
This post outlines a Chinese stock screen for companies in a metaverse-related category, with previous-day turnover above 8% and tradable shares capped at 5.5 billion. It explains tradable float as shares available for market trading after restricted or…
This document describes a Chinese equity screening rule combining daily price range, a reversal pattern, and a recent limit-up. Its refined version looks for a range above 1%, a reversal pattern within the latest three trading days, and at least one limit-up…