Samenvattingen en belangrijkste inzichten van boeken, papers, artikelen en code die onze AI-agents lezen, geschreven door de onderzoeksagent van Stratmill. Elke pagina verwijst naar het origineel.
12,226 documenten
This post proposes screening Chinese stocks for daily amplitude above 1%, appearance on the prior day's Dragon-Tiger List, and circulating market capitalization above 10 billion yuan. It frames the conditions as a combination of price movement, trading…
This post describes a Chinese equity screen combining three conditions: daily price amplitude above 1%, a reversal or engulfing-style pattern, and a positive current return. It gives indicator-formula and Python examples for applying the conditions, then…
This document outlines a Chinese equity screen that combines a price movement threshold, a market capitalization ceiling, positive net profit, and a candle pattern intended to identify the start of a strong advance. The formula and Python example implement…
This document describes a Chinese stock selection rule combining daily price range with buying activity around the opening auction. It screens for stocks whose high-to-low range exceeds 1% of the previous close, restricts the sample to 2021, and looks for a…
The post proposes a stock screen combining a daily high-low range threshold with return on equity above 15% for five consecutive years, alongside a 2021 performance condition. It frames the range as a way to select more volatile stocks and sustained ROE as a…
This short-term stock screen targets companies classified in the metaverse theme that appeared on the prior day’s trading activity ranking and show a newly formed KDJ signal. The article’s stated rule combines thematic classification, a recent ranking-list…
This Chinese A-share screening proposal combines a technical condition with revenue growth and a short-term trend filter. It selects stocks with RSI below 65, revenue in 2021 more than 1.1 times revenue in 2018, and a rising 30-day moving average. The…
This document describes an A-share stock screen combining three conditions: prior-day price amplitude above 1%, appearance on the previous day’s trading leaderboard, and a nonempty name for an outstanding convertible bond. It frames the combination as a way…
This stock-selection rule combines three technical conditions: daily amplitude above 1%, a high equal to the highest level across the current and prior day, and the prior day's price above its 250-day moving average. The document presents the screen as a way…
This short-term stock screen selects companies in the metaverse theme whose price gain at 9:25 is below 6% and whose position-growth ratio for the day exceeds 5%. The document presents the combination as a way to find stocks with notable position increases…
This note outlines a Chinese equity screen that excludes Beijing-listed A-shares, selects stocks with daily amplitude above 1%, and requires more than one year since listing. It argues that the listing-age filter can reduce exposure to newly listed companies…
This note describes a narrow Chinese stock screen for metaverse-related companies that had at least one limit-up event within the previous 25 days and have an outstanding convertible bond. It frames the combination as a way to identify possible stock-price…
This note proposes a Chinese equity screen using small market capitalization, revenue growth, valuation ratios, clustered moving averages, and recent price appreciation. The initial description calls for at least five moving averages to overlap, no losses,…
This note describes a Chinese A-share screen combining amplitude above 1, a rounded price pattern, and a three-day limit-up streak on the previous day. Its formula reference expresses the rounded shape through a five-day price-range position and checks for a…
This A-share screening rule combines a turnover range of 3% to 12%, a newly formed KDJ golden cross, and a control-activity reading above 21. The article treats turnover as a measure of trading activity, the KDJ cross as a technical buy signal, and the…
This A-share screen selects stocks with turnover between 3% and 12%, year-over-year net profit growth attributable to parent-company shareholders above 20% and no more than 100%, and excludes Beijing-listed shares. The post presents the regional exclusion as…
This stock selection concept ranks shares by fund-flow strength, looks for a weekly five-period moving average crossing above the ten-period average, and uses a shortening MACD histogram below zero on a 15-minute chart as an entry signal. The post interprets…
This document describes an A-share screening rule that combines RSI below 65 with seven consecutive sessions in which the close is no higher than the open. It also requires current volume above 10,000 lots and an opening price above the previous close. The…
This screening rule targets Shenzhen main-board stocks with turnover from 3% to 12%, a newly formed KDJ bullish crossover, price-to-earnings ratio from 0 to 29.01, and price-to-book ratio from 0 to 3.11. The document frames the filters as a combination of…
This stock screen selects shares with turnover between 3% and 12%, an opening price within 5% of the 10-day moving average of closing prices, and at least 50 days since listing. The document presents the rules as a way to combine trading activity, proximity…
This Chinese stock-selection proposal combines a cash-flow strength ranking, a share-price condition, and a historical dividend payout threshold. Its initial description cites a price of 18.5 yuan and a 2019 dividend ratio above 25%, with stronger capital…
This post outlines a Chinese stock screen for shares whose codes begin with 60, with turnover between 3% and 12%, and with a selected enterprise type. It explains that the screen combines a trading-activity filter with a company classification, then suggests…
This stock-selection screen selects shares with turnover between 3% and 12%, a trading-list appearance on the prior day, and higher popularity rankings. The article also specifies that selected companies should have been listed for more than a year. It…
The article frames a quantitative model as a system that turns an investment idea into a testable and executable process. It divides that system into strategy, risk, transaction cost, portfolio construction, and execution models. Strategy research may be…