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 Chinese equities screening idea selects stocks with daily amplitude above 1, positive price-to-earnings ratios, and at least two limit-up moves in the prior 500 days. The article interprets amplitude as a sign of trading activity, positive PE as a basic…
This post outlines a historical screen for Shenzhen Main Board stocks in 2021. It selects shares with amplitude above 1, a price-to-earnings ratio from 0 to 29.01, and a price-to-book ratio from 0 to 3.11. The approach combines a basic activity filter with…
This post describes a Chinese equity screening rule that looks for stocks with an amplitude greater than 1, signs of main-force control on the previous day, and a 龙虎榜 appearance on the previous day. It frames range as a measure of activity, main-force…
This document describes an A-share stock screen combining three conditions: a 14-period RSI below 65, a positive MACD value relative to its zero line, and a gain below 6% at the 9:25 observation. The accompanying example also excludes securities flagged as…
This document describes a Chinese equity screen combining three filters: price amplitude above 1, a 2019 dividend ratio above 25%, and prior-day turnover above 8%. It presents the combination as a way to find stocks with strong recent activity and…
This post describes a simple stock-selection screen based on daily price movement. It keeps shares whose high-to-low range exceeds one percent, excludes names containing a reference to Beijing, and requires the close to be above the open. The post supplies…
This post outlines a Chinese A-share stock screen focused on the metaverse theme. It selects stocks when three bullish crossovers occur together: MACD crossing its signal line, the five-day moving average crossing the ten-day average, and the five-day…
This brief notice outlines a composite scoring framework for strategies listed in a marketplace. It assigns weights to three broad categories: performance, risk, and risk-adjusted performance. The listed performance measures are cumulative return and success…
This daily stock screen selects shares with an amplitude above 1, at least two limit-up events within 500 days, and evidence of main-force control on the prior day. The accompanying formula describes that control using main buying greater than main selling…
This Chinese stock-screening post proposes ranking shares by capital-flow strength and requiring the 9:25 opening gain to be below 6%. Its revised screening logic adds a top-100 capital-strength ranking, a price-to-earnings ratio below 20, a price-to-book…
This document proposes screening Chinese shares using turnover between 3% and 12%, a share code beginning with 60, a price-to-earnings ratio between zero and 29.01, and a price-to-book ratio no higher than 3.11. It presents the rules as a mix of trading…
This document describes a Chinese equity screen combining daily turnover, a newly formed KDJ bullish crossover, robot-related classification, and circulating market capitalization below 10 billion yuan. The turnover range is 3% to 12%. It presents the screen…
This stock selection approach combines a volatility screen, a weekly moving average crossover, and a capital flow ranking. It selects stocks with an amplitude above the stated threshold, a weekly five-period moving average crossing above the ten-period…
This post presents a Chinese stock-selection screen based on price action: select stocks with a stated price range threshold, exclude those that hit the daily price limit previously, and require the gain observed at 9:25 to remain below a stated cap. The…
This stock-screening idea combines three technical conditions: daily price amplitude above a stated threshold, a weekly five-period moving average crossing above a ten-period average, and a positive daily MACD reading. The proposed rationale is to find…
This Chinese-language post describes a daily stock screen that combines three conditions: an amplitude measure above a threshold, a change in an institutional volume-flow measure, and detection of a recent rounded upward price pattern. It says the curved…
This stock-screening strategy combines price movement, company size, profitability, and chart structure. It seeks stocks with daily range above 1%, market capitalization no greater than 10 billion yuan, positive net profit in each of the latest four…
The document outlines a Chinese equity selection rule that ranks stocks by volume ratio, then filters for a close above the Bollinger middle band but below the upper band, and a 20-day moving average above the 120-day moving average. The authors interpret…
The document describes a simple screen for Chinese listed equities. It selects shares with turnover between 3% and 12%, codes beginning with 60, and a price around 18.5 yuan. The accompanying example checks recent daily market data and keeps stocks whose…
This proposed Chinese equity screen targets non-special-treatment stocks associated with the metaverse theme. It combines prior-day actual turnover within a specified range with a limit on early-session price weakness and evidence of a recent limit-up or…
This stock screen combines a 14-period RSI below 65, bid-side volume greater than ask-side volume, and a prior close above a long-term moving average. The post presents these conditions as a way to find relatively strong equities, then sketches equivalent…
The proposed A-share screen selects stocks classified in the metaverse industry with circulating share capital no greater than 5.5 billion shares, then ranks candidates by the product of percentage price change and net volume from exceptionally large orders.…
This Chinese-language strategy note proposes screening equities for a specified turnover range, a 2021 listing year, and a weekly five-period moving average crossing above the ten-period average. It presents the crossover as a technical momentum filter and…
The document describes a China equity screening rule that combines three filters: membership in the metaverse industry, a positive institutional-flow measure, and a minimum listing history. It presents the rationale that industry exposure may capture…