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 document describes a Chinese equities screen combining a 3%–12% turnover rate, a “reversal wrap” pattern, and positive MACD lines. Its indicator example also requires the close to exceed a moving average and ranks candidates by the MACD difference. The…
This stock-screening proposal combines three conditions: price amplitude above a threshold, the opening price near the ten-day moving average, and a signal interpreted as institutional buying. The article describes high amplitude as evidence of short-term…
This Chinese equity screening proposal combines a daily price range threshold, a morning star pattern, and an ownership concentration filter. It presents the setup as a short-term technical screen intended to find stocks with potential entry opportunities…
The post proposes a stock screen combining price action and auction-period order flow: select shares with amplitude above one, three consecutive limit-up sessions as of the prior day, and positive net buying attributed to major traders during the opening…
This proposed stock screen combines three signals: at least five moving averages converging, more than two limit-up days within ten days, and a shrinking MACD histogram on a 15-minute chart. The article interprets moving-average convergence as relative…
This stock screen targets companies in the metaverse industry that recorded a limit-up day within the previous 25 days and have weekly MACD above zero. The stated rationale is to combine recent market attention and possible short-term strength with an…
The proposed screen ranks stocks by capital-flow strength and filters for average price above the five-day moving average and more than two limit-up sessions within the previous ten days. The rationale is that strong inflows and a rising short-term price…
This stock screen selects Chinese equities with turnover between 3% and 12%, greater displayed buy-one volume than sell-one volume, and at least one limit-up event during the prior 25 days. The rules combine trading activity, a snapshot of top-level…
This stock selection method combines a daily price-range filter, exclusion of stocks marked ST, a recent price-high condition, and a rising MACD DEA line. It is intended to be applied before 10 a.m. The accompanying example defines MACD using exponential…
This stock-selection screen combines a metaverse industry or concept filter with a rising 30-day moving average and a condition that the current day's low is below the previous day's low. The moving-average test is intended to identify an upward trend, while…
This Chinese equity screening concept combines positive reported returns, a market capitalization below 10 billion yuan, a history without losses, and capital strength ranked from high to low. The article interprets capital strength as a measure of net money…
This stock selection method combines three filters: membership in the metaverse sector, a positive institutional-flow indicator, and appearance on the previous day’s Dragon-Tiger trading list. The document describes the rationale that sector growth,…
This document proposes screening Chinese stocks for amplitude above 1, a three-consecutive-limit-up pattern as of the prior day, and large-order net volume above 0.05 for at least three days. It presents the combination as a way to find active, widely…
This document describes a Chinese stock-selection screen with three conditions: daily turnover between 3% and 12%, the product of the day's price change and super-large-order net volume above zero, and the previous day's auction turnover above 0.26. Its…
This document describes a Chinese equity screen combining daily price range, tradable share count, and MACD. It selects stocks with an amplitude above 1, a circulating share count no greater than 5.5 billion, and MACD above zero. The accompanying explanation…
This stock selection rule screens Chinese A-shares using three conditions: turnover between 3% and 12%, a newly formed KDJ bullish crossover, and first-level bid volume greater than first-level ask volume. The article presents the rule as a way to combine…
This Chinese-language article presents an A-share stock screen combining an RSI reading below 65, seven consecutive sessions in which the close is below the open, and a closing-price condition involving the previous day's low. It also discusses adding…
The screen selects stocks whose daily high-low range exceeds one percent, excludes Beijing-listed A-shares, and requires the opening price to lie above the ten-day moving average of closing prices but below 110% of that average. The article presents the…
The document outlines a Chinese A-share screening idea focused on metaverse stocks with prior-day turnover above 8% and excluding specially treated stocks. Its proposed limit-up pattern looks for activity before 10 a.m. and checks successive five-minute bars…
This stock-selection approach screens Chinese equities in the metaverse industry for a volume ratio above 1.5 and below 6, with the 20-day moving average above the 120-day moving average. A later version adds a market-cap floor of 1 billion yuan. The article…
This guide explains how to configure and operate a live trading node, including its core settings, client registration, cache and message bus backings, strategy configuration, and shutdown behavior. It emphasizes running live nodes as standalone scripts or…
The document presents a Chinese A-share stock screen combining market activity, a prior session’s 9:15 matching price at the limit-down level, and profitability history. It first describes conditions of amplitude above 1 and ROE above 15% for five…
This Chinese-language strategy note proposes screening stocks with turnover between 3% and 12% after seven consecutive declining sessions, while excluding selected board classifications. It frames the screen as a possible way to find established companies…
The document describes a stock screen combining three conditions: daily high-low range above one percent of the previous close, a trading date in 2021, and a MACD value below zero from two trading days earlier. It gives corresponding formula and Python…