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
The proposed Chinese equity screen selects main-board stocks associated with beverage and alcohol imports and exports. Its stated criteria include an RSI below 65 and a daily price rise greater than 1%. The accompanying discussion frames the industry filter…
This stock selection approach combines three signals: more than two limit-up sessions within ten days, a closing price above the previous day's low, and a reported daily position increase above 5%. The post interprets these as signs of buying interest and…
This Chinese stock screen combines a positive MACD reading with a volume ratio between 1.5 and 6 and positive net profit. The rationale is to find shares with upward price momentum, stronger than usual trading activity, and a basic profitability signal. The…
This post describes a stock screen for the metaverse sector that requires a positive return and a weekly crossover of the five-period moving average above the ten-period average. The crossover is presented as a signal of improving short- to medium-term…
This post outlines a Chinese equity screen that combines metaverse-sector membership, an arc-shaped price pattern, and a prior-day close above the 250-day moving average. The long moving-average condition is intended to favor stocks already in an established…
This Chinese stock-selection proposal combines three technical conditions: daily price amplitude above 1%, at least two limit-up events within 500 days, and a reported external-to-internal volume ratio above 1.3. The document interprets the first two…
This document introduces factor research as a quantitative way to study characteristics that may help explain asset returns and risk. It names market capitalization, quality, momentum, low volatility, and yield as examples, and describes using statistical or…
This Chinese A-share stock screen combines a positive MACD reading with a stock-heat ranking and a prior-day actual-turnover range of 3% to 28%. It proposes selecting after the daily close. The accompanying explanation treats MACD as a short-term trend…
This post proposes screening Chinese stocks for a daily price move of at least one percent, a nonempty name for an outstanding convertible bond, and exclusion from a specified market segment. It presents the range condition as a way to identify active stocks…
This post describes a Chinese equity screen combining three conditions: reported position increases above a threshold, the prior close above a long-term moving average, and a limited opening gain at 9:25. It also offers an alternative using turnover and a…
This stock screen combines four filters: price amplitude above a stated threshold, market capitalization below a stated ceiling, positive net profit, and exclusion of the STAR Market. The accompanying discussion presents the amplitude filter as a way to find…
This short-term stock screen combines three conditions: prior-day price amplitude above 1%, a prior-day appearance on China’s Dragon-Tiger list with reported buying greater than selling, and a current high that is the highest over the recent two-day window.…
This document describes a Chinese equity screening idea that combines a turnover range of 3% to 12%, three consecutive declining sessions, and a strong weekly price move. Its stated intent is to find stocks that have recently pulled back while retaining a…
This daily stock screen selects securities before the market opens using three conditions: MACD above zero, a positive price-to-earnings ratio, and more than one year since listing. The document presents MACD as a way to identify an upward trend, treats…
This stock screening approach combines a Metaverse concept classification with an upward-sloping 30-day moving average and fundamental filters. It first selects companies associated with the theme, then looks for a rising average and firms below the stated…
This equity selection proposal combines RSI below 65, a circulating market value between 5 billion and 10 billion yuan, and simultaneous bullish crossovers in three technical indicators, with MACD, KDJ, and DMI offered as examples. It interprets the RSI…
This proposed equity screen looks for stocks with turnover between 3% and 12%, three consecutive declining sessions, and a high product of price change and very large order net volume. The article frames the setup as a possible rebound candidate: the…
This stock-selection rule filters for shares with daily high-low amplitude above 1%, a ten-day return above zero but below 35%, and positive PE. The stated rationale is to find stocks with some recent upward movement without selecting the largest short-term…
The post outlines a daily A-share selection process that keeps stocks with MACD above its zero line, a price condition relative to the five-day moving average, and positive investor attention or “heat,” then ranks candidates by heat. It gives the standard…
The post describes a simple Chinese A-share stock screen requiring daily high-low movement above 1%, a nonempty outstanding-convertible-bond name, and a share price around 18.5 yuan. Its final restatement widens the price condition to 18–19 yuan, while the…
This theme-based stock screen looks for shares with turnover between 3% and 12%, a robot-related classification, floating market value below 10 billion, and a metaverse-related classification. The article supplies an example formula and Python outline. The…
The proposed stock filter combines RSI below 65, best bid volume greater than best ask volume, and exclusion of STAR Market listings. The article interprets RSI as a way to identify relatively low-priced shares and the bid-ask size comparison as a sign of…
This short-term stock screen selects shares with RSI below 65, a daily gain above 1%, and eligibility outside the STAR Market segment. It adds a 15-minute MACD histogram condition: the histogram is negative and becoming less negative, which the document…
This stock screen combines three conditions: daily high-low amplitude above 1%, closing price below 20, and displayed best bid volume greater than best ask volume. The document gives matching formula and Python examples, framing amplitude as a measure of…