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.
12,031 documents
This stock-selection proposal combines three filters: membership in the metaverse theme, positive net buying attributed to major participants during the opening auction, and a close above the middle Bollinger Band but below its upper band. The article…
This stock screen combines three conditions: prior-day price amplitude above a threshold, the current open near the 10-day moving average, and membership in the metaverse theme. The article interprets the range condition as a sign of elevated short-term…
This document presents a China A-share screen centered on turnover between 3% and 12%, a seven-day declining-price condition, current volume above 10,000 lots, and an opening price above the previous close. Its final proposed version adds market…
This brief forum exchange answers whether VeighNa, also known as vn.py, requires Tushare as the sole source of historical A-share data for backtesting. The response says the framework supports multiple data services and points readers to its documentation…
This document describes a stock screen combining turnover, parent-company net profit growth, and a moving-average trend filter. It selects shares with turnover between 3% and 12%, year-over-year net profit growth above 20% and at most 100%, and a 20-day…
This Chinese-language post proposes screening stocks using three conditions: a large daily price range, prior-day turnover within a specified band, and a reversal candle pattern. It presents the combination as a way to find stocks with substantial price…
The article describes a short-term A-share screening rule combining three conditions: prior-session price amplitude above 1%, circulating shares no greater than 5.5 billion, and a stock code beginning with 60. Its sample implementation intersects these…
This research summary examines Shanghai–Hong Kong and Shenzhen–Hong Kong Stock Connect, comparing northbound and southbound trading and describing the traits associated with northbound holdings. It reports that flows did not reliably anticipate market…
This strategy uses a market regime filter built from momentum across 11 sector and style ETFs. It measures each ETF against a 25-day moving average and treats the broad market as showing momentum when at least six ETFs qualify. The portfolio buys small-cap…
This short-term A-share screen focuses on stocks classified in the metaverse theme. It seeks names with an opening gain below 6% and a current high equal to the highest high across two days, combining a thematic universe with a near-term price strength…
This A-share stock screen combines a range expansion condition, a Bollinger Band location filter, and a historical dividend ratio threshold. It selects stocks whose daily high-low range exceeds its 20-day average, whose close lies between the middle and…
The document describes a daily stock screen for Chinese main-board shares. It selects non-ST stocks with turnover between 3% and 12%, a daily gain above 1%, and more than one year since listing. The stated rationale is to combine active trading and positive…
This configuration defines a Qlib workflow for training a Temporal Fusion Transformer model on Alpha158 features for CSI 300 stocks. It sets Chinese market data from 2008 through mid-2020, using 2008–2014 for training, 2015–2016 for validation, and 2017–2020…
This stock-selection rule combines a 14-period RSI below 65, positive daily return, and year-over-year growth in net profit attributable to parent shareholders above 20% and at most 100%. The article presents the combination as a way to find companies with…
This screen selects stocks in the metaverse sector that recorded a limit-up event within the previous 25 days and have year-over-year growth in net profit attributable to parent shareholders above 20% and no more than 100%. It also specifies selecting…
This stock screen combines metaverse-sector membership, a prior-day turnover threshold above 8%, and a rising-bottom chart pattern. The article presents rising bottoms as a way to identify prices recovering from a low and potentially continuing upward, with…
The document outlines a Chinese equity screening rule that combines a metaverse sector filter, a closing price above the 250-day moving average, and a positive product of price change and a large-order net-volume measure. The stated interpretation is that…
This short-term stock screen combines three signals: a high-low range greater than one, a shortening negative MACD histogram on a 15-minute chart, and at least one limit-up move during the past month. The document interprets the range as a sign of…
This screening idea combines a daily high-low range threshold, consistently strong return on equity over five years, and a filter related to the previous day’s limit-up status. The stated rationale is to pair a measure of price movement with a longer-term…
This stock-selection proposal focuses on companies classified in the metaverse sector. It selects stocks that experienced a limit-up move within the prior 25 days and whose current close is above the previous day’s low. The post describes selecting…
This Chinese equity screen selects stocks with turnover between 3% and 12%, displayed first-level bid volume greater than ask volume, and a weekly five-period moving average crossing above the ten-period average. The note describes these filters as proxies…
This note proposes a Chinese equity screen for stocks with amplitude above 1, rising lows, membership in the robotics concept group, and circulating market capitalization below 10 billion yuan. It combines a price-pattern condition with a sector theme and a…
This note describes a Chinese equity screen combining three conditions: price amplitude above 1, circulating market capitalization above 10 billion yuan, and at least one limit-up event in the prior 25 days. It frames the screen as a way to find larger,…
This stock selection approach filters for shares associated with the metaverse theme, then checks for an upward-sloping 30-day moving average and sorts qualifying names by a measure of individual stock interest. The article presents this as a way to combine…