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.
4,510 documents
This research roundup summarizes three studies. The first examines whether unexpected US monetary policy announcements affected hedge fund alpha after the financial crisis, using event studies, structural-break tests, and Markov-switching models. It reports…
This stock selection approach combines moderate trading activity, recent price-limit events, and a cap on tradable shares. It screens for turnover between 3% and 12%, at least one limit-up event in the prior 25 days, and a float threshold stated as 5.5…
This Chinese stock-screening article proposes selecting shares with a daily range above a threshold, rising lows, positive institutional buying, and a 20-day moving average above the 250-day average. It also excludes special-treatment stocks and describes…
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 stock-selection method targets companies in the metaverse concept group, with relative volume above 1.5 and below 6, alongside afternoon net inflows from large orders. The document links large-order inflows to market sentiment and describes the…
This brief description concerns a trading robot that acts on market sentiment and recommends using it with volatile instruments, giving Brent and Sberbank as examples. Its update describes two conditions for closing a position: trading volume falls below a…
The document describes an A-share stock screen intended to find possible short-term rebounds. It combines a 14-period RSI below 65, first-level bid volume greater than ask volume, and a stated daily maximum decline between 4% and 5%. The accompanying…
This stock-selection rule filters for shares whose codes begin with 60, whose turnover is between 3% and 12%, and whose auction-period main-force net buying is positive. The document frames positive net buying as a sign of incoming funds and suggests that…
This stock-selection proposal combines three filters: membership in the metaverse sector, positive institutional activity, and a positive share-price return during 2021. It frames institutional buying as a potentially useful signal and past gains as evidence…
This proposed stock screen combines three ideas: institutional buying activity above a stated share of trading volume, reported institutional accumulation near a price low, and a positive but capped ten-day gain. The article presents the combination as a way…
This brief market note reviews Chinese 50ETF options conditions for the week ending November 2. It reports that the ETF closed at 2.594 after gaining 3.1% for the week, while the trading-value put-call ratio fell from 0.754 on October 26 to 0.575. The note…
The article summarizes research using Forcerank, a platform where participants rank stocks by expected performance over roughly a week. Regressions of consensus ranks on past returns show that participants extrapolate recent performance, with more weight on…
This research summary examines whether hedge funds’ exposure to changes in investor sentiment predicts subsequent performance. It estimates each fund’s sentiment beta with a rolling 36-month window, forms equal-weighted portfolios by beta, and uses…
This proposed daily premarket stock screen combines positive MACD, a non-ST restriction, market-heat ranking, and a five-session limit-up pattern. The pattern is described as five consecutive sessions in which each day reached a stated return threshold over…
The document describes a Chinese equity screen that keeps stocks with turnover between 3% and 12% and at least one limit-up event during the previous 25 days, then ranks candidates by individual-stock popularity. It presents the rule as a way to combine…
This market snapshot assesses an early-2026 crypto rally using price and volume changes alongside open interest, perpetual funding, ETF flows, stablecoin supply, orderbook depth, and volatility. It interprets rising prices, expanding open interest, positive…
This stock-selection screen combines a minimum daily amplitude threshold with a minimum circulating market capitalization, then ranks qualifying shares by a popularity measure. The stated rationale is to focus on stocks that show price movement, have a…
This note describes a stock screen for companies in the metaverse theme with circulating market capitalization above a stated threshold, ranked by individual stock popularity. Its rationale is that ranking by attention may surface securities attracting…
This Chinese-language post describes a mainland Chinese stock screen combining turnover rate, the ratio of outside to inside trading volume, and the current day’s price gain, then restricting candidates to main board stocks. It frames turnover as a liquidity…
This article describes a Chinese A-share screen combining turnover between 3% and 12%, at least one limit-up event in the prior 25 days, current volume above 10,000 lots, and a high-open condition. It argues that moderate turnover and recent limit-ups may…
This market snapshot discusses three digital-asset themes: institutional Bitcoin adoption, prospective uses for autonomous AI systems in decentralized finance, and tokenization of real-world assets. Its Bitcoin analysis describes a sharp rise above $100,000…
This Chinese-language post describes a short-term stock screen using three conditions: a 14-period RSI below 65, first-level buy volume greater than first-level sell volume, and prior-day trading value above 60 million. It frames the RSI as a price-condition…
This market newsletter combines digital-asset developments with indicators and market commentary from October 2024. It reports growth in OpenEden’s tokenized U.S. Treasury vault, contrasts Bitcoin and Ethereum ETF assets and flows, and describes a recovery…
This post summarizes a 2017 J.P. Morgan report on using large and alternative datasets in investment research. It groups alternative data into information generated by individuals, business processes, and sensors, with examples such as social media,…