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.
22,592 documents
This stock screen looks for shares with MACD above zero, ranks qualifying names by reported investor interest, and keeps stocks that appeared on the previous day’s trading leaderboard. It is intended to run after the market opens. The article presents the…
The strategy applies K-Means clustering to daily index features, such as recent average volatility, MACD, and average trading volume, to group trading days into market regimes. With two clusters, it compares each day’s feature vector with cluster centers,…
The document introduces Price and Volume Trend (PVT), a cumulative indicator that combines price changes with trading volume. For each bar, it weights the close-to-close percentage change by that bar’s volume, then adds the resulting values over time. This…
This stock selection strategy uses newly reported financial results to identify companies with year-over-year growth in net profit attributable to parent-company shareholders above 30%. Because announcements are often released after market hours, it enters…
This Chinese equity screen combines three conditions: a positive but below 35% return over ten days, a prior-day 9:15 indicative auction price at the limit-down level, and a current increase in holdings share above 5%. The article interprets the holdings…
This Chinese equity selection method looks for stocks with turnover between 3% and 12%, greater displayed bid volume than ask volume, and positive net buying attributed to major participants during the auction. The post also includes a price trend condition:…
This document describes a Chinese equity screen for robot-related companies with daily amplitude above 1, no limit-up close on the previous day, and circulating market value below 10 billion yuan. It frames amplitude as a way to find active shares, the…
This article describes a Chinese equity screen that combines a 3%–12% turnover range, stock codes beginning with 60, and a ratio of external to internal trading volume above 1.3. It frames turnover as a liquidity consideration and the volume ratio as a…
This Chinese-language article outlines an equity screen for stocks in a metaverse industry classification, using a positive-return condition and a pattern described as three consecutive down days. Its stated rationale is mean reversion: a recent run of…
Directional Frequency labels price as bullish or bearish by comparing the current close with the midpoint between the highest and lowest closes over a chosen lookback period. The example sets the lookback to 14 by convention and colors candles green when the…
This Chinese equity screen combines MACD above zero, upward divergence of the day’s moving averages, and net inflow from large orders during the afternoon. The note interprets these conditions as trend strength and buying pressure. Its illustrative formulas…
This Chinese equity screen selects stocks after each trading-day close when MACD is above zero, price-to-earnings ratio is positive, and closing prices have risen across three consecutive sessions. The note frames positive MACD as a sign of strength,…
This note describes a Chinese equity screen combining three conditions: at least five moving averages converge at a similar price, recent return is positive, and the 30-day moving average is rising. The convergence is interpreted as several trend measures…
This stock selection rule combines a daily turnover range of 3% to 12%, a newly formed KDJ golden cross, and prior-day auction turnover above 0.26. The article frames the turnover range as a way to select active stocks, the KDJ crossover as a momentum or…
This stock-screening proposal combines three filters: membership in the metaverse theme, positive net buying by major participants during the opening auction, and a five-year record of return on equity above the stated threshold. The rationale is to pair…
This report summary describes a composite signal for forecasting changes in futures basis using high-frequency ETF premiums and discounts. It separates ETF observations into intraday comparisons, such as the close versus the open or the day's average, and…
This page summarizes two research papers rather than presenting their full methods. The first applies a non-proportional-thinking model to explain how prices relative to reference values may shape reactions to new information. It proposes that stocks priced…
This post proposes screening stocks with a large daily range that appeared on the previous day’s trading leaderboard, then keeping names whose close is above the Bollinger middle band and below the upper band. It presents the combination as a way to focus on…
This post describes a technical stock screen requiring daily amplitude above a threshold, a morning-star candlestick condition, and a platform metric labeled today’s control above a threshold. It characterizes the metric as a measure related to a stock’s…
This Chinese-language post describes an equity screen that combines membership in the metaverse concept group with a close above the previous day’s low and a positive daily MACD reading. The author frames the conditions as a blend of thematic exposure, price…
This stock screen combines three conditions: price amplitude above 1, turnover greater than 2% but below 9%, and a 2019 dividend payout ratio above 25%. The post presents the criteria as a way to find shares with trading activity and a history of substantial…
The indicator plots a sequence of moving averages, with each average after the first applied to the preceding one. The first line smooths closing prices; subsequent lines repeatedly smooth that result using the same period. Users can adjust the period and…
This stock screen combines a turnover range with an IPO-year filter and a comparison of company revenue across two years. It selects stocks with turnover between 3% and 12%, listed in 2021, whose 2021 revenue exceeded 1.1 times their 2018 revenue. The…
YABSI is described as a chart indicator that marks buy and sell signals using comparisons among recent closing prices, highs, lows, and a typical-price series. Its only listed setting controls whether the typical-price line is shown; that line is also used…