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 ranks companies by a measure of capital strength, such as net inflows or trading value, and requires at least two limit-up sessions within a 500-day window. The article frames the screen as targeting stocks with strong buying interest and…
This page organizes a beginner-oriented quantitative trading curriculum and links to lessons and example strategy projects. The listed foundations include Python, pandas analysis, historical and financial data access, visualization, and DataFrame plotting.…
This Chinese stock-screening strategy combines a turnover range of 3% to 12%, at least one limit-up event in the prior 25 days, and positive net buying by major participants during the opening auction. The article presents a screening expression and a Python…
The document describes a Chinese equity screen combining a daily price range above 1%, a condition that the prior session was not limit-up, and a recent three-session rise. It presents the screen as a way to find volatile stocks with positive price momentum…
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…
The document describes a Chinese equity screen combining daily price amplitude above 1%, membership in a robotics concept group, circulating market capitalization below 10 billion yuan, and a six-period RSI below 65. It gives example implementations in…
This Chinese stock-screening idea selects shares with an amplitude measure above one, upward separation in short-term moving averages, and an auction-period price change between minus two and five percent. The stated rationale is to combine evidence of…
This Chinese market stock screen combines a technical momentum or condition filter with trading-flow and valuation criteria. It selects Shenzhen main-board stocks with RSI below 65, positive product of percentage price change and net super-large-order…
This configuration defines a Qlib workflow for predicting short-horizon CSI 300 stock returns with a temporal convolutional network (TCN). It uses Alpha158 features, filters a specified set of feature columns, applies robust cross-sectional normalization,…
This Chinese-language research summary examines fund performance, subscriptions and redemptions, manager concentration, and sector returns around the first half of 2020. It reports gains for three categories of active equity funds and compares the scale of…
This stock-screening idea combines a relative strength index below a stated threshold with three consecutive down sessions and a moving-average crossover. The written description specifies a weekly five-period average crossing above a ten-period average,…
This short response outlines basic risk controls at both the individual-stock and broad-market levels. For a stock position, it suggests monitoring profit and loss and using risk indicators to trigger an exit, with moving-average crossovers and a multi-day…
This article outlines an equity screen requiring amplitude above 1 and MACD above the zero line, with additional consideration of company characteristics. It interprets elevated amplitude as evidence of volatility and positive MACD as a buy signal, then…
This article describes a China A-share screening rule for Shenzhen main-board stocks. It combines amplitude above 1 with rising lows, a price-to-earnings ratio from 0 to 29.01, and a price-to-book ratio from 0 to 3.11. It provides example implementations in…
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,…
This Chinese-language post describes a stock selection screen built from three conditions: rank stocks by volume ratio and keep the top 500, require at least two limit-up sessions within the past 500 days, and require the 30-day closing-price trend to point…
This stock screen restricts candidates to the metaverse industry, then selects shares whose turnover rate two trading days earlier fell within a specified band and whose current low is below the previous day's low. The article interprets turnover as a sign…
This article proposes screening stocks with a daily range above a threshold, a close above a short moving average, and multiple moving-average crossover conditions. The intended logic combines volatility and an upward price signal with clustering among…
This stock selection method combines a daily range filter with sustained positive large-order net volume and a positive five-day price bias. Its intended effect is to find shares with active buying and prices above their recent average. The article gives…
This proposed Chinese equity screen looks for stocks with daily amplitude above a threshold, signs of main-fund control on the prior day, and an opening price near the ten-day moving average. The stated rationale is to find active stocks whose opening prices…
The document proposes screening Chinese stocks in the metaverse industry for a circulating share count no greater than 5.5 billion, alongside bullish crossovers in three indicator pairs: a 5-day and 10-day moving average, a 5-period and 10-period RSI, and…
This forum post reports that a strategy based on a platform template runs, but simulation fails at a dropna step because of NaN values after the user adds factors. The author’s attempted fix was to fetch 90 calendar days of earlier daily index data,…
The document outlines an A-share screening rule combining daily price amplitude, market capitalization, recent profitability, and relative trading volume. Its refined criteria call for amplitude above 1%, capitalization below 10 billion yuan, positive net…
The document describes a China equity screening rule for metaverse-related stocks. It combines a rounded or arc-like price pattern with prior auction turnover above 0.26, alongside formula conditions involving price movement around the open, recent up-day…