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
A brief trading forum exchange asks how to place an order using the remaining available funds rather than a fixed amount, share count, or percentage of total assets. The reply points to the platform’s stock-account available-cash value as the basis for the…
This Chinese-equity screening idea looks for companies associated with beverage or alcohol imports or exports, with a share price above its five-day moving average and a large daily trading range. The stated rationale combines recent price strength with…
The proposed screen targets A-share companies with turnover between 3% and 12%, market capitalization below 10 billion yuan, and a positive profitability measure. It also checks whether the prior day's high is the highest across a two-day window, then ranks…
This A-share screening proposal combines a turnover range of 3% to 12%, a circulating market value below 10 billion yuan, and a profitability filter intended to exclude loss-making firms. It then selects or ranks stocks whose recent price action reaches a…
This proposed equity screen combines amplitude above one, at least one daily gain of 10% or more within the prior 25 trading days, and return on equity above 15% for five consecutive years. The article presents these as a blend of volatility, recent price…
The proposed screen combines three conditions: price amplitude above one, a shortening negative MACD histogram on a 15-minute interval, and a close above the Bollinger middle band but no higher than its upper band. The author interprets the amplitude…
This article proposes screening Chinese equities in the metaverse sector for an arc-shaped price pattern and a current close above the prior session’s low. It frames the price comparison as a short-term filter and suggests adding fundamental measures such as…
This community post proposes a short-term stock screen combining a price-range condition, a morning-star candlestick pattern, and a rule excluding stocks that closed at their daily price limit on the prior session. The stated rationale is to combine…
This article develops an A-share stock-selection framework around earnings surprises and post-earnings-announcement drift. It groups surprise signals by whether new information comes from analyst revisions, reported fundamentals versus analyst expectations,…
The post asks how to reproduce a backtest setting from JoinQuant in another Chinese trading platform. The JoinQuant setting described allows limit orders to fill directly without checking the submitted price or quantity, which the author wants to use when…
This Chinese-language post proposes a stock-selection screen for Shenzhen main-board shares. It combines prior-session price amplitude above 1%, circulating shares no greater than 5.5 billion, positive price-to-earnings below 29.01, and positive…
This document presents a technical equity screen requiring at least five moving averages to converge, a positive return, and the 20-day moving average to exceed the 120-day average. Its rationale is that clustered averages may indicate relatively stable…
This document describes an equity screen combining daily price amplitude above 1%, market capitalization below 10 billion yuan, positive net profit in each of the latest four quarters, a nonempty convertible-bond short name, and an opening price above the…
This stock screen combines three conditions: daily amplitude above one percent, at least two apparent limit-up moves in the prior 500 days, and three consecutive declines in closing price. The stated rationale is to find historically active stocks that have…
This post presents a proposed Chinese A-share screen using RSI below 65, an external-to-internal trade-volume ratio above 1.3, and exclusion of Beijing-listed stocks. It also describes a 10-day price-change filter in the Python example, retaining stocks with…
This Chinese-language forum post addresses how to identify, for each stock, the day with the greatest trading volume in a prior window and retrieve that day’s closing price along with the previous day’s close. It outlines a windowing approach: shift the data…
This notebook demonstrates an end-to-end Qlib workflow for a China-market stock ranking model. It initializes Qlib data, uses the CSI 300 universe and Alpha158 features, and trains a LightGBM model on historical data with separate training, validation, and…
This post presents an A-share stock screen that combines a technical indicator, reported earnings growth, and institutional ownership. It selects shares with RSI below 65, year-over-year growth in net profit attributable to the parent company above 20% and…
This Chinese-language post outlines a short-term A-share stock screen that combines price activity and a limit-up pattern. Its stated filters include amplitude above a threshold, a claim of main-force control on the prior day, exclusion of ST-designated…
This document outlines a Chinese stock screening idea that combines a daily price-range threshold, a newly formed KDJ crossover, and a company-type condition. The intended output is a pool of candidate stocks. It also sketches formula and Python…
The post describes a stock-selection screen that ranks companies by capital-flow strength and considers share price and revenue growth. Its core growth condition compares 2021 revenue with 2018 revenue, requiring the ratio to exceed 1.1. The final proposed…
This proposed stock screen targets companies classified in the metaverse sector during 2021. It selects stocks that appeared on the previous day’s trading leaderboard, have market capitalization below the stated limit, and report positive net income. The…
This brief description outlines a trading program whose signals use four moving-average indicators, each calculated from a different price field: open, high, low, and close. It states that the system trades only on hedging accounts and includes a parameter…
The paper constructs a monthly measure of fear of missing out from three weighted components: a short-term versus long-term moving-average spread, Google search activity for FOMO-related terms, and investor margin-account use. It examines the index over 2004…