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.
12,140 documents
This stock-selection screen combines membership in the metaverse theme with a long-term price filter and a one-day price-change threshold. It selects shares whose previous-day price is above the 250-day moving average and whose current-day gain exceeds 5%.…
This portfolio overlay begins with CSI 300 constituents whose index weights exceed 0.35%. At the start of each month, it measures each eligible stock’s return over the previous 21 trading days, approximately one month. Stocks with positive returns are…
This document describes a Chinese stock selection screen that combines turnover, price movement, large-order trading activity, and recent strength. The stated core conditions require turnover between 3% and 12%, a positive product of price change and…
This Chinese-language post describes a stock selection screen combining three conditions: turnover within a specified range, first-level bid volume greater than ask volume, and the prior close above the 250-day moving average. Its sample formula also…
The document describes a Chinese equity screen restricted to the metaverse industry. It selects stocks whose average price is above a five-day moving average, whose daily gain exceeds a stated threshold, and whose proprietary “control” measure is above a…
This Chinese stock-screening proposal selects companies classified in the metaverse industry when price is near its 10-day moving average and at least one session in the prior 25 trading days gained 10% or more. The article presents the average-price…
The document outlines an equity screen for stocks associated with the metaverse theme. It combines three filters: membership in that concept group, a current close above the previous day’s low, and a positive daily return at least once within a rolling…
This Chinese A-share screening idea combines three filters: market capitalization below 10 billion yuan, no historical losses, and current trading volume above 10,000 lots. It also describes selecting stocks that open above the previous close, framing the…
DayImpuls T3 combines a DayImpuls measure with a T3 moving average to describe market direction and strength. The oscillator is built from the accumulated difference between open and close prices over a configurable period, then smoothed through a…
This Chinese-language post describes a short-term screen for stocks in the metaverse theme. Its initial conditions are elevated turnover on the prior day and an upward arrangement of moving averages for the current day. The expanded version also requires…
This strategy forms a long-short equity portfolio by ranking stocks on trailing returns, buying the strongest group and shorting the weakest. The ranking uses a twelve-month lookback while skipping the most recent month, a common way to reduce the influence…
The document outlines a short-term Chinese equity screen combining price movement, a morning-star candlestick pattern, and prior-day trading activity. It also presents indicator and Python examples intended to select active stocks while excluding…
The post describes a stock-selection screen for companies classified in the metaverse industry. It requires relative volume to fall between 1.5 and 6 and the prior day’s turnover rate to exceed 8%. The author presents these conditions as a way to identify…
The document describes a TRIX indicator display that adds a signal line and marks their intersections with directional arrows. It defines an upward signal when the signal line moves from below the main TRIX line on the prior bar to above it on the current…
This algorithm describes a weekly long-short strategy among large U.S. equities. It first filters for liquid stocks, then selects the largest companies by market capitalization. From that group, it buys the ten stocks with the weakest returns over the prior…
This Chinese stock-screening strategy combines three conditions: daily amplitude above 1%, at least two limit-up events during the prior 500 days, and positive net buying attributed to major investors during the opening auction. It also proposes ranking…
This proposed short-term stock screen combines a price-range threshold, an opening-auction gain below six percent, and a 15-minute MACD condition described as a shortening negative histogram. The article presents these filters as a way to combine volatility,…
This proposed screen selects stocks using three conditions: a price range greater than one, a 15-minute MACD histogram that is shrinking while negative, and a share price of 18.5. The article interprets the range as a sign of volatility and the histogram…
This note describes a Chinese stock screen targeting shares in the metaverse theme with circulating market capitalization above 10 billion yuan and a positive weekly MACD histogram, referred to as a red weekly bar. The accompanying explanation defines the…
This note outlines a stock selection method combining three filters: daily amplitude above 1, free float no greater than 5.5 billion shares, and a ranking based on the rolling sum of price change multiplied by a measure of net large-order volume. The sample…
This document outlines a short-term Chinese equity screen combining daily price amplitude, a specified share-price level, exclusion of ST-designated stocks, and a recent limit-up pattern. Its stated idea is to look for a possible rebound when a stock has…
This Chinese equity screen selects stocks with turnover between 3% and 12%, at least one limit-up event in the preceding 25 days, and a six-period RSI below 65. The proposed combination uses turnover as a measure of trading activity, a recent limit-up as a…
This stock-screening idea combines an RSI reading below 65, three consecutive bearish candlesticks, and a rising DEA component of MACD. It is presented as a way to find shares with constrained RSI readings and a short-term change in trend direction. The…
MACD-V modifies the classic MACD by scaling the difference between short and long exponential moving averages by the asset’s average true range, then multiplying by 100. The resulting momentum reading is designed to be more comparable across time and markets…