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.
12,226 documents
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 proposed stock screen combines a daily price-range threshold, consistently high return on equity over five years, and large or extra-large buy orders during the opening auction. Its stated logic requires the combined auction buy volume to exceed the…
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 note describes an A-share stock screen combining RSI, a 30-day moving-average condition, and a market-size threshold. The stated selection logic uses RSI below 65, a market size above 200 million, and an upward 30-day average. The sample formulas also…
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 screen combines a daily price-amplitude threshold, a 2021 date filter, and a newly formed KDJ golden cross. The cross is defined as the K line moving above the D line after being below it on the prior observation. The article interprets amplitude…
This article outlines a Chinese equity screen focused on beverage and alcohol manufacturing. It describes combining an RSI below 65 with price-change and very-large-order net-volume information, alongside industry classification, to seek stocks with…
This document describes a Chinese equity screen that selects listed main-board stocks with turnover between 3% and 12%, first-level bid volume greater than ask volume, and a latest price of 18.5 yuan. It presents turnover as a measure of trading activity and…
This stock-selection idea combines three filters: prior-session amplitude above 1, a free float no greater than 5.5 billion shares, and a rising-bottom condition. The accompanying formulas calculate amplitude relative to the prior close and compare recent…
This short-term stock screen selects shares whose amplitude exceeds 1, that appeared on the prior day’s Dragon-Tiger trading list, and whose reported buy amount exceeds sell amount. It then ranks qualifying names by a capital-strength proxy, illustrated with…
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…
The document describes a Chinese A-share stock screen that selects companies classified in the metaverse sector, listed on the prior day’s trading leaderboard, and whose 20-day moving average is above the 120-day average. The moving-average condition is…
The document explains the Dual Thrust trend-following system, which defines a recent trading range from the largest of two high-to-close and close-to-low spreads. It sets upper and lower trigger levels by adding scaled versions of that range to a reference…
This overview introduces autoregressive and moving-average models for representing serial dependence in financial time series. An ARMA model combines lagged observations with lagged errors and assumes stationarity; the article notes that differencing or…
This daily stock screen selects shares with an amplitude above a threshold, at least two limit-up events over a 500-day lookback, and a volume ratio between 1.5 and 6. The article frames amplitude and past limit-up frequency as signs of market activity or…
This stock selection rule combines three conditions: MACD must be above zero, the price-to-earnings ratio must be positive, and short moving averages must cross upward through progressively longer moving averages. The article treats positive MACD as a trend…
This note proposes a stock screen combining daily amplitude above 1, a positive weekly MACD histogram, and a reversal or engulfing-style condition. It includes example formulas for a charting platform and a Python outline that checks amplitude, a MACD value,…
This note outlines a screen for Shenzhen Main Board equities using price amplitude above 1, MACD crossing above zero, positive price-to-earnings below 29.01, and positive price-to-book below 3.11. The intended combination pairs a volatility filter and a…
This note describes a Chinese equity screen combining daily turnover between 3% and 12%, a reversal or engulfing-style price condition, and a 2019 dividend criterion. It gives example formula and Python implementations, including a price-range calculation…
This note describes a daily stock screen for main-board shares, selecting names with turnover between 3% and 12%, circulating market value between 5 billion and 10 billion yuan, and a daily gain above 1%. It frames turnover and company size as liquidity and…
This stock-selection screen combines a short-term technical condition with valuation and historical dividend filters. It selects Shenzhen Main Board shares with a 14-period RSI below 65, positive price-to-earnings and price-to-book ratios below stated upper…
This Chinese-language post describes a stock screen that combines recent buying activity with company and valuation filters. It seeks stocks with a positive daily accumulation measure, positive large-order net flow for several consecutive days, market…