這裡收錄 Stratmill 研究代理對 AI 代理閱讀過的書籍、論文、文章與程式碼所寫的摘要與核心觀點。每個頁面都連結至原始資料。
12,226 份文件
The document outlines a daily post-close stock screen that combines a positive MACD reading, amplitude above 1, and ranking by individual-stock interest or popularity. It presents the standard MACD components based on exponential moving averages and defines…
The document describes a Chinese stock selection screen combining turnover, parent-company net profit growth, market capitalization, and a non-loss condition. It selects stocks with turnover between 3% and 12%, year-over-year net profit growth above 20% and…
This document proposes a Chinese equity screen for stocks associated with the intelligent robotics concept. It requires the intraday high-low range, measured relative to the low, to exceed 1%, and float market capitalization to fall between 5 billion and 10…
The document explains Bollinger Bands as a moving average surrounded by upper and lower envelopes set using a multiple of recent closing-price standard deviation. The center line is an N-day average; the width changes with measured price dispersion. It…
This document describes a Chinese equity screen for main-board stocks outside the STAR Market. It selects shares with turnover between 3% and 12% and a daily gain above 1%, with the gain compared against stocks in the same board segment. The article presents…
This post describes a stock-selection filter requiring price amplitude above a threshold, three consecutive limit-up sessions through the previous day, and a current high equal to the highest high across a two-day window. It interprets the filters as a way…
This Chinese-language post outlines a stock screen using three conditions: price amplitude above a threshold, no limit-up session on the prior day, and a rounded price-chart shape. It presents the rounded bottom as a possible market-bottom pattern and treats…
This document describes a short-term Chinese equity screening rule using three filters: daily amplitude above 1, a current-day decline between 4% and 5%, and a positive recent return below an upper bound. The heading specifies a 10-day gain below 3%, while…
This document describes a stock screen combining three conditions: turnover between 3% and 12%, three consecutive declining sessions, and at least one limit-up event during the prior month. It presents the pattern as a way to find actively traded stocks that…
This post describes a proposed Chinese stock screening rule. It selects shares with a daily high–low range above one percent, at least one limit-up event during the prior twenty-five trading days, and a specified recent-turnover condition. The author…
The document describes a Chinese A-share stock screen combining current trading activity with recent price strength. It selects main-board stocks with turnover between 3% and 12%, a daily gain above 1%, and at least one limit-up session during roughly the…
The document describes an A-share stock screen for companies classified in the metaverse industry. It selects stocks with circulating shares no greater than 5.5 billion and a prior-day actual turnover rate from 3% to 28%. The stated rationale is to focus on…
This screening method combines three conditions for Chinese stocks: MACD above zero, a rising short-term moving-average pattern, and company scale above 200 million. The document interprets these as signs of positive momentum and an upward trend, with a size…
This Chinese A-share screening idea selects stocks with more than two limit-up days within a ten-day window during 2021, then ranks the candidates by capital strength. It frames repeated limit-ups as a sign of strong recent market performance and suggests…
This Chinese-language post describes an equity screening rule that combines a 14-period RSI below 65, price change multiplied by a measure of large-order net inflow, and positive net buying by major participants in the opening auction. Its sample Python…
The document presents a Chinese equity screen for robot-themed stocks with circulating market capitalization below 10 billion yuan, a daily high-to-low range above one percent, and codes beginning with 60. It then expands the proposed screen with valuation…
The document describes a Chinese equity screen limited to the metaverse industry. It selects stocks whose opening price is within five percent of the 10-day average closing price and whose daily MACD is positive, with a stated condition that the prior MACD…
The document describes a Chinese stock screen combining three conditions: prior-day price amplitude above 1%, an opening price near the 10-day moving average, and a prior-day appearance on the 龙虎榜, a list of notable trading activity. It explains the intended…
This analysis examines whether unusually strong net fund flows coincide with investors switching between small-cap and large-cap equity styles. It defines net inflow by subtracting active selling from active buying across large, medium, and extra-large…
The document describes a Chinese equity screening idea that selects stocks associated with the metaverse theme, requires prior-day actual turnover between 3% and 28%, and looks for an upward alignment involving MACD and moving averages. Its rationale is that…
This Chinese stock screen selects shares with turnover between 3% and 12%, first-level bid volume greater than first-level ask volume, and a listing date more than ten years earlier. It then takes up to 30 names, with the formula example also restricting the…
This Chinese equity screen looks for stocks with an amplitude above 1, trading volume above 10,000 lots, a higher opening price, and at least one recent limit-up move within roughly the past month. The accompanying formula and Python example describe ways to…
This Chinese stock screen combines an intraday amplitude threshold, exclusion of special-treatment shares, a five-day closing-price high condition, and a bounded same-day return. It is intended for selection before 10 a.m., though the stated rules also refer…
This tutorial explains how to monitor a stock-selection query on the Supermind platform and send a WeChat notification when stocks meet its conditions. Users adapt a natural-language query, such as one combining technical signals, recent returns, and other…