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 note proposes an A-share screen requiring MACD above zero, a share price below 12 yuan, and exactly one limit-up session in the previous 25 days. It describes running the selection before 10 a.m. each trading day. The stated rationale is that a recent…
This note describes an A-share stock screen combining a 14-period RSI below 65, a rising MACD signal line (DEA), market capitalization below 10 billion yuan, and no reported loss in the prior fiscal year. Its rationale is to pair modest momentum conditions…
The document proposes screening Chinese stocks using price amplitude, market-value concentration, and the gain at the market open. Its initial rule selects stocks with amplitude above a threshold, a stated concentration condition, and an opening gain below…
This Qlib configuration defines a Chinese equity research workflow using the CSI 300 universe and Alpha158 features. It trains a double ensemble of gradient-boosted models, with both sample reweighting and feature selection enabled, then evaluates signals…
This Chinese stock-selection post proposes screening for shares with RSI below 65, circulating market capitalization between 5 billion and 10 billion yuan, and a candlestick condition described as the Kute Intelligent morning-star pattern. The accompanying…
This BigQuant strategy tutorial outlines a framework for combining a broad-market risk signal with individual-stock timing and position management. The proposed workflow builds separate feature expressions for index-level risk and stock-level conditions,…
This Chinese stock-selection post describes a technical screen for shares with daily amplitude above one, excluding ST-designated companies and stocks that hit the daily price limit the previous day. The screen is intended for selections made before 10 a.m.…
The article compares a StockRanker stock-selection strategy with a Deepalpha deep neural network using the same 17 short-term factors, training data, and backtest setup. The strategy selects the top-ranked A-share stock each trading day and sells it the…
This document describes a Chinese A-share stock screen using a turnover ratio from 3% to 12%, circulating market value from 1 billion to 55 billion yuan, and exclusion of stocks whose names contain a Beijing reference. It gives equivalent screening logic and…
This weekly Chinese equity-market note describes a market-regime framework using the distance between 20-day and 120-day moving averages on a broad market index, alongside a measure of market-wide profit-making activity. In the reported week, the short…
This Chinese equity screening proposal combines three conditions: a 20-day moving average above the 120-day average, an amplitude threshold, and exclusion of stocks that hit the upper price limit on the prior day. It presents the moving-average relationship…
This daily, after-close screen selects stocks whose MACD line is above zero and that have a nonempty name for an outstanding convertible bond. It then ranks eligible stocks by individual-stock popularity, with the stated intent of prioritizing names…
This stock selection rule screens companies in the metaverse industry using two recent turnover readings: actual turnover from two sessions earlier must be between 3% and 28%, while the prior session’s turnover must exceed 8%. The document presents the…
This document describes a chart overlay that displays recent daily market data for a selected instrument. It gathers open, high, low, close, and volume values for a configurable number of prior days, and calculates each close’s percentage change relative to…
This summary of a research report examines the Chinese New Year calendar effect in mainland Chinese equities and how it relates to common quantitative factors. It reports that the broad market historically had an unusually favorable risk-adjusted profile…
This document describes a stock screen for Chinese equities that combines three conditions: turnover between 3% and 12%, year-over-year growth in net profit attributable to the parent company above 20% and no more than 100%, and a positive MACD reading. The…
The document proposes screening Chinese A-share stocks in a metaverse sector category using prior-day turnover above 8%, an opening auction change between -2% and 5%, and, in its final rule, a price-to-earnings ratio below 50. The article presents these as a…
The document explains how Level 2 equity market data extends a conventional five-level view to ten bid and ask levels, with aggregate depth, order queue details, and individual order records. It describes possible intraday interpretations of visible…
The document presents a Chinese A-share stock screen that combines an intraday amplitude condition with a low closing-price threshold. The written rules are inconsistent: the headline refers to amplitude above 1 and a price of 18, the body specifies 18.5…
The article describes a Chinese equity screen combining daily price amplitude, a historical dividend-yield threshold, and a signal labeled as the start of a rising trend. It interprets amplitude as a measure of trading activity, dividend yield as a marker of…
The document explains mean reversion as the tendency for prices or business performance to move back toward a longer-term center after unusually strong or weak periods. It connects this idea to contrarian investing: investors may examine past laggards as…
This study examines whether the number of executions recorded in tick data can improve a conventional reversal factor for Chinese A-share equities. It divides the traditional factor using trade-count information and proposes a refined reversal signal. The…
This post describes an A-share screening rule combining daily turnover between 3% and 12%, an opening price within 5% of the 10-day moving average, and a moving-average relationship intended to indicate alignment. It includes a formula-style example and a…
The post asks how to reproduce a Chinese stock industry return series from constituent-level data. It identifies three aggregation methods: equal weighting, weighting by total shares, and weighting by free-float shares. The example query retrieves…