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.
4,194 documents
This post proposes screening Chinese stocks associated with the metaverse theme, positive institutional activity, market capitalization below 10 billion yuan, and no losses over the prior two years. Its stated rationale combines a thematic growth area,…
This Chinese equity research note proposes unexpected profitability as a source of stock-selection alpha. It measures operating profitability with return on net operating assets (RNOA), which separates operating activity from financing and is presented as…
This document outlines a recurring BigQuant program for people developing quantitative trading skills. It has three stages: an online selection round in which participants submit factor models built from a provided template; training for selected entrants;…
This screening method selects Shenzhen main-board stocks that have been listed for more than a year, show daily amplitude above 1, and fall within specified valuation ranges: price-to-earnings above zero and below 29.01, and price-to-book above zero and…
This project note describes iterative construction and evaluation of equity factors using amount, turnover, price, market capitalization, and price-to-book data. Candidate expressions combine standardized ratios and rolling statistics, including volatility,…
This document describes a Chinese equity screen that combines three conditions: price amplitude above 1%, a circulating share count no greater than 5.5 billion, and year-over-year growth in parent-attributable net profit above 20% and no more than 100%. It…
This document outlines a simple Chinese A-share strategy that ranks stocks by return on equity and selects the ten highest-scoring candidates. It describes filtering out special-treatment stocks, suspended shares, recently listed companies, and Beijing Stock…
The document outlines a broad framework for evaluating equity factors. It combines periodic cross-sectional robust linear regression to estimate factor returns, information coefficients (IC) to measure the relationship between factor exposures and subsequent…
This proposed Chinese A-share screen selects companies classified in the metaverse industry, with circulating market capitalization at or below the stated 55 hundred million shares threshold, and a listing age greater than a configurable number of years. The…
This stock-screening idea combines four conditions: daily high-low range greater than 1% of the previous close, a code beginning with 60, a beverage-alcohol industry classification, and market value of at least 1 billion yuan. The article interprets the…
The article summarizes research on whether diversified business groups take longer than single industry firms to have earnings news reflected in share prices. It argues that interpreting segment results is harder when a company spans businesses with…
The document describes a rules based screen for Shenzhen main board stocks associated with robotics. It combines a daily turnover range of 3% to 12%, circulating market value below 10 billion yuan, price to earnings ratios from 0 to 29.01, and price to book…
This brief question-and-answer explains how to assess whether returns across factor-sorted groups are ordered. A factor analysis sorts stocks in a chosen universe by factor value and divides them into groups; the lowest-ranked factor values form the bottom…
This BigQuant example builds a mainland Chinese stock portfolio by screening for eligible main-board shares and excluding suspended, ST, and recently listed names. It requires positive trailing earnings and dividend yield, caps float market capitalization,…
This A-share screening proposal combines a positive MACD reading with ranking by stock popularity and a qualitative preference for high-quality companies. Screening is intended to run after each daily close. The document gives the standard…
This discussion compares high-frequency price and volume strategies with lower-frequency fundamental quant investing in China’s equity market. It argues that high-frequency approaches depend heavily on hardware and execution capabilities, while fundamental…
Alphalens is a Python library for evaluating predictive stock factors. It turns a factor signal and pricing data into a structured dataset of forward returns, optionally assigning observations to quantiles and groups such as sectors. The resulting analysis…
The report analyzes cross-sectional price momentum in Chinese equities and organizes possible improvements along two dimensions: whether a change refines the measurement or the formation process, and whether it uses price or return information. Examples…
This Chinese equity screen combines company size, profitability, and trading activity. Its initial description selects firms valued below 10 billion yuan with no losses and yesterday’s turnover above 60 million yuan, ranking candidates by capital strength.…
This example selects stocks from the Chinese equity market using dividend yield, share price, and circulating market capitalization. It first keeps the highest-dividend-yield quarter of the market and stocks priced below 10 yuan, then excludes certain…
This research summary compares three sources for studying foreign ownership of China A-shares: QFII/RQFII disclosures, Stock Connect holdings, and Refinitiv Ownership data. QFII reports arrive at lower frequency and can be substantially delayed. Stock…
This stock-selection proposal combines three filters: 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 shareholder ownership concentration above 70%. The document…
This document describes a Chinese equities screen using a daily turnover rate between 3% and 12%, a positive product of price change and large-order net flow, and return on equity above 15% in each of the prior five years. It presents the rule as a…
This post proposes screening equities for a daily price range of at least one unit, strong return on equity across five years, and a three-candle morning star pattern. The described pattern consists of an advancing candle, a small indecisive or lower candle,…