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 report explores whether stocks held together by investment funds form a useful relationship network. It offers two explanations: shared holdings may reflect common traits recognized by fund managers, and co-owned stocks may respond similarly because…
This performance note describes Haitong’s broad-market multi-factor portfolio, which scores Chinese stocks using factors related to company size and trading behavior. It selects the 100 highest-scoring stocks for an equal-weight portfolio, with holdings…
This notebook walks through an Alphalens workflow for assessing alpha factors, which assign a value to each asset at each date and are judged by how those relative values relate to subsequent returns. It demonstrates loading daily stock prices, organizing…
This tutorial explains how to prepare data and use Alphalens to evaluate cross-sectional alpha factors. It distinguishes factor research, which tests whether relative signal values predict later returns, from trading strategy evaluation, which also needs to…
The document reviews feature selection as a preprocessing step for machine learning stock selection. It distinguishes filter, wrapper, and embedded approaches, and describes selection criteria such as variance, entropy, F statistics, mutual information,…
This screen seeks profitable companies listed in 2021, with market capitalization no greater than 10 billion yuan and turnover between 3% and 12%. The article presents the rule in prose, an indicator-style expression, and sample Python using stock-list and…
This stock-selection screen combines membership in a metaverse theme with a price above its 250-day moving average and a holder-concentration condition. The prose describes selecting stocks whose concentration is either below 20% or above 70%, while the…
The document describes a Chinese equity screen combining three filters: turnover between 3% and 12%, year-over-year net profit growth attributable to parent-company shareholders above 20% and no greater than 100%, and floating market capitalization above 10…
This stock-screening note focuses on companies in the metaverse sector with yesterday's turnover above 8% and a closing price between the Bollinger middle and upper bands. Its final proposed version adds a market-cap ranking in the top 30% of the market and…
This Chinese-language strategy note describes a stock screen for companies classified in the metaverse sector. It first specifies a relative volume ratio between 1.5 and 6, a market capitalization no greater than 10 billion yuan, and positive net profit in…
The document summarizes research on how macroeconomic conditions relate to cyclically adjusted price earnings ratios and stock returns. CAPE smooths earnings using a long inflation adjusted history, which can make it informative about long horizon returns…
This stock-screening proposal starts with three technical conditions: amplitude above 1, a positive weekly MACD histogram, and no limit-up session the previous day. It frames the screen as a way to find volatile shares with a positive weekly signal while…
This note discusses the relative roles of predictive factors and model design in quantitative strategies. It argues that factor quality usually sets the ceiling for potential performance, while model quality determines how effectively a strategy can use the…
This stock screen combines a technical condition with company size and historical revenue growth. It selects shares with an RSI below 65, circulating market capitalization above 20 million, and 2021 revenue more than 10% higher than 2018 revenue. The article…
This Chinese stock-screening post combines a measure of trading activity with historical revenue growth. Its activity measure multiplies the prior day’s turnover rate by the current day’s auction volume divided by the prior day’s total volume, and it…
The article describes an unsupervised approach to identifying market regimes from the returns of 17 US factors beginning in 1970. A Gaussian mixture model clusters observations by their return distributions; cross-validation is used to choose four clusters.…
The document summarizes a study applying convolutional neural networks (CNNs) to multi-factor stock selection in the Chinese A-share universe. It proposes arranging factor observations as two-dimensional inputs, treating convolution as factor combination,…
This Chinese-market stock screen combines a price-range condition, sustained profitability, and a rising technical signal. Its stated selection logic looks for price amplitude above a threshold, return on equity above 15% in each of five consecutive years,…
The report describes a daily Chinese equity selection model built with a fully connected deep neural network. It derives 98 features from seven basic price and volume inputs using rolling averages, extrema, dispersion, ranks, weighted averages, correlations,…
The document explains volume-weighted average price (VWAP) as an average that gives greater influence to prices recorded with more trading volume. It describes a stock factor calculation that groups intraday bars by instrument and calendar date, then divides…
This equity screen combines daily price amplitude above 1%, a high equal to the highest high over two days, and a company-type condition chosen to fit an investment theme. The note frames the amplitude and recent high as ways to find active, strong stocks,…
This document proposes a Chinese equity screen that combines price amplitude above 1 with five consecutive years of return on equity above 15%, market capitalization below 10 billion yuan, and positive net income. The intended mix is a volatility condition…
This post describes a Chinese equity screen requiring turnover between 3% and 12%, a rising DEA reading, and a 2019 dividend ratio above 25%. It presents the dividend condition as a way to focus on income-oriented companies, while turnover and the indicator…
This Chinese equity screen combines a relative strength index threshold with a circulating-market-value range and positive net profit. The stated aim is to find profitable companies in a middle market-capitalization band while avoiding stocks whose RSI…