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.
5,922 documents
This research summary outlines a monthly tactical framework for rotating among Chinese A-share industries. It combines two approaches: time-series timing based on industry classification, business-cycle indicators, fundamental forecasts, valuation…
This report introduction frames research into how factor and stock weights affect style exposure in multi-factor equity portfolios. It focuses on reducing unintended market-cap, industry, and other style biases, which the authors associate with past setbacks…
This strategy uses language metrics from company filings to form a monthly long-short equity portfolio. It selects a stock universe using liquidity and market-cap filters, retrieves filing metrics, and ranks eligible companies separately on lexical density…
This example describes a high-dividend stock selection model for the Chinese equity market. It first excludes special-treatment stocks, suspended stocks, and Beijing Stock Exchange listings. Within the remaining universe, it selects the 300 largest companies…
The document presents the Brinson framework for explaining portfolio returns through the benchmark, active asset allocation or timing, security selection, and their interaction. The benchmark reflects long-term asset-class weights and passive returns. Timing…
This glossary introduces common measures for evaluating investments and trading strategies. It explains cumulative, annualized, and monthly returns; benchmark-relative performance; win rate and reward-to-risk; information ratio; standard deviation; alpha and…
This report presents a fundamental quantitative stock-selection framework for China’s lithium battery industry. It first reconstructs the supply chain into battery makers, material suppliers, and upstream cobalt and lithium resources, arguing that…
This report summary presents a framework for converting intraday or other medium-to-high-frequency signals into factors intended to predict returns over a monthly horizon. It separates factor construction into signal generation, aggregation from intraday…
The discussion explains how to change a StockRanker strategy’s initial buying schedule when starting a live simulation. The questioner says the strategy gradually adds positions, leaving the portfolio underinvested at launch, and wants the simulation’s first…
This report summary describes a Chinese equity industry-rotation approach that scores sector conditions using financial data from regular reports, earnings forecasts, and earnings bulletins. It evaluates individual accounting measures, then combines…
This BigQuant example builds a long-only Chinese stock portfolio from a filtered universe of main-board shares. It excludes suspended stocks and, in its feature filters, keeps non-ST stocks listed for more than a year, with positive trailing earnings and…
This research summary tests whether machine-generated stock-selection factors add value to established manually designed factor libraries. It uses genetic programming to evolve candidate formulas from market data, then applies random forests to turn factor…
This document catalogs example strategies for a Python trading framework. The collection spans stock buy-and-hold, moving-average crossover, stock momentum rotation, a traditional stock-and-bond allocation, equal-weight Bitcoin and Ethereum, a short options…
This forum post asks how a portfolio-sizing expression allocates cash for purchases and sales. It defines an average cash amount by dividing portfolio value by the holding period, caps buy cash at available cash and a staging-dependent multiple of that…
This implementation describes an equity pairs strategy that selects stocks with highly correlated historical returns, then compares each stock’s return with a portfolio of its selected peers. It estimates a regression coefficient during a formation period…
This note groups four risk-based portfolio approaches—global minimum variance, equal risk contribution, maximum diversification, and equal weight—within one optimization framework. The framework uses three adjustable parameters to represent the individual…
This research summary argues that low valuation alone can select weak businesses, so investors should assess company quality before deciding whether its price is reasonable. It evaluates A-share companies using indicators related to profitability, growth,…
The document reports a mismatch between a portfolio strategy’s expected rebalance schedule and its simulated trading activity. The author says the backtest rebalances every five days or after a take-profit trigger, while the simulation records trades on many…
The document summarizes an analysis of Chinese A-share investor research visits, using public company announcements to identify when institutions visit firms. These events are usually targeted visits involving five or fewer institutions, and announcements…
This summary examines whether frequent constituent changes weaken returns for a portfolio tracking the CSI 300. It reports a Wilcoxon test finding short-term price effects around index adjustments: additions tended to rise and removals to fall, with the…
This Chinese-language manual explains a portfolio optimizer for constructing benchmark-aware equity portfolios. It describes initializing the optimizer with a dated stock universe and benchmark, refreshing factor data for each trading date, and then…
This document summarizes a framework for deciding whether and how to combine single-factor smart beta strategies with multifactor portfolios. It represents each candidate strategy as exposures to a small set of investable elementary smart betas—initially…
This strategy seeks to outperform the CSI 1000 while controlling industry, style, and individual-stock exposures. It proposes combining value, growth, size, quality, volatility or liquidity, and alternative signals. Factors are cleaned for outliers,…
This issue of a Chinese financial engineering research series introduces three overseas studies across stock selection, accounting analysis, and strategic asset allocation. The first builds a stock-selection approach using listed-company merger data and…