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 report develops a framework for rotating between the CSI 300 and ChiNext indices, whose valuations, market capitalizations, and industry exposures differ. It organizes potential drivers of their relative performance into factors covering real economic…
The report estimates a fund’s equity exposure by regressing daily fund returns on daily returns for 29 first-level industry indices. It treats the sum of fitted industry coefficients as the estimated position. Because industry returns are correlated, it…
This brief Chinese-language page introduces a portfolio optimizer as a mathematical tool for selecting and weighting assets subject to constraints. It identifies three possible objectives: maximizing expected return, minimizing risk, or balancing the two.…
This document describes a Chinese equity strategy research approach that uses supervised neural networks to generate many weak alpha factors from a set of input factors. It proposes transforming those outputs into low-correlation components, then weighting…
This forum post asks how a factor dashboard calculates win rates for low and high factor quantiles and for a long–short portfolio. It contrasts two possible interpretations: counting individual stocks with positive returns, or counting rebalancing periods in…
This report summary compares cross-sectional, market-neutral commodity futures strategies based on inventory deviation and historical momentum. The inventory signal favors commodities with inventories below their own trend and shorts those above trend. It is…
This introductory guide outlines a retail trader’s path into quantitative trading. It describes using market data and mathematical models to generate decisions, learning market concepts and a programming language, building models from historical data, and…
This article explains how to measure whether active mutual fund managers adjust holdings in stocks with different downside market sensitivity ahead of market moves. It defines relative downside beta as the portfolio weighted downside beta minus conventional…
The document describes a China A-share index enhancement approach that adds industry rotation to a CSI 300 stock-selection portfolio. Its motivation is that the benchmark has uneven industry weights, making active industry exposure a meaningful part of…
This research summary extends a framework for selecting functional equity funds for fund-of-funds portfolios. It distinguishes sectors where active stock selection may add value from those better served by sector ETFs. For consumer and growth exposures, it…
This 2018 report revisits whether the investment clock can guide asset allocation amid trade tensions and political shocks. Its traditional mapping assigns equities to recovery, commodities to overheating, bonds to recession, and cash to stagflation. It…
The article explains how a long-only smart beta portfolio can combine equity factors to seek steadier returns than relying on one factor. It highlights value, low beta, profitability, investment, momentum, and size, arguing that their different return…
This short VeighNa forum exchange discusses running multiple strategies on the same instrument when one strategy places orders with position locking enabled. The question asks whether other strategies sharing the same PositionHolding object also need to use…
The script demonstrates a classic allocation strategy that holds a portfolio with a target mix of 60% stocks and 40% bonds. It uses a drift rebalancer: when asset weights move away from their targets by a configured threshold, the strategy sells assets that…
This note compares portfolio construction approaches, including equal weighting, market-cap weighting, and stratified sampling, with optimization methods such as mean-variance optimization, risk parity, target-risk, ABL, and tracking-error models. It…
The document explains sliced inverse regression (SIR) as a supervised dimension-reduction method for financial prediction. Unlike principal component analysis, which summarizes variation in predictors without using the target, SIR uses the forecast variable…
This brief summary of a research presentation describes changes in China’s public equity fund industry over a ten-year period. It highlights shrinking scale among smaller fund companies, managers, and products, alongside turnover among leading firms and…
This Chinese-language summary introduces TS-Boost, a machine-learning framework for equity factor selection. It identifies two challenges in financial data: observations may not share the same distribution over time, and market signals can have low…
This introductory section points new users to three FinRL tutorial notebooks. One is presented as a recommended first exercise, walking through a full deep reinforcement learning workflow for stock trading. Another demonstrates connecting FinRL to Tushare…
This Q&A examines a Chinese A-share small-cap strategy that selects the market’s smallest stocks by capitalization. The user expected the backtest to buy at its August 24 start date, but the first trade appeared on September 23. The explanation is that the…
This 2019 strategy review discusses how Chinese equity quant investors might respond to a weak market and changing asset-management conditions. It questions the near-term outlook for multi-factor approaches, noting that technical factors could remain under…
The document explains how to calculate a portfolio’s expected return as the weighted sum of the assets’ expected returns. It describes portfolio standard deviation as a function of each asset’s weight and volatility, together with the correlations between…
The article reviews a method for evaluating active mutual funds by adjusting performance first for factor exposures and then for the characteristics of stocks held. It begins with Carhart four-factor alpha, then uses either a cross-sectional regression on…
This brief description introduces a strategy-rotation framework for adapting a portfolio to different market environments. It proposes tracking shifts in market style, identifying the style characteristics of individual strategies, and using quantitative…