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 document summarizes long-run performance of Chinese equity factor portfolios and compares their results across market, economic, interest-rate, and volatility regimes. It reports that the portfolios had positive long-term returns, with size and…
This forum post raises a factor-data debugging question: why can an industry-neutralized price-to-book factor contain missing values when the raw factor appears complete? It identifies an industry-neutralization function applied using a first-level industry…
This report surveys hedging choices for U.S. equity portfolios during drawdowns and recessions, drawing on a historical sample from 1985 through 2018. It contrasts rolling index puts and short credit risk with Treasury and gold exposures, then examines…
This review compares passive and active approaches to protecting U.S. equity portfolios during severe drawdowns and recessions. Its sample covers 1985–2018, including eight equity declines greater than 15% and three U.S. recessions. It discusses rolling S&P…
The post proposes a Chinese equity screen combining daily price amplitude above 1%, a robotics concept classification, circulating market value below 10 billion, and selected beverage or alcohol related industries. It outlines the conditions in prose and…
This document presents a simple Chinese equity screening rule: select stocks with turnover between 3% and 12%, circulating market capitalization between 5 billion and 10 billion yuan, and a positive return. It gives both a formula-style expression and a…
This Chinese equity screening idea combines price amplitude above 1%, appearance on the prior day’s trading list, and return on equity above 15% for five consecutive years. The post frames these conditions as a blend of short-term volatility, market…
This article argues that LSTM models trained on historical prices can appear to forecast stocks accurately because predicted daily prices often remain close to the previous day’s price. When plotted against actual prices, this persistence can look…
This proposed stock-selection method combines three conditions: a historical dividend payout ratio above a stated cutoff, an opening price near the ten-day moving average, and at least five moving averages described as overlapping. The rationale is to find…
The document presents a Chinese equities screening idea combining a robot-industry concept, a circulating market value below 10 billion yuan, a turnover band of 3% to 12%, and exclusion of stocks associated with northbound capital. It suggests sorting…
This summary of a research report examines whether trade counts from tick-level transaction data can refine a traditional reversal factor in China’s order-driven A-share market. Trade count is defined as the number of matched transactions. The report says it…
The article summarizes a method for extracting priced common factors from stock returns. First, a Fama-MacBeth cross-sectional regression uses several return-predictive characteristics to estimate stocks’ expected returns. Stocks are then sorted into…
This daily stock-selection method combines price activity, past limit-up events, and valuation filters. It screens Shenzhen Main Board stocks for amplitude above 1, at least two limit-ups during the prior 500 days, a price-to-earnings ratio between 0 and…
The report uses Hong Kong Exchange disclosures on holdings associated with northbound Stock Connect trading seats to estimate stock positions and sector-level additions. It argues that aggregate flows can obscure differences among market participants, then…
This stock-selection recipe screens Chinese equities before each trading day for three conditions: MACD above zero, a positive price-to-earnings ratio, and a positive recent return. The return calculation compares the prior close with the close from an…
The report summary examines whether stock momentum spreads among companies linked by industry, geography, supply chains, or similar technologies. For A-shares, it reports that portfolios formed on industry momentum had higher average monthly returns at the…
This report excerpt describes a weekly framework for monitoring profitability and business conditions across selected primary and secondary industries in China's CITIC classification. It tracks trailing-twelve-month return on equity and places current…
This guide explains how long-short equity portfolios combine stocks expected to rise with stocks expected to fall. It discusses possible return sources, including security selection, market timing, and exposure to factors such as value, growth, momentum, and…
This Chinese-language post describes a stock screen combining price amplitude, recent actual turnover, and a moving-average trend condition. It selects shares with amplitude above a threshold, turnover within a specified band, and the shorter moving average…
The document summarizes a slack-based manager efficiency index (SMEI) for evaluating mutual fund managers as a whole rather than judging each fund in isolation. The data envelopment analysis framework treats risk, portfolio turnover, and a combined…
This meetup note surveys several topics in equity quant work. It outlines reversal-factor ideas based on recent returns, technical indicators such as RSI and Bollinger Bands, and fundamental changes such as valuation or a return to profitability. It suggests…
This document outlines a China A-share stock selection strategy using market, size, and book-to-market factors. It starts with constituents of a benchmark index, filters out stocks that are suspended or marked as special treatment, and uses a historical…
This assignment outlines a style-rotation process built from three stock strategies: small-capitalization, below-book-value, and oversold-rebound approaches. After backtesting each strategy, it proposes saving the return and position series, then comparing…
The strategy screens Chinese stocks using three conditions: price amplitude above 1, tradable share float no greater than 5.5 billion shares, and a positive return over the prior seven trading sessions. It describes the amplitude and positive return filters…