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
The document explains cross-sectional stock momentum: rank stocks by their prior returns, then buy recent winners and sell recent losers. Its example uses a 12-month formation period that excludes the latest month to reduce microstructure and liquidity…
This document describes an industry-level stock strategy based on proximity to the 52-week high. Each month, it calculates each stock’s price-to-high ratio, then forms market-cap-weighted averages for 20 industries. It buys stocks in the six industries with…
This document describes a long-short equity factor that ranks nonfinancial U.S. stocks by a composite measure of earnings quality. It combines cash flow relative to reported earnings, return on equity, cash flow relative to assets, and debt relative to…
The document describes the equity size effect: the claim that smaller-capitalization stocks can outperform larger stocks. Its basic portfolio sorts NYSE, AMEX, and NASDAQ stocks by market value into deciles, then buys the smallest decile and shorts the…
The document describes a stock return premium around scheduled earnings announcements and a strategy that uses past trading volume to identify stocks expected to announce. At the start of each month, stocks are ranked by the concentration of their volume…
This document describes a country-level equity value strategy based on Shiller’s cyclically adjusted price-to-earnings ratio (CAPE). At each year-end, it ranks 32 countries by CAPE and invests equally in the least expensive third, provided their CAPE is…
The document outlines a global tactical allocation strategy that combines value and momentum signals across asset classes. It ranks investable markets using 12-month momentum, 1-month momentum, and an asset-specific valuation measure: earnings yield for…
The document describes a process for turning academic finance research into systematic strategy summaries. Strategies are grouped by market and theme, with trading rules, rebalancing schedules, performance and risk characteristics, and references to…
The document describes a process for turning academic finance research into systematic strategy summaries. Strategies are grouped by market and theme, with trading rules, rebalancing schedules, performance and risk characteristics, and references to…
The document describes a process for turning academic finance research into systematic strategy summaries. Strategies are grouped by market and theme, with trading rules, rebalancing schedules, performance and risk characteristics, and references to…
The document describes a process for turning academic finance research into systematic strategy summaries. Strategies are grouped by market and theme, with trading rules, rebalancing schedules, performance and risk characteristics, and references to…
This document describes a quarterly, long-only US equity strategy modeled on a value ETF. It starts with NYSE stocks, removes financial firms, ADRs, and REITs, then screens for liquidity using average dollar volume over a 90-day window. Among eligible…
This screen combines a daily amplitude threshold of at least 1 with return on equity above 15% in each of the last five years, then looks for three consecutive down days. It joins a historical profitability filter with a short-term price pattern. The article…
This research summary examines the ChiNext 50 index through the supply chains of its constituents, arguing that sector weights alone miss how technology firms connect to suppliers and customers. It describes the index as concentrated in technology, with…
The article introduces supervised machine learning for quantitative stock selection through StockRanker, a method that predicts future returns and ranks stocks. It outlines a workflow: define and label the return target, divide observations into training and…
This tutorial outlines a workflow for developing and backtesting an end-of-day, cross-sectional momentum strategy with Moonshot. It begins with collecting daily historical equity data and selecting a universe, then moves into momentum factor research and…
The document describes a monthly strategy that combines a portfolio of smart factors with a broad US equity market proxy. It uses five factor return series based on large US stocks. For each factor, it measures one-month and twelve-month momentum, ranks the…
This notebook constructs artificial price and factor data to demonstrate the input structure expected by Alphalens and to provide a controlled setting for factor analysis. It creates daily prices for six assets with different deterministic paths, assigns…