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
The study summary describes estimating bond fund asset exposures from externally available data when reported holdings are delayed, infrequent, and incomplete. Its central method is regression: fund returns are related to price-weighted asset returns, using…
This notebook demonstrates an end-to-end Qlib workflow for a China-market stock ranking model. It initializes Qlib data, uses the CSI 300 universe and Alpha158 features, and trains a LightGBM model on historical data with separate training, validation, and…
This essay defines quantitative investing as using mathematical methods, data, and factors to guide security selection and trading. It groups approaches by time-series versus cross-sectional decisions, by signal source such as price and volume factors or…
This report summary outlines the structure of the U.S. retirement system and the investment choices available through employer plans and individual retirement accounts. It describes these arrangements as part of a broader retirement landscape and notes that…
This research digest reviews two portfolio topics. The first concerns Shiller’s cyclically adjusted price-to-earnings ratio (CAPE): it can help forecast long-run equity returns as valuations tend to mean-revert, but its short-term signal is unreliable when…
The article describes a daily, long-only ETF rotation system that applies a five-day and a 42-day closing-price moving average to each asset. Crossovers generate buy and sell decisions, while available capital is allocated equally among positions with buy…
This report discusses fixed-amount periodic investing in funds as a way to align contributions with investor cash flows and reduce the pressure to time volatile equity markets. It distinguishes investing an existing balance from investing new contributions…
The post describes a simple random stock-selection process: buy ten stocks, hold them for five days, sell the two weakest performers, then randomly choose two replacements and repeat. It frames the strategy as a challenge to expert stock picking and notes…
This event-driven equity strategy buys stocks at the open after financial results are announced, selecting companies whose year-over-year net profit attributable to parent shareholders has grown by more than 30%. Eligible stocks are ranked by growth, and the…
This educational article explains a crypto bubble as a rapid price rise driven by investment enthusiasm and expectations of quick gains, followed by the possibility of a sharp decline. It attributes bubble formation to new investors, fear of missing out,…
This report examines whether removing stocks selected by high-frequency multi-factor short portfolios can improve a CSI 300 index-enhancement strategy. It compares three approaches: combine standardized factor scores, use a regression model to forecast…
The document explains the correlation coefficient as a measure of how two financial instruments move together. Values near positive one indicate similar movement, values near negative one indicate opposite movement, and values around zero indicate little…
Fundamental quantitative investing applies statistical methods and algorithms to company accounts, industry information, and macroeconomic data to rank stocks by estimated value or quality. The document describes analyzing profitability, financial strength,…
This report examines changes in concentrated holdings among Chinese active equity funds using quarterly disclosures and a daily estimate of fund exposure to a core group of crowded stocks. It compares the core group’s holdings over time, separates changes in…
This MT5 indicator summarizes closed-deal history from the trading account and displays the results in a chart panel. It reads deals through the terminal’s history functions, aggregates them over a configurable lookback period, and refreshes on a timer. It…
This short BigQuant assignment describes a daily stock-ranking approach built from a combination of total equity and trailing-twelve-month average return on equity. Each day, the strategy holds stocks with comparatively high values of the combined factor. It…
This overview introduces three types of company data associated with FactSet: a six-level product and service based industry classification, company-to-company supply-chain relationships, and geographic revenue exposure. The classification is presented as a…
The speaker outlines a systematic trend-following approach that uses historical testing to support a rules-based process for entries, exits, profit taking, and position sizing. The strategy seeks to capture medium-term moves across a broad set of…
This China equity strategy ranks stocks cross-sectionally using circulating market capitalization and earnings per share, combining the rankings into a total score and sorting from low to high. It excludes special-treatment and suspended stocks, requires…
This review of research on equity factor investing explains why low unconditional correlations between factors may not provide protection when macroeconomic conditions deteriorate. It describes selecting fast-moving state variables that reflect expectations…
This report examines why investment portfolios turn over, how to manage that turnover, and how turnover control affects portfolio outcomes. It frames the drivers across the research and trading process: alpha changes influence target holdings, optimization…
The document briefly introduces a multi-factor investment platform, focusing on how to estimate stock and portfolio factor exposures. Stock exposures are derived from database values such as price-to-earnings and price-to-book ratios, then cleaned and…
This weekly competition report presents diagnostic summaries for the ten highest-ranked submitted factors and tracks a China 1000 index-enhancement portfolio. Factor diagnostics include average exposures to BARRA style factors and sector-level average Rank…
This overview introduces reinforcement learning as a way to learn sequential decisions by interacting with an environment and maximizing accumulated reward. It outlines the agent, environment, policy, and reward, and explains how delayed feedback differs…