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 article examines how benchmark choice affects estimates of active mutual fund skill. It distinguishes investable index benchmarks from factor-based benchmarks, arguing that omitted common risks can bias factor-model alpha, while choosing the wrong index…
The article reviews how benchmark choice affects estimates of active mutual fund performance. It argues that factor benchmarks and investable index benchmarks are not necessarily equivalent: omitted common risks can make factor-model alpha misleading, while…
The document summarizes a research approach that reframes asset allocation as factor allocation. It selects macroeconomic and style factors, estimates each asset class’s exposure, and builds a factor-mimicking portfolio for each factor. It then forecasts…
The document describes a portfolio stage in a systematic trading framework that converts subsystem positions into portfolio-level positions. It applies instrument weights and a diversification multiplier, optionally scales positions with a risk overlay, then…
This report summary studies whether mutual funds that performed relatively well continue to do so, and whether weak performers remain weak. It defines persistence through the serial relationship in a fund’s Sharpe ratios: each month, it calculates Sharpe…
This general guide links crypto market volatility to small market size, speculation and sentiment, regulatory developments, and changes in the global economy. It recommends researching trades, learning from past mistakes, following a plan, and accepting that…
This stock-selection note combines three conditions: MACD above its zero line, three consecutive declining sessions, and a positive return over the prior ten days capped below 35%. The proposed interpretation is that the MACD condition retains stocks with…
This analysis examines Bitcoin’s role in a diversified portfolio before and after the market’s financialization, using 2013–2017 and 2018–2023 as separate periods. It compares historical returns, volatility, drawdowns, and correlations, then applies…
The article argues that greater differences among stocks can improve the opportunity set for systematic equity strategies. When company returns, sectors, and factors diverge, models can rank securities using valuation, momentum, quality, earnings revisions,…
This A-share stock selection example screens for companies meeting three stated criteria: profit growth above 15%, return on equity above 15% for three consecutive years, and a price-to-earnings ratio below 35. The implementation treats profit growth, return…
The document describes a study of four MSCI smart beta equity indexes and a market weighted benchmark. It uses principal component analysis (PCA) to separate shared market movements from strategy specific components, then regresses those components on Fama…
This paper summary describes a reinforcement-learning approach to continuous-time mean-variance portfolio selection. It frames the problem as entropy-regularized relaxed stochastic control, aiming to balance theoretical tractability with practical…
This Chinese-language example describes a value-oriented stock selection strategy that refreshes its portfolio every 30 trading days. It selects stocks with positive price-to-book ratios below 1.5 and positive price-to-earnings ratios below 15, provided they…
This summary of a Chinese financial-engineering report examines whether Northbound capital flows can inform A-share timing and portfolio selection. It describes fixed daily and weekly inflow or outflow thresholds, then a dynamically adjusted timing indicator…
This document is a categorized directory of software libraries and learning resources used in quantitative finance. Its sections span numerical computing and time-series data, financial instrument pricing, technical indicators, trading and backtesting,…
These course notes discuss practical ways to follow a stock strategy built around pullbacks after strong stocks hit their price limits and later rebound with market sentiment. They caution that entering after a strategy has recently risen can mean buying…
This configuration describes a Qlib workflow that trains a CatBoost model on Alpha360 features for China’s CSI 500 universe. Its label is a forward close-to-close return, normalized cross-sectionally after missing labels are dropped. The data is divided into…
This guide explains how to split one live futures account into multiple locally managed strategy accounts with TqSdk. Each strategy account keeps its trading data separate across sessions, allowing positions, orders, funds, and profit and loss to be viewed…
These notes summarize a systematic approach to trading that begins with personal goals, constraints, and psychological tendencies. They review common judgment errors in system design, testing, and live execution, including overfitting, hindsight bias, seeing…
This research summary examines whether factor crowding measures can help time factor returns or adjust multi-factor portfolio weights in Chinese equities. It constructs eight relative crowding indicators across valuation spreads, pairwise correlations,…
This research overview examines the development and current state of China’s pension arrangements, alongside the management of pension assets. It organizes retirement provision into three pillars: basic public pensions, occupational plans such as enterprise…
The discussion explains why a small-cap daily strategy may signal a full exit on one day and then recommend buying the same stocks in a new task the next day. The response attributes this to daily portfolio recalculation: if the selection changes from one…
The document outlines crypto portfolio diversification as a way to reduce dependence on any one asset and manage exposure to a volatile market. It suggests spreading investments across cryptocurrencies, market sectors, and strategies, with attention to how…
This research summary argues that conventional momentum is a weak alpha signal in the Chinese stock market and proposes rebuilding it from intraday returns. The approach divides each trading day’s price change into five time segments, then recombines the…