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 document summarizes research on forecasting the correlation between stock and bond returns, a quantity used in portfolio construction, hedging, and risk assessment. It argues that simply extrapolating historical monthly correlations can be unreliable…
This report summary describes the risk-prediction component of a multi-factor investment framework. It outlines adjustments to factor covariance estimates, including Newey–West autocorrelation correction, eigenvalue adjustment, and volatility-bias…
The report presents DFQ-2018, a structured risk model for Chinese A-shares. It combines industry and style factors to identify exposures, estimate stock-return covariance, and support portfolio performance analysis. Among its design choices, it uses a…
The report describes two steps for improving an equity alpha model: remove factors that duplicate information, then optimize the remaining signals while accounting for their correlations. It uses Fama–MacBeth regressions to screen factors and reports…
This article explains a contrarian rebalancing strategy that maintains a target allocation between cash and Bitcoin. When Bitcoin’s value rises enough to move the portfolio away from its target balance, the strategy sells some BTC; when it falls enough, it…
This short VeighNa community exchange asks whether the platform can run the same strategy separately across multiple instruments and report each instrument’s profit and loss. A respondent suggests implementing the batch process in a Jupyter notebook with a…
This report summary examines how to select timing variables and forecast equity factor returns within a multi-factor strategy. It proposes Lasso and Elastic Net regression for screening predictors and estimating factor returns. It also describes extensions…
This short strategy post describes a monthly small-capitalization stock-selection approach. On the first trading day of each month, it selects the 30 stocks with the lowest market values after excluding ST-designated stocks, ChiNext-board stocks, and Beijing…
This guide describes a workflow for exploring crypto investments: select a themed basket, compare available strategies, review each strategy's stated idea, and inspect its historical profit chart. Baskets group cryptocurrencies by a shared theme or…
This report applies a parametric portfolio policy approach to equity factor timing, using external variables to adjust factor weights. It tests the approach on Chinese A-share data and compares two ways to use information: time-series models and…
The study applies machine learning to estimate an optimal rebalancing frequency for pairs trading. It uses minute-level prices for 50 large cryptocurrencies from Binance during 2022 and 2023. For each asset pair, a simulated pairs-trading algorithm…
This Chinese-language article curates research papers and books on reinforcement learning (RL) in finance. Its examples span trading and market applications, Q-learning combined with Black–Scholes, option hedging and dynamic replication, portfolio…
The document introduces covariance as a measure of how two assets move together, then outlines a matrix-based approach to portfolio risk. It describes collecting observations for several stocks, calculating each series’ mean, subtracting that mean, and using…
The document explains how a multi-strategy backtest module combines strategies. It applies user-set weights to the return series from each strategy’s backtest and aggregates those weighted series into a single performance curve. The weight therefore applies…
This report studies whether gaps between consensus forecasts for macroeconomic indicators and their released values help explain subsequent returns across asset classes. It places the signal in an allocation framework that combines long-term strategic…
This model seeks to rotate between Chinese equity growth and value styles, represented by high and low price-to-earnings indices. It combines six signals drawn from technical conditions, domestic and overseas liquidity, and periods when equities may be…
The document explains what LumiBot’s HTML backtest tear sheet and companion machine-readable metrics file contain. It lists return and risk measures such as annualized and total return, Sharpe and Sortino ratios, return over maximum drawdown, maximum…
This learning exercise describes an investor's established approach of making long-term, recurring purchases of index ETFs, including funds tracking large-cap Chinese, Hong Kong technology, and US technology markets. The account does not specify purchase…
This brief Chinese equity strategy rebalances on the first trading day of each month. It excludes stocks designated as special treatment, as well as listings on the STAR Market and Beijing Stock Exchange, then selects the 30 stocks with the smallest market…
This study examines whether supplier and customer links help explain dependence between listed companies’ returns. It constructs a directed company network from Bloomberg relationship data, resolving cases with links in both directions by choosing the…
This configuration describes a Qlib workflow that trains a PyTorch deep neural network on Alpha158 features for CSI 300 stocks, using the Shanghai 300 index as its benchmark. It defines training, validation, and test periods, drops the VWAP feature, fills…
The report examines how factor evaluation can guide factor inclusion and, especially, factor weights in a multi-factor return model. It argues for evaluating single factors through optimized portfolios with controlled risk exposures, aiming to make measured…
This configuration specifies a Qlib workflow for training an ADARNN model on CSI 300 equities in the Chinese market. It uses Alpha360 features, robust z-score normalization with outlier clipping, feature filling for missing values, and cross-sectional rank…
These release notes describe additions to pyfolio, a toolkit for evaluating trading portfolios. New analyses include performance attribution to common factors, factor and sector risk exposures, rolling volatility, capacity, bootstrap uncertainty in…