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.
2,013 documents
This notebook describes adapting Diffusion-TS to generate synthetic ETF return sequences. Its denoiser predicts the clean sequence as a sum of polynomial trend, Fourier seasonal, and residual components, while a combined time-domain and Fourier-domain loss…
This analysis profiles a fixed universe of 100 ETFs across nine asset groups. It checks coverage by fund and year, confirms that the price panel matches the group configuration, reviews nulls and OHLC ordering, and compares trading volume across groups. It…
This notebook demonstrates a shared OHLCV interface across Yahoo Finance, a long-history U.S. equity archive, and FRED macroeconomic series. It builds an ETF universe for a later rotation case study, shows how to combine historical and current sources, and…
This notebook builds the long-only, fully invested mean-variance framework for a diversified ETF universe. It constructs feasible portfolios and an efficient frontier, then solves for maximum-Sharpe and minimum-variance weights using estimated returns and…
This notebook compares linear models for predicting ETF returns from overlapping price-derived features. Since multiple return horizons and indicator families can encode similar information, ordinary least squares may assign unstable opposing coefficients to…
This notebook compares six long-only portfolio allocations for a multi-asset ETF universe. It uses Ledoit–Wolf covariance shrinkage to reduce the sampling variation that can destabilize optimization, and compares maximum Sharpe, minimum variance, risk…
This notebook shows how to use PCMCI to search for delayed relationships among ETF and volatility returns without specifying a causal graph in advance. It contrasts panel-based conditional-independence testing with pairwise Granger tests, which account for a…
This configuration defines a weekly futures research universe spanning equity indexes, government bonds, energy, metals, currencies, agriculture, and livestock. It sets Friday settlement as the decision snapshot and Monday open as the execution point. The…
This dataset guide describes a collection of continuous CME futures contracts spanning equity indexes, rates, energy, metals, currencies, agriculture, and livestock. It explains the hourly source data and derived daily frequency, multiple contract tenors,…
This notebook compares linear models on ETF features built from overlapping return windows and related momentum, volatility, and oscillator measures. Such predictors are collinear, making ordinary least squares coefficients unstable. The experiment fits…
This chapter maps financial data across market, fundamental, and alternative sources, then compares how asset classes shape what prices, liquidity, and observations mean. It emphasizes that timestamps, adjustments, identifiers, and revisions are part of a…
This notebook inventories model-based feature columns across nine market case studies by reading Parquet schemas rather than loading full datasets. It excludes identifier fields, counts columns by market, and assigns feature families through tokens in their…
This record documents a multi-agent research run on whether the United States would enter a recession by the end of 2026 under a specified resolution rule based on consecutive quarterly GDP contractions or an NBER recession date. Three agents searched for…
This notebook uses a Gaussian mixture model to group months by the joint behavior of nine factor and asset-class return series. It standardizes monthly observations, drops months with missing values, and compares candidate cluster counts using BIC, AIC, and…
This document describes a daily ETF dataset intended as a candidate pool for momentum and cross-asset research. It covers nine categories, including US and international equities, fixed income, commodities, specialty funds, and currencies. Data is sourced…
This notebook develops features that require multiple asset series. It compares Engle-Granger and Johansen tests for cointegration, explains why co-movement alone does not imply a stationary spread, and estimates hedge ratios both with a full-sample…
The document describes using the Graph-based Coalition Structure Generation algorithm, GCS-Q, to cluster assets represented as a signed, weighted graph of return correlations. The motivation is that common clustering approaches can lose information when they…
The document presents a multi-asset model with two investor types: fundamentalists, who respond to perceived differences between stock prices and fundamentals, and chartists, who use price trends. Both groups make investment decisions by maximizing constant…
The document studies long-term investment in a stochastic factor model when investors maximize robust expected power utility. Robustness means accounting for an adverse alternative model, rather than optimizing only under a single assumed model. The authors…
This study considers how to allocate trend-following strategies across multiple assets whose returns may be correlated. Under Gaussian-market assumptions and linear strategies, it derives formulas for portfolio mean and variance, then uses them to form a…
DeepUnifiedMom is a portfolio construction framework that combines time-series momentum signals across multiple time horizons. It uses multi-task learning with a multi-gate mixture-of-experts architecture to form unified portfolios, aiming to capture…
The paper analyzes equilibrium pricing for a positive, mean-reverting asset in continuous time when investors differ in their beliefs about the speed of mean reversion and the asset’s long-run mean. Its central result is a condition for the existence of…
This paper compares fixed stock-and-bond and stock, bond, and gold allocations with long-only dynamic portfolios that may also hold cash. The portfolios use public data, rebalance monthly, and are assessed using return, volatility, excess Sharpe ratio,…
This work connects the rough volatility observed in financial assets with the microscopic dynamics linking multiple asset prices. While much prior modeling has focused on a single asset, the authors investigate how multivariate rough volatility models can…