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 documents
This conference trip report summarizes a talk about seeking trading signals in alternative data. Examples include satellite and drone imagery, purchase receipts, social media, industrial sensor data, agriculture, energy supply and demand, weather, and…
The document explains why futures backtests need a method for joining prices from contracts with different expiration dates. Contango and backwardation can create price gaps at the splice, so the article compares three approaches: additive Panama…
The article evaluates whether an aluminum producer’s equity and a natural gas ETF could form a mean-reverting pair, based on the role of gas in aluminum production. It tests adjusted price series with a cointegrated Augmented Dickey-Fuller procedure,…
The article introduces deep learning, explains its layered approach to learning data representations, and outlines why it may help reduce hand-built feature engineering. It discusses possible quantitative finance applications, including time-series analysis,…
This article describes how to simulate statically allocated, periodically rebalanced portfolios with QSTrader. It uses an All Weather style allocation across US equities, long and intermediate government bonds, gold, and commodities as an example, and…