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
The primer frames the metaverse as a gradual shift toward spending more time in persistent virtual worlds, complementing and potentially succeeding mobile applications. It argues that richer spatial context could increase engagement, while acknowledging that…
This overview compares free and paid sources for historical market data accessed through Python APIs. It describes retrieving single and multiple instruments, using daily or intraday frequencies, and handling several asset classes, with examples involving…
The article introduces derivatives as contracts whose value depends on an underlying asset, index, or rate. It describes forwards, futures, options, and swaps, explaining basic contract features such as long and short positions, strike prices, option…
The document outlines a conference about artificial intelligence, machine learning, and sentiment analysis in financial services. It describes research that processes news, social media, and other alternative data to classify sentiment and study its…
This article introduces Nasdaq Data Link as a source of traditional financial, ESG, and alternative datasets, then explains how to retrieve data through the Quandl API in Python. It describes dataset categories and subscription access, and outlines the…
This guide introduces index futures as standardized contracts linked to stock indexes, generally settled in cash rather than through delivery of constituent shares. It illustrates settlement by multiplying the change between the agreed index level and the…
The document outlines a framework for deciding whether to expand algorithmic trading into another country or exchange. It groups the assessment into four considerations: market access and regulation, the technical requirements for connectivity, traded…
This broad primer surveys financial markets, trading styles, instruments, analysis methods, risk management, trading plans, psychology, algorithmic trading, regulation, ethics, portfolio management, and company financial statements. It distinguishes…
This introduction explains portfolio management as selecting and combining assets to pursue a return objective while controlling risk. It contrasts passive, active, and aggressive management, and describes bottom-up security selection alongside top-down…
The document explains covariance and correlation as measures of how two variables move together. Covariance indicates the direction of their linear co-movement, while correlation also expresses its strength on a standardized scale from negative one to…
The document explains the real effective exchange rate (REER) as an inflation-adjusted, trade-weighted measure of a currency against a basket of trading partners. It describes how a country’s REER can help assess changes in currency strength and trade…
The article classifies market events as black swans (unexpected), grey swans (possible but unlikely), or white swans (expected), then considers how they may affect stocks, bonds, and derivatives. It suggests that strategies should reflect how much warning…
This project outlines a market-neutral long-short portfolio framework that selects assets with cross-sectional momentum and compares equal weighting, inverse-volatility weighting, Hierarchical Risk Parity (HRP), and Hierarchical Equal Risk Contribution…
The document introduces portfolio management when the portfolio’s components are trading strategies as well as assets. It contrasts equal weighting as a starting point with Markowitz efficient-frontier allocation, which balances return against a risk…
In this interview, trader Nikolas Pareschi recounts his move from discretionary trading to algorithmic research and describes how he developed ideas through finance papers and statistical testing. He emphasizes that many indicators and methods fail…
This introductory guide explains how financial markets connect buyers and sellers, how participants access exchanges through brokers or direct market access, and what instruments trade there. It introduces stocks and the distinction between primary and…
Steven Downey describes using quantitative research to test investment beliefs rather than accepting them without evidence. His examples include examining whether gold behaves as an inflation hedge, whether oil and an energy company’s shares are related, and…
Tomás García-Purriños describes a medium- to long-term approach to multi-asset investing that combines technical indicators with fundamental measures, especially macroeconomic data, and indicators of investor sentiment and market flows. He argues that no…
This article explains how academic and industry research can generate ideas for systematic trading. It describes a screening approach that considers whether a strategy can be implemented, the length of its backtest, and the overall soundness of its evidence…
This article explains how exchange-traded funds pool securities into units traded on exchanges, then surveys market, sector, dividend, style, commodity, currency, and bond ETFs. It describes their potential uses, including broad diversification, targeted…
The article explains cloud computing as internet-delivered access to computing resources and outlines service models—software, platform, and infrastructure—as well as private, hybrid, and public deployment. It describes possible trading uses, including…
This overview curates Python resources for quantitative and algorithmic trading rather than developing one strategy. The listed topics include market-data retrieval and visualization, technical indicators, VaR estimation, machine-learning classification,…
The article surveys factors that can shape algorithmic strategy design across cash equities, bonds, derivatives, commodities, and foreign exchange. It presents general practices such as testing strategies on in-sample and out-of-sample data, setting…
This project describes a long-only portfolio that reallocates capital among a small basket of sector or asset ETFs and cash on a fixed weekly schedule. It compares classifier-based allocations with a rule-based momentum baseline. The baseline averages recent…