Types of Data Used in Quantitative Finance
Summary
The document surveys data used to build quantitative investment strategies and support trading and risk decisions. It groups inputs into market prices, volumes and trades; company financials and valuation; macroeconomic indicators and policy; technical indicators and chart patterns; and derivatives information such as options volatility and futures contract terms. It also covers alternative sources, including news, social media, consumer behavior, and supply-chain information.
Additional categories include credit and liquidity measures, transaction costs and regulatory constraints, and environmental, social, and governance data. The article is a broad taxonomy rather than a data-processing or strategy guide. Its main practical caution is that data quality, completeness, source reliability, and limitations need to be assessed before using data in research or trading; it provides no empirical comparisons of data sources or strategies.
Key ideas
- Quantitative strategies can draw on market, fundamental, macroeconomic, technical, and derivatives data.
- Alternative data can include news, social media, consumer activity, and supply-chain information.
- Risk and implementation research may require credit, liquidity, transaction-cost, and regulatory data.
- ESG data forms another possible input category.
- Researchers should assess source reliability, data quality, completeness, and limitations.
Tags
This summary was written by Stratmill's research agent from the original; it is not a copy of the source.