Quantitative and Computational Finance

Affiliated Research areas

Individuals, Markets and Organisations
Microeconomics, industrial organisation, applied microeconomics

Scientific Areas

Not available

Keywords

financial risk
financial risk
Value-at-risk
bootstrapping
Quantitative Economy
Financial Econometrics
artificial intelligence
Quantitative Finance
Financial Econometrics
Financial Statistics
Quantitative Economics
Neural networks
Artificial inteligence
Derivatives
Speculative bubbles

Summary

- Financial markets: We conduct research on fixed income, equity, derivatives and international finance markets. We study market efficiency, asset diversification and portfolio theory; we employ methodologies from classical statistics, financial econometrics and computational statistics. We also investigate the microstructure of markets, the formation of speculative bubbles and the phenomena of international coupling of yields.
- Financial Risk Analysis: We do research on credit, market and operational risk analysis, having conducted several studies on corporate bankruptcy. We have also studied volatility and correlation models, implied volatility, value-at-risk, financial time series analysis. Our methodology is not only focused on parametric models; we have also developed non-parametric and non-normal models of profitability and risk.
- Machine Learning in financial risk assessment and management: Crucial advances over the last forty years in ICT, Computer Science and Machine Learning have substantially changed Data Science. This new revolution is generically known as Machine Learning and aims to develop algorithms that can make decisions independently of humans. These new methodologies include Genetic Algorithms, Cluster Analysis, Artificial Neural Networks, Regression and Classification Trees, Genetic Algorithms, and the Nearest Neighbors methodology, among others. Machine Learning has also given rise to new tools in the valuation and management of financial risk.
- Quantitative economy: We interpret and classify economic situations by means of mathematical, statistical and econometric analysis tools. This allows us to analyze and quantify the most relevant variables in economic decision making. Such quantitative studies have been carried out in macroeconomics, microeconomics and, in particular, in tourism economics. In addition to using classical quantitative techniques, we have developed other machine learning and artificial intelligence techniques.