Financial Engineering and Econometrics

Signal processing and financial engineering are seemingly different areas that share strong connections underneath. Both areas rely on the statistical analysis and modeling of systems and signals, either from the financial markets or from communication channels. In both cases, accurate characterization is essential to predict the behavior of practical algorithms and optimize their performance. The exploration of these connections reveals ways to capitalize on existing mathematical tools and methodologies developed and widely applied in the context of signal processing applications. As a matter of fact, the techniques underlying optimal strategies for reliable communications over wireless links prove to be very useful in approaching open issues and recurring problems in quantitative finance.


  • highOrderPortfolios: Design of High-Order Portfolios via Mean, Variance, Skewness, and Kurtosis

  • imputeFin: Imputation of Financial Time Series with Missing Values

  • fitHeavyTail: Mean and Covariance Matrix Estimation under Heavy Tails

  • portfolioBacktest: Automated Backtesting of Portfolios over Multiple Datasets

  • riskParityPortfolio: Design of Risk Parity Portfolios

  • sparseIndexTracking: Design of Portfolio of Stocks to Track an Index