The Problem with Modern Signal Processing in Finance, joint with Taylor Canann and Patrick Opitz
This paper sets out to critique the current use of signal processing or statistical filtering used in finance and offer an alternative that is effective and easy to use. In econometrics, time series offers many methods of analysis. Signal Processing is a method of analysis done using a differing type of model or filter. Studying financial markets or product filters can provide meaningful insight. Time series analysis can provide insight into market predictions such as forecasting future stock prices and volatility. Filters do this job by providing high accuracy in the estimation and reduce errors in the model. The benefit is known in engineering, statistics, and econometrics; however, the full capacity of these signal processing tools are not used in finance.
Nowcasting Argentina's GDP: A Comparison of Multiple Methodologies, joint with NĂ©stor Grion and Pablo Roccatagliata
Trade Protection and Capital Misallocation: an application to Argentina