A substitution effect takes place when two or more explanatory variables share a substantial amount of information (predictive power).Under the presence of substitution effects, feature importance methods may not be able to determine robustly which variables are significant.This presentation...

Many problems in finance require the clustering of variables or observations. Despite its usefulness, clustering is almost never taught in Econometrics courses. In this seminar we review two general clustering approaches: partitional and hierarchical

Two random variables are codependent when knowing the value of one helps us determine the value of the other. This should not me confounded with the notion of causality.Correlation is perhaps the best known measure of codependence in econometric studies. Despite its popularity among economists,...

We measure the loss potential of Hedge Funds by combining three market risk measures: VaR, Draw-Down and Time Under-The-Water. Calculations are carried out considering three different frameworks regarding Hedge Fund returns: i) Normality and time-independence, ii) Non-normality and...

We develop a novel ranking methodology to rank the market forecaster. In particular, we distinguish forecasts by their specificity, rather than considering all predictions and forecasts equally important, and we also analyze the impact of the number of forecasts made by a particular forecaster....

Finance cannot become a rigorous science (in the Popperian or Lakatosian sense), however it can still operate as an “industrial science”. This article describes the scientific method by which industrial finance discovers through experimentation, and avoids false discoveries

This paper introduces the Hierarchical Risk Parity (HRP) approach. HRP portfolios address three major concerns of quadratic optimizers in general and Markowitz's CLA in particular: Instability, concentration and underperformance.HRP applies modern mathematics (graph theory and machine learning...

Financial economics is a surprisingly prolific, topic redundant, asocial field, where most papers go largely ignored. Author collaboration improves scientific output, and yet financial economics seems to be one of the least cooperative empirical fields. If these trends continue, financial...

Empirical Finance is in crisis: Our most important discovery tool is historical simulation, and yet, most backtests and time series analyses published in journals are flawed. The problem is well-known to professional organizations of Statisticians and Mathematicians, who have publicly criticized...

With the advent in recent years of large financial data sets, machine learning and high-performance computing, analysts can backtest millions (if not billions) of alternative investment strategies. Backtest optimizers search for combinations of parameters that maximize the simulated historical...