RiskPortfolios is an R package for constructing risk-based portfolios. It provides a set of functionalities to build mean-variance, minimum variance, inverse-volatility weighted (Leote De Carvalho, Lu, and Moulin (2012)), equal-risk-contribution (Maillard, Roncalli, and Teïletche (2010)),...

This research note describes the construction of news-based Economic Policy Uncertainty (EPU) indices for Flanders, Wallonia and Belgium. The indices are computed from January 2001 until May 2020. Important domestic and more global events coincide with spikes in the indices. The COVID-19...

Shariah law prohibits investments in equities of companies for which interest income is a considerable source of revenue. In practice this is often enforced by prohibiting investments in firms for which the reported interest-based revenues exceed a predetermined percentage of the firm's total...

The technical conversion factor (TCF) is a survey-based estimate of the percentage of carcass weight obtained per unit of live weight. Practitioners and researchers have used it to predict the corresponding price ratio. We use both in-sample regressions and out-of-sample forecasting analysis to...

We use intraday data to estimate the daily foreign exchange exposure of U.S. multinationals and show that macroeconomic news affects these firms’ foreign exchange exposure. News creates a substantial shift in the joint distribution of stock and exchange rate returns that has both a...

Modern calculation of textual sentiment involves a myriad of choices for the actual calibration. We introduce a general sentiment engineering framework that optimizes the design for forecasting purposes. It includes the use of the elastic net for sparse data-driven selection and weighting of...

We perform a large-scale empirical study to compare the forecasting performance of single-regime and Markov-switching GARCH (MSGARCH) models from a risk management perspective. We find that, for daily, weekly, and ten-day equity log-returns, MSGARCH models yield more accurate Value-at-Risk,...

Financial risk managers routinely use non-linear time series models to predict the downside risk of the capital under management. They also need to evaluate the adequacy of their model using so-called backtesting procedures. The latter involve hypothesis testing and evaluation of loss functions....

We describe the package MSGARCH, which implements Markov-switching GARCH models in R with efficient C++ object-oriented programming. Markov-switching GARCH models have become popular methods to account for regime changes in the conditional variance dynamics of time series. The package MSGARCH...