This paper studies the macroeconomic effects of uncertainty shocks with an emphasis on the interaction between elevated uncertainty and credit market conditions when the economy is in different regimes (recessions vs. non-recessions). We use a smooth-transition factor-augmented vector...

This paper will provide information on what happened in the financial crisis of 2008 and how to graph volatility outside of the option market. We will investigate the causes of the financial crisis, as well as some of the social inequalities that still exist today. We will explore household...

The COVID-19 pandemic has led to enormous data movements that strongly affect parameters and forecasts from standard VARs. To address these issues, we propose VAR models with outlier-augmented stochastic volatility (SV) that combine transitory and persistent changes in volatility. The resulting...

We propose a new approach to predictive density modeling that allows for MIDAS effects in both the first and second moments of the outcome. Specifically, our modeling approach allows for MIDAS stochastic volatility dynamics, generalizing a large literature focusing on MIDAS effects in the...

It has been established in the literature that volatility of stock returns exhibits complex properties of not only volatility clustering, but also long memory, regime change, and substantial outliers during turbulent and calm periods. Hence, this paper seeks to analyze volatility spillover,...

In this research paper ARCH-type models are applied in order to estimate the Value-at-Risk (VaR) of an inflation-index futures portfolio for several time-horizons. The empirical analysis is carried out for Mexican inflation-indexed futures traded at the Mexican Derivatives Exchange (MEXDER). To...

This paper shows that the explanation of the decline in the volatility of GDP growth since the mid-eighties is not the decline in the volatility of exogenous shocks but rather a change in their propagation mechanism.

Any measure of unobserved inflation uncertainty relies on specific assumptions which are most likely not fulfilled completely. This calls into question whether an individual measure delivers a reliable signal. To reduce idiosyncratic measurement error, we propose using common information...