In this paper we provide a unified methodology for conducting likelihood-based inference on the unknown parameters of a general class of discrete-time stochastic volatility (SV) models, characterized by both a leverage effect and jumps in returns. Given the nonlinear/non-Gaussian state-space...

Despite decades of research, the parameters of the Phillips curve (old or new) remain uncertain, because their estimation is fraught with endogeneity issues: confounding from supply shocks, unobserved inflation expectations and an unobserved output gap. In this work, we use sequences of past...

This paper explores the application of machine learning (ML) techniques to nowcast the monthly year-over-year growth rate of both total and non-primary GDP in Peru. Using a comprehensive dataset that includes over 170 domestic and international predictors, we assess the predictive performance of...

Consider the problem of smoothing a time series for extracting its low frequency characteristics, collectively called its trend. This paper proposes a competitive, to existing methods, solution in choosing the optimal degree of smoothing based on the distribution of the residuals from the smooth...

In this paper I consider the problem of optimal linear filtering, smoothing and trend extraction for m-period differences of processes with a unit root. Such processes arise naturally in economics and finance, in the form of rates of change (price inflation, economic growth, financial returns)...

Since the 1970s the characteristics of international business cycles have changed and deeper economic integration has modified the features of cross-country comovement. We formally test for correlation shifts in measures of real economic activity and economic/financial integration. In Europe we...

We introduce a statistical test for comparing the predictive accuracy of competing copula specifications in multivariate density forecasts, based on the Kullback-Leibler Information Criterion (KLIC). The test is valid under general conditions: in particular it allows for parameter estimation...

This paper proposes a new nonparametric mixed data sampling (MIDAS) model and develops a framework to infer clusters in a panel regression with mixed frequency data. The nonparametric MIDAS estimation method is more flexible and substantially simpler to implement than competing approaches. We...

We investigate for the first time the spot rate dynamics for Very Large Gas Carriers (VLGCs) by means of multrifractal detrended fluctuation analysis (MF-DFA) and rescaled range (R/S) analysis. Both methods allow for a rigorous statistical analysis of the freight process by detecting...

Controlling and managing potential losses is one of the main objective of the Risk Management. Following Ben Ameur and Prigent (2007) and Chen et al. (2008), and extending the first results by Hamidi et al. (2009) when adopting a risk management approach for defining insurance portfolio...