In this paper we examine the empirical performance of affine jump diffusion models with stochastic volatility in a time series study of crude oil prices. We compare four different models and estimate them using the Markov Chain Monte Carlo method. The support for a stochastic volatility model...

This paper investigates the role of investor attention in forecasting realized volatility for fourteen international stock markets, by means of Google Trends data, over the sample period January 2004 through November 2021. We devise an augmented Empirical Similarity model that combines three...

While it is widely agreed that Purchasing Power Parity (PPP) holds as a long-run concept the specific dynamic driving the process is largely build upon a priori economic belief rather than a thorough statistical modeling procedure. The two prevailing time series models, i.e. the exponential...

In this paper we test for the presence of fractional integration, or long memory, in the daily returns of exchange rates using ARFIMA(p,d,q) models. We consider 34 exchange rates against the US dollar (USD) covering the period April 1991 to April 2006. The results suggest that 17 exchange rates...

This paper examined the long memory features of GDP per capita data before the global financial crisis, using a sample of 26 African countries. The study employed fractional integration and tested the stability of the differencing parameter across the sample period for each country. The results...

In this paper we document that realized variation measures constructed from high-frequency returns reveal a large degree of volatility risk in stock and index returns, where we characterize volatility risk by the extent to which forecasting errors in realized volatility are substantive. Even...

The slope coefficient estimator in predictive regressions for stock returns is biased by a lagged stochastic regressor. There is also a spurious regression if the underlying expected return is highly persistent. This paper studies how the interactions between the two biases affect inferences...