Edoardo Otranto

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The transmission mechanisms of volatility between markets can be characterized within a new Markov Switching bivariate model where the state of one variable feeds into the transition probability of the state of the other. A number of model restrictions and hypotheses can be tested to stress the role of one market relative to another (spillover,(More)
In the field of financial time series analysis it is widely accepted that the returns (price variations) are unpredictable in the long period [1]; nevertheless, this unappealing constraint could be somehow relaxed if sufficiently short time intervals are considered. In this paper this alternative scenario is investigated with a novel methodology, aimed at(More)
* The first results of this work have been presented at the final meeting of the research project " Modelli stocastici e metodi di simulazione per l'analisi di dati dipendenti " held at Campobasso (Italy) – 28th and 29th April 2004 – and benefited of the discussion arisen there. The authors are solely responsible of any remaining error. Abstract The problem(More)
This article includes a unique data set of a balanced daily (Monday, Tuesday and Wednesday) for oil and natural gas volatility and the oil rich economies' stock markets for Saudi Arabia, Qatar, Kuwait, Abu Dhabi, Dubai, Bahrain and Oman, using daily data over the period spanning Oct. 18, 2006-July 30, 2015. Additionally, we have included unique GAUSS codes(More)
Several models have been developed to capture the dynamics of the conditional correlations between time series of financial returns, but few studies have investigated the determinants of the correlation dynamics. A common opinion is that the market volatility is a major determinant of the correlations. We extend some models to capture explicitly the(More)