A Hidden Markov Model (HMM) is used to model the VIX (the Cboe Volatility Index). A 4- state Gaussian mixture is fitted to the VIX price history from 1990 to 2022. Using a growing window of training data, the price of the S&P500 is predicted and two trading algorithms are presented, based on the...

In this paper, a method is introduced for approximating the likelihood for the unknown parameters of a state space model. The approximation converges to the true likelihood as the simulation size goes to infinity. In addition, the approximating likelihood is continuous as a function of the...

Volatility is a central tenet of financial markets, impacting a wide range of investors’ daily activities, including risk management, portfolio construction and option pricing. To improve their investment decisions, investors are spending considerable time and effort on finding new ways to...

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...

We perform a comprehensive Monte Carlo comparison between nine procedures available in the literature to detect jumps in financial assets proposed by Barndorff-Nielsen and Shephard (2006), Andersen et al. (2007), Lee and Mykland (2008), A¨ıt-Sahalia and Jacod (2008), Jiang and Oomen (2008),...

The interaction of volatility between the financial markets and gold market is analyzed. The volatility of the price of gold in euros, the price of gold in dollars, the U.S. industrial production índex, the S&p500 index, the VIX índex and the PSI20 index for a time horizon between January 1993...

In the past decades, there has been an unprecedented increase in cross border transactions between countries in terms of goods and financial flows. This integration has been fuelled by search of lower risk investments, risk diversification, search for cost effective and more efficient factors of...

High frequency financial data allows us to learn more about volatility, volatility of volatility and jumps.  One of the key techniques developed in the literature in recent years has been bipower variation and its multipower extension, which estimates time-varying volatility robustly to...

This paper investigates sensitivity of U.S. natural gas price to crude oil price changes, using time-varying coefficient models. Identification of the range of variation of the sensitivity of natural gas price to oil price change allows more accurate assessment of upper and minimum risk levels...

This is a study to investigate the exchange rate volatility and it impacts on international trade growth: evidence from Bangladesh. To establish the empirical relationship between exchange rate volatility and impact on international trade growth in Bangladesh, different quantitative techniques...