The Markov Tree model is a discrete-time option pricing model that accounts for short-term memory of the underlying asset. In this work, we compare the empirical performance of the Markov Tree model against that of the Black-Scholes model and Heston's stochastic volatility model. Leveraging a...

This study is designed to model and forecast Nigeria's stock market using the AllShare Index (ASI) as a proxy. By employing the Markov regime-switching autore-gressive (MS-AR) model with data from April 2005 to September 2019, the studyanalyzes the stock market volatility in three distinct...

We show that the compensation for rare events accounts for a large fraction of the average equity and variance risk premia. Exploiting the special structure of the jump tails and the pricing thereof we identify and estimate a new Investor Fears index. The index suggests both large and...

We show that the compensation for rare events accounts for a large fraction of the equity and variance risk premia in the S&P 500 market index. The probability of rare events vary significantly over time, increasing in periods of high market volatility, but the risk premium for tail events...

Daily returns of financial assets are frequently found to exhibit positive autocorrelation at lag 1. When specifying a linear AR(l) conditional mean, one may ask how this predictability affects option prices. We investigate the dependence of option prices on autoregressive dynamics under...

The aim of the paper is to compare reactions of two stock markets, the German and the French, to releases of macroeconomic fundamentals emanating from Germany and the U.S. We examine the reaction of intraday returns and volatility of the CAC40 and the DAX indices to macroeconomic surprises. We...

This paper presents the first comparison of the accuracy of density forecasts for stock prices. Six sets of forecasts are evaluated for DJIA stocks, across four forecast horizons. Two forecasts are risk-neutral densities implied by the Black-Scholes and Heston models. The third set are...