This article details a Bayesian analysis of the Nile river flow data, using a simple state space model. This allows the article to concentrate on implementation issues surrounding this model. For this data set, Metropolis-Hastings and Gibbs sampling algorithms are implemented in the programming...

The major purpose of this research exercise is to assess the volatility dynamics of the stock returns of the banks of India and to determine the factor which influence and explains the stock returns. For this the two important methodologies are applied, for understanding the sensitivity of stock...

The exchange rate between the Naira and other currencies has continued to witness variability with depreciation. This variability makes it difficult to predict returns. Against this background, this paper examines the naira exchange rate vis-a-vis four other currencies. The impact of exogenous...

Risk neutral densities (RND) can be used to forecast the price of the underlying basis for the option, or it may be used to price other derivates based on the same sequence. The method adopted in this paper to calculate the RND is to firts estimate daily the diffusion process of the underlying...

In this article, the Universal Approximation Theorem of Artificial Neural Networks (ANNs) is applied to the SABR stochastic volatility model in order to construct highly efficient representations. Initially, the SABR approximation of Hagan et al. [2002] is considered, then a more accurate...

In a recent study, we present a tree methodology to evaluate the expected generalized realized variance in a general stochastic volatility model. This provides an efficient way of calculating the fair value of the strike for variance swaps. In this article, we expand the methodology to price...

This paper analyses the implementation and calibration of the Heston Stochastic Volatility Model. We first explain how characteristic functions can be used to esti-mate option prices. Then we consider the implementation of the Heston model, showing that relatively simple solutions can lead to...

This paper analyses the implementation and calibration of the Heston Stochastic Volatility Model. We first explain how characteristic functions can be used to estimate option prices. Then we consider the implementation of the Heston model, showing that relatively simple solutions can lead to...

We propose the option realized variance as an observable variable to summarize information from high-frequency option data. This variable aggregates intraday option returns from midquote prices to compute the option's total variability for a given day. Using the S&P 500 index time series and...

This research examines if there exists an appealing distribution for jump amplitude in the sense that with this distribution, the stochastic volatility double jump-diffusions (SVJJ) model would potentially have a superior option market fit while keeping a sound balance between reality and...