Robust Estimation in Nonlinear Modeling of Volatility Transmission in Stock Market S.B. Ebrahimi * Department of Industrial Engineering, K.N.Toosi University of Technology, Tehran, Iran * Email: [email protected] (Received: 12 September 2015; Revised: 8 May 2016; Accepted: 24 June 2016) Volatility transmission means the connection between different markets in a way that volatility can be tr...

A method for online estimation of the volatility when observing a stock price is proposed. This is based on modeling the volatility dynamics as a stochastic differential equation that is constructed using a technique from the control theory [1]. Identification of the model parameters using the observations is proposed afterwards [2]. It is based on some stochastic calculus. Volatility estimatio...

We study pricing under the local volatility. Our research is mainly intended for pedagogical purposes. In the first part of our work we study the local volatility modeling. We derive the local volatility formula in terms of the European call prices and in terms of the market implied volatilities. We propose and calibrate to the DAX option data a functional form for the implied volatility which ...

The two most popular equity derivatives pricing models among practitioners are the local volatility model and the Heston model. While the former has the appealing property that it can be calibrated exactly to any given set of arbitrage free European vanilla option prices, the latter delivers a more realistic smile dynamics. In this article we combine both modeling approaches to the Heston stoch...

This paper extends the existing fully parametric Bayesian literature on stochastic volatility to allow for more general return distributions. Instead of specifying a particular distribution for the return innovations, nonparametric Bayesian methods are used to flexibly model the distribution’s skewness and kurtosis while volatility dynamics follow a parametric structure. Our Bayesian approach p...

This paper offers a new approach to modeling and forecasting of nonstationary time series with applications to volatility modeling for financial data. The approach is based on the assumption of local homogeneity: for every time point, there exists a historical interval of homogeneity, in which the volatility parameter can be well approximated by a constant. The proposed procedure recovers this ...

The Real Option Theory (OR) offers a modern methodology for the valuation of an investment project because it considers the value of managerial flexibility facing project uncertainties. The present work seeks to study the deferral option value for a polypropylene petrochemical plant investment project. Perhaps the most critical step of OR is the estimation of the project volatility. This work e...

A general approach for modeling the volatility process in continuous-time is based on the convolution of a kernel with a non-decreasing Lévy process, which is non-negative if the kernel is non-negative. Within the framework of Continuous-time Auto-Regressive Moving-Average (CARMA) processes, we derive a necessary condition for the kernel to be non-negative, and propose a numerical method for ch...