In this paper we apply Bayesian methods to estimate a stochastic volatility model using both the prices of the asset and the prices of options written on the asset. Implicit posterior densities for the parameters of the volatility model, for the latent volatilities and for the market price of volatility risk are produced. The method involves augmenting the data generating process associated wit...

introduction: the relationship between different market levels is an essential issue in economy. understanding of linkages between different market levels will help to assess the potential impact of agricultural policies. given the importance of the vertical market relationship, the present study examines price volatility spillover in vertical market levels of iranian livestock and poultry mark...

The notion of realized volatility as a model-free measurement of the quadratic variation of the underlying log price process loses its asymptotic validity in the presence of market microstructure noise. Should microstructure contaminations be present, the summing of an increasing number of squared return data (as in the definition of the realized volatility estimator) simply entails increasing ...

This paper studies the relationship between the systematic risk of financial instruments and the volatility of their equilibrium prices in a two-period stochastic asset valuation model. Whereas there is no link between the relative risk of assets and their price volatility in standard representative-agent models with additively-separable preferences, in this model with nonseparable preferences ...

This study aims to analyze the determinants of influence oil price volatility and limits on Energy sub-sector companies listed Indonesia Stock Exchange in 2018-2021 before after Covid-19. uses Eviews 10 program as information preparation results irregular are selected see relationship between dependent independent variables which calculates (WTI), limit (PL), return assets (ROA), earnings per s...

The limitations of volatilities computed with daily data as well as simple statistical considerations strongly suggest to use intraday data in order to obtain accurate volatility estimates. Under a continuous time arbitrage-free setup, the quadratic variations of the prices would allow us, in principle, to construct an approximately error free estimate of volatility by using data at the highest...

The application of the Malliavin calculus to the computations of price sensitivities were introduced by [1] for models with deterministic volatility. In this work, we compute the Greeks, for stochastic volatility models where the underlying asset price is driven by Brownian information. We consider stochastic volatility models, since these models, unlike those with deterministic volatility, tak...

Stochastic volatility (SV) models play an important role in finance. Under these models, the volatility of an asset follows an individual stochastic process. In contrast to the GARCH model, the volatility process in the SV model is autonomous with no need to refer to the asset price. It is often assumed that the log-volatility process follows a standard ARMA process in an SV model. However, emp...

This study develops and estimates a stochastic volatility model of commodity prices that nests many of the previous models in the literature. The model is an affine three-factor model with one state variable driving the volatility and is maximal among all such models that are also identifiable. The model leads to quasianalytical formulas for futures and options prices. It allows for time-varyin...

Manufacturers launch new product models at various time increments to meet changing market requirements over time. At each design period, product design and price may change. While price decisions can be made at product launching time, redesign decisions must be made in advance. Real options theory addresses such time gap decisions. This paper presents a real options approach with a binomial la...