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Jump contagion among stock market indices : evidence from option markets

Boswijk, Herman Peter; Laeven, Roger J. A.; Lalu, Andrei; … - 2021

This paper explores the contagious propagation of jumps among international stock market indices by exploiting a rich …, time and space amplification of jumps in option markets. We develop a semi-parametric estimation procedure employing a …

Persistent link: https://www.econbiz.de/10012650140

Asymmetry in the price impact of trades in an high-frequency microstructure model with jumps

Jondeau, Eric; Lahaye, Jérôme; Rockinger, Michael - 2013

We estimate a general microstructure model of the transitory and permanent impact of order flow on stock prices. Jumps …-capitalization stocks traded on the Euronext-Paris Bourse. We find that, at tick frequency, the overnight return, the intraday jumps, and … microstructure model explains on average 47.7% of the total variation. Once jumps are filtered and parameters are estimated in real …

Persistent link: https://www.econbiz.de/10010256970

Leverage effect in energy futures

Kristoufek, Ladislav - Institut für Volkswirtschaftslehre, … - 2014

We propose a comprehensive treatment of the leverage effect, i.e. the relationship between returns and volatility of a specific asset, focusing on energy commodities futures, namely Brent and WTI crude oils, natural gas and heating oil. After estimating the volatility process without assuming...

Persistent link: https://www.econbiz.de/10010958896

Leverage effect in energy futures

Kristoufek, Ladislav - 2014

Persistent link: https://www.econbiz.de/10010398704

Leverage effect in energy futures

Kristoufek, Ladislav - 2014

Persistent link: https://www.econbiz.de/10010407507

Estimation of Stochastic Volatility Models by Nonparametric Filtering

Kanaya, Shin; Kristensen, Dennis - School of Economics and Management, University of Aarhus - 2010

A two-step estimation method of stochastic volatility models is proposed: In the first step, we estimate the (unobserved) instantaneous volatility process using the estimator of Kristensen (2010, Econometric Theory 26). In the second step, standard estimation methods for fully observed diffusion...

Persistent link: https://www.econbiz.de/10008677955

Estimating a semiparametric asymmetric stochastic volatility model with a Dirichlet process mixture

Jensen, Mark J.; Maheu, John M. - In: Journal of Econometrics 178 (2014) P3, pp. 523-538

We extend the asymmetric, stochastic, volatility model by modeling the return-volatility distribution nonparametrically. The novelty is modeling this distribution with an infinite mixture of Normals, where the mixture unknowns have a Dirichlet process prior. Cumulative Bayes factors show our...

Persistent link: https://www.econbiz.de/10010730133

Martingale unobserved component models

Shephard, Neil - Department of Economics, Oxford University - 2013

I discuss models which allow the local level model, which rationalised exponentially weighted moving averages, to have a time-varying signal/noise ratio. I call this a martingale component model. This makes the rate of discounting of data local. I show how to handle such models...

Persistent link: https://www.econbiz.de/10011004138

Estimating a Semiparametric Asymmetric Stochastic Volatility Model with a Dirichlet Process Mixture

Jensen, Mark J.; Maheu, John M. - Rimini Centre for Economic Analysis (RCEA) - 2012

In this paper we extend the parametric, asymmetric, stochastic volatility model (ASV), where returns are correlated with volatility, by flexibly modeling the bivariate distribution of the return and volatility innovations nonparametrically. Its novelty is in modeling the joint, conditional,...

Persistent link: https://www.econbiz.de/10010555040

Estimating a Semiparametric Asymmetric Stochastic Volatility Model with a Dirichlet Process Mixture

Jensen, Mark J; Maheu, John M - University of Toronto, Department of Economics - 2012

Persistent link: https://www.econbiz.de/10010556277