Narrow search
Showing 1 - 10 of 12,174
Cover Image
How precise is the finite sample approximation of the asymptotic distribution of realised variation measures in the presence of jumps?
Veraart, Almut - In: AStA Advances in Statistical Analysis 95 (2011) 3, pp. 253-291
Persistent link: https://www.econbiz.de/10009324602
Cover Image
Jump tails, extreme dependencies, and the distribution of stock returns
Bollerslev, Tim; Todorov, Viktor; Li, Sophia Zhengzi - In: Journal of Econometrics 172 (2013) 2, pp. 307-324
. Our estimates are based on in-fill asymptotics for directly identifying the jumps, together with Extreme Value Theory (EVT … that the distributions of the systematic and idiosyncratic jumps are both generally heavy-tailed and close to symmetric …
Persistent link: https://www.econbiz.de/10011052337
Cover Image
Estimation of Jump Tails
Bollerslev, Tim; Todorov, Viktor - Duke University, Department of Economics - 2010
with in-fill asymptotic arguments for uniquely identifying the \large" jumps from the data. The estimation allows for very …
Persistent link: https://www.econbiz.de/10008549046
Cover Image
The role of jumps in volatility spillovers in foreign exchange markets: meteor shower and heat waves revisited
Neely, Christopher; Lahaye, Jerome - Federal Reserve Bank of St. Louis - 2014
We investigate the role of jumps in transmitting volatility between foreign exchange markets (Engle, Ito, and Lin, 1990 … different implications for the impact of jumps on exchange rate volatility transmission. Specifically, isolated and successive … jumps have opposite predictions for future volatility. Although the realized volatility literature finds that heat wave …
Persistent link: https://www.econbiz.de/10010951615
Cover Image
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
Cover Image
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
Cover Image
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
Cover Image
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
Cover Image
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
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/10010556277
Cover Image
Martingale unobserved component models
Shephard, Neil - Economics Group, Nuffield College, University of Oxford - 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 effectively using...
Persistent link: https://www.econbiz.de/10010823426