International audienceWe consider a threshold autoregressive stochastic volatility model where the driving noises are sequences of iid regurlarly random vatiables. We prove that both the right and the left tails of the marginal distribution of the log-volatility process are regularly varying with tail exponent. We also determine the exact values of the coefficients in the tail of the considered process
In this paper we study the possible microscopic origin of heavy-tailed probability density distribut...
AbstractExtreme values of a stationary, multivariate time series may exhibit dependence across coord...
AbstractWe examine the tail behaviour and extremal cluster characteristics of two-state Markov-switc...
International audienceWe consider a threshold autoregressive stochastic volatility model where the d...
Empirical volatility changes in time and exhibits tails, which are heavier than normal. Moreover, em...
AbstractThis paper describes the limiting behaviour of tail empirical processes associated with long...
A stochastic volatility model in which the log volatilities follow a threshold autoregressive proces...
The simple stochastic volatility process (Xt)t∈Z is given by the equation Xt = σt Zt, t ∈ Z, (1) whe...
This paper examines two asymmetric stochastic volatility mod-els used to describe the heavy tails an...
We collect some of the probabilistic properties of a strictly stationary stochas-tic volatility proc...
International audienceWe study the asymptotic behaviour of the extreme values of a stochastic volati...
In this paper we study the tail and the extremal behavior of stationary solutions of autoregressive ...
Modeling the dependence between consecutive observations in a time series plays a crucial role in ri...
ABSTRACT We characterize joint tails and tail dependence for a class of stochastic volatility proces...
Financial instruments are known to exhibit abrupt and dramatic changes in behaviour. This paper inve...
In this paper we study the possible microscopic origin of heavy-tailed probability density distribut...
AbstractExtreme values of a stationary, multivariate time series may exhibit dependence across coord...
AbstractWe examine the tail behaviour and extremal cluster characteristics of two-state Markov-switc...
International audienceWe consider a threshold autoregressive stochastic volatility model where the d...
Empirical volatility changes in time and exhibits tails, which are heavier than normal. Moreover, em...
AbstractThis paper describes the limiting behaviour of tail empirical processes associated with long...
A stochastic volatility model in which the log volatilities follow a threshold autoregressive proces...
The simple stochastic volatility process (Xt)t∈Z is given by the equation Xt = σt Zt, t ∈ Z, (1) whe...
This paper examines two asymmetric stochastic volatility mod-els used to describe the heavy tails an...
We collect some of the probabilistic properties of a strictly stationary stochas-tic volatility proc...
International audienceWe study the asymptotic behaviour of the extreme values of a stochastic volati...
In this paper we study the tail and the extremal behavior of stationary solutions of autoregressive ...
Modeling the dependence between consecutive observations in a time series plays a crucial role in ri...
ABSTRACT We characterize joint tails and tail dependence for a class of stochastic volatility proces...
Financial instruments are known to exhibit abrupt and dramatic changes in behaviour. This paper inve...
In this paper we study the possible microscopic origin of heavy-tailed probability density distribut...
AbstractExtreme values of a stationary, multivariate time series may exhibit dependence across coord...
AbstractWe examine the tail behaviour and extremal cluster characteristics of two-state Markov-switc...