Results 231 to 240 of about 3,426,931 (297)

Empirical‐Process Limit Theory and Filter Approximation Bounds for Score‐Driven Time Series Models

open access: yesJournal of Time Series Analysis, EarlyView.
ABSTRACT This article examines the filtering and approximation‐theoretic properties of score‐driven time series models. Under specific Lipschitz‐type and tail conditions, new results are derived, leading to maximal and deviation inequalities for the filtering approximation error using empirical process theory.
Enzo D'Innocenzo
wiley   +1 more source

Testing for Rough Volatility When Prices Are Purely Discontinuous

open access: yesJournal of Time Series Analysis, EarlyView.
ABSTRACT We consider the problem of nonparametric testing for rough volatility, using high‐frequency data with a fixed time span, in a setting where the price is purely discontinuous. More specifically, we analyze the asymptotic properties of a test we developed in previous work in a pure‐jump setting.
Carsten H. Chong, Viktor Todorov
wiley   +1 more source

On Testing for Independence Between Generalized Error Models of Several Time Series

open access: yesJournal of Time Series Analysis, EarlyView.
ABSTRACT We define generalized innovations associated with generalized error models having arbitrary distributions, that is, distributions that can be mixtures of continuous and discrete distributions. These models include stochastic volatility models and regime‐switching models with possibly zero‐inflated regimes.
Kilani Ghoudi   +2 more
wiley   +1 more source

Asymptotics of Time‐Varying Processes in Continuous‐Time Using Locally Stationary Approximations

open access: yesJournal of Time Series Analysis, EarlyView.
ABSTRACT We introduce a general theory on stationary approximations for locally stationary continuous‐time processes. Based on the stationary approximation, we use θ$$ \theta $$‐weak dependence to establish laws of large numbers and central limit type results under different observation schemes.
Robert Stelzer, Bennet Ströh
wiley   +1 more source

Detecting Multiple Change Points in Linear Models With Heteroscedasticity

open access: yesJournal of Time Series Analysis, EarlyView.
ABSTRACT The problem of detecting change points in the parameters of a linear regression model with errors and covariates exhibiting heteroscedasticity is considered. Asymptotic results for weighted functionals of the cumulative sum (CUSUM) processes of model residuals are established when the model errors are weakly dependent and non‐stationary ...
Lajos Horváth   +2 more
wiley   +1 more source

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