98 research outputs found
Stochastic Analysis of Gaussian Processes via Fredholm Representation
We show that every separable Gaussian process with integrable variance
function admits a Fredholm representation with respect to a Brownian motion. We
extend the Fredholm representation to a transfer principle and develop
stochastic analysis by using it. We show the convenience of the Fredholm
representation by giving applications to equivalence in law, bridges, series
expansions, stochastic differential equations and maximum likelihood
estimations
Parameter Estimation for the Langevin Equation with Stationary-Increment Gaussian Noise
We study the Langevin equation with stationary-increment Gaussian noise. We
show the strong consistency and the asymptotic normality with Berry--Esseen
bound of the so-called alternative estimator of the mean reversion parameter.
The conditions and results are stated in terms of the variance function of the
noise. We consider both the case of continuous and discrete observations. As
examples we consider fractional and bifractional Ornstein--Uhlenbeck processes.
Finally, we discuss the maximum likelihood and the least squares estimators
Integral representation with adapted continuous integrand with respect to fractional Brownian motion
We show that if a random variable is a final value of an adapted Holder
continuous process, then it can be represented as a stochastic integral with
respect to fractional Brownian motion, and the integrand is an adapted process,
continuous up to the final point
Conditional-Mean Hedging Under Transaction Costs in Gaussian Models
We consider so-called regular invertible Gaussian Volterra processes and
derive a formula for their prediction laws. Examples of such processes include
the fractional Brownian motions and the mixed fractional Brownian motions. As
an application, we consider conditional-mean hedging under transaction costs in
Black-Scholes type pricing models where the Brownian motion is replaced with a
more general regular invertible Gaussian Volterra process.Comment: arXiv admin note: text overlap with arXiv:1706.0153
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