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Understanding Models and Model Bias with Gaussian Processes

Cook, Thomas R.; Palmer, Nathan - 2023

Despite growing interest in the use of complex models, such as machine learning (ML) models, for credit underwriting, ML models are difficult to interpret, and it is possible for them to learn relationships that yield de facto discrimination. How can we understand the behavior and potential...

Persistent link: https://www.econbiz.de/10014353867

Estimation of the long-memory stochastic volatility model parameters that is robust to level shifts and deterministic trends

McCloskey, Adam - 2012 - This version: October 2012

I provide conditions under which the trimmed FDQML estimator, advanced by McCloskey (2010) in the context of fully … lowfrequency contamination. A simulation study examines the finite sample properties of the robust estimator, showing substantial …

Persistent link: https://www.econbiz.de/10009660446

Relating stochastic volatility estimation methods

Bos, Charles S. - 2011

Estimation of the volatility of time series has taken off since the introduction of the GARCH and stochastic volatility models. While variants of the GARCH model are applied in scores of articles, use of the stochastic volatility model is less widespread. In this article it is argued that one...

Persistent link: https://www.econbiz.de/10011386124

Estimation of the Long-Memory Stochastic Volatility Model Parameters that is Robust to Level Shifts and Deterministic Trends

McCloskey, Adam - 2012

I provide conditions under which the trimmed FDQML estimator, advanced by McCloskey (2010) in the context of fully … types of lowfrequency contamination. A simulation study examines the finite sample properties of the robust estimator …

Persistent link: https://www.econbiz.de/10013098304

Realized Stochastic Volatility Models with Generalized Gegenbauer Long Memory

Asai, Manabu - 2017

In recent years fractionally diﬀerenced processes have received a great deal of attention due to their ﬂexibility in ﬁnancial applications with long memory. In this paper, we develop a new realized stochastic volatility (RSV) model with general Gegenbauer long memory (GGLM), which...

Persistent link: https://www.econbiz.de/10012944285

Variance Comparison between Infinitesimal Perturbation Analysis and Likelihood Ratio Estimators to Stochastic Gradient

Cui, Zhenyu; Liu, Yanchu; Wang, Ruodu - 2021

We theoretically compare variances between the Infinitesimal Perturbation Analysis (IPA) estimator and the Likelihood … Ratio (LR) estimator to Monte Carlo gradient for stochastic systems. The conditions proposed in [Cui et al., 2020] when the … IPA estimator has a smaller variance can yield sharper inequalities or be further relaxed. We also prove a practically …

Persistent link: https://www.econbiz.de/10013220887

Long memory dynamics for multivariate dependence under heavy tails

Janus, Paweł; Koopman, Siem Jan; Lucas, André - 2011

Persistent link: https://www.econbiz.de/10009720703

Momentum-Space Approach to Asymptotic Expansion for Stochastic Filtering

Fujii, Masaaki - 2013

This paper develops an asymptotic expansion technique in momentum space for stochastic filtering. It is shown that Fourier transformation combined with a polynomial-function approximation of the nonlinear terms gives a closed recursive system of ordinary differential equations (ODEs) for the...

Persistent link: https://www.econbiz.de/10013090246

Bias in the Estimation of Mean Reversion in Continuous-Time Lévy Processes

Bao, Yong - 2016

whether the initial condition is fixed or random. The approximate bias is used to construct a bias corrected estimator. The …This paper develops the approximate bias of the ordinary least squares estimator of the mean reversion parameter in … performance of the approximate bias and the bias corrected estimator is examined using simulated data …

Persistent link: https://www.econbiz.de/10012997979

Estimation of Long Memory in Integrated Variance

Rossi, Eduardo - 2011

A stylized fact is that realized variance has long memory. We show that, when the instantaneous volatility is driven by a fractional Brownian motion, the integrated variance is characterized by long-range dependence. As a consequence, the realized variance inherits this property when prices are...

Persistent link: https://www.econbiz.de/10013127184

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