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Markov Chain Monte Carlo Models, Gibbs Sampling, & Metropolis Algorithm for High-Dimensionality Complex Stochastic Problems

Malhotra, Yogesh - 2015

Markov chain Monte Carlo (MCMC) methods have an important role in solving high dimensionality stochastic problems characterized by computational complexity. Given their critical importance, there is need for network and security risk management research to relate the MCMC quantitative...

Persistent link: https://www.econbiz.de/10013029835

A robust test for predictability with unknown persistence

Liu, Guannan; Yao, Shuang - In: Economics letters 189 (2020), pp. 1-5

Persistent link: https://www.econbiz.de/10012228019

Volatility behavior of asset returns based on robust volatility ratio : empirical analysis on global stock indices

Shaik, Muneer; Maheswaran, S. - In: Cogent economics & finance 7 (2019) 1, pp. 1-27

In this paper we come up with an alternate theoretical proof for the independence and unbiased property of extreme value robust volatility estimator with respect to the standard robust volatility estimator as proposed in the paper by Muneer & Maheswaran (2018b). We show that the robust...

Persistent link: https://www.econbiz.de/10012023869

Bayesian estimation of large-scale simulation models with Gaussian process regression surrogates

Barde, Sylvain - 2022

Large scale, computationally expensive simulation models pose a particular challenge when it comes to estimating their parameters from empirical data. Most simulation models do not possess closed form expressions for their likelihood function, requiring the use of simulation-based inference,...

Persistent link: https://www.econbiz.de/10013439970

Robust Estimation of Nonstationary, Fractionally Integrated, Autoregressive, Stochastic Volatility

Jensen, Mark J. - 2017

Empirical volatility studies have discovered nonstationary, long-memory dynamics in the volatility of the stock market and foreign exchange rates. This highly persistent, infinite variance—but still mean reverting—behavior is commonly found with nonparametric estimates of the fractional...

Persistent link: https://www.econbiz.de/10012970590

Robust estimation of nonstationary, fractionally integrated, autoregressive, stochastic volatility

Jensen, Mark J. - 2015

Empirical volatility studies have discovered nonstationary, long-memory dynamics in the volatility of the stock market and foreign exchange rates. This highly persistent, infinite variance - but still mean reverting - behavior is commonly found with nonparametric estimates of the fractional...

Persistent link: https://www.econbiz.de/10011382237

Estimating Correlated Jumps and Stochastic Volatilities

Witzany, Jiri - 2011

We formulate a bivariate stochastic volatility jump-diffusion model with correlated jumps and volatilities. An MCMC Metropolis-Hastings sampling algorithm is proposed to estimate the model's parameters and latent state variables (jumps and stochastic volatilities) given observed returns. The...

Persistent link: https://www.econbiz.de/10013121407

Multivariate Stochastic Volatility Models with Correlated Errors

Chan, David X. - 2008

We develop a Bayesian approach for parsimoniously estimating the correlation structure of the errors in a multivariate … stochastic volatility model. Since the number of parameters in the joint correlation matrix of the return and volatility errors … is potentially very large, we impose a prior that allows the off-diagonal elements of the inverse of the correlation …

Persistent link: https://www.econbiz.de/10012727256

Tail distribution of the maximum of correlated Gaussian random variables

Botev, Zdravko I.; Mandjes, Michel; Ridder, Ad - 2015

In this article we consider the efficient estimation of the tail distribution of the maximum of correlated normal random variables. We show that the currently recommended Monte Carlo estimator has difficulties in quantifying its precision, because its sample variance estimator is an inefficient...

Persistent link: https://www.econbiz.de/10011431354

A General Parametrization of Correlation Matrix for a Multidimensional Stochastic Volatility Model

Sahel, Fouad - 2013

build a parameterization of the correlation matrix of a multidimensional model with stochastic volatility, given that:1. The … correlation between each asset and its volatility is specified.2. The correlations between different assets are specified.In the …

Persistent link: https://www.econbiz.de/10013078296