This paper presents an overview of the efficient Monte Carlo counterparty credit risk (CCR) estimation framework recently developed by Ghamami and Zhang (2014). We focus on the estimation of credit value adjustment (CVA), one of the most widely used and regulatory-driven counterparty credit risk...

The aim of this paper is to propose and test a novel PF method called Sequential Gibbs Particle Filter allowing to estimate complex latent state variable models with unknown parameters. The framework is applied to a stochastic volatility model with independent jumps in returns and volatility....

We compare several models that forecast ex-ante Bitcoin one-day Value-at-Risk (VaR), starting from the simplest ones like Parametric Normal and Historical Simulation and arriving at Historical Filtered Bootstrap and Extreme Value Theory Historical Filtered Bootstrap. We also consider Gaussian...

In this paper, we introduce a methodology that allows for imposing views on density forecasts of a (frequency domain) factor based time series model. Such a model produces a density forecast for the future evolution of economic and financial variables such as interest rates, asset returns and...

A large number of exact inferential procedures in statistics and econometrics involve the sampling distribution of ratios of random variables. If the denominator variable is positive, then tail probabilities of the ratio can be expressed as those of a suitably defined difference of random...

This note discusses some problems possibly arising when approximating via MonteCarlo simulations the distributions of goodness-of-fit test statistics based on the empirical distribution function. We argue that failing to reestimate unknown parameters on each simulated Monte-Carlo sample - and...

This paper analyzes the higher-order properties of nested pseudo-likelihood (NPL) estimators and their practical implementation for parametric discrete Markov decision models in which the probability distribution is defined as a fixed point. We propose a new NPL estimator that can achieve...

Correlation coefficients among multiple variables are commonly described in the form of matrices. Applications of such correlation matrices can be found in many fields, such as finance, engineering, statistics, and medicine. This article proposes an efficient way to sequentially obtain the...

Credit value adjustment (CVA) and related charges have emerged as important risk factors following the Global Financial Crisis. These charges depend on uncertain future values of underlying products, and are usually computed by Monte Carlo simulation. For products that cannot be valued...

Johan Gielis showed that all closed curves might be considered as some sort of deformed ellipses. He gave a superformula to parameterize such shapes. In this study an attempt has been made to estimate the parameters of Gielis' superformula from empirical data. We use an optimum search algorithm...