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Risk Modelling and Management: An Overview

Chang, Chia-Lin; Allen, David E.; McAleer, Michael; … - 2013

The papers in this special issue of Mathematics and Computers in Simulation are substantially revised versions of the papers that were presented at the 2011 Madrid International Conference on “Risk Modelling and Management” (RMM2011). The papers cover the following topics: currency hedging...

Persistent link: https://www.econbiz.de/10010326135

Risk Modeling and Management: An Overview

Chang, Chia-Lin; Allen, David E.; McAleer, Michael; … - Department of Economics and Finance, College of … - 2013

The papers in this special issue of Mathematics and Computers in Simulation are substantially revised versions of the papers that were presented at the 2011 Madrid International Conference on “Risk Modeling and Management” (RMM2011). The papers cover the following topics: currency hedging...

Persistent link: https://www.econbiz.de/10010907434

Multi-period credit default prediction with time-varying covariates

Orth, Walter - 2011 - First draft: March 17, 2011

In credit default prediction models, the need to deal with time-varying covariates often arises. For instance, in the context of corporate default prediction a typical approach is to estimate a hazard model by regressing the hazard rate on time-varying covariates like balance sheet or stock...

Persistent link: https://www.econbiz.de/10008939079

Assessing the Credit Risk of Crypto-Assets Using Daily Range Volatility Models

Fantazzini, Dean - 2023

In this paper, we analyzed a dataset of over 2000 crypto-assets to assess their credit risk by computing their probability of death using the daily range. Unlike conventional low-frequency volatility models that only utilize close-to-close prices, the daily range incorporates all the information...

Persistent link: https://www.econbiz.de/10014350946

A Multivariate Approach for the Simultaneous Modelling of Market Risk and Credit Risk for Cryptocurrencies

Fantazzini, Dean - 2019

This paper proposes a set of models which can be used to estimate the market risk for a portfolio of crypto-currencies, and simultaneously to estimate also their credit risk using the Zero Price Probability (ZPP) model by Fantazzini et al (2008), which is a methodology to compute the...

Persistent link: https://www.econbiz.de/10012863029

Shapley-Lorenz Decompositions in eXplainable Artificial Intelligence

Giudici, Paolo - 2020

Explainability of artificial intelligence models has become a crucial issue, especially in the most regulated fields, such as health and finance. In this paper, we provide a global explainable AI model which is based on Lorenz decompositions, thus extending previous contributions based on...

Persistent link: https://www.econbiz.de/10012840407

Predictive Analytics as an Instrument to Prevent Bankruptcy

Kiseleva, Elena - 2020

As of today there are a lot of well-known bankruptcy prediction models. Scientists have been paying much attention to the development of bankruptcy prediction models since 1970. However, most of them are unable to predict bankruptcy, thereby making it impossible for firms to prevent it today....

Persistent link: https://www.econbiz.de/10012825141

A Study of Applicability of Bankruptcy Prediction Models for Small Businesses

Kiseleva, Elena - 2020

The paper investigates predictive ability of existing bankruptcy prediction models suitable for small business by using dates of accounting report of Russian's firms. Combination of financial ratios analysis with bankruptcy prediction models' testing made it possible to identify the models...

Persistent link: https://www.econbiz.de/10012825156

Discussing Copulas with Sergey Aivazian : A Memoir

Fantazzini, Dean - 2020

Sergey Aivazian was the head of my department at the Moscow School of Economics, but he was much more than that. He played an important role in my life, and he contributed to my studies devoted to copula modelling. This small memoir reports how this amazingly polite and smart scientist helped me...

Persistent link: https://www.econbiz.de/10012826199

The Impact of Parameter and Model Uncertainty on Market Risk Predictions from GARCH-Type Models

Ardia, David - 2019

VaR forecasts. To this end, we evaluate the predictive performance of several GARCH-type models estimated via Bayesian and … indexes are predicted over about 13 years from the early 2000s. We find that Bayesian predictive densities improve the VaR … backtest at the 1% risk level for single models and for linear and log pools. We also find that the robust VaR backtest …

Persistent link: https://www.econbiz.de/10012903836