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Systemic risk contributions : a credit portfolio approach

Düllmann, Klaus; Puzanova, Natalia - 2011

We put forward a Merton-type multi-factor portfolio model for assessing banks’ contributions to systemic risk. This model accounts for the major drivers of banks’ systemic relevance: size, default risk and correlation of banks’ assets as a proxy for interconnectedness. We measure systemic...

Persistent link: https://www.econbiz.de/10009011220

Adaptive polar sampling with an application to a Bayes measure of value-at-risk

Bauwens, Luc; Bos, Charles S.; Dijk, Herman K. van - 1999

Adaptive Polar Sampling (APS) is proposed as a Markov chain Monte Carlomethod for Bayesian analysis of models with ill-behaved posteriordistributions. In order to sample efficiently from such a distribution,a location-scale transformation and a transformation to polarcoordinates are used. After...

Persistent link: https://www.econbiz.de/10011302625

Enhanced Valuation of European Options Under Jump Processes and Innovative Characterization of Implied Volatility Smile

Dubrana, Ludovic - 2011

An enhanced option pricing framework that makes use of both continuous and discontinuous time paths based on a geometric Brownian motion and Poisson-driven jump processes respectively is performed in order to better fit with real-observed stock price paths while maintaining the analytical...

Persistent link: https://www.econbiz.de/10013118115

Implied Volatility Surface : Construction Methodologies and Characteristics

Homescu, Cristian - 2011

The implied volatility surface (IVS) is a fundamental building block in computational finance. We provide a survey of methodologies for constructing such surfaces. We also discuss various topics which can influence the successful construction of IVS in practice: arbitrage-free conditions in both...

Persistent link: https://www.econbiz.de/10013122634

Estimating Financial Institutions’ Intraday Liquidity Risk : A Monte Carlo Simulation Approach

León, Carlos - 2012

The most recent financial crisis unveiled that liquidity risk is far more important and intricate than regulation have conceived. The shift from bank-based to market-based financial systems and from Deferred Net Systems to liquidity-demanding Real-Time Gross Settlement of payments explains some...

Persistent link: https://www.econbiz.de/10013104142

Monte Carlo Pricing with Local Volatility Grids

Abasto, Damian - 2013

Local volatility models are widely used to manage many exotic options in a way consistent with available market prices of vanilla options. Once calibrated, a local volatility grid can be used in numerical methods such as PDE or Monte Carlo to price and hedge exotic options consistently with...

Persistent link: https://www.econbiz.de/10013083196

Bilateral Counterparty Risk Valuation for Interest-Rate Products : Impact of Volatilities and Correlations

Brigo, Damiano - 2010

The purpose of this paper is introducing rigorous methods and formulas for bilateral counterparty risk credit valuation adjustments (CVA's) on interest-rate portfolios. In doing so, we summarize the general arbitrage-free valuation framework for counterparty risk adjustments in presence of...

Persistent link: https://www.econbiz.de/10013150257

Efficient Computation of Value at Risk with Heavy-Tailed Risk Factors

Fuh, Cheng-der - 2009

The probabilities considered in value-at-risk (VaR) are typically of moderate deviations. However, the variance … reduction techniques developed in the literature for VaR computation are based on large deviations methods. Modeling heavy …-tailed risk factors using multivariate $t$ distributions, we develop a new moderate-deviations method for VaR computation. We show …

Persistent link: https://www.econbiz.de/10013156820

Machine Learning SABR Model of Stochastic Volatility With Lookup Table

Lokvancic, Mahir - 2020

We present an embarrassingly simple method for supervised learning of SABR model's European option price function based on lookup table or rote machine learning. Performance in time domain is comparable to generally used analytic approximations utilized in financial industry. However, unlike the...

Persistent link: https://www.econbiz.de/10012835457

Teasing Out Tail Risk or, Quantum Mechanics to the Rescue : A Practical Method for Characterizing Downside Risk in Non-Gaussian Return Distributions

Stock, Robert D. - 2020

Using equations that arise in quantum mechanics, this paper describes a way to more accurately and efficiently represent non-Gaussian return distributions than the standard method of invoking skewness and kurtosis. Then, it provides a new single intuitive number, defined here as the “crash...

Persistent link: https://www.econbiz.de/10012844430

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