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A novel nonlinear value-at-risk method for modeling risk of option portfolio with multivariate mixture of normal distributions

Rongda Chen, Lean Yu
2013 Economic Modelling  
a r t i c l e i n f o This paper proposes a novel nonlinear model for calculating Value-at-Risk (VaR) when the market risk factors of an option portfolio are heavy-tailed.  ...  numerical integration into the nonlinear VaR model for option portfolio are applied for calculation of VaR values of option portfolio.  ...  integration for calculating nonlinear VaR of option portfolio.  ... 
doi:10.1016/j.econmod.2013.09.003 fatcat:ipuyaxizn5eftippx6bli4tgmi

Market risk management in a post-Basel II regulatory environment

Mikica Drenovak, Vladimir Ranković, Miloš Ivanović, Branko Urošević, Ranko Jelic
2017 European Journal of Operational Research  
The optimization is performed using a parallel framework for optimization based on the Nondominated Sorting Genetic Algorithm II.  ...  We propose a novel method of Mean-Capital Requirement portfolio optimization.  ...  Acknowledgements: We thank Emanuele Borgonovo (Editor) and an anonymous referee for their helpful suggestions. We are also grateful to Norman Schürhoff, Amit Goyal, Diane  ... 
doi:10.1016/j.ejor.2016.08.034 fatcat:peab364r7rd43aaq22jduo3lca

Don't Fall from the Saddle: The Importance of Higher Moments of Credit Loss Distributions

Jan Annaert, Joao Garcia, Jeroen Lamoot, Gleb Lanine
2007 Social Science Research Network  
Hence, the saddlepoint approximations are not a universal substitute to the Panjer recursion algorithm.  ...  A much-hailed solution for the flaws of the Panjer recursion is the saddlepoint approximation method.  ...  The set-up VaR estimates for different levels of confidence are computed via the original Panjer recursion algorithm and the LR 11 and the BN formulas.  ... 
doi:10.2139/ssrn.994182 fatcat:l7yoe64cbnc6dod6rgk2e65tyq

Copulas and Portfolios in the Electric Vehicle Sector

Andrej Stenšin, Daumantas Bloznelis
2022 Journal of Risk and Financial Management  
They facilitate portfolio optimization targeted at a chosen combination of risk and reward.  ...  With daily data from 2012 to 2020, we illustrate the models' applicability by building a minimum expected shortfall portfolio and comparing its performance to that of an equally weighted benchmark.  ...  We are not aware of any formal tests to warrant a decision at a desired confidence level.  ... 
doi:10.3390/jrfm15030132 fatcat:767okfjtf5fz7kw3bybctlufyu

Trading book and credit risk: How fundamental is the Basel review?

Jean-Paul Laurent, Michael Sestier, Stéphane Thomas
2016 Journal of Banking & Finance  
JEL Classification: G18 C51 Keywords: Fundamental review of the trading book Portfolio credit risk modeling Factor models Risk contribution a b s t r a c t Within the new Basel regulatory framework for  ...  Banks using the internal model approach are required to use a two-factor model and a 99.9% VaR capital charge.  ...  This work was achieved as part of a R&D program initiated by PHAST Solutions Group, it received a grant by the French National Research and Technology Association (ANRT) for the accomplishment of a PhD  ... 
doi:10.1016/j.jbankfin.2016.07.002 fatcat:th6fyqtfzzehlgbwzxvsewhm2m

An importance sampling method for portfolio CVaR estimation with Gaussian copula models

Pu Huang, Dharmashankar Subramanian, Jie Xu
2010 Proceedings of the 2010 Winter Simulation Conference  
We developed an importance sampling method to estimate Conditional Value-at-Risk for portfolios in which inter-dependent asset losses are modeled via a Gaussian copula model.  ...  It turns out that VaR is not coherent and a coherent alternative is Conditional Value-at-Risk (CVaR). In this paper, we present an importance sampling procedure for CVaR portfolio risk estimation.  ...  INTRODUCTION Estimating the risk of a portfolio through Monte Carlo simulation is a fundamental task in risk management. Different measures of risk call for different simulation techniques.  ... 
doi:10.1109/wsc.2010.5678974 dblp:conf/wsc/HuangSX10 fatcat:mhonnyuzmra25kbafmkxwfnyq4

A Survey on Financial Applications of Metaheuristics

Amparo Soler-Dominguez, Angel A. Juan, Renatas Kizys
2017 ACM Computing Surveys  
A non-exhaustive list of examples includes rich portfolio optimization, index tracking, enhanced indexation, credit risk, stock investments, financial project scheduling, option pricing, feature selection  ...  Modern heuristics or metaheuristics are optimization algorithms that have been increasingly used during the last decades to support complex decision making in a number of fields, such as logistics and  ...  In this regard, Yamai and Yoshiba [2005] illustrate how the tail risk of VaR can become problematic for a concentrated credit portfolio.  ... 
doi:10.1145/3054133 fatcat:hr4fggpodnbzjdk3fkg6thxjma

Management Science, Economics and Finance: A Connection

Chia Lin Chang, Michael McAleer
2016 International Journal of Economics & Management Sciences  
This paper provides a brief review of the connecting literature in management science, economics and finance, and discusses some research that is related to the three disciplines.  ...  Ma and Wong [30] establish some behavioural foundations for various types of Valueat-Risk (VaR) models, including VaR and conditional-VaR (C-VaR), as measures of downside risk.  ...  [4] develop an algorithm to obtain the SD admissible sets by stock selection. Hammond [5] suggests SD rules for risk seekers.  ... 
doi:10.4172/2162-6359.1000358 fatcat:djjjopsp25ggnpjiozk3vkejj4

Analyzing the impact of credit migration in a portfolio setting

Yaakov Tsaig, Amnon Levy, Yashan Wang
2011 Journal of Banking & Finance  
For a typical loan portfolio, we find credit migration can explain as much as 51% of volatility and 35% of economic capital.  ...  Credit migration is an essential component of credit portfolio modeling. In this paper, we outline a framework for gauging the effects of credit migration on portfolio risk measurements.  ...  Trück and Rachev (2005a) draw similar conclusions, finding that migration matrices estimated at different points of the business cycle produce significantly different VaR measures for a test portfolio.  ... 
doi:10.1016/j.jbankfin.2010.09.027 fatcat:rppekademjazjet5wefvejoy74

Decomposing portfolio value-at-risk: a general analysis

Winfried Hallerbach
2003 Journal of Risk  
Aside from the total portfolio's VaR, there is a growing need for information about (i) the marginal contribution of the individual portfolio components to the diversified portfolio VaR, (ii) the proportion  ...  We derive a general expression for the marginal contribution of an instrument to the diversified portfolio VaR − whether this instrument is already included in the portfolio or not.  ...  VaR) for the augmented portfolios A, B and C. portfolios A, B and C.  ... 
doi:10.21314/jor.2003.076 fatcat:b5iab7afdve23ado6zoyuatmny

Probability Approach in Estimating Value at Risk of Bond Portfolios for Effective Hedging

Bavani Chandra Kumar, Ravindran Ramasamy, Zulkifflee Mohamed
2020 Asian Economic and Financial Review  
We have applied standard risk measures of bond portfolios, portfolio duration and portfolio convexity to assess the Value at Risk (VaR) accurately and this will lead to minimum cost of hedging.  ...  and to observe the differences and the reasons for them.  ...  VaR assesses risk which is a loss of portfolio value and has become a benchmark for measuring and estimating risk in diverse portfolios and other complex instruments (Cakir & Raei, 2007) .  ... 
doi:10.18488/journal.aefr.2020.105.502.515 fatcat:k2yugrseybhm5ayf4umdqdhy7u

Sequential Design and Spatial Modeling for Portfolio Tail Risk Measurement [article]

Michael Ludkovski, James Risk
2018 arXiv   pre-print
In the respective nested simulation framework, the goal is to estimate portfolio tail risk, quantified via VaR or TVaR of a given collection of future economic scenarios representing factor levels at the  ...  The GP framework also yields better uncertainty quantification for the resulting VaR/TVaR estimators that reduces bias and variance compared to existing methods.  ...  algorithm [27] , or not using a spatial model for smoothing [8] .  ... 
arXiv:1710.05204v2 fatcat:42kczn6mljhzzfgxgi2twy52wa

Information-based Trading, Price Impact of Trades, and Trade Autocorrelation

Kee H. Chung, Mingsheng Li, Thomas H. McInish
2004 Social Science Research Network  
The positive relation remains significant even after controlling for the effects of stock attributes.  ...  These results provide direct empirical support for the information models of trade and quote revision.  ...  The authors are solely responsible for the content of the paper.  ... 
doi:10.2139/ssrn.551143 fatcat:6jmi65extjdylemhl2ztnddpyy

Developing a stress testing framework based on market risk models

Carol Alexander, Elizabeth Sheedy
2008 Journal of Banking & Finance  
The Basel 2 Accord requires regulatory capital to cover stress tests, yet no coherent and objective framework for stress testing portfolios exists.  ...  We propose a new methodology for stress testing in the context of market risk models that can incorporate both volatility clustering and heavy tails.  ...  Acknowledgements Many thanks to two anonymous referees for extensive comments on earlier drafts, which helped to improve this paper considerably.  ... 
doi:10.1016/j.jbankfin.2007.12.041 fatcat:rwc5bcsjbvhdtkq6vcmybk2adi

Risk Aggregation [chapter]

Paul Embrechts, Giovanni Puccetti
2010 Copula Theory and Its Applications  
Risk Aggregation concerns the study of the aggregate financial position Ψ (X), for some measurable function Ψ : R d → R.  ...  A risk measure ρ then maps Ψ (X) to ρ(Ψ(X)) ∈ R, to be interpreted as the regulatory capital needed to be able to hold the aggregate position Ψ (X) over a predetermined fixed time period.  ...  Acknowledgements The first author would like to thank the Swiss Finance Institute for financial support.  ... 
doi:10.1007/978-3-642-12465-5_5 fatcat:lxco4d3h5vgubi23c4qtnljjnu
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