Modern risk systems
Papers published in 2010

Companion sites: Russian version


  1. Novosyolov A.A. Modeling coherent preference relations in decision-making under risk. Proceedings of the IASTED International Conferences on Automation, Control and Information Technology (ACIT 2010), Novosibirsk, 2010, 313-315.
    Abstract
    Coherent risk measures proved to be a useful tools in financial risk management and decision-making under risk. Their limitations are relaxed by using generalized coherent risk measures. The present paper is devoted to establishing a representation theorem for generalized coherent risk measures, which gives rise to algorithms of calculation of their values.
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    paper, presentation

  2. Novosyolov A.A. Stress testing of factor models. Proceedings of the IX International conference on financial and actuarial mathematics, Krasnoyarsk, KGTEI, SFU, 2010, 245-246. (in Russian)
    Abstract
    The paper dewcribes a method of stress testing a market risk model by distorbing its correlation structure keeping positive definiteness.
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  3. Novosyolov A, Satchkov D. Portfolio crash testing: making sense of extreme event exposures. Journal of Risk Model Validation, 4 (2010), 3, 53-67.
    Abstract
    The topic of extreme events is becoming ever more important for risk management. Stress testing is a technique that is explicitly designed to deal with extreme shocks; however, its methodology and place in the risk process is often unclear to risk managers. This paper addresses some common misconceptions about stress testing and provides methodology for its incorporation into the risk process as a supplement to risk measures such as VaR and tracking error. Two stress testing models are presented and empirically validated on actual extreme periods. Both are based on multivariate normal distributions conditional on a factor shock, differing only in the way that covariances are estimated. The first model uses temporal weighting commonly used in the risk model construction; the other uses event weighting, which assigns a higher weight to extreme events that are similar to the factor shock specified. The key conclusion is that the Time Weighted model performs better in moderate or semi-expected shocks, while the Event Weighted model performs better in more extreme and unexpected shocks like the LTCM crisis, 9/11 terrorist attacks, and Fall 2008 financials-led meltdown. The Event Weighted model, which is designed to reflect the rise in correlations and variances during extreme markets, produces a more conservative estimate of return impacts. Our results support the conclusion that stress testing can be a very valuable addition to standard risk measures.
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  4. Novosyolov A.A. Building multidimensional discrete distributions with given correlation structure. SibGAU journal, 5 (2010), 49-52. (in Russian)
    Abstract
    The paper presents a few methods of building multidimensional discrete distributions with given correlation structure and marginal distributions. The problem is solved via mixing some basic distributions and solving optimization problems.
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  5. Novosyolov A.A. Parametrization of control system models. SibGAU journal, 5 (2010), 52-56. (in Russian)
    Abstract
    The paper describes application of orthogonal series method to building control systems models under non-parametric uncertainty. The key point is selecting the series length via observations, that is, selecting the model parametric structure. The method is demonstrated for estimating probability density function and regression function. A few generalizations are also proposed.
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  6. Novosyolov A.A. Canonic representing functionals for some preference classes. Proceedings of the XIV International conference on eventological mathematics and related topics, Krasnoyarsk, KGTEI, SFU, 2010, 161-163. (in Russian)
    Abstract
    In the paper we present methods for building representing functionals for preference classes described by expected utility, coherent risk measures and their generalizations.
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