New Economics Papers
on Risk Management
Issue of 2013‒08‒23
seven papers chosen by

  1. Multi-asset risk measures By Walter Farkas; Pablo Koch-Medina; Cosimo-Andrea Munari
  2. Default Risk Calculation based on Predictor Selection for the Southeast Asian Industry By Wolfgang Karl Härdle; Dedy Dwi Prastyo; ; Dieter
  3. How useful is the marginal expected shortfall for the measurement of systemic exposure? A practical assessment By Idier, Julien; Lamé, Gildas; Mésonnier, Jean-Stéphane
  4. Optimal asset structure of a bank - bank reactions to stressful market conditions By Hałaj, Grzegorz
  5. A market-based approach to sector risk determinants and transmission in the euro area By Saldías, Martín
  6. A financial systemic stress index for Greece By Louzis, Dimitrios; Vouldis, Angelos
  7. Achieving Speedup in Aggregate Risk Analysis using Multiple GPUs By A. K. Bahl; O. Baltzer; A. Rau-Chaplin; B. Varghese; A. Whiteway

  1. By: Walter Farkas; Pablo Koch-Medina; Cosimo-Andrea Munari
    Abstract: We study risk measures for financial positions in a multi-asset setting, representing the minimum amount of capital to raise and invest in eligible portfolios of traded assets in order to meet a prescribed acceptability constraint. We investigate finiteness and continuity properties of these multi-asset risk measures, highlighting the interplay between the acceptance set and the class of eligible portfolios. We develop a new approach to dual representations of convex multi-asset risk measures which relies on a characterization of the structure of closed convex acceptance sets. To avoid degenerate cases we need to ensure the existence of extensions of the underlying pricing functional which belong to the effective domain of the support function of the chosen acceptance set. We provide a characterization of when such extensions exist. Finally, we discuss applications to conical market models and set-valued risk measures, optimal risk sharing, and superhedging with shortfall risk.
    Date: 2013–08
  2. By: Wolfgang Karl Härdle; Dedy Dwi Prastyo; ; Dieter
    Abstract: Probability of default prediction is one of the important tasks of rating agencies as well as of banks and other financial companies to measure the default risk of their counterparties. Knowing predictors that significantly contribute to default prediction provides a better insight into fundamentals of credit risk analysis. Default prediction and default predictor selection are two related issues, but many existing approaches address them separately. We employed a unified procedure, a regularization approach with logit as an underlying model, which simultaneously selects the default predictors and optimizes all the parameters within the model. We employ Lasso and elastic-net penalty functions as regularization approach. The methods are applied to predict default of companies from industry sector in Southeast Asian countries. The empirical result exhibits that the proposed method has a very high accuracy prediction particularly for companies operating Indonesia, Singapore, and Thailand. The relevant default predictors over the countries reveal that credit risk analysis is sample specific. A few number of predictors result in counter intuitive sign estimates.
    Keywords: Default risk, Predictor selection, logit, Lasso, Elastic-net
    JEL: C13 C61 G33
    Date: 2013–08
  3. By: Idier, Julien; Lamé, Gildas; Mésonnier, Jean-Stéphane
    Abstract: We explore the practical relevance from a supervisor's perspective of a popular market-based indicator of the exposure of a financial institution to systemic risk, the marginal expected shortfall (MES). The MES of an institution can be defined as its expected equity loss when the market itself is in its left tail. We estimate the dynamic MES recently proposed by Brownlees and Engle (2011) for a panel of 65 large US banks over the last decade and a half. Running panel regressions of the MES on bank characteristics, we first find that the MES can be roughly rationalized in terms of standard balance sheet indicators of bank financial soundness and systemic importance. We then ask whether the cross section of the MES can help to identify ex ante, i.e. before a crisis unfolds, which institutions are the more likely to suffer the most severe losses ex post, i.e. once it has unfolded. Unfortunately, using the recent crisis as a natural experiment, we find that standard balance-sheet metrics like the tier one solvency ratio are better able than the MES to predict equity losses conditionally to a true crisis. JEL Classification: C5, E44, G2
    Keywords: balance sheet ratios, MES, panel, systemic risk, tail correlation
    Date: 2013–05
  4. By: Hałaj, Grzegorz
    Abstract: The aim of the paper is to propose a model of banks' asset portfolios to account for the strategic and optimising behavior of banks under adverse economic conditions. In the proposed modelling framework, banks are assumed to respond in an optimising manner to changes in their economic environment (e.g. interest rate and credit risk shocks, funding disruptions, etc.). The modelling approach is based on the risk-return optimal program in which banks aim at a particular composition of their assets to maximise risk-adjusted returns while taking into account regulatory capital and liquidity constraints. The approach is designed for applications in banks' stress testing context, as an alternative to the typical static balance sheet assumption. The stress testing applications are illustrated for a large sample of European banks. JEL Classification:
    Keywords: banking, Portfolio optimisation, stress-testing
    Date: 2013–04
  5. By: Saldías, Martín
    Abstract: In a panel data framework applied to Portfolio Distance-to-Default series of corporate sectors in the euro area, this paper evaluates systemic and idiosyncratic determinants of default risk and examines how distress is transferred in and between the financial and corporate sectors since the early days of the euro. This approach takes into account observed and unobserved common factors and the presence of different degrees of cross-section dependence in the form of economic proximity. This paper contributes to the financial stability literature with a contingent claims approach to a sector-based analysis with a less dominant macro focus while being compatible with existing stress-testing methodologies in the literature. A disaggregated analysis of the different corporate and financial sectors allows for a more detailed assessment of specificities in terms of risk pro file, i.e. heterogeneity of business models, risk exposures and interaction with the rest of the macro environment. JEL Classification: G01, G13, C31, C33
    Keywords: common correlated effects, contingent claims analysis, macro-prudential analysis, Portfolio credit risk measurement
    Date: 2013–08
  6. By: Louzis, Dimitrios; Vouldis, Angelos
    Abstract: The paper develops a financial systemic stress index (FSSI) for Greece. We present a methodology for constructing and evaluating a systemic stress index which: i) adopts the suggestion of Hollo et al. (2012) [Hollo, Kremer, and Lo Duca (2012) “CISS – A Composite Indicator of Systemic Stress in the Financial System” ECB Working Paper 1426] to incorporate time-varying correlations between different market segments, and uses a multivariate GARCH approach which is able to capture abrupt changes in correlations; ii) utilizes both market and balance sheet data; and iii) evaluates the FSSI utilizing the results of a survey, conducted among financial experts, in order to construct a benchmark chronology of financial crises for Greece, which in turn is used to investigate whether changes in the FSSI are good indicators for financial crises. The results show that the FSSI is able to provide a precise periodization of crises. JEL Classification: G01, G10, G20, E44
    Keywords: financial crisis, multivariate GARCH, stress index, systemic stress
    Date: 2013–07
  7. By: A. K. Bahl; O. Baltzer; A. Rau-Chaplin; B. Varghese; A. Whiteway
    Abstract: Stochastic simulation techniques employed for the analysis of portfolios of insurance/reinsurance risk, often referred to as `Aggregate Risk Analysis', can benefit from exploiting state-of-the-art high-performance computing platforms. In this paper, parallel methods to speed-up aggregate risk analysis for supporting real-time pricing are explored. An algorithm for analysing aggregate risk is proposed and implemented for multi-core CPUs and for many-core GPUs. Experimental studies indicate that GPUs offer a feasible alternative solution over traditional high-performance computing systems. A simulation of 1,000,000 trials with 1,000 catastrophic events per trial on a typical exposure set and contract structure is performed in less than 5 seconds on a multiple GPU platform. The key result is that the multiple GPU implementation can be used in real-time pricing scenarios as it is approximately 77x times faster than the sequential counterpart implemented on a CPU.
    Date: 2013–08

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