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on Risk Management |
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Issue of 2005‒10‒22
four papers chosen by |
| By: | Ying Chen; Wolfgang Härdle; Seok-Oh Jeong |
| Abstract: | In this paper we propose the GHADA risk management model that is based on the generalized hyperbolic (GH) distribution and on a nonparametric adaptive methodology. Compared to the normal distribution, the GH distribution possesses semi-heavy tails and represents the financial risk factors more appropriately. The nonparametric adaptive methodology has the desirable property of estimating homogeneous volatility in a short time interval. For DEM/USD exchange rate data and a German bank portfolio data the proposed GHADA model provides more accurate value at risk calculation than the traditional model based on the normal distribution. All calculations and simulations are done with XploRe. |
| Keywords: | adaptive volatility estimation, generalized hyperbolic distribution, value at risk, risk management |
| JEL: | C |
| Date: | 2004–10 |
| URL: | http://d.repec.org/n?u=RePEc:hum:wpaper:sfb649dp2005-001&r=rmg |
| By: | Marco Del Negro; Robin Brooks |
| Abstract: | We estimate a latent factor model that decomposes international stock returns into global, country-, and industry-specific shocks and allows for stock-specific exposures to these shocks. We find that across stocks there is substantial dispersion in these exposures, which is partly explained by the extent to which firms operate across countries. We show that portfolios consisting of stocks with low exposures to country shocks achieve substantial variance reduction relative to the global market, both in- and out-of-sample. The shock exposures are thus a stock-selection device for international portfolio diversification. |
| Keywords: | Globalization , International capital markets , Risk premium , Export diversification , Industrialization , Stock markets , Economic models , |
| Date: | 2005–03–21 |
| URL: | http://d.repec.org/n?u=RePEc:imf:imfwpa:05/52&r=rmg |
| By: | Hamerle, Alfred; Knapp, Michael; Wildenauer, Nicole |
| Abstract: | Im vorliegenden Beitrag wird untersucht, wie die Assetkorrelation zwischen zwei Sektoren auf einfache Weise berechnet werden kann und wie sich unterschiedliche Korrelationsannahmen auf die Form und Risikomaße von Verlustverteilungen auswirken. Dazu werden Ausfallzeitreihen von zwei us-amerikanischen Sektoren untersucht. Zum einen wird das Segment „Industrieunternehmen“ und zum anderen das Retailsegment „Kreditkarten“ betrachtet. Es wird gezeigt, wie unter Verwendung eines dynamischen Modells die Schuldnerbonität bzw. die Ausfallwahrscheinlichkeit unter Einbeziehung schuldnerspezifischer und makroökonomischer Faktoren geschätzt werden kann. Es stellt sich heraus, dass durch die Einbeziehung vor allem makroökonomischer Größen die Ausfallwahrscheinlichkeit „Point in Time“ prognostiziert und sowohl die Assetkorrelation innerhalb eines Sektors bzw. Risikosegments als auch die intersektorale Korrelation verringert werden können. Dies führt im Allgemeinen zu präziseren Prognosen der Verlustverteilungen. |
| Keywords: | Probability of Default, asset correlation, default correlation, credit risk, credit risk management |
| JEL: | G21 C1 |
| Date: | 2005–10–18 |
| URL: | http://d.repec.org/n?u=RePEc:bay:rdwiwi:582&r=rmg |
| By: | Tanya Araujo; Francisco Louçã |
| Abstract: | This paper investigates the dynamics of stocks in the S&P500 index for the last 30 years. Using a stochastic geometry technique, we investigate the evolution of the market space and define a new measure for that purpose, which is a robust index of the dynamics of the market structure and provides information on the intensity and the sectoral impact of the crises. With this measure, we analyze the effects of some extreme phenomena on the geometry of the market. Nine crashes between 1987 and 2001 are compared by looking at the way they modify the shape of the manifold that describes the S&P500 market space. These crises are identified as (a) structural, (b) general and (c) local. |
| Keywords: | financial markets; stochastic geometry; complexity; market spaces; market structures. |
| JEL: | C0 G1 |
| URL: | http://d.repec.org/n?u=RePEc:ise:isegwp:wp152005&r=rmg |