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on Risk Management |
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Issue of 2006‒11‒18
seven papers chosen by |
| By: | Panayiotis Diamantis (Department of Business Administration, Athens University of Economics and Business); George Kouretas (Department of Economics, University of Crete, Greece); Leonidas Zarangas (Department of Finance and Auditing, Technological Educational Institute of Epirus, Greece) |
| Abstract: | This paper provides Value-at-Risk estimates for daily stock returns with the application of various parametric univariate models that belong to the class of ARCH models which are based on the skewed Student distribution. We use daily data for three stock indexes of the Athens Stock Exchange (ASE) and three stocks of Greek companies listed in the ASE. We conduct our analysis with the adoption of the methodology suggested by Giot and Laurent (2003). Therefore, we estimate an APARCH model based on the skewed Student distribution to fully take into account the fat left and right tails of the returns distribution. We show that the estimated VaR for traders having both long and short positions in the Athens Stock Exchange is more accurately modeled by a skewed Student APARCH model that by a normal or Student distributions. |
| Keywords: | Value-at-Risk, risk management, APARCH models, skewed Student |
| JEL: | C53 G21 G28 |
| Date: | 2006–01 |
| URL: | http://d.repec.org/n?u=RePEc:crt:wpaper:0614&r=rmg |
| By: | George Kouretas (Department of Economics, University of Crete, Greece); Leonidas Zarangas (Department of Finance and Auditing, Technological Educational Institute of Epirus, Greece) |
| Abstract: | This paper employs a new approach due to Engle and Manganelli (2004) in order to examine market risk in several major equity markets, as well as for major companies listed in New York Stock Exchange and Athens Stock Exchange. By interpreting the VaR as the quantile of future portfolio values conditional on current information, Engle and Manganelli (2004) propose a new approach to quantile estimation that does not require any of the extreme assumptions of the existing methodologies, mainly normality and i.i.d. returns. The CAViaR model shifts the focus of attention from the distribution of returns directly to the behaviour of the quantile. We provide a comparative evaluation of the predictive performance of four alternative CAViaR specifications, namely Adaptive, Symmetric Absolute Value, Asymmetric Slope and Indirect GARCH(1,1) models. The main findings of the present analysis is that we are able to confirm some stylized facts of financial data such as volatility clustering while the Dynamic Quantile criterion selects different models for different confidence intervals for the case of the five general indices, the US companies and the Greek companies respectively. |
| Keywords: | Non-linear Regression Quantile, Value-at-Risk, Risk Management, |
| JEL: | C53 G21 G28 |
| Date: | 2005–11 |
| URL: | http://d.repec.org/n?u=RePEc:crt:wpaper:0521&r=rmg |
| By: | Toker Doganoglu (University of Munich); Christoph Hartz (University of Munich); Stefan Mittnik (University of Munich, Center for Financial Studies and ifo) |
| Abstract: | Assumptions about the dynamic and distributional behavior of risk factors are crucial for the construction of optimal portfolios and for risk assessment. Although asset returns are generally characterized by conditionally varying volatilities and fat tails, the normal distribution with constant variance continues to be the standard framework in portfolio management. Here we propose a practical approach to portfolio selection. It takes both the conditionally varying volatility and the fat-tailedness of risk factors explicitly into account, while retaining analytical tractability and ease of implementation. An application to a portfolio of nine German DAX stocks illustrates that the model is strongly favored by the data and that it is practically implementable. |
| Keywords: | Multivariate Stable Distribution, Index Model, Portfolio Optimization, Value-at-Risk, Model Adequacy |
| JEL: | C13 C32 G11 G14 G18 |
| Date: | 2006–11–03 |
| URL: | http://d.repec.org/n?u=RePEc:cfs:cfswop:wp2000624&r=rmg |
| By: | Diana Barro (Department of Applied Mathematics, University of Venice); Antonella Basso (Department of Applied Mathematics, University of Venice) |
| Abstract: | This contribution studies the effects of credit contagion on the credit risk of a portfolio of bank loans. To this aim we introduce a model that takes into account the counterparty risk in a network of interdependent firms that describes the presence of business relations among different firms. The location of the firms is simulated with probabilities computed using an entropy spatial interaction model. By means of a wide simulation analysis we use the model proposed to study the effects of default contagion on the loss distribution of a portfolio. |
| Keywords: | credit risk, bank loan portfolios, contagion models, entropy spatial models |
| JEL: | G33 G21 C15 |
| Date: | 2006 |
| URL: | http://d.repec.org/n?u=RePEc:vnm:wpaper:143&r=rmg |
| By: | Einmahl,John H.J.; Li,Jun; Liu,Regina Y. (Tilburg University, Center for Economic Research) |
| Abstract: | Risk assessments often encounter extreme settings with very few or no occurrences in reality. Inferences about risk indicators in such settings face the problem of insufficient data. Extreme value theory is particularly well suited for handling this type of problems. This paper uses a multivariate extreme value theory approach to establish thresholds for signaling levels of risk in the context of simultaneous monitoring of multiple risk indicators. The proposed threshold system is well justified in terms of extreme multivariate quantiles, and its sample estimator is shown to be consistent. As an illustration, the proposed approach is applied to developing a threshold system for monitoring airline performance measures. This threshold system assigns different risk levels to observed airline performance measures. In particular, it divides the sample space into regions with increasing levels of risk. Moreover, in the univariate case, such a thresholding technique can be used to determine a suitable cut-off point on a runway for holding short of landing aircrafts. This cut-off point is chosen to ensure a certain required level of safety when allowing simultaneous operations on two intersecting runways in order to ease air traffic congestion. |
| Keywords: | Extreme value theory;extreme quantile;multiple risk indicators;multivariate quantile;rare event;statistics of extremes;threshold system |
| JEL: | C13 C14 C15 L93 |
| Date: | 2006 |
| URL: | http://d.repec.org/n?u=RePEc:dgr:kubcen:2006104&r=rmg |
| By: | Roman Kraeussl (Center for Financial Studies, Frankfurt am Main, Germany) |
| Abstract: | This paper deals with the proposed use of sovereign credit ratings in the “Basel Accord on Capital Adequacy” (Basel II) and considers its potential effect on emerging markets financing. It investigates in a first attempt the consequences of the planned revisions on the two central aspects of international bank credit flows: the impact on capital costs and the volatility of credit supply across the risk spectrum of borrowers. The empirical findings cast doubt on the usefulness of credit ratings in determining commercial banks’ capital adequacy ratios since the standardized approach to credit risk would lead to more divergence rather than convergence between investment-grade and speculative-grade borrowers. This conclusion is based on the lateness and cyclical determination of credit rating agencies’ sovereign risk assessments and the continuing incentives for short-term rather than long-term interbank lending ingrained in the proposed Basel II framework. |
| Keywords: | Sovereign Risk, Credit Ratings, Basel II |
| JEL: | E44 E47 G15 |
| URL: | http://d.repec.org/n?u=RePEc:crt:wpaper:0318&r=rmg |
| By: | Francesco Bertoluzzo (Consorzio Venezia Ricerche); Marco Corazza (Department of Applied Mathematics, University of Venice) |
| Abstract: | In this paper we propose a financial trading system whose trading strategy is developed by means of an artificial neural network approach based on a learning algorithm of recurrent reinforcement type. In general terms, this kind of approach consists: first, in directly specifying a trading policy based on some predetermined investorâs measure of profitability; second, in directly setting the financial trading system while using it. In particular, with respect to the prominent literature, in this contribution: first, we take into account as measure of profitability the reciprocal of the returns weighted direction symmetry index instead of the wide-spread Sharpe ratio; second, we obtain the differential version of the measure of profitability we consider, and obtain all the related learning relationships; third, we propose a simple procedure for the management of drawdown-like phenomena; finally, we apply our financial trading approach to some of the most prominent assets of the Italian stock market. |
| Keywords: | Financial trading system, recurrent reinforcement learning, no-hidden-layer perceptron model, returns weighted directional symmetry measure, gradient ascent technique, Italian stock market. |
| JEL: | C45 C61 C63 G31 |
| Date: | 2006–10 |
| URL: | http://d.repec.org/n?u=RePEc:vnm:wpaper:141&r=rmg |