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Der vorliegende Beitrag zeigt auf, wie hedonische Preisindizes für Immobilien auf der Basis von Transaktionen berechnet werden können. Der Heterogenität der Immobilien wird dabei durch ein ökonometrisches Modell Rechnung getragen, wobei in dieser Arbeit das Problem der Wahl einer geeigneten Funktionsform durch eine Transformation nach dem Ansatz von Box/Cox (1964) explizit berücksichtigt wird. Die Datenbasis deckt etwa 65% der Transaktionen des Wohnungsmarktes im Zeitraum 1990-1999 ab. Die Korrektur aufgrund unvollständiger Angaben führt zu einem Datensatz von 84 686 Transaktionen. Dieser Datensatz ist ein Vielfaches dessen, was bisher vergleichbaren Studien zugrunde lag und stellt damit eine international einmalige Datengrundlage dar.
We analyze exchange rates along with equity quotes for 3 German firms from New York (NYSE) and Frankfurt (XETRA) during overlapping trading hours to see where price discovery occurs and how stock prices adjust to an exchange rate shock. Findings include: (a) the exchange rate is exogenous with respect to the stock prices; (b) exchange rate innovations are more important in understanding the evolution of NYSE prices than XETRA prices; and (c) most (but not all) of the fundamental or random walk component of firm value is determined in Frankfurt.
In this paper we study the benefits derived from international diversification of stock portfolios from German and Hungarian point of view. In contrast to the German capital market, which is one of the largest in the world, the Hungarian Stock Exchange is an emerging market. The Hungarian stock market is highly volatile, high returns are often accompanied by extremely large risk. Therefore, there is a good potential for Hungarian investors to realize substantial benefits in terms of risk reduction by creating multi-currency portfolios. The paper gives evidence on the above me ntioned benefits for both countries by examining the performance of several ex ante portfolio strategies. In order to control the currency risk, different types of hedging approaches are implemented.
The present paper seeks to study the possible diversification potential by the integration of indirect real estate investments in international portfolios. To this end, monthly index-return time-series in the time-period from January 1985 till December 1998 from real estate investment companies as well as common stocks and bonds in Germany, France, Switzerland, Great Britain and the USA were used. We utilize, due to the critical normal distribution assumption, a mean/lower-partial-moment framework. In order to take into account the influence of the currency risk for international investments the analyses have been undertaken both with as well as without hedging the currency risk. We take the viewpoint of a German as well as that of a US-investor to gain insight into the dependency of the diversification potential on the reference currency of the investor.
In this paper we have developed a financial model of the non-life insurer to provide assistance for the management of the insurance company in making decisions on product, investment and reinsurance mix. The model is based on portfolio theory and recognizes the stochastic nature of and the interaction between the underwriting and investment income of the insurance business. In the context of an empirical application we illustrate howa portfolio optimisation approach can be used for asset-liability management.
Evaluating the quality of credit portfolio risk models is an important question for both banks and regulators. Lopez and Saidenberg (2000) suggest cross-sectional resampling techniques in order to make efficient use of available data and to produce measures of forecast accuracy. We first show that their proposal disregards crosssectional dependence in simulated subportfolios, which renders standard statistical inference invalid. We proceed by suggesting another evaluation methodology which draws on the concept of likelihood ratio tests. Specifically, we compare the predictive quality of alternative models by comparing the probabilities that observed data have been generated by these models. The distribution of the test statistic can be derived through Monte Carlo simulation. To exploit differences in cross-sectional predictions of alternative models, the test can be based on a linear combination of subportfolio statistics. In the construction of the test, the weight of a subportfolio depends on the difference in the loss distributions which alternative models predict for this particular portfolio. This makes efficient use of the data, and reduces computational burden. Monte Carlo simulations suggest that the power of the tests is satisfactory.
JEL classification: G2; G28; C52
Evaluating the quality of credit portfolio risk models is an important issue for both banks and regulators. Lopez and Saidenberg (2000) suggest cross-sectional resampling techniques in order to make efficient use of available data. We show that their proposal disregards cross-sectional dependence in resampled portfolios, which renders standard statistical inference invalid. We proceed by suggesting the Berkowitz (1999) procedure, which relies on standard likelihood ratio tests performed on transformed default data. We simulate the power of this approach in various settings including one in which the test is extended to incorporate cross-sectional information. To compare the predictive ability of alternative models, we propose to use either Bonferroni bounds or the likelihood-ratio of the two models. Monte Carlo simulations show that a default history of ten years can be sufficient to resolve uncertainties currently present in credit risk modeling.