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Banking and markets
(2001)
This paper integrates a number of recent themes in the literature in banking and asset markets–optimal risk sharing, limited market participation, asset-price volatility, market liquidity, and financial crises–in a general-equilibrium theory of the financial system. A complex financial system comprises both financial markets financial institutions. Financial institutions can take the form of intermediaries or banks. Banks, inlike intermediaries, are subject to runs, but crises do not imply market failure. We show that a sophisticated financiel system–a system with complete markets for aggregate risk and limited market participation–is incentive-efficient, if the institutions take the form of intermediaries, or else constrained-efficient, of they take the form of banks. We also consider an economy in which the markets for aggregate risks are incomplete. In this context, there is a rolefpr prudential regulation: regulating liquidity can improve welfare.
Real options theory applies techniques known from finance theory to the valuation of capital investments. The present paper investigates further into this analogy, considering the case of a portfolio of real options. An implementation of real option models in practice will mostly be concerned with a portfolio of real options, so the analysis of portfolio aspects is of both academic and practical interest. Is a portfolio of real options special? In order to shed some light on this question, the present paper will outline the relevant features of a portfolio of real options. It will show that the analogy to financial options remains great if compound option models are applied. As a result, a portfolio of real options, and therefore the firm as such, generally is to be understood as one single compound, real option.
We analyse the coordination problem in multi-creditor relationships empirically, relying on a unique panel data set that contains detailed credit-file information on distressed lending relationships in Germany, including information on creditor pools, a legal institution aiming at coordinating lender interests in borrower distress. We report three major findings. First, the existence of creditor pools increases the probability of workout success. Second, the results are consistent with coordination costs being positively related to pool size. Third, major determinants of pool formation are found to be the number of banks, the distribution of lending shares, and the severity of the distress shock.
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 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.
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
Our study provides evidence on the share price reactions to the announcement of equity issues in Germany, where capital market is characterized by institutional features distinct from the U.S. market. German seasoned equity issues yield a positive market reaction which contrasts to the significant negative abnormal returns reported for the U.S. We provide evidence that these results are due to differences in both issuing characteristics and floatation methods, and in the corporate governance and ownership structures of the two countries. Our study explains much of the empirical puzzle of different market reactions to seemingly similar events across financial markets.
In this paper, we estimate the demand for homeowner insurance in Florida. Since we are interested in a number of factors influencing demand, we approach the problem from two directions. We first estimate two hedonic equations representing the premium per contract and the price mark-up. We analyze how the contracts are bundled and how contract provisions, insurer characteristics and insured risk characteristics and demographics influence the premium per contract and the price mark-up. Second, we estimate the demand for homeowners insurance using two-stage least squares regression. We employ ISO's indicated loss costs as our proxy for real insurance services demanded. We assume that the demand for coverage is essentially a joint demand and thus we can estimate the demand for catastrophe coverage separately from the demand for noncatastrophe coverage. We determine that price elasticities are less elastic for catastrophic coverage than for non-catastrophic coverage. Further estimated income elasticities suggest that homeowners insurance is an inferior good. Finally, we conclude based on the results of a selection model that our sample of ISO reporting companies well represents the demand for insurance in the Florida market as a whole.