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    <title>EconStor Collection: CoFE-Diskussionspapiere, Universität Konstanz</title>
    <link>http://hdl.handle.net/10419/238</link>
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  <item rdf:about="http://hdl.handle.net/10419/32191">
    <title>Information asymmetries and securitization design</title>
    <link>http://hdl.handle.net/10419/32191</link>
    <description>Title: Information asymmetries and securitization design
&lt;br/&gt;
&lt;br/&gt;Authors: Franke, Günter; Herrmann, Markus; Weber, Thomas
&lt;br/&gt;
&lt;br/&gt;Abstract: The strong growth in collateralized debt obligation transactions raises the question how these transactions are designed. The originator designs the transaction so as to maximize her benefit subject to requirements imposed by investors and rating agencies. An important issue in these transactions is the information asymmetry between the originator and the investors. First Loss Positions are the most important instrument to mitigate conflicts due to information asymmetry. We analyse the optimal size of the First Loss Position in a model and the actual size in a set of European collateralized debt obligation transactions. We find that the asset pool quality, measured by the weighted average default probability and the diversity score of the pool, plays a predominant role for the transaction design. Characteristics of the originator play a small role. A lower asset pool quality induces the originator to take a higher First Loss Position and, in a synthetic transaction, a smaller Third Loss Position. The First Loss Position bears on average 86 % of the expected default losses, independent of the asset pool quality. This loss share and the asset pool quality strongly affect the rating and the credit spread of the lowest rated tranche.</description>
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  <item rdf:about="http://hdl.handle.net/10419/32190">
    <title>Two-dimensional risk neutral valuation relationships for the pricing of options</title>
    <link>http://hdl.handle.net/10419/32190</link>
    <description>Title: Two-dimensional risk neutral valuation relationships for the pricing of options
&lt;br/&gt;
&lt;br/&gt;Authors: Franke, Günter; Huang, James; Stapleton, Richard C.
&lt;br/&gt;
&lt;br/&gt;Abstract: The Black-Scholesmodelis basedona one-parameter pricingkernel with constantelasticity. Theoretical and empirical results suggest declining elasticity and, hence, a pricing kernel withat leasttwo parameters.We price European-style optionson assets whose probability distributions have two unknown parameters. We assume a pricing kernel which also has two unknown parameters. When certain conditions are met,atwo-dimensional risk-neutral valuation relationship exists for the pricing of these options: i.e. the relationshipbetween the price of the option and the prices of the underlying asset and one other option on the assetisthe sameasitwouldbe under risk neutrality.In this classofmodels,the priceof the underlying asset and that of one other option take the place of the unknown parameters.</description>
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  <item rdf:about="http://hdl.handle.net/10419/32189">
    <title>Importance sampling for backward SDEs</title>
    <link>http://hdl.handle.net/10419/32189</link>
    <description>Title: Importance sampling for backward SDEs
&lt;br/&gt;
&lt;br/&gt;Authors: Bendera, Christian; Moseler, Thilo
&lt;br/&gt;
&lt;br/&gt;Abstract: In this paper we explain how the importance sampling technique can be generalized from simulating expectations to computing the initial value of backward SDEs with Lipschitz continuous driver. By means of a measure transformation we introduce a variance reduced version of the forward approximation scheme by Bender and Denk [4] for simulating backward SDEs. A fully implementable algorithm using the least-squares Monte Carlo approach is developed and its convergence is proved. The success of the generalized importance sampling is illustrated by numerical examples in the context of Asian option pricing under different interest rates for borrowing and lending.</description>
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  <item rdf:about="http://hdl.handle.net/10419/32188">
    <title>The dynamics of overconfidence: Evidence from stock market forecasters</title>
    <link>http://hdl.handle.net/10419/32188</link>
    <description>Title: The dynamics of overconfidence: Evidence from stock market forecasters
&lt;br/&gt;
&lt;br/&gt;Authors: Deaves, Richard; Lüders, Erik; Schröder, Michael
&lt;br/&gt;
&lt;br/&gt;Abstract: As a group, market forecasters are egregiously overconfident. In conformity to the dynamic model of overconfidence of Gervais and Odean (2001), successful forecasters have become more overconfident. What's more, more experienced forecasters have learned to be overconfident, and hence are more susceptible to this behavioral flaw than their less experienced peers . It is not just individuals who are affected. Markets also become more overconfident when market returns have been high.</description>
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