24 research outputs found

    Minimizing shortfall risk for multiple assets derivatives

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    The risk minimizing problem E[l((HXTx,π)+)]πmin\mathbf{E}[l((H-X_T^{x,\pi})^{+})]\overset{\pi}{\longrightarrow}\min in the Black-Scholes framework with correlation is studied. General formulas for the minimal risk function and the cost reduction function for the option HH depending on multiple underlying are derived. The case of a linear and a strictly convex loss function ll are examined. Explicit computation for l(x)=xl(x)=x and l(x)=xpl(x)=x^p, with p>1p>1 for digital, quantos, outperformance and spread options are presented. The method is based on the quantile hedging approach presented in \cite{FL1}, \cite{FL2} and developed for the multidimensional options in \cite{Barski}.

    Quantile hedging for multiple assets derivatives

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    The problem of quantile hedging for multiple assets derivatives in the Black-Scholes model with correlation is considered. Explicit formulas for the probability maximizing function and the cost reduction function are derived. Applicability of the results for the widely traded derivatives as digital, quantos, outperformance and spread options is shown.

    Heath-Jarrow-Morton-Musiela equation with linear volatility

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    The paper is concerned with the problem of existence of solutions for the Heath-Jarrow-Morton equation with linear volatility. Necessary conditions and sufficient conditions for the existence of weak solutions and strong solutions are provided. It is shown that the key role is played by the logarithmic growth conditions of the Laplace exponent.

    Substrate Specificity, Inhibitor Selectivity and Structure-Function Relationships of Aldo-Keto Reductase 1B15: A Novel Human Retinaldehyde Reductase

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    Human aldo-keto reductase 1B15 (AKR1B15) is a newly discovered enzyme which shares 92% amino acid sequence identity with AKR1B10. While AKR1B10 is a well characterized enzyme with high retinaldehyde reductase activity, involved in the development of several cancer types, the enzymatic activity and physiological role of AKR1B15 are still poorly known. Here, the purified recombinant enzyme has been subjected to substrate specificity characterization, kinetic analysis and inhibitor screening, combined with structural modeling. AKR1B15 is active towards a variety of carbonyl substrates, including retinoids, with lower kcat and Km values than AKR1B10. In contrast to AKR1B10, which strongly prefers all-trans-retinaldehyde, AKR1B15 exhibits superior catalytic efficiency with 9-cis-retinaldehyde, the best substrate found for this enzyme. With ketone and dicarbonyl substrates, AKR1B15 also shows higher catalytic activity than AKR1B10. Several typical AKR inhibitors do not significantly affect AKR1B15 activity. Amino acid substitutions clustered in loops A and C result in a smaller, more hydrophobic and more rigid active site in AKR1B15 compared with the AKR1B10 pocket, consistent with distinct substrate specificity and narrower inhibitor selectivity for AKR1B15
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