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The Determinants of Credit Spread Changes.

by Pierre Collin-Dufresne , Robert S Goldstein , J Spencer Martin , Gurdip Bakshi , Greg Bauer , Dave Brown , Francesca Carrieri , Peter Christoffersen , Susan Christoffersen , Greg Duffee , Darrell Duffie , Vihang Errunza , Gifford Fong , Mike Gallmeyer , Laurent Gauthier , Rick Green , John Griffin , Jean Helwege , Kris Jacobs , Chris Jones , Andrew Karolyi , Dilip Madan , David Mauer , Erwan Morellec , Federico Nardari , N R Prabhala , Tony Sanders , Sergei Sarkissian , Bill Schwert , Ken Singleton , Chester Spatt , René Stulz - Journal of Finance , 2001
"... ABSTRACT Using dealer's quotes and transactions prices on straight industrial bonds, we investigate the determinants of credit spread changes. Variables that should in theory determine credit spread changes have rather limited explanatory power. Further, the residuals from this regression are ..."
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-quadratic regression σ(K) = a + bK + cK 2 , where K is the strike price. Our estimate of this slope, jump t , is defined via where F is the at-the money strike price, which equals the current futures price. We choose to look at the implied volatility at K = .9F because we do not want 6 to extrapolate the quadratic

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by unknown authors
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unknown title

by Jani Lukkarinen, Peng Mei, Herbert Spohn , 2012
"... ar ..."
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1On the Identifiability of Overcomplete Dictionaries via the Minimisation Principle Underlying K-SVD

by Karin Schnass , 2013
"... This article gives theoretical insights into the performance of K-SVD, a dictionary learning algorithm that has gained significant popularity in practical applications. The particular question studied here is when a dictionary Φ ∈ Rd×K can be recovered as local minimum of the minimisation criterion ..."
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it is further demonstrated that given a finite number of training samples N, such that N / logN = O(K3d), except with probability O(N−Kd) there is a local minimum of the K-SVD criterion within distance O(KN−1/4) to the generating dictionary. Index Terms dictionary learning, sparse coding, K-SVD, finite sample

1 Approximate Ergodic Capacity of a Class of Fading 2-user 2-hop Networks

by Sang-woon Jeon, Chien-yi Wang, Student Member, Michael Gastpar
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ftp ejde.math.swt.edu (login: ftp) RADIAL MINIMIZER OF A VARIANT OF THE P-GINZBURG-LANDAU FUNCTIONAL

by Yutian Lei
"... Abstract. We study the asymptotic behavior of the radial minimizer of a variant of the p-Ginzburg-Landau functional when p ≥ n. The location of the zeros and the uniqueness of the radial minimizer are derived. We also prove the W 1,p convergence of the radial minimizer for this functional. 1. ..."
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Abstract. We study the asymptotic behavior of the radial minimizer of a variant of the p-Ginzburg-Landau functional when p ≥ n. The location of the zeros and the uniqueness of the radial minimizer are derived. We also prove the W 1,p convergence of the radial minimizer for this functional. 1.

1 An Algebraic Approach to Physical-Layer Network Coding

by Chen Feng, Danilo Silva, Frank R. Kschischang
"... ar ..."
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:1

by Jani Lukkarinen, Peng Mei, Herbert Spohn , 2014
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Function Alignment and Converse Theorems

by Changho Suh, Naveen Goela, Michael Gastpar
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"... ftp ejde.math.swt.edu ftp ejde.math.unt.edu (login: ftp) Asymptotic behavior of regularizable minimizers of a Ginzburg-Landau functional in higher dimensions ∗ ..."
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ftp ejde.math.swt.edu ftp ejde.math.unt.edu (login: ftp) Asymptotic behavior of regularizable minimizers of a Ginzburg-Landau functional in higher dimensions ∗
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