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Dynamic Correlation (dynamic + correlation)
Selected AbstractsLeft,right and dynamic correlationINTERNATIONAL JOURNAL OF QUANTUM CHEMISTRY, Issue 2 2002Kian Molawi Within density functional theory, it is natural to separate the correlation energy into two parts: left,right correlation and dynamic correlation. Left,right correlation arises from the exchange part of functionals, and dynamic correlation arises from the correlation part of functionals. We examine the nature of these correlation energies as molecules are distorted. We observe that such a natural separation is not possible using the methods of quantum chemistry. © 2002 Wiley Periodicals, Inc. Int J Quantum Chem, 2002 [source] A valence bond study of the dioxygen moleculeJOURNAL OF COMPUTATIONAL CHEMISTRY, Issue 1 2007Peifeng Su Abstract The dioxygen molecule has been the subject of valence bond (VB) studies since 1930s, as it was considered as the first "failure" of VB theory. The object of this article is to provide an unambiguous VB interpretation for the nature of chemical bonding of the molecule by means of modern VB computational methods, VBSCF, BOVB, and VBCI. It is shown that though the VBSCF method can not provide quantitative accuracy for the strongly electronegative and electron-delocalized molecule because of the lack of dynamic correlation, it still gives a correct qualitative analysis for wave function of the molecule and provides intuitive insights into chemical bonding. An accurate quantitative description for the molecule requires higher levels of VB methods that incorporate dynamic correlation. The potential energy curves of the molecule are computed at the various VB levels. It is shown that there exists a small hump in the PECs of VBSCF for the ground state, as found in previous studies. However, higher levels of VB methods dissolve the hump. The BOVB and VBCI methods reproduce the dissociation energies and other physical properties of the ground state and the two lowest excited states in very good agreement with experiment and with sophisticated MO based methods, such as the MRCI method. © 2006 Wiley Periodicals, Inc. J Comput Chem, 2007 [source] THE TEN COMMANDMENTS FOR OPTIMIZING VALUE-AT-RISK AND DAILY CAPITAL CHARGESJOURNAL OF ECONOMIC SURVEYS, Issue 5 2009Michael McAleer Abstract Credit risk is the most important type of risk in terms of monetary value. Another key risk measure is market risk, which is concerned with stocks and bonds, and related financial derivatives, as well as exchange rates and interest rates. This paper is concerned with market risk management and monitoring under the Basel II Accord, and presents Ten Commandments for optimizing value-at-risk (VaR) and daily capital charges, based on choosing wisely from (1) conditional, stochastic and realized volatility; (2) symmetry, asymmetry and leverage; (3) dynamic correlations and dynamic covariances; (4) single index and portfolio models; (5) parametric, semi-parametric and non-parametric models; (6) estimation, simulation and calibration of parameters; (7) assumptions, regularity conditions and statistical properties; (8) accuracy in calculating moments and forecasts; (9) optimizing threshold violations and economic benefits; and (10) optimizing private and public benefits of risk management. For practical purposes, it is found that the Basel II Accord would seem to encourage excessive risk taking at the expense of providing accurate measures and forecasts of risk and VaR. [source] | ||||||||||