03268cam a22003495a 45000010009000000050017000090080041000260100017000670200031000840200031001150400029001460420008001750820024001831000050002072450138002572600058003953000033004535000026004865040032005125050262005445201740008065900011025466500046025576500048026036510010026516530024026616530024026857000018027099420028027279990017027559520146027721822980920161018130323.0140717s2015    nyua   frb    001 0 eng d  a  2014025178  a9780199338290 (alk. paper)  a9780199338306 (alk. paper)  aDLCbengcDLCdEG-ScBUE   apcc04222a332.015195bDIE1 aDiebold, Francis X.,‏ ‎d1959-‏ 94155810aFinancial and macroeconomic connectedness :ba network approach to measurement and monitoring /cFrancis X. Diebold and Kamil Yilmaz.  aNew York ;aOxford :bOxford University Press,c2015.  axv, 265 p. :bill. ;c24 cm.  aIndexes : p. 241-265.  aBibliography : p. 233 -239.  aMeasuring and monitoring financial and macroeconomic connectedness -- U.S. asset classes -- Major U.S. financial institutions -- Global stock markets -- Sovereign bond markets --
Foreign exchange markets -- Assets across countries -- Global business cycles.  a"The approach to connectedness proposed by the authors is intimately related to the familiar econometric notion of variance decomposition. The full set of variance decompositions from vector auto-regressions produces the core of the 'connectedness table.' The connectedness table makes clear how one can begin with the most disaggregated pair-wise directional connectedness measures and aggregate them in various ways to obtain total connectedness measures. The authors also show that variance decompositions define weighted, directed networks, so that these proposed connectedness measures are intimately related to key measures of connectedness used in the network literature. After describing their methods in the first part of the book, the authors proceed to characterize daily return and volatility connectedness across major asset (stock, bond, foreign exchange and commodity) markets as well as the financial institutions within the U.S. and across countries since late 1990s. These specific measures of volatility connectedness show that stock markets played a critical role in spreading the volatility shocks from the U.S. to other countries. Furthermore, while the return connectedness across stock markets increased gradually over time the volatility connectedness measures were subject to significant jumps during major crisis events. This book examines not only financial connectedness, but also real fundamental connectedness. In particular, the authors show that global business cycle connectedness is economically significant and time-varying, that the U.S. has disproportionately high connectedness to others, and that pairwise country connectedness is inversely related to bilateral trade surpluses"--The publisher.   aWessam 7aFinancexEconometric models.2BUEsh93155 7aFinancexMathematical models.2BUEsh922542  2BUEsh  bBUSADMcOctober2016  bBUSECOcOctober20161 aYlmaz, Kamil.  2ddce22k332.015195 DIE  c22676d22648  00102ddc40708AcademicaMAINbMAINc1STd2016-10-18ePurchaseg385.00h9154l0o332.015195 DIEp000033443r2025-07-15 00:00:00v481.00yBB