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ePub What Determines U.S. Swap Spreads? (World Bank Working Papers) download

by Adam Kobor,Lishan Shi,Ivan Zelenko

ePub What Determines U.S. Swap Spreads? (World Bank Working Papers) download
Author:
Adam Kobor,Lishan Shi,Ivan Zelenko
ISBN13:
978-0821363386
ISBN:
0821363387
Language:
Publisher:
World Bank Publications (July 11, 2005)
Category:
Subcategory:
Investing
ePub file:
1296 kb
Fb2 file:
1687 kb
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Rating:
4.8
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300

Kobor, Adam; Shi, Lishan; Zelenko, Ivan.

Multifactor models that were estimated on observed swap rates highlighted the central role played by the liquidity component in explaining swap-spread dynamics over the past 15 years. The multifactor models also found some puzzling empirical results. Kobor, Adam; Shi, Lishan; Zelenko, Ivan. World Bank Working Paper No. 62. Washington, DC: World Bank.

Swap Spreads? Adam Kobor Lishan Shi Ivan Zelenko. 26 World Bank Working Paper. are the major long-term determinant, with the most appropriate methodology based on the concept of cointegration. THE WORLD BANK Washington, . Our overview of existing empirical works tells us that this methodology has not been applied entirely to . We wish to obtain a good explanation of the past, based on a good fit to real data.

World Bank Working Papers). by Ádám Kóbor, Adam Kobor, Lishan Shi, Ivan Zelenko. This paper studies the determinants of . Dollar (US$) interest rate swap spreads from 1994 to 2004 and presents an econometric model based on this analysis. Published July 15, 2005 by World Bank Publications.

By Adam Kobor, Lishan Shi and Ivan Zelenko; Abstract: This paper . Adam Kobor, Lishan Shi and Ivan Zelenko. The error-correction model fits observed swap spreads quite well over the sample period

By Adam Kobor, Lishan Shi and Ivan Zelenko; Abstract: This paper examines the evolution of the . interest swap market. No 7272 in World Bank Publications from The World Bank. Abstract: This paper examines the evolution of the . The error-correction model fits observed swap spreads quite well over the sample period. The authors illustrate how the same model can be used to carry out scenario analysis.

Swap spreads? Article in World Bank Working Paper · January 2005 with 25 Reads. This paper examines the evolution of the . How we measure 'reads'. swap spreads and estimate an error-correction model for maturities of 2, 5, and 10 years from 1994 to 2004. Financial theory depicts swaps as contr acts indexed on London interbank offered (LIBOR) rates, rendered almost free of counterparty default risk by mark-to-market and collateralization.

This title examines the evolution of the . Adam Kobor, Lishan Shi., Ivan Zelenko. Multifactor models which were estimated on observed swap rates highlighted the central role played by the liquidity component in explaining swap spread dynamics over the past fifteen years. They also found, however, some puzzling empirical results.

Swap Spreads? Adam Kobor, Lishan Shi, Ivan Zelenko. Published: 24 June 2005. in Le système educatif Béninois: Analyse sectorielle pour une politique éducative plus équilibrée et plus efficace. Le système educatif Béninois: Analyse sectorielle pour une politique éducative plus équilibrée et plus efficace ; doi:10.

Other Authors: Shi, Lishan.

This title examines the evolution of the . swap spreads and estimates an error correction model for maturities of 2-, 5- and 10-year over the period 1994-2004 Full description. Other Authors: Shi, Lishan.

This title examines the evolution of the U.S. interest swap market. It reviews the theory and past empirical studies on U.S. swap spreads and estimates an error correction model for maturities of 2-, 5- and 10-year over the period 1994-2004. Financial theory depicts swaps as contracts indexed on LIBOR rates, rendered almost free of counterparty default risk by mark-to-market and collateralization. Swap spreads reflect the LIBOR credit quality (credit component) and a liquidity convenience premium present in Treasury rates (liquidity component). Multifactor models which were estimated on observed swap rates highlighted the central role played by the liquidity component in explaining swap spread dynamics over the past fifteen years. They also found, however, some puzzling empirical results. Statistical models, on the other hand, mainly based on market analysis, faced technical difficulties, arising from the presence of regime changes, the non-stationarity in swap spreads, and the co-existence of long-term and shorter-term determinants.Against this background, the authors applied the error correction methodology based on the concept of cointegration. They find that U.S. dollar swap spreads and the supply of U.S. Treasury bonds are cointegrated, suggesting that the Treasury supply is a key determinant on a long-term horizon. They then estimate an error correction model which integrates this long-term relationship with the influence of four shorter-term determinants: the AA spread, the repo rate, the difference between on-the-run and off-the-run yields, and the duration of mortgage backed securities. The error correction model fits observed swap spreads quite well over the sample period. The authors then illustrate how the same model can be used to carry out scenario analysis.