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Signed spillover effects building on historical decompositions

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Abstract

The spillover effects of interconnectedness between financial assets is decomposed into both sources of shocks and whether they amplify or dampen volatility conditions in the target market. We use historical decompositions to rearrange information from a VAR which includes sources, direction and signs of effects building on the unsigned forecast error variance decomposition approach of Diebold and Yilmaz (2009). A spillover index based on historical decompositions has simple asymptotic properties, permitting the derivation of analytical standard errors of the index and its components. We apply the methodology to a panel of CDS spreads of sovereigns and financial institutions for the period of 2003-2013 and identify how these entities contribute to global systemic risk.

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  • Dungey, Mardi & Harvey, John & Siklos, Pierre & Volkov, Vladimir, 2017. "Signed spillover effects building on historical decompositions," Working Papers 2017-11, University of Tasmania, Tasmanian School of Business and Economics.
  • Handle: RePEc:tas:wpaper:23671
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    1. Mert Demirer & Francis X. Diebold & Laura Liu & Kamil Yilmaz, 2018. "Estimating global bank network connectedness," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(1), pages 1-15, January.
    2. Claudio Borio & Anna Zabai, 2018. "Unconventional monetary policies: a re-appraisal," Chapters, in: Peter Conti-Brown & Rosa M. Lastra (ed.), Research Handbook on Central Banking, chapter 20, pages 398-444, Edward Elgar Publishing.
    3. Graciela L. Kaminsky & Carmen Reinhart, 2003. "The Center and the Periphery: The Globalization of Financial Turmoil," NBER Working Papers 9479, National Bureau of Economic Research, Inc.
    4. Pesaran, M. Hashem & Yang, Cynthia Fan, 2020. "Econometric analysis of production networks with dominant units," Journal of Econometrics, Elsevier, vol. 219(2), pages 507-541.
    5. Paul Glasserman & Peyton Young, 2015. "Contagion in Financial Networks," Economics Series Working Papers 764, University of Oxford, Department of Economics.
    6. Daron Acemoglu & Asuman Ozdaglar & Alireza Tahbaz-Salehi, 2015. "Systemic Risk and Stability in Financial Networks," American Economic Review, American Economic Association, vol. 105(2), pages 564-608, February.
    7. Bostanci, Gorkem & Yilmaz, Kamil, 2020. "How connected is the global sovereign credit risk network?," Journal of Banking & Finance, Elsevier, vol. 113(C).
    8. Leonardo Gambacorta & Jing Yang & Kostas Tsatsaronis, 2014. "Financial structure and growth," BIS Quarterly Review, Bank for International Settlements, March.
    9. Diebold, Francis X. & Yilmaz, Kamil, 2015. "Financial and Macroeconomic Connectedness: A Network Approach to Measurement and Monitoring," OUP Catalogue, Oxford University Press, number 9780199338306, Decembrie.
    10. Lutkepohl, Helmut, 1990. "Asymptotic Distributions of Impulse Response Functions and Forecast Error Variance Decompositions of Vector Autoregressive Models," The Review of Economics and Statistics, MIT Press, vol. 72(1), pages 116-125, February.
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    Cited by:

    1. Dungey, Mardi & Islam, Raisul & Volkov, Vladimir, 2020. "Crisis transmission: Visualizing vulnerability," Pacific-Basin Finance Journal, Elsevier, vol. 59(C).
    2. Christian Gross & Pierre L. Siklos, 2020. "Analyzing credit risk transmission to the nonfinancial sector in Europe: A network approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(1), pages 61-81, January.
    3. Islam, Raisul & Volkov, Vladimir, 2020. "Contagion or interdependence? Comparing signed and unsigned spillovers," Working Papers 2020-05, University of Tasmania, Tasmanian School of Business and Economics.
    4. Mardi Dungey & Renee Fry‐Mckibbin & Vladimir Volkov, 2020. "Transmission of a Resource Boom: The Case of Australia," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 82(3), pages 503-525, June.
    5. Islam, Raisul & Volkov, Vladimir, 2020. "Calm before the storm: an early warning approach before and during the COVID-19 crisis," Working Papers 2020-09, University of Tasmania, Tasmanian School of Business and Economics.

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    More about this item

    Keywords

    Historical decomposition; DY Spillover; Granger Causality; Networks;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)

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