IMF Working Papers

Linkages Among Asset Markets in the United States: Tests in a Bivariate GARCH Framework

By Parha Deb, Salim M. Darbar

November 1, 1999

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Parha Deb, and Salim M. Darbar Linkages Among Asset Markets in the United States: Tests in a Bivariate GARCH Framework, (USA: International Monetary Fund, 1999) accessed November 21, 2024
Disclaimer: This Working Paper should not be reported as representing the views of the IMF.The views expressed in this Working Paper are those of the author(s) and do not necessarily represent those of the IMF or IMF policy. Working Papers describe research in progress by the author(s) and are published to elicit comments and to further debate

Summary

This paper develops a bivariate GARCH model that allows for time-varying conditional correlations and simultaneous testing of two Granger-causal linkages: the impact of return volatility in a market on intermarket correlation and the impact of return volatility in one market on the volatility of another. Using daily data from stock, bond, currency, and commodity markets in the United States, the paper finds evidence of each form of linkage. Furthermore, the conditional correlations change over time and exhibit considerable persistence. The estimated time-varying conditional correlations provide insight into the nature of the stock market crash of 1987.

Subject: Currency markets, Financial markets, Financial sector policy and analysis, Revenue administration, Securities markets, Small taxpayer office, Spillovers, Stock markets

Keywords: Asset volatility, Conditional correlation, Covariance matrix, Cross-asset correlation, Currency markets, GARCH model, Global, Granger causality, Logistic Exponential GARCH, Market mechanism, Securities markets, Small taxpayer office, Spillover coefficient, Spillovers, Stock markets, Volatility spillover, WP

Publication Details

  • Pages:

    25

  • Volume:

    ---

  • DOI:

    ---

  • Issue:

    ---

  • Series:

    Working Paper No. 1999/158

  • Stock No:

    WPIEA1581999

  • ISBN:

    9781451857566

  • ISSN:

    1018-5941

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