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

_IMF Working Papers, November 1, 1999_

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## Bibliographic details
- Authors: Parha Deb, Salim M. Darbar
- Published: November 1, 1999
- Series: IMF Working Papers
- DOI: https://doi.org/10.5089/9781451857566.001

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### Model and methodology
- Develops a bivariate GARCH model that allows for time-varying conditional correlations.
- Enables simultaneous testing of two Granger-causal linkages:
  - The impact of return volatility in a market on intermarket correlation.
  - The impact of return volatility in one market on the volatility of another.
- Uses daily data from stock, bond, currency, and commodity markets in the United States.
- Employs technical terminology and model features as in the source: conditional correlation, covariance matrix, cross-asset correlation, Granger causality, Logistic Exponential GARCH, spillover coefficient, volatility spillover.

### Key findings
- Finds evidence of both forms of linkage (volatility → intermarket correlation; volatility in one market → volatility in another).
- Conditional correlations are time-varying and exhibit considerable persistence.
- The estimated time-varying conditional correlations provide insight into the nature of the stock market crash of 1987.

### Implications and interpretation
- Demonstrates that volatility in one asset market can influence both cross-market correlations and volatility dynamics in other markets.
- Time-varying conditional correlations are important for understanding episodes of market stress (example cited: stock market crash of 1987).
- Results are relevant to analyses of spillovers across Currency markets, Securities markets, and Stock markets.

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## Content in this bundle

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_Source: https://www.imf.org/en/publications/wp/issues/2016/12/30/linkages-among-asset-markets-in-the-united-states-tests-in-a-bivariate-garch-framework-3337_