Time varying correlations are often estimated with multivariate generalized autoregressive conditional heteroskedasticity (GARCH) models that are linear in squares and cross products of the data. A new class of multivariate models called dynamic conditional correlation models is proposed. These have the flexibility of univariate GARCH models coupled with parsimonious parametric models for the correlations. They are not linear but can often be estimated very simply with univariate or two-step methods based on the likelihood function. It is shown that they perform well in a variety of situations and provide sensible empirical results.

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Dynamic Conditional Correlation: A Simple Class of Multivariate Generalized Autoregressive Conditional Heteroskedasticity Models

ARCH modeling in finance: A review of the theory and empirical evidence

A long memory property of stock market returns and a new model

Heteroskedasticity biases tests for contagion based on correlation coefficients. When contagion is defined as a significant increase in market comovement after a shock to one country, previous work suggests contagion occurred during recent crises. This paper shows that correlation coefficients are conditional on market volatility. Under certain assumptions, it is possible to adjust for this bias. Using this adjustment, there was virtually no increase in unconditional correlation coefficients (i.e., no contagion) during the 1997 Asian crisis, 1994 Mexican devaluation, and 1987 U.S. market crash. There is a high level of market comovement in all periods, however, which we call interdependence.

/pdf/no-contagion-only-interdependence-measuring-stock-market-2e4xwzrnsw.pdf

No Contagion, Only Interdependence: Measuring Stock Market Comovements

This paper defines the news impact curve which measures how new information is incorporated into volatility estimates. Various new and existing ARCH models including a partially nonparametric one are compared and estimated with daily Japanese stock return data. New diagnostic tests are presented which emphasize the asymmetry of the volatility response to news. Our results suggest that the model by Glosten, Jagannathan, and Runkle is the best parametric model. The EGARCH also can capture most of the asymmetry; however, there is evidence that the variability of the conditional variance implied by the EGARCH is too high.

/pdf/measuring-and-testing-the-impact-of-news-on-volatility-533bchskmf.pdf

Measuring and Testing the Impact of News on Volatility

The short-run interdependence of prices and price volatility across three major international stock markets is studied. Daily opening and closing prices of major stock indexes for the Tokyo, London, and New York stock markets are examined. The analysis utilizes the autoregressive conditionally heteroskedastic (ARCH family of statistical models to explore these pricing relationships. Evidence of price volatility spillovers from New York to Tokyo, London to Tokyo, and New, York to London is observed but no price volatility spillover effects in other directions are found for the pre-October 1987 period.

Correlations in Price Changes and Volatility Across International Stock Markets

The short-run interdependence of prices and price volatility across three major international stock markets is studied Daily opening and closing prices of major stock indexes for the Tokyo, London, and New York stock markets are examined The analysis utilizes the autoregressive conditionally heteroskedastic (ARCH) family of statistical models to explore these pricing relationships Evidence of price volatility spillovers from New York to Tokyo, London to Tokyo, and New York to London is observed, but no price volatility spillover effects in other directions are found for the pre-October 1987 period Article published by Oxford University Press on behalf of the Society for Financial Studies in its journal, The Review of Financial Studies

https://www.jstor.org/stable/pdfplus/2962024.pdf

Correlations in Price Changes and Volatility across International Stock Markets

Restoration of TET2 Function Blocks Aberrant Self-Renewal and Leukemia Progression

Asset pricing with a factor-arch covariance structure

https://deepblue.lib.umich.edu/bitstream/handle/2027.42/30125/0000501.pdf?sequence=1

Victor Ng

Papers

Correlations in Price Changes and Volatility Across International Stock Markets

Correlations in Price Changes and Volatility across International Stock Markets

Restoration of TET2 Function Blocks Aberrant Self-Renewal and Leukemia Progression

Asset pricing with a factor-arch covariance structure

A multi-dynamic-factor model for stock returns