Identifying Volatility Signals from Time-Varying Simultaneous Stock Market Interaction
AbstractIn the academic literature, the economic interpretation of stock market volatility is inherently ambivalent, being considered an indicator of either information flow or uncertainty. We show in a stylized model economy that both views suggest volatility-dependent cross-market spillovers. If higher volatility in one market leads to higher (lower) reactions in another market, volatility reflects information (uncertainty). We introduce a simultaneous time-varying coefficient model, where structural ARCH-type variances serve two purposes: governing the time variation of spillovers and ensuring statistical identification. The model is applied to data of US and further stock markets. Indeed, we find strong nonlinear, volatility-dependent effects. --
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Bibliographic InfoPaper provided by Verein für Socialpolitik / German Economic Association in its series Annual Conference 2013 (Duesseldorf): Competition Policy and Regulation in a Global Economic Order with number 79903.
Date of creation: 2013
Date of revision:
Find related papers by JEL classification:
- G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
- C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
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