Determinants of asymmetric return comovements of gold and other financial assets |
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Institution: | 1. Centre for Research in Finance, School of Management, Cranfield University, England MK43 0AL, United Kingdom;2. University of Derby, England DE1 3LD, United Kingdom;1. Riskcenter- IREA and Department of Econometrics, University of Barcelona, Av. Diagonal, 690, 08034 Barcelona, Spain;2. Department of Econometrics, University of Barcelona, Barcelona, Spain;3. Faculty of Economics and Business Studies, Open University of Catalonia, Spain;1. School of Business, Providence College, 1 Cunningham Square, Providence, RI 02918, United States;2. Department of Finance, Real Estate and Business Law, University of Southern Mississippi, 118 College Drive, Hattiesburg, MS 39406, United States;3. Finance Department, The University of Tampa, 401 W. Kennedy Blvd., Tampa, FL 33606, United States |
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Abstract: | Using conditional time-varying copula models, we characterize the dependence structure of return comovements of gold and other financial assets (stocks, bonds, real estate and oil) during economic expansion and contraction regimes. We also investigate which key macroeconomic and non-macroeconomic variables significantly impact the asset return comovements using a two stage Markov Switching Stochastic Volatility (MSSV) framework. Our results show that the non-macro variables have significant influence on the return comovements. We find that gold is an inappropriate hedge against interest rate changes for real-estate and oil-based portfolios, while for bond portfolios, gold offers a good hedge against inflation uncertainty. We also provide evidence that the “flight to safety” phenomenon is due to the implied volatility of the stock market, rather than the observed stock market uncertainty. Finally, we forecast the asset return comovements and examine their economic significance. We show that a dynamic MSSV model which includes the macroeconomic and non-macroeconomic variables yields superior forecast of future asset return comovements when compared with a multivariate conditional covariance model. |
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