On the asymmetric impact of macro–variables on volatility |
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| Institution: | 1. School of Finance, Yunnan University of Finance and Economics, China;2. School of Economics & Management, Southwest Jiaotong University, China;1. DiSIA, University of Firenze, Italy;2. Italian Court of Audits (Corte dei conti) and NYU in Florence, Italy;1. School of Business Administration, Hunan University, 410082, Changsha, China;2. Nanjing Audit University, 211815, Nanjing, China;3. School of Economics, Hunan Agricultural University, 410128, Changsha, China |
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| Abstract: | We extend the GARCH–MIDAS model to take into account possible different impacts from positive and negative macroeconomic variations on financial market volatility: a Monte Carlo simulation which shows good properties of the estimator with realistic sample sizes. The empirical application is performed on the daily S&P500 volatility dynamics with the U.S. monthly industrial production and national activity index as additional (signed) determinants. We estimate the Relative Marginal Effect of macro variable movements on volatility at different lags. In the out-of-sample analysis, our proposed GARCH–MIDAS model not only statistically outperforms the competing specifications (GARCH, GJR-GARCH and GARCH–MIDAS models), but shows significant utility gains for a mean-variance investor under different risk aversion parameters. Attention to robustness is given by choosing different samples and estimating the model in an international context (six different stock markets). |
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| Keywords: | Volatility Asymmetry GARCH–MIDAS Forecasting |
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