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on Econometric Time Series |
| By: | Robert F. Engle; Jose Gonzalo Rangel |
| Abstract: | 25 years of volatility research has left the macroeconomic environment playing a minor role. This paper proposes modeling equity volatilities as a combination of macroeconomic effects and time series dynamics. High frequency return volatility is specified to be the product of a slow moving deterministic component, represented by an exponential spline, and a unit GARCH. This deterministic component is the unconditional volatility, which is then estimated for nearly 50 countries over various sample periods of daily data. Unconditional volatility is then modeled as an unbalanced panel with a variety of dependence structures. It is found to vary over time and across countries with high unconditional volatility resulting from high volatility in the macroeconomic factors GDP, inflation and short term interest rate, and with high inflation and slow growth of output. Volatility is higher for emerging markets and for markets with small numbers of listed companies and market capitalization, but also for large economies. The model allows long horizon forecasts of volatility to depend on macroeconomic developments, and delivers estimates of the volatility to be anticipated in a newly opened market. |
| Keywords: | . Arch, garch, global volatility, spline and volatility. |
| JEL: | C14 C19 |
| Date: | 2005–12 |
| URL: | http://d.repec.org/n?u=RePEc:cnb:wpaper:2005/13&r=ets |
| By: | Luc, BAUWENS (UNIVERSITE CATHOLIQUE DE LOUVAIN, Department of Economics); Genaro, SUCARRAT |
| Abstract: | The general-to-specific (GETS) approach to modelling is widely employed in the modelling of economic series, but less so in financial volatility modelling due to computational complexity when many explanatory variables are involved. This study proposes a simple way of avoiding this problem and undertakes an out-of-sample forecast evaluation of the methodology applied to the modelling of weekly exchange rate volatility. Our findings suggest that GETS specifications are especially valuable in conditional forecasting, since the specification that employs actual values on the uncertain information performs particularly well. |
| Keywords: | Exchange Rate Volatility, General to Specific, Forecasting |
| JEL: | C53 F31 |
| Date: | 2006–02–15 |
| URL: | http://d.repec.org/n?u=RePEc:ctl:louvec:2006013&r=ets |
| By: | Gael M. Martin; Andrew Reidy; Jill Wright |
| Abstract: | This paper presents a comprehensive empirical evaluation of option-implied and returns-based forecasts of volatility, in which new developments related to the impact on measured volatility of market microstructure noise and random jumps are explicitly taken into account. The option-based component of the analysis also accommodates the concept of model-free implied volatility, such that the forecasting performance of the options market is separated from the issue of misspecification of the option pricing model. The forecasting assessment is conducted using an extensive set of observations on equity and option trades for News Corporation for the 1992 to 2001 period, yielding certain clear results. According to several different criteria, the model-free implied volatility is the best performing forecast, overall, of future volatility, with this result being robust to the way in which alternative measures of future volatility accommodate microstructure noise and jumps. Of the volatility measures considered, the one which is, in turn, best forecast by the option-implied volatility is that measure which adjusts for microstructure noise, but which retains some information about random jumps. |
| Keywords: | Volatility Forecasts; Quadratic Variation; Intraday Volatility Measures; Model-free Implied Volatility. |
| JEL: | C10 C53 G12 |
| Date: | 2006 |
| URL: | http://d.repec.org/n?u=RePEc:msh:ebswps:2006-10&r=ets |