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Conditional heteroskedasticity is an important feature of many macroeconomic and financial time series. Standard residual-based bootstrap procedures for dynamic regression models treat the regression error as i.i.d. These procedures are invalid in the presence of conditional heteroskedasticity....
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We examine local-stochastic volatility models and derive a simple condition such models need to obey so that the carry …-even levels of the local volatility model - itself in the admissible class …
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With the recent availability of high-frequency financial data the long range dependence of volatility regained … researchers' interest and has lead to the consideration of long memory models for realized volatility. The long range diagnosis of … volatility, however, is usually stated for long sample periods, while for small sample sizes, such as e.g. one year, the …
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Volatility has been one of the most active and successful areas of research in time series econometrics and economic … empirical insights to emerge from this burgeoning literature, with a distinct focus on forecasting applications. Volatility is … inherently latent, and Section 1 begins with a brief intuitive account of various key volatility concepts. Section 2 then …
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section compares stochastic volatility models with GARCH. …
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