We introduce a model for the analysis of intra-day volatility based on unobserved components. The stochastic seasonal component is essential to model time-varing intra-day effects. The model is estimated with high frequency data for Deutsche mark-US dollar for 1993 and 1996. The model performs well in terms of coherence with the theoretical aggregation properties of GARCH models, it is effective in terms of both forecasting ability and describing reactions to macroeconomic news.
Beltratti, A., Morana, C. (2001). Deterministic and stochastic methods for estimation of intra-day seasonal components with high frequency data. ECONOMIC NOTES, 30(2), 205-234 [10.1111/j.0391-5026.2001.00054.x].
Deterministic and stochastic methods for estimation of intra-day seasonal components with high frequency data
Morana, C
2001
Abstract
We introduce a model for the analysis of intra-day volatility based on unobserved components. The stochastic seasonal component is essential to model time-varing intra-day effects. The model is estimated with high frequency data for Deutsche mark-US dollar for 1993 and 1996. The model performs well in terms of coherence with the theoretical aggregation properties of GARCH models, it is effective in terms of both forecasting ability and describing reactions to macroeconomic news.
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