Abstract
The system intrinsic true label of the effect of an unexpected news on the time series of volatility estimates determines the class of news, which can either be a “No volatility shock” or “Volatility shock” causing event. The class of news, in turn, is used to train the supervised learning algorithms on historical incidents, which will then be used to predict the class of a new and unexpected news.
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© 2016 Springer Fachmedien Wiesbaden
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Kömm, H. (2016). Benchmarking. In: Forecasting High-Frequency Volatility Shocks. Springer Gabler, Wiesbaden. https://doi.org/10.1007/978-3-658-12596-7_7
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DOI: https://doi.org/10.1007/978-3-658-12596-7_7
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Publisher Name: Springer Gabler, Wiesbaden
Print ISBN: 978-3-658-12595-0
Online ISBN: 978-3-658-12596-7
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