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Forecasting High-Frequency Volatility Shocks

An Analytical Real-Time Monitoring System

(Autor)

Buch | Softcover
XXIX, 171 Seiten
2016 | 1st ed. 2016
Springer Fachmedien Wiesbaden GmbH (Verlag)
978-3-658-12595-0 (ISBN)

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Forecasting High-Frequency Volatility Shocks - Holger Kömm
CHF 74,85 inkl. MwSt
This thesis presents a new strategy that unites qualitative and quantitative mass data in form of text news and tick-by-tick asset prices to forecast the risk of upcoming volatility shocks. Holger Kömm embeds the proposed strategy in a monitoring system, using first, a sequence of competing estimators to compute the unobservable volatility; second, a new two-state Markov switching mixture model for autoregressive and zero-inflated time-series to identify structural breaks in a latent data generation process and third, a selection of competing pattern recognition algorithms to classify the potential information embedded in unexpected, but public observable text data in shock and nonshock information. The monitor is trained, tested, and evaluated on a two year survey on the prime standard assets listed in the indices DAX, MDAX, SDAX and TecDAX.

Dr. Holger Kömm is research associate at the chair of statistics and quantitative methods in the economics & business department of the Catholic University Eichstätt-Ingolstadt. 

Integrated Volatility.- Zero-inflated Data Generation Processes.- Algorithmic Text Forecasting.

Erscheinungsdatum
Zusatzinfo XXIX, 171 p. 19 illus.
Verlagsort Wiesbaden
Sprache englisch
Maße 148 x 210 mm
Gewicht 272 g
Themenwelt Wirtschaft Betriebswirtschaft / Management Unternehmensführung / Management
Wirtschaft Volkswirtschaftslehre Finanzwissenschaft
Wirtschaft Volkswirtschaftslehre Makroökonomie
Schlagworte Algorithmic Text Forecasting • Economics and finance • Economic Theory/Quantitative Economics/Mathematica • Integrated Volatility • Macroeconomics/Monetary Economics//Financial Econo • Monitoring • R & D/Technology Policy • R & D/Technology Policy • Time Series and Textual Data • Zero-inflated Data Generation Processes
ISBN-10 3-658-12595-0 / 3658125950
ISBN-13 978-3-658-12595-0 / 9783658125950
Zustand Neuware
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