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Forecasting High-Frequency Volatilit...
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SpringerLink (Online service)
Forecasting High-Frequency Volatility Shocks = An Analytical Real-Time Monitoring System /
Record Type:
Language materials, printed : Monograph/item
Title/Author:
Forecasting High-Frequency Volatility Shocks/ by Holger Kömm.
Reminder of title:
An Analytical Real-Time Monitoring System /
Author:
Kömm, Holger.
Description:
XXIX, 171 p. 19 illus.online resource. :
Contained By:
Springer Nature eBook
Subject:
Macroeconomics. -
Online resource:
https://doi.org/10.1007/978-3-658-12596-7
ISBN:
9783658125967
Forecasting High-Frequency Volatility Shocks = An Analytical Real-Time Monitoring System /
Kömm, Holger.
Forecasting High-Frequency Volatility Shocks
An Analytical Real-Time Monitoring System /[electronic resource] :by Holger Kömm. - 1st ed. 2016. - XXIX, 171 p. 19 illus.online resource.
Integrated Volatility -- Zero-inflated Data Generation Processes -- Algorithmic Text Forecasting.
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. Contents • Integrated Volatility • Zero-inflated Data Generation Processes • Algorithmic Text Forecasting Target Groups • Teachers and students of economic science with a focus on financial econometrics< • Executives and consultants in the field of business informatics and advanced statistics About the Author 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. .
ISBN: 9783658125967
Standard No.: 10.1007/978-3-658-12596-7doiSubjects--Topical Terms:
554837
Macroeconomics.
LC Class. No.: HB172.5
Dewey Class. No.: 339
Forecasting High-Frequency Volatility Shocks = An Analytical Real-Time Monitoring System /
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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. Contents • Integrated Volatility • Zero-inflated Data Generation Processes • Algorithmic Text Forecasting Target Groups • Teachers and students of economic science with a focus on financial econometrics< • Executives and consultants in the field of business informatics and advanced statistics About the Author 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. .
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