Advanced Text Mining Methods for the Financial Markets and Forecasting of Intraday Volatility
Abstract:
The flow of information in financial markets is covered in two parts.
An high-order estimator of intraday volatility is introduced in order to boost risk forecasts.
Over the last decade, text mining of news and its application to finance were a vibrant topic of research as well as in the finance industry. This thesis develops a coherent approach to financial text mining that can be utilized for automated trading.
An high-order estimator of intraday volatility is introduced in order to boost risk forecasts.
Over the last decade, text mining of news and its application to finance were a vibrant topic of research as well as in the finance industry. This thesis develops a coherent approach to financial text mining that can be utilized for automated trading.
| Zugehörige Institution(en) am KIT | Fakultät für Wirtschaftswissenschaften – Institut für Wirtschaftstheorie und Statistik (ETS) |
| Publikationstyp | Hochschulschrift |
| Publikationsjahr | 2011 |
| Sprache | Englisch |
| Identifikator | urn:nbn:de:swb:90-253968 KITopen-ID: 1000025396 |
| Verlag | Karlsruher Institut für Technologie (KIT) |
| Art der Arbeit | Dissertation |
| Fakultät | Fakultät für Wirtschaftswissenschaften (WIWI) |
| Institut | Fakultät für Wirtschaftswissenschaften – Institut für Wirtschaftstheorie und Statistik (ETS) |
| Prüfungsdaten | 08.12.2011 |
| Schlagwörter | Text Mining News Financial Volatility |
| Referent/Betreuer | Rachev, S. T. |