News Arrivals, Jumps and Variance in Stock Markets
Research output: Book/Report › Doctoral thesis › Monograph
|Publisher||Tampere University of Technology|
|Number of pages||116|
|Publication status||Published - 20 Nov 2017|
|Publication type||G4 Doctoral dissertation (monograph)|
|Name||Tampere University of Technology. Publication|
The ﬁrst part of this thesis concentrates on the impact of news on jumps. First, a non-parametric statistical framework is introduced to examine the association between news arrivals and jumps in stock prices. To uncover the market reaction to news alerts, I focus on the time distances (waiting time) between news arrivals and the nearest detected jumps. For a given news item, both backward and forward waiting times are calculated with the jumps detected before and after the news arrival. In particular, backward waiting times may reﬂect possible information leakage. To examine whether observed jumps are associated with real news, a set of timestamps of general reference news is simulated considering intraday seasonality. Applying non-parametric tests, we are able to extract the statistical proﬁles of the empirical waiting times and their simulated references. As a result, the association between news and jumps is quantitatively demonstrated.
Taking advantage of the developed statistical framework, a thorough empirical analysis is implemented using Nordic and U.S. data to show the impacts of Nordic ﬁrm-speciﬁc and U.S. macroeconomic announcements on stock prices in both Nordic and U.S. markets. Speciﬁcally, the impact of scheduled and non-scheduled ﬁrm-speciﬁc announcements on Nordic stock prices is tested. I also investigate the sizes of jumps related to Nordic scheduled and non-scheduled ﬁrm-speciﬁc announcements following the same non-parametric methodology. In order to feature the importance of certain types of ﬁrm-level news, such as acquisitions, ﬁve important ﬁrm-speciﬁc announcements are selected to test their impact on Nordic stock prices in term of jumps. Regarding U.S. economic news, I provide empirical results for the impact of U.S. macroeconomic announcements on the U.S. stock index. In addition, U.S. macroeconomic announcements are grouped by announcing time. Their impacts on Nordic stock prices are studied to examine the importance of announcing clock time and the global inﬂuence of U.S. economic releases.
The second part in this research relates to the impact of macroeconomic news on equity variance modeling and the related option valuation performance with GARCH models. Impact variables of macroeconomic news are constructed using both the arrival timings of U.S. macroeconomic announcements and realized variance, and are incorporated into classical GARCH models. The impact variables of macroeconomic news slightly improve the joint likelihood of returns and VIX for all models compared with standard GARCH models. Regarding option valuation, an affine GARCH model with news event data consistently outperforms a pure affine GARCH model. However, there is no such consistent result for NGARCH and GJR models, implying that the explicit use of macroeconomic news events data does not improve the performance of variance modeling and option pricing with non-affine GARCH models.