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Dissertation Committee:
Jan Hanousek (chair)
Randall K. Filer
Štěpán Jurajda
Jiří Trešl
 

Abstract:

This thesis studies financial markets and the information we can obtain from observing the actions of financial market participants.

In the first chapter, I study how the combination of different accounting ratios, which are considered to be the financial signals of future performance, can affect the analysts’ and managers’ earnings forecast releases. The findings show that analysts treat the firms differently depending on whether the firms have only strong financial indicators (high signal group), weak financial indicators (low signal group), and those with both positive and negative signals (mixed signal group). The study also provides the evidence that the managers may realize the heterogeneity in analysts’ treatment, and as the result the managers’ earnings forecasts will be affected both by the signal group type of the firm and the analysts’ bias characteristic for the appropriate signal group. At the same time, the findings show that the analysts sometimes fail to disregard the managers’ forecast biases and are misled by the managers. This provides evidence of inaccuracy on the part of analysts and potential gaming on information disclosure between analysts and managers’.

In the second chapter, I examine whether trading activity responds to the industry-related earnings announcement and whether this activity is informative. I find that the subsequent announcer’s abnormal trading volume is informative about their stock performance upon the first and own subsequent announcement and in the post announcement performance. While the first announcer’s earnings surprise is expected to be informative about that of the subsequent announcer, I also show that not only the first announcer’ earnings surprise in the current quarter but the history of both first and subsequent announcers can predict the latter's earnings surprise. I also check whether the informativeness of the subsequent announcer’s abnormal trading volume is not solely explained by the market agents’ ability to incorporate the predictability of their earnings surprises. The results suggests that although the subsequent announcer's trading activity is driven by updating of beliefs made upon the first announcement, the market fails to fully incorporate the earnings surprise predictability, which provides some evidence of market inefficiency.

In the third chapter (with Yuko Hashimoto), we study whether the EU member countries act as a single investor due to the stronger financial integration over recent years. Although we find evidence that the portfolio investments of the EU countries tend to move together, there is still some diversity among the Union members. In our analysis, we distinguish two types of countries: those who prefer to invest more evenly among counterparties (low concentration type) versus those who invest more heavily in some counterparties (high concentration type). Consistent with our hypothesis, we find that the level of investment concentration and investment share at the destination play a role in the way the countries will respond to the changes in the macrovariables. We also find evidence of the crisis period affecting both the co-movements of EU members’ investment shares at destination and the macrovariables driving international portfolio investments. In particular, variables of the health of the financial system become important determinants for portfolio investment during the crisis.

Full Text: “Essays on Financial Markets” by Iuliia Brushko

Economics Discovery Hub is proud to cooperate with Czechitas, a Czech non-profit organization which aims to bring more girls into the programming and data world. We organize R Programming course for them, where you will learn basics of programming in R and data manipulation.

If you are a woman and interested in learning about R programming, find out more information and register at Czechitas website.  

Tuesdays, 18:00-20:00 
Starting date: 25 October, 2016
Finishing date: 15 November, 2016

About the facilitator: Kuan-Heng Lin
Kuan-Heng Lin is a PhD student at CERGE-EI. 

Prof. Bo E. Honoré

Princeton University, USA

Authors: Bo E. Honoré and Luojia Hu

The seminar will be based on this paper http://www.princeton.edu/~honore/papers/PoorWomansBootstrap.pdf as well as a follow-up paper (which is in progress).

Here is a combined abstract:   

     The bootstrap is a convenient tool for calculating standard errors of the parameter estimates of complicated econometric models. Unfortunately, the fact that these models are complicated often makes the bootstrap extremely slow or even practically infeasible. This research proposes an alternative to the bootstrap that relies only on the estimation of one-dimensional parameters. We introduce the idea in the context of M- and GMM-estimators. A modification of the approach can be used to estimate the variance of two-step estimators.

We also propose an alternative and simpler method. We compare the two methods in terms of their statistical and practical performance, and we demonstrate their usefulness in Monte Carlo studies and empirical applications.