Essays in Monetary Policy and Asset Pricing

This thesis uses machine learning techniques and text data to investigate the relationships that arise between the Fed and financial markets, and their consequences for asset prices.The first chapter, entitled Market Expectations and the Impact of Unconventional Monetary Policy: An Application to Twitter Data, is an answer to (Greenlaw et al., 2018), who show, by looking at a large set of monetary policy announcements made between November 2008 and December 2017 - FOMC meetings, release of minutes and speeches of the Fed Chair - that long term yields tended to increase following these events. By doing so, the authors challenge common wisdom according to which the central bank intervention in the aftermath of the financial crisis lowered long term rates (Gagnon, 2016). Using machine learning and twitter data, this chapter develops a novel measure of market expectations of monetary policy, and shows that the increase in yields was simply due to a marginal adjustment of market expectations following announcements being less dovish than expected.The second chapter, entitled Informational Feedback Loop, Monetary Policy Decisions and Asset Prices Dynamics, investigates the consequences of a Fed that uses (1) its own private signal and (2) fed funds futures to take its monetary policy decision. Fed funds futures aggre- gate private information received by financial markets participants - traders - but they also depend on traders' expectations about the Fed's behavior, which makes futures endogenous in the central bank decision. The theoretical model shows that the surprise generated by monetary policy announcements and the subsequent adjustment in short term U.S. treasury yields depend on the precision of the signals received by each agent. When the signal received by traders is more precise than the central bank's, the latter relies more on fed funds futures to take its decision, and the surprise and adjustment of short term yields are smaller. By contrast, long term yields adjust only because the announcement provides traders with new information about the state of the economy, by revealing the central bank's private signal. Finally, when the Fed is averse to financial markets volatility, it tends to put some weight on fed funds futures even if they are not informative about the state of the economy. The empirical part of the paper provides some evidence supporting these channels, by using a topic and tone approach (Hansen and McMahon, 2016) to extract the precision of the signals received by the central bank and traders from FOMC minutes and tweets respectively.

Essays in Information-Based Asset Pricing

Michael Hasler

I started my Ph.D. studies in the Fall 2008, a period ex-post perceived as being at the core of the Financial Crisis. At that time my ideas were vague and I struggled to find a good research topic. As surprising as it might appear, in one single week the discussions I had with my relatives provided me with enough ideas needed to write my thesis. Indeed, during that single week my relatives contacted me and complained about the fact that they had lost money invested in the financial market. They wanted me to advise them. I simply told them to invest their money in relatively safe bonds. My relatives did not realize how fruitful their behavior was for me. Indeed, after having advised them I wondered whether their willingness to gather information in bad times was optimal or pure irrationality. This issue is addressed in the first chapter of my thesis. The last two chapters investigate the impact of the willingness to gather more information in bad times than in good times on the dynamics of asset prices. My thesis answers two very important questions: When should investors acquire information given that information-processing is costly and what is the impact of the optimal information acquisition strategy on asset price dynamics? Consequently, the main topic of my thesis is the transmission of acquired information in financial markets. In the first chapter I consider a dynamic portfolio choice and costly information acquisition problem. Consistent with my relatives behavior, I show that it is optimal to gather more information in bad times than in good times. As the state of the economy worsens, investors optimally re-balance their portfolio towards safer investment and spend more and more money to gather more and more accurate information regarding future market moves. This result derived in a purely rational setup helps to understand the empirical observation that people tend to pay fluctuating attention to news, focusing more in downturns than in upturns. To the best of my knowledge, this paper is the first to consider costly information acquisition in a dynamic setting. The main contribution is to provide insights on how investors should optimally allocate their wealth to the financial market on the one hand and to information market on the other hand given current market conditions. In the second chapter (with Daniel Andrei) we model the optimal information acquisition strategy obtained in the first chapter in a general equilibrium framework and we show that this strategy (fluctuating attention paid to news) has very interesting implications on the dynamics of asset prices. Our main contribution is to highlight a J-shaped relationship between attention and volatility. By constructing an empirical measure of attention to news, we show that the theoretical prediction of our model holds in the data. Moreover, we are the first to provide a theoretical foundation for the fact that the slope of the term structure of equity premia is pro-cyclical. In the third chapter I investigate the impact of fluctuating attention to news in a multi-asset general equilibrium framework. My main contribution is to show that fluctuating attention to news generates return and volatility spillover effects among financial markets. As a bad shock hits one market, investors raise their attention to that particular market. This implies a simultaneous increase in each market volatility and in each cross-market correlation, a phenomenon called financial contagion. Moreover, I document that the interconnection between attention and uncertainty generates persistence in cross-market correlations. This very interesting result proves that persistence can be generated through Bayesian learning. Finally, I am the first to provide a theoretical foundation for the observed shape of the term structure of correlation. Consistent with empirical findings, I show that fluctuating attention implies an upward sloping term structure of correlation where the shorthand is wider than the longhand.

EPFL2013

Corporate Science and Voluntary Disclosure

Markus Simeth

The dissertation investigates the phenomenon of firms that make voluntary contributions to the stock of scientific knowledge. Such a firm behaviour appears counterintuitive from a traditional viewpoint, since no direct financial returns can be expected while the disclosure of research outcomes may lead to knowledge spillovers to competing firms. This raises the questions why firms engage in those boundary-spanning activities, how scientific disclosure strategies are implemented, and to what extent scientific disclosure strategies affect the firm performance. The dissertation provides empirical evidence on these questions using representative firm-level data and econometric analysis techniques. The first chapter of the dissertation reviews the relevant literature, underlines the relevance of doing research on this topic by providing descriptive evidence on the amounts of scientific contributions by firms, and includes some novel insights from interviews which I conducted at several large R&D performing firms. I discuss the potential benefits, costs and organizational challenges of scientific disclosure strategies and position scientific publications as an expression of openness in the light of alternative openness definitions prevalent in innovation research. The second chapter focuses on the question why firms publish in scientific journals using a cost-benefit framework. In particular, I analyse whether scientific contributions of firms are used as an instrument to get access to academic knowledge networks. Moreover, I explore environmental conditions by considering the effectiveness of appropriation instruments and the spillover levels in a sector that may impact the firms’ decision-making process. The analysis relies on data from the French Innovation survey and provides evidence for the predictions that firms show reciprocal behaviour in exchange of obtaining valuable academic knowledge. However, the propensity of firms to publish is rather sensitive to the spillover threats. The third chapter examines how are firms able to publish by testing the requirements and origins of scientific contributions by firms. I explicitly consider the heterogeneity of scientific outputs and provide a complementary view on the requirements for the creation of inventive outcomes. The requirements considered can be classified according to the research orientation and the demographic composition of the R&D labs. The analysis revealed that scientific disclosure strategies require specific resource allocations and capabilities, which are in part not necessary for the generation of inventive outcomes. The findings support the view that disclosure strategies can be costly and are not only a by-product of the “usual” R&D activities. The fourth chapter addresses the performance effects of scientific activities of firms. More specifically, I examine whether scientific publications stocks provide valuable information to the financial markets, potentially leading to different valuations. I consider the heterogeneity of scientific and inventive outcomes and found evidence for a positive impact of scientific contributions on the firm’s Tobin’s Q beyond the effects of R&D stocks, patent stocks and patent quality.

EPFL2013

Essays in Information-Based Asset Pricing

Michael Hasler

EPFL2013

Corporate Science and Voluntary Disclosure

Markus Simeth

EPFL2013