Using an early warning system (EWS) methodology, this thesis analyses the predictability of stock market crises from the perspective of behavioural fnance. Specifcally, in our EWS based on the multinomial logit model, we consider in- vestor sentiment as one of the potential crisis indicators. Identifcation of the relevant crisis indicators is based on Bayesian model averaging. The empir- ical results reveal that price-earnings ratio, short-term interest rate, current account, credit growth, as well as investor sentiment proxies are the most rele- vant indicators for anticipating stock market crises within a one-year horizon. Our thesis hence provides evidence that investor sentiment proxies should be a part of the routinely considered variables in the EWS literature. In general, the predictive power of our EWS model as evaluated by both in-sample and out-of-sample performance is promising. JEL Classifcation G01, G02, G17, G41 Keywords Stock market crises, Early warning system, In- vestor sentiment, Crisis prediction, Bayesian model averaging Title Predicting stock market crises using investor sentiment indicators

Thesis advisor: Rui Albuquerque / Thesis advisor: Thomas J. Chemmanur / In my first essay, I develop a model of investor behavior around prescheduled macroeconomic announcements to analyze the optimal allocation of investor attention between systematic and idiosyncratic risk factors when a macroeconomic announcement is anticipated. Skilled investors, when producing information under a limited attention capacity, optimally allocate more of their attention to analyzing the idiosyncratic risk factor when they anticipate more precise public information about the systematic risk factor from the macroeconomic announcement. Consequently, my model predicts that, the more informative (precise) the macroeconomic announcement is expected to be about the underlying risk factors, ceteris paribus, the more uncertainty pre-announcement, the more resolution of uncertainty post-announcement, and the higher the trading volume around the announcement on the market index. My empirical analysis of trading by investors around both FOMC and CPI announcements support my model's predictions. In particular, my empirical findings are consistent with model predictions about the effect of the anticipated macroeconomic announcement precision on investor attention allocation, the effect of investor attention on the levels of pre-announcement and post-announcement trading volumes, and the effect of investor attention on the ratio of post-announcement trading volume over the pre-announcement trading volume. In my second essay, we analyze, theoretically and empirically, how investor attention affects the stock market reaction to innovation announcements. In a dynamic model with limited investor attention, we show that the immediate reaction to innovation announcements increases, while the post-announcement stock return drift decreases, in investor attention. We empirically confirm our model predictions using a matched sample of pharmaceutical industry patent grant and subsequent FDA drug approval announcements and also a general USPTO patent sample. We show that post-announcement drift has predictive power for firm growth, profitability, and productivity, drawing implications for enhancing measures of patents' economic value and for trading strategy. In my third essay, we analyze, theoretically and empirically, the implications of a fraction of investors in the equity market paying only delayed attention to SEO announcements. We first show theoretically that, in the above setting, the announcement effect of an SEO will be positively related to the fraction of investors paying attention to the announcement and that there will be a post-announcement stock-return drift that is negatively related to investor attention. In the second part of the paper, we test the above predictions using the media coverage of firms announcing SEOs as a proxy for investor attention, and find evidence consistent with the above predictions. In the third part of the paper, we develop and test various hypotheses relating investor attention paid to the issuing firm (between the announcement and the equity issue) to various SEO characteristics. We empirically show that SEO underpricing, institutional investor participation in SEOs, and the post-SEO equity market valuation of firms are all positively related to investor attention. The results of our identification tests show that the above results are causal. / Thesis (PhD) — Boston College, 2020. / Submitted to: Boston College. Carroll School of Management. / Discipline: Finance.

A new paradigm in investing has been created where people have easier access than ever to invest in the stock market from the convenience of their phones. Through zero-commission trading apps, like Robinhood, less starting capital is required. This research is used to investigate the relationship between the frequency of social media mentions on Twitter and a particular stock’s volatility. This will be done using the qualitative data analyzing tool AtlasTi to calculate the frequency in which a particular stock ticker is mentioned on Twitter during trading hours. The volatility of the stock will be calculated using data from Yahoo! Finance. Using a panel data analysis, our evaluation reveals that there is a statistically significant relationship between the number of Tweets both one and two days before and the volatility of the stock based on percent change. Additionally, there is a statistically significant relationship between the number of Tweets the day before and the volatility of the stock based on volume traded. It is intended that our research will aid future investors when making decisions on how to invest in assets heavily mentioned on social media.

Includes abstract. Includes bibliographical references.

The objective of this dissertation is to study the dynamics of size and value risk premia in an equilibrium model with belief dependent preferences and to analyze the impact of investor attention on asset pricing. There is ample evidence that size and value risk premia are non-constant and vary over the business cycle. Empirical patterns, however, are unknown and traditional equilibrium models cannot fit the observed dynamic patterns. The representative agent model with belief dependent preferences is known to fit both unconditional moments such as the equity premium as well as times-series features of volatilities and market prices of risk. The basic model is extended to capture the dynamics of size and value risk premia. The representative agent in this model is a rational Bayesian decision maker who updates her beliefs continuously when new information arrives. However, information processing costs are non-zero and opportunity costs of non-continuous updating of beliefs are higher during times of crisis. In the second part of this dissertation, the representative agent model with beliefs dependent preferences is extended to incorporate the notion of investor attention. The attention version of the model is shown to increase the dynamic fit of equilibrium asset pricing quantities by dampening the volatility of bond yields, market prices of risk, and stock volatility. As such the inattention version of the model with belief dependent preferences is shown to improve the intertemporal fit. Chapter 1 provides a overview of existing studies about the dynamics of size and value risk premia and investor attention. Chapter 2 investigates the dynamic features for size and value risk premia. An asset pricing model with regime dependent risk aversion and incomplete information about economic regimes is introduced to derive closed-form formulas for market prices of risk, asset prices, their volatilities, and risk premia of value and size style indices. Both size and value risk premia vary across normal, recession and boom periods. The premia amplify in recession times but tend to reverse or disappear during boom times. Such findings match the historical performances of small-minus-big (SMB) and high-minus-low (HML) portfolios. Chapter 3 integrates investor attention into regime-switching learning model with regime-dependent risk aversion. The model provides a good fit to the time series of stock volatility, bond volatility and bond yields. Investor attention at the aggregate level is captured by a new representative agent measure which combines the continuously updated beliefs about regimes of a rational Bayesian decision maker with those of a decision maker using steady state regime probabilities. The new representative agent measure can capture the scenario where investor updates her beliefs about economic regimes according to time-varying attention to the available market information. Equilibrium asset pricing quantities are obtained in closed form in the extended model with investor attention. Unconditional asset pricing model moments match their empirical counterparts including the equity premium, the stock volatility and the correlations between stock returns and consumption and dividends. Dynamics features of the data can be well captured. Stock and bond volatilities, bond yield and interest rate time series all have smaller mean square errors compared to the model which does not consider investor attentions. The scale and volatilities for these financial time series are also close to real financial data.

The aim is to analyze selected methods of budgeting and the valuation used in the Czech Republic. Explain the essential concepts of both fields, signal and break down their principles and rules of different methods, show creation process, imagine a software base budgeting and valuation, and consequently the practical example demonstrating its use.

This thesis defines the methods of building price determination. In my work I tried to explain the concepts related to budgeting and valuation, to describe and use methods for determining specific prices for my chosen family house in the town Bílina. The first part is used to get acquainted with the terminology related to the creation of the budget and the use of valuation methods in construction. I also tried to describe the principles and rules of budgeting and specific valuation methods, which I used on my chosen family house. The second part contains a practical solution to the problem. First, I create a budget in the budget program BUILDpowerS and then, here I use valuation methods and create prices for a family house. Finally, I compared the prices, which were created using valuation methods and the created budget, evaluated and its subsequent use.

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The objective of this study was to gain increased knowledge regarding BlackRock’s ability to influence their Swedish owned companies. The scope of this thesis has been to study eight companies where BlackRock have holdings. The actions of BlackRock are studied from two approaches, direct influence and indirect influence based on the literature review. The direct influence is a formal approach, including information regarding BlackRock’s participation in the nomination committee, the board of directors and their votes during the annual general meetings. The indirect influence consists of non-legal binding activities and includes information regarding BlackRock’s use of broad-based communication in form of CEO letter, where interpretations of the CEO letter have been compared to the studied companies’ annual reports. The study uses a qualitative method strategy with a deductive approach, together with data triangulation. The collected results and the analysis showed that BlackRock uses both direct and indirect methods to influence and deviates from the Swedish corporate code of governance in their methods of influence. One of the conclusions was that BlackRock, with their CEO letter, managed to influence their owned companies in regards to sustainability reporting according to SASB och TCFD framework.

This dissertation is a study of fundamental questions in macro-finance using modern tools from textual analysis. These questions include how financial constraints affect firm investment and financing decisions when they are not presently binding, and whether stock returns are predictable based on concerns revealed in conversations between firms and investors. The first chapter examines whether financial covenants are an important consideration for firm decisions when they are not presently in violation. A key empirical challenge is measuring the risk of future covenant violations, which is not directly observed. I propose a novel measure of concerns about future violations by distinguishing between discussions of covenants in earnings calls that relate to the future as opposed to the past or present. As validation, I show that the measure predicts future violations and covaries intuitively with earnings, leverage, and default risk. Importantly, I find that concerns about covenants are significantly associated with reductions in investment as well as debt and equity financing activities. These responses persist even after controlling for standard measures of investment opportunities and are economically large relative to the effects of actual violations. The second chapter empirically analyzes two explanations for how covenants concerns relate to a firm's investment decisions. One explanation is that covenant concerns coincide with a deterioration in expected profitability, which dampens firms' incentives to invest. A second explanation is that firms become concerned when they expect violations to be more costly, which indicates future difficulties with funding investments. To shed light on the relevance of these two explanations, I examine empirical patterns in analyst expectations of future earnings, loan amendments in SEC filings, and the stock returns of firms that mention covenant concerns. The evidence suggest that both explanations are relevant mechanisms driving the correlation between covenant concerns and firm activity. However, I find that the second channel is more economically significant, suggesting that covenant concerns are informative about the degree to which firms are constrained by financial covenants. In the third chapter, I investigate how covenant concerns relate to firm policies in a standard model of investments with financial frictions. In the model, the theoretical object that most naturally links to covenant concerns is the expected shadow cost of the borrowing constraint. As in the data, the shadow cost of the borrowing constraint covaries negatively with earnings as well as firm investment and financing activity. Through an analysis of impulse response functions, I show how the empirical correlations between covenant concerns and firm policy arise in the model. One channel is through negative productivity shocks, which raises covenant concerns and leads to a fall in investment, debt, and equity issuance. The second channel is through higher leverage, holding fixed productivity. In the model, firm with higher debt levels are more concerned about covenants when hit by a negative productivity shock, and also choose less investment, debt issuance, and equity issuance. In this chapter, I also discuss several shortcomings of the model and suggest avenues for modifications. The final chapter investigates a new question: are stock returns predictable based on the extent to which firms are concerned about the macroeconomy? We document that firms that pay more attention to the macroeconomy earn lower average returns relative to firms that pay less attention to the macroeconomy. Differences in returns are economically significant and are not explained by traditional asset pricing factors, such as market beta, size, value, and idiosyncratic volatility. To explain the negative macroeconomic attention premium, we propose a model of attention allocation that links analyst attention to fundamental shocks affecting firm cash flows. In the model, attention to the macroeconomy is increasing in the share of earning news explained by the macroeconomic component. Firms with a greater share of cash flow news explained by the macroeconomic component face lower cash flow risk, hence earn lower expected returns.