Three Essays on the Monitoring Role of Financial Analysts


Book Description

This dissertation consists of three chapters that present three standalone essays on the monitoring role of financial analysts. Chapter 1 investigates the monitoring role of financial analysts in the financial reporting process by examining the informativeness and monitoring effect of their written comments on earnings quality. I find that these comments have incremental predictability with respect to future accounting restatements, and convey information to investors beyond that in the earnings forecasts, stock ratings, price targets, and other qualitative text in analyst reports. Further analyses suggest that the market's reaction to these comments is primarily driven by negative comments and comments written with certainty. In addition, controlling for accrual reversals, I find that firms significantly reduce the level of accruals-based earnings management after receiving negative comments, and this reduction is not accompanied by an increase in real activities management. Overall, the first chapter provides direct evidence on analysts' monitoring role in financial reporting. Chapter 2 examines whether and how analysts' monitoring of the financial reporting process alleviates a well-known agency problem in which a manager inflates her compensation by manipulating earnings. I argue that analysts' monitoring reduces a manager's ability to conceal earnings management from directors, thus facilitating directors' adjustment of executive compensation in the presence of earnings management. Consistent with this argument, I find that earnings carry a lower weight in the determination of CEO compensation in firms that are criticized by analysts regarding earnings quality, but only when directors are likely to be aware of the critical analyst reports. The main findings are robust to matching on performance and controlling for firm-fixed effects and are not driven by other text in the analyst reports. Additional analyses suggest that the weight placed on earnings decreases as the actual accruals deviate from analysts' accruals forecasts. Overall, the second chapter emphasizes analysts' monitoring role in alleviating managerial rent extraction in executive compensation. Chapter 3 provides evidence on the impact of recent analyst independence reforms (the National Association of Securities Dealers [NASD] Rule 2711 and the companion New York Stock Exchange [NYSE] Rule 472 Amendment, and the Global Settlement) on analysts' monitoring role in the financial reporting process. The NASD Rule 2711 requires brokerage firms to structurally separate investment banking from equity research; meanwhile, the Global Settlement mandates the participating banks to fund independent research firms to the amount of 432.5 million dollars from 2004 to 2009. I find evidence consistent with an increase in analysts' monitoring effectiveness following the reforms. Further analyses suggest that this increase is primarily driven by the Global Settlement, rather than by the adoption of NASD Rule 2711. The evidence is robust to a difference-in-difference specification with Canadian firms as the control group. Moreover, I document a reversal of the increase in monitoring effectiveness following the end of the Global Settlement's five-year funding. Overall, the third chapter highlights the interaction between the monitoring role of financial analysts and the regulatory environment.




Three Essays on Environmental, Social, and Governance Transparency


Book Description

This dissertation is comprised of three essays on determinants and consequences of Environmental, Social, and Governance (ESG) Transparency. Transparency refers to high quantity of material and value relevant information about ESG issues. In the first essay, we explore the relationship between our two variables of interest (i.e., audit quality and public media exposure) and ESG transparency on a sample of publicly listed Canadian firms in in the S&P/TSX Index of the Toronto Stock Exchange. Results show that audit quality and public media exposure are two main drivers of ESG transparency, hence, commitment to high quality audits and exposure to high public media coverage drive firms to be more transparent about ESG issues. Finally, as a consequence of ESG transparency, we find a negative association between ESG transparency and firm-level investment inefficiency. The second essay examine whether the transparency of environmental and social (E&S) information affects financial analysts' forecast properties that reflect their information set. Focusing on a sample of non-financial and non-utility U.S. firms from the S&P 500 index, results suggest that the level of transparency vis-à-vis both E&S information is negatively related to analysts' forecast errors as well as forecast dispersion. These negative relationships become more pronounced for firms with low financial reporting quality, low media coverage, and for those with weak governance. Finally, we find that E&S transparency relates with investment efficiency essentially via analysts` information environment, which thus acts as a mediating variable. This finding is consistent with financial analysts also playing a monitoring role in capital markets. The third essay, we investigate how a firm's (E&S) transparency relates with its cash holdings. Focusing on a large sample of S&P 500 firms, results show that a higher level of E&S transparency implies lower firm-level cash holdings. The negative relationship is more pronounced for firms suffering from high information asymmetry, with low financial reporting quality, and for those with weak governance. Further analyses document that the two channels and mechanisms by which E&S transparency affect firm-level cash holdings are the cost of debt and financial constraints. Finally, our findings suggest that E&S transparency increases the market value relevance of an additional dollar in cash holdings.
















The Value of Financial Intermediaries


Book Description

This dissertation consists of three essays regarding the value of various financial intermediaries in capital markets. In the first essay, we examine the value of hedge fund activists, conditional on a firm’s existing monitoring presence. Traditional corporate governance theory designates analysts and institutional investors as the primary external monitors of the firm, and therefore, hedge fund activists are more likely to add value when these forces are inadequate. Consistent with this hypothesis, in the two years following the arrival of a hedge fund activist, we find the greatest abnormal returns and changes in fundamentals to be taking place in low-monitored firms. In the second essay, we determine the impact that hedge fund activism has on the quality of analyst content and analyst ability. We find a preponderance of recommendations that move to or are reinstated at the Hold level following the arrival of a hedge fund activist. Furthermore, the predictive content of analyst recommendations and their ability to accurately forecast earnings is diminished in the presence of a hedge fund activist. Overall, the quality of the important functions of an analyst is reduced by the arrival of a hedge fund activist, questioning the degree of social good that Jensen and Meckling (1976) argue security analysts provide. In the third essay, I examine the profitability of analysts’ consensus recommendation level, conditional on a firm’s synchronicity. Roll (1988), and many others, conclude that low r-squared from standard factor models, sometimes called low synchronicity, coincides with a more efficient incorporation of firm-specific information into stock prices. Under this view, analyst recommendations issued to firms with low synchronicity should be more profitable, primarily because analysts disseminate firm-specific information. I find the consensus recommendation level of analysts to be more profitable for low synchronicity firms. Moreover, this enhanced profitability is present primarily in good economic times and only in the post Regulation Fair Disclosure time period.










Three Essays on Business Analytics


Book Description

In my dissertation, I propose a general research framework of MAD---Monitoring, Analyzing, and Data Informed Decision-making---for financial decision-making. I present three essays which concentrate on two consequential aspects of decision-making for financial risk management. The first two essays focus on better monitoring and analyzing the risk, and the last one focuses on better data-informed decision-making based on the observation and analysis. In the first essay, I study the modeling of joint mortality for the practice of life insurance and annuity pricing. Specifically, I develop a new mathematical model to describe the joint mortality for coupled dependent lives. This model can be used to guide the risk management strategy and the pricing policy for insurance and annuity products. It is shown that it improves the current methods for modeling financial decision-making related to dependent life structures (such as joint life insurance, last survivor annuities, and defined benefit plans for married couples). In the second essay, I study the prediction of Bitcoin price movement and the relevant implications for business analytics. I exploit Bitcoin transaction networks and link network characteristics with the Bitcoin market exchange price. Based on this linkage and the data record, I construct predictive models for Bitcoin price movement. With the innovative use of Bitcoin transaction network data, the predictive models lead to more accurate results which outperform existing models. This methodological innovation also presents new managerial insights from network perspectives. In the third essay, I focus on data-driven decision-making in contexts of the allocation of disaster relief funds. Specifically, I tackle methodological challenges in disaster management when data are extremely sparse and insufficient in the beginning of the disaster evolution, and slowly become more available and reliable as time unfolds. Here I propose an iterative learning method within the general MAD framework to estimate disaster damage losses using very limited and slowly obtained data. Results show that this iterative learning method leads to highly accurate results with fast convergence of the estimation error to a very low level. The framework and results of this essay can be further used for disaster management and resource allocation in various scenarios