<p> The financial economics profession has determined that identical agents in a dynamic, stochastic, general equilibrium (DSGE) model does not provide price and trading dynamics realized in financial markets. There has been quite a bit of research over the last three decades extending heterogeneity to the Lucas asset pricing framework, to address this issue. Once the assumption of homogeneous agents is relaxed, the problem becomes increasingly complex due to a state space including the wealth distribution, continuation utilities, and wealth distribution dynamics. To establish a more computationally feasible model, specical modifications have been made such as heterogeneity in idiosyncratic shocks and not risk aversion, including aggregate or idiosyncratic risk (but not both), or assuming no growth in the economy (steady state). </p><p> In this research, I will define a DSGE model with heterogeneous agents. This heterogeneity will refer to differing CRRA utilities through risk aversion. The economy will have growth due to the assumed dividend process. Agents will face idiosyncratic and aggregate shocks in a complete markets setting. The framework of the provided algorithm will enable issues to be addressed beyond homogeneous agent models. </p><p> The numerical simulation results of this model provide considerable asset price volatility and high trading volume. These results occur even in the complete markets setting, where investors are expected to fully insure. Given these dynamics from the simulations of the algorithm, I demonstrate the ability to calibrate this model to address specific financial economic issues, such as the equity premium puzzle. More importantly this exercise will assume realistic agent parameters of risk aversion and discount factors, relative to economic theory.</p>

<p> Due to the increase in corporate bankruptcy, financial distress studies have flourished since 1968. Firms do find themselves in financially distressful situations because of several factors including changing economic environment such as a decrease in aggregate demand, an increase in the cost of borrowed funds, and changes in government regulation. In addition to the Altman's z-score model, the sustainable growth rate (SGR) is another tool that is used primarily for financial planning. The problem with Altman's z-score model is that it does not consider whether a firm can be financially distressed or not if the sustainable growth rate of the firm is in fact higher than the growth rate of the firm's reported revenues. The purpose of this quantitative study was to investigate the efficacy of using ltman's z-score in forecasting financial distress of a firm when the sustainable growth rate was higher than the growth rate of the reported revenues. The sample for this study was drawn from all non-financial firms traded on the NYSE. The research question was investigated using two group design in two phases. Phase 1 involved the calculation of the sustainable growth rate (SGR), the growth rate of reported revenues, and the calculation of Altman's z-score. The Altman's z-score of the two groups were compared using Mann-Whitney <i>U</i> test to determine whether a statistically significant difference exists in the z-score. Phase 2 involved the correlation between the values of SGR and the values of Altman's z-score to determine if there was a statistically significant relationship between the two scores. The result of this research indicates that the Alman's z-score and the sustainable growth rate are conceptually independent and both can be used to ascertain whether a firm is financially distressed or not. In addition, result of this study provide practical application that could help management of firms reach important financial and managerial decisions. While the result of this study provided useful information and added to existing knowledge on financial distress, additional research using more than one year of financial data is recommended in order to confirm the results of this study.</p>

<p> Modern portfolio theory states that investments with greater beta, a common measure of risk, require greater returns from investors in order to compensate them for taking greater risk. Therefore, under the premise that market participants act rationally and therefore markets run efficiently, investments with higher beta should generate higher returns vis-&agrave;-vis investments with lower beta over the long run. In fact, many studies suggest that investments with lower beta actually generate equal to or higher returns relative to investments with higher beta. In looking at data for the S&P; 500 going back 22 years between 1990 and 2012, this study found that there was very low correlation between beta and returns. In fact, portfolios with very low risk generated commensurate to better returns versus portfolios with very high beta. Therefore, we find that beta appears to be a poor measure of risk as it relates to the stock market. In addition to beta and returns, this study looked at the fundamental characteristics of each company specifically corporate profitability and balance sheet leverage which are commonly used by investors in assessing the underlying quality of a company. We find that companies with higher levels of return on equity combined with lower levels of balance sheet leverage tend to outperform companies with lower levels of profitability and higher balance sheet leverage. As a result, we find a high correlation between balance sheet leverage, ROE and stock returns. This paper suggests that in fact, fundamental factors such as leverage and ROE tend to be better measures of risk vis-&agrave;-vis beta. One important final observation is the fact that while in general, companies with high ROEs and low leverage tend to outperform companies with low profitability and high leverage, portfolios of those companies with the highest ROE and lowest leverage and portfolios of those companies with the lowest ROE and highest leverage actually underperform on the whole other portfolios. In other words, portfolios of companies that exhibit the most extreme of characteristics in terms of ROE and leverage underperform portfolios of companies with more moderate characteristics. One plausible explanation for these observations is rooted in behavioral economic theory known as the favorite long shot bias and the opposite favorite long shot bias. The opposite favorite long shot bias suggests that market participants tend to "over-bet" an asset and/or an investment with high probability of a payoff but low overall return if the payoff occurs (ie the sure bet). In fact, market participants go so far to secure a payoff that they actually place a higher bet on the probability of success than the actual odds would suggest. In stock market terms, investors will tend to over-value the least-riskiest stocks to the point where risk and return is no longer favorable. Similar phenomenon can be observed in horse race betting and sports drafts. The favorite long shot bias is the inverse of the opposite favorite longshot bias. This theory suggests that market participants actually "over bet" an asset and/or an investment with the lowest probability of a payoff but with significant overall returns if the payoff occurs. Similar phenomenon takes place in the purchase of insurance to insure against large potential losses with small probabilities as well as lottery ticket purchases. We see the most striking evidence of this when looking at the returns of stocks with the highest ROEs and the lowest levels of debt/capital as of 1990. In that year, investors would have based their investments in stocks using current attributes at that time. We can see that stocks with the highest ROEs and lowest levels of debt/capital garner higher valuations relative to the broad stock market. We also see that stocks with the lowest ROEs and highest debt/capital also command premium valuations to the market as a whole. Therefore, risk-averse investors will tend to overvalue companies with the least risky prospects while risk loving investors will tend to overvalue companies with the riskiest prospects at the same time. As a result, we can see from looking at the future returns that companies that exhibit extreme characteristics in terms of ROE and debt/capital tend to underperform the broad market. Similar to high profile athletes and horse track betting, we find that investors tend to over-bet sure shot investments while simultaneously over-betting long shot investments.</p>

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Thesis (Ph.D.)--Indiana University, Dept. of Economics and Dept. of Finance, 2007. / Source: Dissertation Abstracts International, Volume: 68-05, Section: A, page: 2094. Advisers: Eric L. Leeper; Gregory F. Udell. "Title from dissertation home page (viewed Jan. 24, 2008)."

Thesis (M.S.)--Rutgers University, 2007. / "Graduate Program in Electrical and Computer Engineering." Includes bibliographical references (p. 78-79).

Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2006. / Source: Dissertation Abstracts International, Volume: 67-11, Section: A, page: 4276. Adviser: Anil K. Bera. Includes bibliographical references. Available on microfilm from Pro Quest Information and Learning.

Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2006. / Source: Dissertation Abstracts International, Volume: 67-07, Section: A, page: 2494. Adviser: Kern Alexander. Includes bibliographical references (leaves 96-118) Available on microfilm from Pro Quest Information and Learning.

This work consists of five separate essays that examine the banking industry from a number of viewpoints. In the first essay, I consider how the ratchet effect interacts with workers' ability to cooperate to determine effort provision in teams. I show how the dominant constraint varies with both the size of the team and the members' ability to monitor each other's effort. Small teams tend to have their effort provision constrained by the ratchet effect; large teams are instead constrained by the inability of the team members to demand effort from each other. In the second essay, I examine the phenomenon of large team transfers in professional service firms, especially investment banks. I argue that large team moves occur because employees benefit by working with the most talented coworkers. Above-average teams may move together to effectively exclude younger, less-talented workers. These team transfers are optimal when employees are remunerated with team-based bonuses, which may explain their significance in investment banking. In the third essay, I consider the securitization market. First, I provide an explanation for equilibrium credit ratings inflation that does not require investor irrationality. Second, I argue that moral hazard in securitization results in banks either selling the entirety of securitized products, or none at all. Finally, I consider a number of possible government interventions in the market and conclude that many proposed interventions are either ineffectual or counterproductive. In the fourth essay, we design an improved LIBOR reporting mechanism. This mechanism, which we name the "whistleblower mechanism," uses the revealed preference of other banks to determine the borrowing rate of a given bank. Truthful reporting is the sole equilibrium of the mechanism that we design; the mechanism is budget-balanced. In the fifth essay, we consider the analogy between systemic risk and pollution. We argue that an ex post tax cannot replicate capital regulation because of a 'polluter cannot pay' problem. Secondly, we show an equivalency result between ex ante taxation and capital regulation. We then show that unless the ex ante tax is levied in capital, however, it may perversely increase the amount of debt in the financial system. We argue for further capital regulation.