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<p>I examine whether financial statement preparers (managers and auditors) treat recognized versus disclosed fair value of option compensation differently. Recognition refers to items that appear on the face of financial statements and that are included in subtotal figures that appear in the summary accounts; disclosure refers to items that appear in words and amounts in only the financial statement footnotes. I find that fair value recognition of option compensation is likely to have a significant impact on net income. Firms in my sample granted options amounting to a median fair value of 7% of profits in 1996 and 11% of profits in 2004. I compare the terms of option grants and the properties of fair value estimation under a disclosure reporting regime to terms and properties under a recognition regime. Under a fair value recognition regime, I find firms reduce/eliminate option grants across all levels of employees, reduce the statutory length of options, and substitute restricted stock and bonuses for option compensation. The fair value reduction in option grants is on average 9% (0.4%) of absolute net income. In contrast, under a fair value disclosure regime, option compensation was not reduced. I also find that firms increase the bias in three inputs to fair value option estimation: volatility, dividend, and interest. This increase amounts to 4%, 2%, and 0.3% of fair value cost. Mandatory recognition firms also display increased dividend and interest input accuracy. Combined, these results suggest that financial statements reflect differences in behavior between recognition and disclosure reporting regimes, such that both real actions and fair value estimation are used to reduce recognized values.</p> / Dissertation

The study examines the impact on subjects' ratings of performance when service efforts and accomplishments (SEA) measurements were included with traditional financial data. The study analyzes subjects' ratings of economy, efficiency and effectiveness over selected highway maintenance data. Information content of SEA measures is inferred from differences in subjects' ratings. / Subjects received actual financial and performance information for the State of Florida Department of Highway Maintenance for three years and were asked to rate the performance of the department. Each subject received one of three information presentations: traditional financial information, SEA measures, or both traditional financial information and SEA measures. Dependent variables were the ratings made by the subjects and their confidence in the ratings. / Results indicate that subjects clearly made different ratings of performance depending on which set of information they received. Subjects using traditional financial information tended to make higher ratings of performance than subjects using either SEA or combined data. In addition, subjects receiving combined data were more confident in their ratings than subjects receiving either SEA data or only traditional financial information. Consensus between subjects was also examined. Results were mixed, but type of information received did not appear to be a major factor affecting consensus among subjects. If consensus is a better proxy for judgment accuracy, there were few differences in accuracy between conditions. / Lastly, the subjects were asked to provide information on data sufficiency and on value of the types of data items. Subjects found the combined data format more sufficient for decision making, and also reported that types of information available in SEA measures were more valuable in these tasks. / Source: Dissertation Abstracts International, Volume: 54-07, Section: A, page: 2644. / Major Professor: William A. Hillison. / Thesis (Ph.D.)--The Florida State University, 1993.

Jensen's free cash flow theory produces numerous merger-related predictions. Existing empirical evidence is consistent with many of the predictions of the free cash flow theory, though little has been done to test this theory. This dissertation contributes to the understanding of the role that free cash flow plays in acquisitions. Different measures of free cash flow are investigated. / This dissertation addresses two specific issues. The first issue is the ability of free cash flow to explain consummated mergers. This is accomplished by determining whether free cash flow is matched (according to Jensen's theory) or mismatched between acquiring and acquired firms. Results indicate that free cash flow does play a role in the pairing of merger participants; however, the predictions of free cash flow theory are not supported. The inability to support Jensen's free cash flow theory may result from other factors not controlled for in this analysis. / The second issue is whether free cash flow can be used to explain firms that are acquired. This is accomplished by estimating a logit model for a sample consisting of acquired and non-acquired firms that includes free cash flow proxies and other variables. Free cash flow, growth, size, and exchange listing are observed to be characteristics that distinguish acquired firms from non-acquired firms. A model that includes a free cash flow measure relative to the industry is able to correctly predict 71.3 percent of acquired firms and 59.7 percent of all firms in the holdout sample. / The conclusions from the two issues addressed indicate that free cash flow does have a significant effect on merger activity. However, results do not support the predictions of Jensen's free cash flow theory of takeovers. An extension of this study would be to evaluate the abnormal returns of portfolios formed by free cash flow based models. Future research should also investigate whether free cash flow measures can explain the wealth effects observed for merger participants at the merger announcement date. / Source: Dissertation Abstracts International, Volume: 51-09, Section: A, page: 3168. / Major Professor: Pamela P. Peterson. / Thesis (Ph.D.)--The Florida State University, 1990.

This dissertation is a discussion of information production and disclosure as separate activities in the setting of entrepreneur-insiders of a firm trading shares of the firm with outside investors. One major task of the analysis is to establish the two informational activities as independent determining factors in the equilibrium framework of noisy rational expectations. In solving for the equilibrium, a particular question addressed is whether the produced information is fully revealed or partially revealed in the equilibrium. The model is then used to illustrate the separate effects of information production and disclosure. The significance of this analysis shows in the differences of the results here from previous ones obtained using a simplified treatment of information production and disclosure. Among these are some reasons provided here that support the practice of mandatory disclosure / acase@tulane.edu

Evolutionary algorithms attempt to find solutions to problems where the solution space is too large to be examined in its entirety. These algorithms have been used in applications ranging from Biology to Economics. Genetic Algorithms and Genetic Programming are variants of evolutionary computation that can be applied to problems in Accounting and Finance. This dissertation evaluates the applicability of Genetic Programming to option pricing and time-series modeling and the applicability of Genetic Algorithms to financial statement analysis The Black-Scholes model is a landmark in option pricing theory and has found wide acceptance in financial markets. The search for a better option pricing model continues, however, as the Black-Scholes model was derived under strict assumptions that do not hold in the real world and model prices exhibit systematic biases from observed option prices. I successfully apply Koza's (1992) Genetic Programming methodology to develop option-pricing models. This method is well suited to the task and offers some advantages over alternative methods There is often a need in accounting research for a proxy of the markets' expectation of earnings. Quarterly earnings forecasts from both analysts and mechanical models have been traditionally used as such proxies. Mechanical models, although easy to implement, have unfortunately never been able to consistently beat analysts' forecasts, of which Value Line (VL) is an example. I use Genetic Programming to develop forecasting and forecast combining models for the time-series of quarterly earnings. However, the models developed using this technique fail to perform better than traditional linear models One of the goals of financial statement analysis is to extract firm-value-relevant information from financial statements. The process by which this information is processed can be considered a black box. In making forecasts and reports, analysts examine financial statement variables and derived quantities and aggregate this information with outside information. The process is subjective and it is a stylized fact that some information is always purposely or by necessity left out. It is humanly impossible to coherently aggregate information from so many variables. Therefore, a methodology in which information is extracted automatically is potentially attractive not just to analysts but also to lay investors. Ou and Penman (1989) propose one such automated methodology. They develop what they term the 'Pr measure' to aggregate financial statement information and predict the signs of changes in annual company earnings adjusted for drift. However, Ou and Penman's methodology may have some weaknesses. I develop predictive models that ameliorate some of the potential weaknesses in Ou and Penman's method. My methodology combines genetic algorithms and LOGIT to predict the signs of earnings changes / acase@tulane.edu

According to the seasonal random walk model, the expected earnings for the current quarter is the actual earnings from the same quarter in the previous year. However, the time-series of quarterly earnings are shown to follow a process that is more complicated than the seasonal random walk model indicates. Specifically, the seasonally differenced quarterly earnings are positively autocorrelated at the first three lags and negatively autocorrelated at the fourth lag Previous studies have shown that the stock market partially anchors its earnings expectations based on the seasonal random walk model, and underestimates the magnitudes of these autocorrelations by on average fifty percent for the first four lags. The stock market's underreaction to past earnings information is shown to be a contributing factor to the post-earnings-announcement drift phenomenon. Financial analysts have also been shown to underreact to various kinds of publicly available information. It is possible that the stock market's apparent inefficiency is due to the similar behavior by financial analysts This study investigates, first, whether financial analysts fully reflect information in past earnings in their quarterly earnings forecasts, and second, its implications for the post-earnings-announcement drift phenomenon. Specifically, I study whether analysts fully exploit the autocorrelations in seasonally differenced quarterly earnings. I find that the implied analysts' estimates for the lag one and lag two autocorrelations in seasonally differenced quarterly earnings are about 24% and 36%, respectively, of the corresponding time-series estimates, suggesting underreaction to past earnings information by financial analysts. The results are not driven by the existence of potentially stale forecasts or by firms with poor prior earnings performance. When relating analysts' underreaction to post-earnings-announcement drift, I find that the majority of the stock market's underreaction to past earnings information can be attributed to analysts' underreaction. Based on the above results, I construct a forecasting model to predict analysts' forecast error based on the past earnings information, and I show that profitable trading rules can be formed using the above earnings surprise forecasting model / acase@tulane.edu

Firms undertaking spinoffs, on average, earn positive abnormal returns at the time of announcement and over one to three years following spinoffs. This thesis examines whether an increase in focus is an explanation for the stock market gains associated with spinoffs. For a sample of 155 spinoffs between the years 1975 and 1991, we find that the announcement period as well the long-run abnormal returns for the focus-increasing sample are significantly larger than the abnormal returns for the non-focus-increasing sample. The long-run abnormal performance of the non-focus increasing firms is actually negative. The results are robust to using alternative benchmark portfolios to compute abnormal returns, removal of firms that were taken over following spinoffs, and a separate examination of the parents and the subsidiaries. We conclude that focus-increasing spinoffs are associated with a superior stock market performance while non-focus-increasing spinoffs are not This thesis also tests the improved efficiency hypothesis by examining the change in operating efficiency following spinoffs and whether an increase in focus is an explanation for the improved operating efficiency following spinoffs. Using a sample of 75 industrial spinoffs completed between 1977 and 1991, we find a significant improvement in the operating performance of the pro-forma combined firm following the spinoff. There is a positive and significant relationship between the announcement period abnormal returns and the change in operating performance following spinoffs indicating that expectations of improved efficiency underlie the market's positive reaction to the announcement of spinoffs. A separate examination of the parents and the subsidiaries following spinoffs reveals that the parents exhibit a superior industry adjusted performance following spinoffs, while the performance of the subsidiaries is similar to their industry matching firms The focus-increasing firms show superior industry-adjusted operating performance following spinoffs, a finding consistent with the stock market performance of the focus-increasing firms documented in this thesis. The same is true when the parents are analyzed separately. However, unlike the negative industry adjusted stock market performance documented for the full sample, we do not find negative industry adjusted operating performance for the non-focus-increasing parents, subsidiaries or the pro-forma combined firm. We believe that this inconsistency can be attributed to the survivorship bias induced in the industrial sample due to our reliance on Compustat and due to possible disappearance of poorly performing firms before reporting one full year of accounting results in the year after the spinoff / acase@tulane.edu

The fundamental valuation process uses financial and operational information to assess future earnings and risk to arrive at a conclusion on the pricing of a risky investment project. We show that the market participants use this fundamental valuation process to assess the premium paid by acquirers to target firms following disciplinary takeovers. Using changes in Value Line forecasts before and after mergers announcements as a proxy for the investors' information about the fundamental values of the target firm, we show that this valuation plays a significant role in the investors' assessment of the target shareholders premium following the takeover announcements, after incorporating the bidders takeover motive as an integral part of the valuation process. Analysis of the target firm operating performance provides corroborative evidence of an inefficient target management The second part of the dissertation identifies and estimates the potential tax benefits as sources of gains in Mergers. First, we isolate the tax benefits from interest deductions associated with an increase in the debt of the combined firm after the merger. The results seem to suggest that these tax benefits are mainly associated with mergers that use either cash or both cash and stock as means of transaction. Mergers that use strictly stock as means of exchange are not followed with any significant leverage increase either immediately or in the next five years. The increase in debt could be either because of an increase in the combined firms' debt capacity following a merger or optimally utilizing any under utilized pre merger debt. Second, the revaluation of the target firms' asset at the acquisition price (stepped up basis) allows the acquirer with the option of increased depreciation deductions. Third, the net value of the tax benefits for the combined firm from net operating loss carryforwards and investment tax credits associated with tax free mergers. We estimate these potential tax benefits. Additionally, we also control for synergy, an increase in the post-merger operating performance (similar to Healy et. al.(1991)). Finally we show that these benefits are able to explain the wealth gains associated with mergers around the announcement dates, after controlling for increases in post-merger operating performance / acase@tulane.edu

This dissertation provides an investigation of the earnings surprise associated with the quarterly earnings announcement. The examination of a wide variety of forecast models allows insight into the ability of these models to capture the earnings expectations of the market. / The analysis addresses two issues. The first issue is the value of the earnings surprise. Among the forecasts models considered in the examination of forecast accuracy are: (1) a random walk model; (2) the standardized unexpected earnings (SUE) model; (3) three autoregressive integrated moving average (ARIMA) models; (4) an autoregressive conditional heteroskedasticity (ARCH) model; (5) a generalized autoregressive conditional heteroskedasticity (GARCH) model; (6) a price-based model; and (7) four analyst models. / The ARIMA models produce more accurate statistical forecasts than the random walk, SUE, ARCH, GARCH, or price-based models. Further, the analysts' forecasts are more accurate than any statistical alternative. The broader set of information considered by analysts gives them an advantage over statistical models. Further, the ability of the analysts to incorporate recent information gives them a timing advantage. / The second issue is the market response to earnings surprise, where surprise is defined by the different forecast models. The correlation between the forecast errors of the different models and the announcement period response provides evidence of the model that best captures the earnings expectation. The highest correlation is associated with the forecast errors of the most recent analyst forecasts. / Further analysis of the market response forms portfolios based on the most positive and negative earnings surprise securities. This provides insight into the value of the earnings announcement. Positive announcement period abnormal returns are associated with the positive surprise portfolios. In contrast to previous work, the abnormal returns associated with the negative surprise portfolios seldom differ from zero. With respect to the post-announcement period, positive abnormal returns are associated with both the positive and negative earnings surprise portfolios. This anomalous behavior is inconsistent with previous findings. Regardless, the introduction of round-trip transaction costs may eliminate any economic motivation to trade on this information. / Source: Dissertation Abstracts International, Volume: 52-06, Section: A, page: 2230. / Major Professor: Pamela P. Peterson. / Thesis (Ph.D.)--The Florida State University, 1991.