Suresh Govindaraj

The Tylenol Incident, Ensuing Regulation, and Stock Prices

The much publicized Tylenol incident in 1982 led to stringent packaging regulations for over-the-counter pharmaceutical drugs. The sudden incident and the swift progression of associated events offer a unique opportunity to assess the wealth effects of the resultant regulations. The market value of common stock of Johnson & Johnson, makers of Tylenol, declined by approximately 29 percent, amounting to

Large time and small noise asymptotic results for mean reverting diffusion processes with applications

2.31 billion. Although other firms in the industry also suffered significantly, their share price decline did not occur around the Tylenol incident but occurred around the subsequent packaging regulation proceedings. On average, 28 other pharmaceutical firms analyzed in this study experienced a decline of

Reference-Day Risk: Observations and Extensions

310 million per firm, or a total of about

Discussion: “Opportunities Knocking: Residual Income Valuation of an Adaptive Firm”

8.68 billion. The results suggest that the regulation had a significant negative effect on the common stock prices of firms in the pharmaceutical industry.

Linear Valuation Models in Continuous Time with Accounting Information

Summary. We use the theory of large deviations to investigate the large time behavior and the small noise asymptotics of random economic processes whose evolutions are governed by mean-reverting stochastic differential equations with (i) constant and (ii) state dependent noise terms. We explicitly show that the probability is exponentially small that the time averages of these process will occupy regions distinct from their stable equilibrium position. We also demonstrate that as the noise parameter decreases, there is an exponential convergence to the stable position. Applications of large deviation techniques and public policy implications of our results for regulators are explored.

The Post Earnings Announcement Drift and Option Traders

Our paper confirms and extends the central result of Acker and Duck (2007) on reference-day risk. Using data from Datastream, they show substantial variations in the estimated monthly returns, variances, and betas across series beginning on different (reference) days of the same month. We show that the results are similar when we use data from the Center for Research in Security Prices daily files. We also show that reference-day risk extends to estimations based on daily returns. Finally, we find variations across series of daily returns computed using prices at different times of the day (reference-time risk). These findings carry potential implications for prior papers that rely on monthly or daily returns for analysis.

Using Option Implied Volatilities to Predict Absolute Stock Returns - Evidence from Earnings Announcements and Annual Shareholders’ Meetings

There are essentially two interesting and distinct, though not disparate, issues addressed in the paper. The first issue concerns the development of an analytical framework to explain the empirical phenomenon as to why firms, such as the Internet companies, with low earnings carry inexplicably high market values. The financial market seems to almost ignore low earnings, treating it as a temporary phenomenon with little predictive power about future earnings. However, high earnings are treated as informative and value relevant by the market. Therefore, there is a convexity in the valuation of earnings. One explanation for this is that firms with low earnings will definitely switch to high earnings projects to survive; consequently, current low earnings are a transient phenomenon with little information about future earnings. A related concept in the accounting literature is what the paper calls complementarity. This pertains to the empirical observation that financial markets value the balance sheet items more than the income statement items for firms with low earnings and conversely for firms with high earnings. The traditional explanation for this is that at low earnings levels, book value and balance sheet items provide information about the liquidation value, making them relatively more important. The second issue in the paper concerns the development of an extension of the Edwards-Bell-Ohlson (EBO) equation that would be consistent with convexity and complementarity. Picking up on the explanations above for convexity and complementarity, the paper introduces a notion called aduprution where firms have the option to optimally switch to better projects in order to survive. The paper argues that given adaptation, the Modigliani-Miller world, a Markovian accounting environment such as those introduced in the papers by Ohlson, Feltham, and others, convexity and complementarity are equivalent and the required EBO pricing equation is necessarily nonlinear. The nonlinearity is clearly traced to the option feature of adaptation. When current projects are generating high earnings, firms will have no reason to exercise their option to switch and the EBO model holds. When current earnings are low, firms are more likely to exercise their option switch to projects with higher earnings, and so current low earnings are less likely to persist, which

Valuation of Tax Loss Carryforwards and Carrybacks, and Its Implications for Dynamic Portfolio Selection

Two decades of empirical research in capital markets have produced considerable evidence of the information content of accounting numbers for security pricing. The theory of financial economics has also progressed enormously during this period. It is, therefore, surprising to note the paucity of theoretical models, in finance and accounting, that explicitly incorporate the empirical and structural characteristics of accounting variables in security valuation. In the absence of such theory, empiricists and practitioners have often relied on experience, intuition, and some good fortune in assessing the role of accounting information in pricing securities. I attempt, in this paper, to provide an economic framework for analyzing the role of accounting information in security valuation. ’ I begin by deriving a general, continuous-time, equilibrium-based security pricing model that is linear in accounting variables. This model identifies and defines theoretically consistent features of an economy that support the linear relationship. There are primarily three reasons for pursuing linearity. First, it is amenable to testing procedures using well-established linear regression techniques. Second, the linear structure allows me to make theoretical observations on commonly used ratios. Finally, it provides a link between my model and earlier models in the literature. The continuous-time setting for the model provides a realistic platform for financial accounting and reporting. It recognizes and captures the notion of continuous economic events. It also emphasizes the continuity of a firm’s activities and existence. Within this economic framework, I derive sufficient conditions to re-

Market Reaction to Quantitative and Qualitative Order Backlog Disclosures

The Post-Earnings Announcement Drift (PEAD) anomaly refers to the tendency of stock prices to continue drifting in the same direction as earnings surprises well through the subsequent earnings announcements; ignoring the autocorrelations in extreme earnings surprises across adjacent quarters. Currently, the two major competing theories to explain PEAD are: the risk premium hypothesis (RPH), which argues that the anomaly exists only because risk has been measured improperly; and, the under-reaction (behavioral) hypothesis (URH), which assumes investors do not completely utilize the auto-correlations of earnings surprises. We test the former (RPH) by using a finer metric for risk than used in prior research, namely, the change in implied volatilities obtained from options prices immediately before and after the earnings announcements. Inconsistent with the predictions of RPH: (1) we do not find a positive correlation between the implied volatility changes and earnings surprises; and (2) we find that implied volatilities (risk) actually decrease most after the earnings announcements for firms with the most positive earnings surprises. Using volatility based option trading strategies (straddles), we examine if option traders have a similar URH bias to those of equity traders. We find that option straddles based on extreme earnings surprises in the prior quarter are not more profitable than straddles on mild earnings surprises, indicating that option traders already incorporate the prior earnings surprise in option prices.

Retirement, Nonmarket Valuation, and Partnership Contracts

We provide evidence that an option implied volatility-based measure predicts future absolute excess returns of the underlying stock around earnings announcements and annual meetings of shareholders, even after controlling for the realized stock return volatility shortly before these information events, and the volatility of excess stock returns around these two events in the past. Our results imply that option traders anticipate the change in uncertainty around these two scheduled events, and also trade on the expected volatility. In addition, we show that net straddle returns (after transaction costs) around earnings announcements and annual meetings of shareholders are significantly and negatively related to the predicted volatility of returns around the events. This suggests that the writers of call and put options expect to be compensated for the predicted volatility. Overall, we find that option traders anticipate and correctly incorporate the volatility induced by the information released in quarterly earnings announcements, and annual meetings of shareholders.