Tests For Unit Roots: A Monte Carlo Investigation

Recent work by Said and Dickey (1984 ,1985) , Phillips (1987), and Phillips and Perron(1988) examines tests for unit roots in the autoregressive part of mixed autoregressive-integrated-moving average (ARIHA) models (tests for stationarity). Monte Carlo experiments show that these unit root tests have different finite sample distributions than the unit root tests developed by Fuller(1976) and Dickey and Fuller (1979, l981) for autoregressive processes. In particular, the tests developed by Philllps (1987) and Phillips and Perron (1988) seem more sensitive to model misspeciflcation than the high order autoregressive approximation suggested by Said and Diekey(1984).

Stock Volatility and the Crash of '87

This paper analyzes the behavior of stock return volatility using daily data from 1885 through 1987. The October 1987 stock market crash was unusual in many ways relative to prior history. In particular, stock volatility jumped dramatically during and after the crash, but it returned to lower. more normal levels quickly. I use data on implied volatilities from call option prices and estimates of volatility from futures contracts on stock indexes to confirm this result.

Business Cycles, Financial Crises, and Stock Volatility

This paper shows that stock volatility increases during recessions and financial crises from 1834-1987. The evidence reinforces the notion that stock prices are an important business cycle indicator. Using two different statistical models for stock volatility, I show that volatility increases after major financial crises. Moreover. stock volatility decreases and stock prices rise before the Fed increases margin requirements. Thus, there is little reason to believe that public policies can control stock volatility. The evidence supports the observation by Black [1976] that stock volatility increases after stock prices fall.

Mark-Up Pricing in Mergers and Acquisitions

This paper studies the premiums paid in successful tender offers and mergers involving NYSE and Amex-listed target firms from 1975-91 in relation to pre-announcement stock price runups. It has been conventional to measure corporate control premiums including the price runups that occur before the initial formal bid. There has been little evidence on the relation between the pre-bid runup and the post-announcement premium (the premium paid to target stockholders measured from the date of the first bid). Under what circumstances are runups associated with larger total premiums? The evidence in this paper shows that in most cases, the pre-bid runup and the post- announcement premium are uncorrelated (i.e. little or no substitution between the runup and the post-announcement premium), so the runup is an added cost to the bidder. This has important implications for assessing the costs of illegal insider trading based on private information about a potential bid.

Biases in the IPO Pricing Process

By investigating the entire IPO pricing process, beginning when the offering is filed, the paper contributes to the existing literature along four dimensions. First, price updates during the registration period are predictable based on firm and offer-specific characteristics known at the time the offer is filed. Second, price updates reflect market movements prior to the initial filing date as well as during the registration period. Third, positive and negative information learned during the registration period affect the offer price asymmetrically. Finally, public and private information learned during the registration period have different effects on the offer price. While a number of the biases that we uncover are consistent with one or more theories regarding IPOs, many remain a puzzle.

IPO Market Cycles: Bubbles or Sequential Learning?

We examine the strong cycles in the number of initial public offerings (IPOs) and in the average initial returns realized by investors who participated in the IPOs. At the aggregate level, initial returns are predictably related to past initial returns and also to future IPO volume from 1960-1997. To understand these patterns, we use firm-level data from 1985-97 to model the initial return. Our results show that aggregate IPO cycles occur because of the time it takes to complete an IPO, the clustering of similar types of IPOs in time, and information spillovers among IPOs.

The Variability of IPO Initial Returns

The monthly volatility of IPO initial returns is substantial, fluctuates dramatically over time, and is considerably larger during "hot" IPO markets. Consistent with IPO theory, the volatility of initial returns is higher among firms whose value is more difficult to estimate, i.e., among firms with higher information asymmetry. Our findings highlight underwriters' difficulty in valuing companies characterized by high uncertainty, and, as a result, raise serious questions about the efficacy of the traditional firm commitment underwritten IPO process. One implication of our results is that alternate mechanisms, such as auctions, may be beneficial, particularly for firms that value price discovery over the auxiliary services provided by underwriters.

Stock Volatility During the Recent Financial Crisis

This paper uses monthly returns from 1802-2010, daily returns from 1885-2010, and intraday returns from 1982-2010 in the United States to show how stock volatility has changed over time. It also uses various measures of volatility implied by option prices to infer what the market was expecting to happen in the months following the financial crisis in late 2008. This episode was associated with historically high levels of stock market volatility, particularly among financial sector stocks, but the market did not expect volatility to remain high for long and it did not. This is in sharp contrast to the prolonged periods of high volatility during the Great Depression. Similar analysis of stock volatility in the United Kingdom and Japan reinforces the notion that the volatility seen in the 2008 crisis was relatively short-lived. While there is a link between stock volatility and real economic activity, such as unemployment rates, it can be misleading.

Hostility in Takeovers: In the Eyes of the Beholder?

This paper examines whether hostile takeovers can be distinguished from friendly takeovers, empirically, based on accounting and stock performance data. Much has been made of this distinction in both the popular and the academic literature, where gains from hostile takeovers are typically attributed to the value of replacing incumbent managers and the gains from friendly takeovers are typically attributed to strategic synergies. Alternatively, hostility could reflect just a perceptual distinction arising from different patterns of public disclosure, where negotiated outcomes are the rule and transactions tend to be characterized as friendly when bargaining remains undisclosed throughout, and hostile when the public becomes aware of the negotiation before its resolution. Empirical tests show that most deals described as hostile in the press are not distinguishable from friendly deals in economic terms, and that negotiations are publicized earlier in hostile transactions.

Anomalies and Market Efficiency

Anomalies are empirical results that seem to be inconsistent with maintained theories of asset-pricing behavior. They indicate either market inefficiency (profit opportunities) or inadequacies in the underlying asset-pricing model. The evidence in this paper shows that the size effect, the value effect, the weekend effect, and the dividend yield effect seem to have weakened or disappeared after the papers that highlighted them were published. At about the same time, practitioners began investment vehicles that implemented the strategies implied by some of these academic papers. The small-firm turn-of-the-year effect became weaker in the years after it was first documented in the academic literature, although there is some evidence that it still exists. Interestingly, however, it does not seem to exist in the portfolio returns of practitioners who focus on small-capitalization firms. All of these findings raise the possibility that anomalies are more apparent than real. The notoriety associated with the findings of unusual evidence tempts authors to further investigate puzzling anomalies and later to try to explain them. But even if the anomalies existed in the sample period in which they were first identified, the activities of practitioners who implement strategies to take advantage of anomalous behavior can cause the anomalies to disappear (as research findings cause the market to become more efficient).