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.

"as violated by the school as by my rapist" Sexual Violence, Title IX and Purity Culture on Religious College Campuses

HonorsSociologyUniversity of Michiganhttp://deepblue.lib.umich.edu/bitstream/2027.42/169415/1/kschwert.pd

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.

Measuring deal premiums in takeovers

We investigate whether the merger announcement dates provided in the Securities Data Corporation (SDC) database are handled correctly by researchers performing event studies. We find that in 24.1% of deals, the popular choice of using the SDC’s “Date Announced” (DA) field as the event date leads to biased estimates of target firm abnormal returns because of earlier abnormal price movements due to merger-related events such as merger rumors or search-for-buyer types of announcements. We hand collect the merger-related events from news sources and make the complete dataset publicly available at the Financial Management website

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.