The broad import of the evidence is that the application and qualification by a firm for listing on one of the two major American securities exchanges did, at least during the years encompassed by our investigation, constitute an event with which were associated abnormal positive investment returns on the shares involved. Even though a portion of those returns seem subsequently to have been surrendered, the initial net effect from application through listing date was quite substantial, and the later correction thereto was much more modest. The average combined impact visible in Table 3 during the six-month period beginning with the listing application, for example, was a net positive annualized return approximately 17 percent above that enjoyed concurrently by the general run of comparable-systematic-risk securities in the market. The explicit consideration of such risk distinguishes the present investigation from earlier studies in the area [7] [8] [10] [12] [13] [18].

On balance, then, it appears not unreasonable to conclude that listing did indeed “have value” for the companies examined. While one could argue that it was, intrinsically, the corporate developments (and the dissemination of the news thereof) which led to listing that were the real sources of value, the observed concentration of excess returns in the close proximity of the various application and listing dates would suggest that those actions provided useful market signals which did, in themselves, have a detectable favorable payoff—perhaps if only by way of accelerating the investment community's appreciation of the improvement in the applying firm's underlying operating circumstances. We interpret the evidence as supportive of that hypothesis.

The implications of the same evidence for questions of market efficiency, however, are somewhat more ambiguous. There would seem, as noted, to be in the data indications of certain possible information-response time lags that are not totally consistent with efficiency; and there is an apparent systematic initial price overreaction to application-cum-listing which is later remedied. Transactions costs, on the other hand, have not been considered here, and these clearly would impede the adjustment process by raising the threshold for investor action. Despite some cause for suspicion, therefore, a definitive judgment about efficiency must await further investigation.

We propose a methodology for assessing model risk and apply it to the implied volatility function (IVF) model. This is a popular model among traders for valuing exotic options. Our research is different from other tests of the IVF model in that we reflect the traders' practice of using the model for the relative pricing of exotic and plain vanilla options at one point in time. We find little evidence of model risk when the IVF model is used to price and hedge compound options. However, there is significant model risk when it is used to price and hedge some barrier options.

This paper critically evaluates the claim in recent papers that precisely estimated betas explain the cross-sectional differences in expected returns across size-based portfolios. In these studies, the correlations between firm size and betas across the test portfolios are close to one in magnitude, yielding potentially spurious inferences. This paper shows that when the test portfolios are constructed so that the correlations between firm size and beta are small, the betas explain virtually none of the cross-sectional differences in portfolio returns.

We investigate how government interventions such as blanket guarantees, liquidity support, recapitalizations, and nationalizations affect banking competition. These issues are critical for stability, access to finance, and economic growth. Exploiting cross-country and cross-time variation in the timing of interventions and accounting for their nonrandomness, we document that liquidity support, recapitalizations, and nationalizations trigger large increases in competition. We also find some more nuanced evidence that zombie banks’ market shares in crisis countries evolve together with interventions. A higher frequency of interventions coincides with greater zombie bank presence, and increases in competition are larger when zombie banks occupy bigger market shares.

Estimating difference-in-differences models on a comprehensive data set of Italian companies, we provide novel insights into the literature on political uncertainty and firm investment. We first establish that local political uncertainty leads to declining investment. Next, we show that family control neutralizes this effect: Family firms are more likely than other firms to invest during politically uncertain times, especially when operating in industries dependent on public spending and/or managed by family members. Finally, we document that this investment resilience of family firms under political uncertainty translates into significantly greater profitability and growth.

This paper studies the link between population age structure, net outflows (dividends plus repurchases less net issues) from the stock market, and stock market returns in an overlapping generations framework. I find support for the traditional lifecycle models—the outflows from the stock market are positively correlated with the changes in the fraction of old people (65 and over) and negatively correlated with the changes in the fraction of middle-aged people (45 to 64). Changes in population age structure also add significant explanatory power to equity premium regressions. The population structure adds to the predictive power of regressions involving the investment/savings rate for the U.S. economy. Finally, international demographic changes have some power in explaining international capital flows.

Is the decision to go public or private a stock-market-driven “sideshow” or does it have significant effects on investment and profitability? We address this issue using a comprehensive data set of private and public companies in the U.K. during 1996–2006. Firms with high investment-financing needs, lower information-production costs, and high industry market-to-book ratios are more likely to go public. In contrast to the literature, we find that capital investment and profitability increase substantially after the initial public offering (IPO). Consistent with the agency-cost-based theories of going private, firms decrease investment but increase profits after going private, especially firms bought out by private equity investors. Our analysis also highlights the effects of market conditions on the ownership structure decision.

Are auction markets or dealer markets better able to identify informed traders? Our analysis of firms that transfer to an alternative exchange structure indicates that traders are more anonymous in a competing dealer market than in an auction environment. Our evidence also shows that the associated changes in the probability of trading with an informed trader are related to changes in the bid-ask spread. The reduction in bid-ask spreads is more pronounced for firms with higher probability of transacting with an informed trader prior to the relocation from a dealer to an auction market.

We empirically compare a wide range of term structure models used in the pricing and, in particular, hedging of caps and swaptions. We analyze the influence of the number of factors on the hedging and pricing results, and investigate the type of data—interest rate or derivative price—in combination with the estimation technique that should be used to obtain the best hedging and pricing results. We use data on interest rates, and cap and swaption prices from 1995–1999. The empirical results show that, if the number of hedge instruments is equal to the number of factors, multi-factor models outperform one-factor models in hedging caps and swaptions. However, if one uses a large set of hedge instruments, one-factor models perform as well as multi-factor models. We find that models with two or three factors imply better out-of-sample predictions of cap and swaption prices than one-factor models. Estimation on the basis of current derivative prices leads to more accurate out-of-sample prediction of cap and swaption prices than estimation on the basis of interest rate data.

In an effort to increase transparency, the chair of the Federal Reserve now holds a press conference (PC) following some, but not all, Federal Open Market Committee (FOMC) announcements. Evidence from financial markets shows that investors lower their expectations of important decisions on days without PCs and that these announcements convey less price-relevant information. Correspondingly, we show that investors pay more attention to upcoming announcements with PCs. This coordination of attention can reduce welfare in models of the social value of public information. Consistent with theories of investor attention, the market risk premium is larger on days with PCs.

Previous tests of stock index arbitrage models have rejected the no-arbitrage constraint imposed by these models. This paper provides a detailed analysis of actual S&P 500 arbitrage trades and directly relates these trades to the predictions of index arbitrage models. An analysis of arbitrage trades suggests that i) short-sale rules are unlikely to affect the cash-futures mispricing, ii) the opportunity cost of arbitrage funds exceeds the Treasury bill rate, and iii) the average price discrepancy captured by arbitrage trades is small. Tests of the models provide some support for a version of the arbitrage model that incorporates an early liquidation option. The ability of these models to explain arbitrage trades, however, is surprisingly low.

We develop a theory of unit IPOs in which the firm going public issues a package of equity with warrants. We model an equity market where insiders have private information about the riskiness as well as the expected value of their firm's future cash flows. We demonstrate that, in equilibrium, high risk firms issue underpriced “units” of equity and warrants; lower risk firms, on the other hand, issue underpriced equity alone. In contrast to the existing literature, underpricing arises as a signal in our model in the context of a one-shot equity offering. Though developed in the context of IPOs, our model can also explain the issuance of seasoned equity offerings packaged with warrants. Further, the intuition behind the model generalizes readily to provide a new rationale for packaging call-option-like claims with risky securities other than equity, including convertible debt and debt with warrants.

This paper describes the application of a convergence acceleration technique to the binomial option pricing model. The resulting model, termed the accelerated binomial option pricing model, also can be viewed as an approximation to the Geske-Johnson model for the value of the American put. The new model is accurate and faster than the conventional binomial model. It is applicable to a wide range of option pricing problems.

In this paper we show that selecting mutual funds using alpha computed from a fund’s holdings and security betas produces better future alphas than selecting funds using alpha computed from a time-series regression on fund returns. This is true whether future alphas are computed using holdings and security betas or a time-series regression on fund returns. Furthermore, we show that the more frequently the holdings data are available, the greater the benefit. This has major implications for the Securities and Exchange Commission’s recent ruling on the frequency of holdings disclosure and the information plan sponsors should collect from portfolio managers. We also explore the effect of conditioning betas on macroeconomic variables as suggested by Ferson and Schadt (1996) to identify superior-performing mutual funds as well as the alternative way of employing holdings data proposed by Grinblatt and Titman (1993).

At subsecond horizons, bids and offers in U.S. equity markets are more volatile than what would be implied by long-term fundamentals. To assess costs and consequences, this paper suggests that traders’ random delays (latencies) interact with quote volatility to generate execution price risk and relative latency costs. Analysis of the behavior of quote setters suggests that this volatility is more likely to arise from recurrent cycles of undercutting similar to the Edgeworth cycles found in product markets rather than mixed strategies of limit-order placement.

This paper considers the Arbitrage Pricing Theory when investors have incomplete information on the parameters generating asset returns. Each asset in the economy may have a different amount of information available on it. Bayesian investors use their prior beliefs in conjunction with the total available information to assign an expected return and a set of factor betas to each asset. The assigned expected returns are shown to be linear in their associated factor betas. However, the factor betas and prices of assets differ from those under complete information. Specifically, risky assets with high (low) information are priced relatively higher (lower). On the other hand, factor betas of high (low) information assets are relatively lower (higher). The analysis has econometric implications for testing the APT. In this paper's framework, maximum likelihood estimates of factor betas, which are based on normality assumptions, are too high (low) for high (low) information assets. In addition, sequentially increasing the sample size by adding new securities to a factor analysis procedure can result in the detection of apparent additional priced factors when they do not really exist.

In the United States, momentum portfolios formed from 12 to 7 months prior to the current month deliver higher future returns than momentum portfolios formed from 6 to 2 months prior, suggesting an “echo” in returns. In 37 countries excluding the United States, there is no robust evidence of such an echo. In portfolios that combine securities in developed and emerging markets, or across three major geographic regions (Americas excluding United States, Asia, and Europe), there is also no evidence of an echo. Any echo in the United States appears to be driven largely by a carryover of short-term reversals from month − 2.

Since the publication of the work of Modigliani and Miller (MM) in the late 1950s there has been a recurrent controversy in the finance and economics literature about the interdependence of investment and financial variables. The arguments are too well known to recount at any length here. Basically MM would argue that in perfect capital markets, investment is, and should be independent of financing (which we will identify, as they would, with financial variables like dividends and new debt). The opposing view would argue that capital markets are sufficiently imperfect that the firm must consider financing in its investment decision. At least some of the proponents of this other view would argue that the firm must raise funds and allocate these scarce funds between investment and dividends. This view, then, holds that the firm's investment, dividend, and financing decisions are interdependent and must be studied in the context of a simultaneous equation model. There have been many articles discussing the MM position and many attempts to test it empirically. The first to focus directly on the question of interest here was done by Dhrymes and Kurz [1] in 1967. We will attempt to show that, despite several later studies, Dhrymes and Kurz were correct in their assertion that the investment and financing decisions are made simultaneously and must be studied in the context of a simultaneous equation model. To set the stage for our study we shall review the Dhrymes-Kurz study and subsequent related studies and show that each contained some error that affected their results.

This paper numerically solves the decision problem of a multiperiod constant relative risk aversion individual who faces transaction costs and has access to two risky assets, both with predictable returns. With proportional transaction costs and independent and identically distributed returns, we numerically find the rebalancing rule to be a no-trade region for the portfolio weights with rebalancing to the boundary. The shape of the no-trade region depends on the correlation between the two risky assets. With predictable returns, there is instead a no-trade region for each state. We also examine several important economic questions, including the utility cost of not being able to buy on margin or short stock.

We find evidence that labor unions affect chief executive officer (CEO) compensation. First, we find that firms with strong unions pay their CEOs less. The negative effect is robust to various tests for endogeneity, including cross-sectional variations and a regression discontinuity design. Second, we find that CEO compensation is curbed before union contract negotiations, especially when the compensation is discretionary and the unions have a strong bargaining position. Third, we report that curbing CEO compensation mitigates the chance of a labor strike, thus providing a rationale for firms to pay CEOs less when facing strong unions.