An important problem facing managers is how to enhance the credibility, or believability, of their earnings forecasts. In this paper, we experimentally test whether a characteristic of a management earnings forecast—namely, whether it is disaggregated—can affect its credibility. We also test whether disaggregation moderates the relation between managerial incentives and forecast credibility. Disaggregated forecasts include an earnings forecast as well as forecasts of other key line items comprising that earnings forecast. Our results indicate that disaggregated forecasts are judged to be more credible than aggregated ones and that disaggregation works to counteract the effect of high incentives. We also develop and test an original model that explains how disaggregation positively impacts three factors that, in turn, influence forecast credibility: perceived precision of management's beliefs, perceived clarity of the forecast, and perceived financial reporting quality. We show that forecast disaggregation works to remedy incentive problems only via its effect on perceived financial reporting quality. Overall, our study adds to our understanding of how managers can credibly communicate their expectations about the future to market participants.

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Underwriters using bookbuilding can allocate shares of initial public offerings (IPOs) on the basis of, among other things, commissions paid by investors. In testing the hypothesis that investors trade liquid stocks in order to affect their IPO allocations, we find that money left on the table by IPOs is related to the trading volume of the 50 most liquid stocks near the offer date. For an IPO that leaves $1 billion on the table, there is abnormal volume of 2.7% to 4.1% in the 50 most liquid stocks over the six days ending on the day that trading commences in that IPO, although only during the internet bubble period is this volume increase statistically significant.

This article uses a unique option data set to provide detailed descriptive statistics on the purchased and written open interest and open buy and sell volume of several classes of investors. We also show that volatility trading through straddles and strangles accounts for a small fraction of option trading volume and presents evidence that a large percentage of call writing is part of covered call positions. Finally, we find that during the stock market bubble of the late 1990s and early 2000 the least sophisticated investors in the data set substantially increased their purchases of calls on growth but not value stocks.

The acquisition of a partial stake in a target firm has been positively linked to the likelihood that the target will be involved in a follow on full acquisition involving either the original bidder or a third party bidder. Existing studies provide only suggestive evidence of this linkage by comparing the abnormal returns to partial targets that are ultimately acquired to those that are not. Using a sample of partial acquisitions, we identify characteristics that impact the probability of a full acquisition and provide a tangible link between partial target gains and the ex ante probability of acquisition. Partial targets experience positive announcement effects, and the gains are greater for subsequently acquired targets. Partial bids initiated by corporate bidders are more likely to result in a full acquisition, and the size of the acquired stake and the level of institutional ownership are positively linked to the probability of acquisition. Further, the partial target gains are positively linked to the ex ante probability of acquisition even after controlling for any increased monitoring and discipline that the partial bidder is expected to impose. The findings are robust across various time horizons and model specifications.

The exposition of the quadrature (QUAD) method (Andricopoulos, Widdicks, Duck, and Newton, 2003. Universal option valuation using quadrature methods. Journal of Financial Economics 67, 447–471 (see also Corrigendum, Journal of Financial Economics 73, 603 (2004)) is significantly extended to cover notably more complex and difficult problems in option valuations involving one or more underlyings. Trials comparing several techniques in the literature, adapted from standard lattice, grid and Monte Carlo methods to tackle particular types of problem, show that QUAD offers far greater flexibility, superior convergence, and hence, increased accuracy and considerably reduced computational times. The speed advantage of QUAD means that, even under the curse of dimensionality, it is not necessary to resort to Monte Carlo methods (certainly for options involving up to five underlying assets). Given the universality and flexibility of the method, it should be the method of choice for pricing options involving multiple underlying assets, in the presence of many features, such as early exercise or path dependency.

We report experimental results from long sequences of decisions in environments that are theoretically prone to severe information cascades. Observed behaviour is much different—information cascades are ephemeral. We study the implications of a theoretical model based on quantal response equilibrium, in which the observed cascade formation/collapse/formation cycles arise as equilibrium phenomena. Consecutive cascades may reverse states, and usually such a reversal is self-correcting: the cascade switches to the correct state. These implications are supported by the data. We extend the model to allow for base rate neglect and find strong evidence for overweighting of private information. The estimated belief trajectories indicate fast and efficient learning dynamics.

A long-run link between money and prices is evident for the United States since the Korean War if the M2 measure of money is used and the velocity of M2 (V2) is modeled as a mean-reverting series. This link between M2 and prices is the basis for a dynamic model of inflation that compares favorably in forecasting exercises with Phillips-curve and more typical monetarist approaches. The behavior of V2 is examined from 1870 to the present, providing a basis for reconsidering previous findings that V2 follows a random walk.

In this paper we develop a strongly stable (L-stable) and highly accurate method for pricing exotic options. The method is based on Padé schemes and also utilizes partial fraction decomposition to address issues regarding accuracy and computational efficiency. Due to non-smooth payoffs, which cause discontinuities in the solution (or its derivatives), standard A-stable methods are prone to produce large and spurious oscillations in the numerical solutions which would mislead to estimating options accurately. The proposed method does not suffer these drawbacks while being easy to implement on concurrent processors. Numerical results are presented for digital options, butterfly spread and barrier options in one and two assets. In addition, the methods are tested on the Heston stochastic volatility model.