Knowledge that Transforms

This paper studies the role that trading activity plays in the price discovery process of a NYSE-listed stock. We measure the expected information content of each trade by estimating its permanent price impact. It depends on observable trade features and market conditions. We also estimate the time required for quotes to incorporate all the information content of a particular trade. Our results show that price discovery is faster after risky trades and also at the extreme intervals of the session. The quote adjustment to trade-related shocks is progressive and this causes risk persistency and unusual short-term market conditions.

The parameters of application scorecards are usually estimated using a sample that excludes rejected applicants which may prove biased when applied to all applicants. This paper uses a rare sample that includes those who would normally be rejected to examine the extent to which (1) the exclusion of rejected applicants undermines the predictive performance of a scorecard based only on accepted applicants, and (2) reject inference techniques can remedy the influence of this exclusion.

This paper demonstrates the importance of using a flexible cost function specification when analyzing economies of scale and estimating the cost effect of banking mergers. The inflexibility of the translog cost function is illustrated and results are compared to more flexible spline and Fourier cost functions. Using these different approaches we predict the ex ante effect on average cost from mergers over 1987–1998 using a balanced panel of 130 Norwegian banks. On average mergers are predicted to lower costs. Predictions using the Fourier or spline approach are in overall agreement with computed actual average merger-cost changes ex post. Cost effects of electronic payments are also estimated and exceed cost reductions associated with mergers.

This paper introduces a parameterization of the normal mixture diffusion (NMD) local volatility model that captures only a short-term smile effect, and then extends the model so that it also captures a long-term smile effect. We focus on the ‘binomial’ NMD parameterization, so-called because it is based on simple and intuitive assumptions that imply the mixing law for the normal mixture log price density is binomial. With more than two possible states for volatility, the general parameterization is related to the multinomial mixing law. In this parsimonious class of complete market models, option pricing and hedging is straightforward since model prices and deltas are simple weighted averages of Black–Scholes prices and deltas. But they only capture a short-term smile effect, where leptokurtosis in the log price density decreases with term, in accordance with the ‘stylised facts’ of econometric analysis on ex-post returns of different frequencies and the central limit theorem. However, the last part of the paper shows that longer term smile effects that arise from uncertainty in the local volatility surface can be modeled by a natural extension of the binomial NMD parameterization. Results are illustrated by calibrating the model to several Euro–US dollar currency option smile surfaces.

Surveys on the use of agency credit ratings reveal that some investors believe that rating agencies are relatively slow in adjusting their ratings. A well-accepted explanation for this perception on the timeliness of ratings is the through-the-cycle methodology that agencies use. According to Moody’s, through-the-cycle ratings are stable because they are intended to measure default risk over long investment horizons, and because they are changed only when agencies are confident that observed changes in a company’s risk profile are likely to be permanent. To verify this explanation, we quantify the impact of the long-term default horizon and the prudent migration policy on rating stability from the perspective of an investor – with no desire for rating stability. This is done by benchmarking agency ratings with a financial ratio-based (credit-scoring) agency-rating prediction model and (credit-scoring) default-prediction models of various time horizons. We also examine rating-migration practices. The final result is a better quantitative understanding of the through-the-cycle methodology. By varying the time horizon in the estimation of default-prediction models, we search for a best match with the agency-rating prediction model. Consistent with the agencies’ stated objectives, we conclude that agency ratings are focused on the long term. In contrast to one-year default prediction models, agency ratings place less weight on short-term indicators of credit quality. We also demonstrate that the focus of agencies on long investment horizons explains only part of the relative stability of agency ratings. The other aspect of through-the-cycle methodology – agency-rating migration policy – is an even more important factor underlying the stability of agency ratings. We find that rating migrations are triggered when the difference between the actual agency rating and the model predicted rating exceeds a certain threshold level. When rating migrations are triggered, agencies adjust their ratings only partially, consistent with the known serial dependency of agency-rating migrations.

We present two internal capital allocation models and compare the capital ratios they generate with those prescribed by the latest revision of Basel’s New Capital Accord proposal for advanced retail portfolios, which allows for explicit future margin income recognition. Given a test portfolio of credit card exposures that we assemble, we find that Basel’s ratios are closer to those generated by our models for low credit risk segments. We attribute the discrepancies to the different ways Basel and our models account for future margin income, to Basel’s assumptions about asset correlations and to one model taking macroeconomic conditions into account.

Hirshleifer et al. (J. Account. Econom. 38 (2004)) and Taffler, Lu and Kausar (J. Account. Econom. 38 (2004)) document large and statistically significant abnormal returns from trading on balance sheet data and audit opinions. However, the statistical tests ignore high transactions costs, especially for selling short, that would likely make the trading strategies unprofitable. The accounting anomalies literature is adding little to what we know about how and why markets operate more or less efficiently. I identify some research questions and opportunities, highlighting those with accounting and auditing implications.

This paper extends the variance decomposition framework of Campbell [1991], Campbell and Ammer [1993], and Vuolteenaho [2002] to address the relative value relevance of accrual news, cash flow news, and expected‐return news in driving firm‐level equity returns. The extension is based on the Feltham‐Ohlson [1995, 1996] clean surplus relations. Using three models, this study shows that all three factors, accruals, cash flows, and expected future discount rates are value relevant. Moreover, accrual news is found to significantly dominate expected‐return news in driving firm‐level stock returns. Operating income news is also found to significantly dominate both expected‐return news and free cash flow news in driving firm‐level stock returns. Furthermore, after splitting net income into cash flow and accrual earnings components in the Vuolteenaho model, accrual earnings news and cash flow earnings news are found to equally drive firm‐level stock returns and to dominate expected‐return news. Further disaggregation of the data yields some evidence that accrual earnings news is a more important factor than cash flow earnings news in driving current stock returns. Overall, the three models indicate that changes in expected future accruals are a primary driver, if not the primary driver, of current stock returns.

ABSTRACT Inflation and foreign exchange raise new issues with respect to accounting representations of equity value. For example, inflation creates an earnings illusion as an artifact of the mismatching of expenses based on allocations of historical costs with current revenues in determining earnings. This mismatching distorts mappings of aggregate earnings and book values into equity value such that value‐relevant information is lost. In this article we consider the consequences of inflation and foreign exchange accounting policies, including those contained in accounting standards, on the value relevance of bottom‐line accounting numbers. Policies are identified that achieve efficient accounting in the sense that aggregate (comprehensive) earnings and book values are sufficient for an accounting representation of equity value. The linear relations that emerge provide predictions on capitalization coefficients that help explain results of empirical inquiries. As well, our analysis provides a theoretical foundation for policies contained in accounting standards that contributes to the resolution of controversies such as that concerning foreign exchange accounting.

A speaker wishes to persuade a listener to accept a certain request. The conditions under which the request is justified, from the listener's point of view, depend on the values of two aspects. The values of the aspects are known only to the speaker and the listener can check the value of at most one. A mechanism specifies a set of messages that the speaker can send and a rule that determines the listener's response, namely, which aspect he checks and whether he accepts or rejects the speaker's request. We study mechanisms that maximize the probability that the listener accepts the request when it is justified and rejects the request when it is unjustified, given that the speaker maximizes the probability that his request is accepted. We show that a simple optimal mechanism exists and can be found by solving a linear programming problem in which the set of constraints is derived from what we call the L-principle.