A Performance Comparison Between Cross-Sectional Stochastic Dominance and Traditional Event Study Methodologies

In this study, the performance of cross-sectional stochastic dominance (SD), first proposed by Falk and Levy (FL) (1989), is compared with three traditional event study methodologies: the Mean Adjusted model, the Market Adjusted model, and the Market and Risk Adjusted Returns model. The comparison technique we use is a simulations approach similar to that of Brown and Warner (BW) (1980). BW show that the Mean Adjusted and Market Adjusted Returns models perform as well as the more sophisticated Market and Risk Adjusted Returns model. FL, however, provide a very compelling argument against the three traditional event study methodologies. The problem, they note, is not the theoretical need for risk adjustment; it is the definition and measurement of risk. FL assert that the observed abnormal returns (or lack thereof) may be due to omitted variables, a market proxy effect, or other specification errors in implementing the traditional event study methodologies.The present research finds that SD analysis without the bootstrap method for statistical testing is not very useful at any level of abnormal return. However, when the bootstrap method of statistical testing is employed, SD is found to perform as well as, and sometimes better than, the three traditional models in detecting simulated abnormal performance at all test levels. The results are consistent with FL\'s assertion that the improved performance may result from the SD methodology being free from the specification errors inherent in the three traditional event study models.     

The value of reputation on eBay: A controlled experiment

We conducted the first randomized controlled field experiment of an Internet reputation mechanism. A high-reputation, established eBay dealer sold matched pairs of lots—batches of vintage postcards—under his regular identity and under new seller identities (also operated by him). As predicted, the established identity fared better. The difference in buyers’ willingness-to-pay was 8.1% of the selling price. A subsidiary experiment followed the same format, but compared sales by relatively new sellers with and without negative feedback. Surprisingly, one or two negative feedbacks for our new sellers did not affect buyers’ willingness-to-pay. JEL Classification D82 · L14 · Z13     

Return enhancement trading strategies for size based portfolios

Recent theoretical work suggests that definitions of market efficiency that allow for the possibility of time-varying risk-premia will generally lead to return sign predictability. Consistent with this theory, we show that a logit model based on the lagged value of the market risk premium is useful for successfully predicting the return sign for CRSP small decile portfolio returns, but not large ones. We additionally employ this model in market timing simulations of micro-cap mutual funds in which investment can actually be made. The results indicate that a market-timing strategy based on our return-sign forecasting model outperforms a buy-and-hold strategy for 13 of 14 micro-cap funds studied. On average, the buy-and-hold strategy produces an average compound return of 11.98% per annum versus an average of 16.60% for the market-timing strategy. Nevertheless, trading restrictions make the return-sign forecasting model more practical to employ by the micro-cap fund portfolio manager rather than the individual fund investor.

An ex ante analysis of put-call parity

The authors previously had extended the theoretical put-call parity models developed by Stoll (1969) and Merton (1973) to include a dividend term. Ex post tests of the models were generally consistent with market efficiency, but a sufficient number of hedges had high enough returns to warrant analysis of ex ante results. The purpose of this study was to construct hedges 5 and 15 minutes after they were initially identified as having an ex post return in excess of $20 per hedge. The results indicate that mispriced options adjust and that economic profit is sensitive to the level of transaction costs and unlikely even for member firms.     

The size distribution of cities: An examination of the Pareto law and primacy

This paper examines the Pareto and primacy measures of the size distribution of cities. The mean Pareto exponent for a sample of 44 countries is 1.136, somewhat greater than the exponent of one implied by the rank-size rule. We find that value of the Pareto exponent is quite sensitive to the definition of the city and the choice of city sample size. The significance of non-linear terms in variants of the Pareto distribution also indicate that the rank-size rule is only a first approximation to a complete characterization of the size distribution of cities within a country. The relatively low correlation between primacy and Pareto measures confirms the need for a variety of measures of city size distributions. This paper also suggests that large cities are growing faster than small cities in most of the countries in our sample. This is indicated by the positive coefficient on the first non-linear term introduced into the Pareto equation. Finally, variations in the Pareto exponent and measures of primacy are partly explained by economic, demographic, and geographic factors.     

Service worker appearance and the retail service encounter: the influence of gender and age

This study explores how the age and gender of service workers influence customers' perceptions of the retail service encounter in a health and beauty retailer. An analysis of qualitative interviews with 40 customers and 20 service workers suggests that customers seek reassurance in the service encounter by ‘matching’ and ‘mirroring’ the age and gender of customer-facing staff with their expectations of who should deliver appropriate service during the retail service encounter. These non-verbal cues, as a way of assessing the credibility of the service provider, are particularly important when customers are involved in high-involvement purchase occasions.     

ESTIMATING THE DEPENDENCE STRUCTURE OF SHARE PRICES: A COMPARATIVE STUDY OF THE UNITED STATES AND JAPAN

In this paper, we show that estimating the correlation structure of domestic share prices via the Overall Mean method cannot be considered universally superior to estimation at the Full Historical level for all countries. Specifically, the Japanese data show that the Full Historical Model outperforms the Overall Mean Model in forecasting accuracy, while the opposite is true with the U.S. data. We derive a Composite Model that analytically explains this contrasting result. The Industry Mean Model, which allows for efficient ex ante portfolio selection via a simple algorithm, is likely to be the best forecasting model applicable to both the U.S. and Japanese stock markets.