The notion of equity styles has been around for decades. An equity style is simply an equity class, a portfolio of stocks that share a common characteristic (e.g., small-cap stocks). A large body of both academic and industry research has been devoted to style investing. In recent years, average return differences between styles, such as the difference between growth and value stocks, have become the focus of many investigations. For example, Rosenberg, Reid, and Lanstein (1985), Fama and French (1992), Lakonishok, Shleifer, and Vishny (1994), and Roll (1997), among many others, have examined the long-term relative performances between growth, value, small-cap, and large-cap stocks. Meanwhile, the potential success of style rotation strategies has also attracted numerous studies (e.g., Beinstein (1995), Fan (1995), Sorensen and Lazzara (1995), Kao and Shumaker (1999), Levis and Liodakis (1999), and Asness et al. (2000)). These studies conclude that various dynamic style strategies are profitable and suggest that relative performances between equity styles are time-varying and predictable. In addition to the attempts to explore investment strategies, the concept of styles has also been utilized in the evaluation of managed portfolios. Most notably, Sharpe (1992) proposes an asset class factor model for performance attribution of mutual funds. Daniel et al. (1997), Fung and Hsieh (1997), and Ibbotson and Kaplan (2000) have extended Sharpe's style analysis in several ways.
In this article, we provide a multifactor analysis of style momentum. Style momentum is a combination of style rotation and momentum strategies. Specifically, we consider a set of size and book-to-market sorted portfolios that represent well-known investment styles, and rank the style portfolios in each month according to their returns over the previous month. A style momentum strategy buys the winner style and short-sells the loser style. This style strategy generates significant profits. Over the period from 1960 to 2001, the average return of the winner is, on an annualized basis, more than 16 percent higher than that of the loser. This return difference is significantly larger than the difference between the average returns of any two style portfolios. More surprisingly, conventional risk adjustment using the Fama and French (1993) three factor model appears to strengthen, rather than explain, the style momentum profits, although the model does capture much of the variation in the returns of the underlying style portfolios. The Fama-French three factor regressions do not provide any evidence that the strategy of buying the winner is any riskier than that of buying the loser. According to the regression intercepts, the risk-adjusted return difference between the winner and loser strategies is even larger than the raw return difference.
This paper examines the link between price, quality, seller claims and seller reputation in Internet auctions. To obtain a precise measure of quality, we purchased actual baseball cards and have them professionally graded. These cards were systematically purchased so half of the sample came from sellers making high quality claims and the other half from sellers making modest or no claim. We compare the quality data to the prices paid by online buyers for goods with similar claims.
We find that some buyers in the online ungraded market are misled by non-credible claims of quality. They pay higher prices but do not receive better quality and in fact are defrauded more often. Online seller reputation is found to be effective for identifying good-faith sellers. But conditional on completed auctions, reputable sellers do not provide better quality. Evidence also suggests that high-claim sellers target less experienced buyers. We attribute these data patterns to misleading signals in the online ungraded market and two loopholes in the eBay rating system, namely universal ratings and costless switching of anonymous identities.
This paper is an attempt to model the joint behavior of prices and wages in a way consistent with intertemporal optimization and rational expectations. Its ultimate goal is to construct a Phillips curve specification that is consistent both with U.S. data and with optimizing behavior, to respond to the well known 0Lucas critique.
The Phillips curve relationship has undergone a fruitful re exploration in recent years. The effort has been devoted to explain the relation between nominal and real variables in rigorously specified general equilibrium, optimizing models. For example, the so called New Keynesian1 Phillips Curve (NKPC), which describes current inflation as a function of expected future inflation and a measure of output gap, is derived in the context of a general equilibrium, optimizing model, that allows some form of nominal rigidities, either by assuming staggered price setting (for example, in the style of Calvo (1983) model), or by assuming staggered wage setting, or both (for ex. Erceg et al. 1999).
