Papers being browsed today

Draft of 2006.08.24 ☛ 2015.03.18

Just what crossed my desk this morning. No recommendation for, nor argument against; just sayin’ I’m lookin’ at ‘em.

Abstract: We compared forecasts of stock market volatility based on real-time and revised macroeconomic data. To this end, we used a new dataset on monthly real-time macroeconomic variables for Germany. The dataset covers the period 1994-2005. We used a statistical, a utility-based, and an options-based criterion to evaluate volatility forecasts. Our main result is that the statistical and economic value of volatility forecasts based on real-time data is comparable to the value of forecasts based on revised macroeconomic data.

Abstract: This paper studies the behaviour of Internet prices. It compares price rigidities on the Internet and in traditional brick-and-mortar stores and provides a cross-country perspective. The data set covers a broad range of items typically sold over the Internet.It includes more than 5 million daily price quotes downloaded from price comparison web sites in France, Germany, Italy, the UK and the US. The following results emerge from our analysis. First, and contrary to the recent findings for common CPI data, Internet prices in the EU countries do not change less often than online prices in the US. Second, prices on the Internet are not necessarily more flexible than prices in traditional brick-and-mortar stores. Third, there is substantial heterogeneity in the frequency of price change across shop types and product categories. Fourth, the average price change on the Internet is relatively large, but smaller than the respective values reported for CPI data. Finally, panel logit estimates suggest that the likelihood of observing a price change is a function of both state- and time-dependent factors.

Abstract: This paper explores the determinants of corporate failure and the pricing of financially distressed stocks using US data over the period 1963 to 2003. Firms with higher leverage, lower profitability, lower market capitalization, lower past stock returns, more volatile past stock returns, lower cash holdings, higher market-book ratios, and lower prices per share are more likely to file for bankruptcy, be delisted, or receive a D rating. When predicting failure at longer horizons, the most persistent firm characteristics, market capitalization, the market-book ratio, and equity volatility become relatively more significant. Our model captures much of the time variation in the aggregate failure rate. Since 1981, financially distressed stocks have delivered anomalously low returns. They have lower returns but much higher standard deviations, market betas, and loadings on value and small-cap risk factors than stocks with a low risk of failure. These patterns hold in all size quintiles but are particularly strong in smaller stocks. They are inconsistent with the conjecture that the value and size effects are compensation for the risk of financial distress.

Abstract: A very promising literature has been recently devoted to the modeling of ultra-high-frequency (UHF) data. Our first aim is to develop an empirical application of Autoregressive Conditional Duration GARCH models and the realized volatility to forecast future volatilities on irregularly spaced data. We also compare the out sample performances of ACD GARCH models with the realized volatility method. We propose a procedure to take into account the time deformation and show how to use these models for computing daily VaR.

Abstract: Rational herd behavior and informationally efficient security prices have long been considered to be mutually exclusive but for exceptional cases. In this paper we describe conditions on the underlying information structure that are necessary and sufficient for informational herding. Employing a standard sequential security trading model, we argue that people may be subject to herding if and only if there is sufficient amount of noise and, loosely, their information leads them to believe that extreme outcomes are more likely than moderate ones. We then show that herding has a significant effect on prices: prices can move substantially during herding and they become more volatile than if there were no herding. Furthermore, herding can be persistent and can affect the process of learning. We also characterize conditions for contrarian behavior. Our analysis suggests that herding (and contrarian behavior) may be more pervasive than was originally thought. Hence, the paper provides a new perspective on herding in financial markets with efficient prices.

Abstract: What factors determine how well consumers make their actual choices with regard to financial products? This paper empirically evaluates two different choices consumers make when buying deferred annuities. One choice concerns the type of insurance policy, the other concerns the choice of insurance provider. For both choices we will analyse what factors explain the quality of the choice made. In particular, we will investigate the role of financial advice in the decision making process. By combining Dutch consumer survey data and data on quotations by Dutch life insurance companies, we obtain the following results. First, respondents who buy their policy directly from an insurer attain a significantly better match between their risk preferences and the type of policy chosen than respondents who purchase their policy through an insurance broker. Second, respondents who buy their policy through an insurance broker obtain a significantly lower pay-out than respondents who purchased their policy directly from an insurance company. These results raise doubts about the functioning of both the market for financial advice and the market for life insurances.

Abstract: Since the underlying of the weather derivatives is not a traded asset, these contracts cannot be evaluated by the traditional financial theory. Cao and Wei (2004) price them by using the consumption-based asset pricing model of Lucas (1978) and by assuming different values for the constant relative risk aversion coefficient. Instead of taking this coefficient as given, we suggest in this paper to estimate it by using the consumption data and the quotations of one of the most transacted weather contracts which is the New York weather futures on the Chicago Mercantile Exchange (CME). We will apply the well-known generalized method of moments (GMM) introduced by Hansen (1982) to estimate it as well as the simulated method of moments (SMM) attributed to Lee and Ingram (1991) and Duffie and Singleton (1993). This last method is studied since we think that it can give satisfactory results in the case of the weather derivatives for which the prices are simulated. We find that the estimated coefficient from the SMM approach must have improbably high values in order to have the calculated weather futures prices matching the observations. This finding is in accordance with the results of the prior works which have shown the empirical failures of the consumption-based asset pricing model.