Effect of Price Change Alert on Perceptions of Hotel Attribute-based Room Pricing (ABP) versus Traditional Room Pricing (TRP)

Aside from marketing information on traditional room rates, hotels and online travel agents (OTAs) are trying a new pricing technique based on the attributes of guestrooms. This research investigates how attribute-based room pricing (ABP) differs from traditional room pricing (TRP) in influencing consumer reactions when consumers receive a price change alert before (vs. after) sales. Through a series of experiments, we found that TRP and ABP result in similar alert attitude, brand attitude, and visit intention for presale price change alert. However, ABP leads to more favorable results for postsale price change alert. We examined the underlying mechanism and found that perceived fairness mediates the effect of pricing strategy on brand attitude, price alert attitude, and visit intention for postsale alert only. This research provides hotel managers and OTA marketers with guidance on when to send either type of price change message to consumers.     

Unbiased estimation of expected return using CAPM

Estimation of expected return is required for many financial decisions. For example, an estimate for cost of capital is required for capital budgeting and cost of equity estimates are needed for performance evaluation based on measures such as EVA. Estimates for expected return are often based on the Capital Asset Pricing Model (CAPM), which states that expected excess return (expected return minus the risk-free rate) is equal to the asset's sensitivity to the world market portfolio (β) times the risk premium on the “world market portfolio” (the market risk premium). Since the world market portfolio, by definition, contains all assets in the world, it is not observable. As a result, an estimate for expected return is commonly obtained by taking an estimate for β based on some index (as a proxy for the world market portfolio) and an estimate for the market risk premium based on a potentially different index and multiplying them together. In this paper, it is shown that this results in a biased estimate for expected return. This is undesirable since biased estimates lead to misallocation of funds and biased performance measures. It is also shown in this paper that the straightforward procedure suggested by Fama and MacBeth [J. Financ. Econ. 1 (1974) 43] results in an unbiased estimate for expected return. Further from the analysis done, it follows that, for an unbiased estimate, it does not matter what proxy is used, as long as it is used correctly an unbiased estimate for expected return results.     

Density estimation in the uniform deconvolution model

We consider the problem of estimating a probability density function based on data that are corrupted by noise from a uniform distribution. The (nonparametric) maximum likelihood estimator for the corresponding distribution function is well defined. For the density function this is not the case. We study two nonparametric estimators for this density. The first is a type of kernel density estimate based on the empirical distribution function of the observable data. The second is a kernel density estimate based on the MLE of the distribution function of the unobservable (uncorrupted) data.     

中国郑州棉花期货市场的国际定价功能研究

本文借助计量经济学的分析方法,对郑州商品交易所、纽约期货交易所期棉价格与国内棉花现货价格这三者的关系进行了研究,并测算了郑州商品交易所与纽约期货交易所在价格发现中的贡献份额。研究结果表明,三者之间存在协整关系,纽约期货市场在国际棉花定价体系中占有主导地位,而导致郑州棉花期货市场国际定价功能弱化的原因则是国内棉花期货市场与现货市场缺乏有机联系。     

Demarketing as a differentiation strategy

Demarketing discourages consumers from buying. This paper shows that demarketing can be a profitable alternative when differentiation through product improvements is not cost effective. The impact of differentiating demarketing on profit, market share, consumers, and total welfare is investigated.This research began while Hess was visiting MIT's Sloan School of Management and was finished while visiting University of Haifa; he thanks both for their support.     

Nonparametric estimation of distribution functions

Summary Using Silverman and Young’s (1987) idea of rescaling a rescaled smoothed empirical distribution function is defined and investigated when the smoothing parameter depends on the data. The rescaled smoothed estimator is shown to be often better than the commonly used ordinary smoothed estimator.     

A Pricing and Hedging Comparison of Parametric and Nonparametric Approaches for American Index Options

This article investigates the extent to which options on theAustralian Stock Price Index can be explained by parametricand nonparametric option pricing techniques. In particular,comparisons are made of out-of-sample option pricing performanceand hedging performance. The dataset differs from many of thoseused previously in the empirical options pricing literaturein that it consists of American options. In addition, a broaderspectrum of techniques are considered: a spline-based nonparametrictechnique is considered in addition to the standard kernel techniques,while the performance of a Heston stochastic volatility modelis also considered. Although some evidence is found of superiorperformance by nonparametric techniques for in-sample pricing,the parametric methods exhibit a markedly better ability toexplain future prices and show superior hedging performance.     

A semiparametric GARCH model for foreign exchange volatility

A semiparametric extension of the GJR model (Glosten et al., 1993. Journal of Finance 48, 1779–1801) is proposed for the volatility of foreign exchange returns. Under reasonable assumptions, asymptotic normal distributions are established for the estimators of the model, corroborated by simulation results. When applied to the Deutsche Mark/US Dollar and the Deutsche Mark/British Pound daily returns data, the semiparametric volatility model outperforms the GJR model as well as the more commonly used GARCH(1,1) model in terms of goodness-of-fit, and forecasting, by correcting overgrowth in volatility.     

基于遗传算法的核函数参数优化

核主分量分析是一种输入输出特征非线性变换技术。选择最优或接近最优的非线性变换核函数参数,使类的可分性测度最大,是KPCA应用于特征提取的关键。本文采用高斯变异遗传算法作优化技术,实现了KPCA和GA的集成,适合核函数参数的优化选择。仿真表明,该技术可行、有效。     

论电信业互联互通规制创新

互联互通是一个世界性的监管难题,但又是电信业改革的基础。如果没有互联互通,新兴的运营商就难以进入市场,电信业的竞争发展就无从谈起。从我国实际情况出发,有效成分定价原则和整体价格上限法的综合运用不但能提高企业效率,降低成本,促进行业竞争,而且能避免掠夺性定价行为,价格战等行为的发生,它是我国现阶段可以考虑的一种较优的接入定价选择。