Neyman–Pearson Lemma for Fuzzy Hypotheses Testing with Vague Data

In hypotheses testing, such as other statistical problems, we may confront imprecise concepts. One case is a situation in which both hypotheses and observations are imprecise. This paper tries to develop a new approach for testing fuzzy hypothesis when the available data are fuzzy, too. First, some definitions are provided, such as: fuzzy sample space, fuzzy-valued random sample, and fuzzy-valued random variable. Then, the problem of fuzzy hypothesis testing with vague data is formulated. Finally, we state and prove a generalized Neyman–Pearson Lemma for such problem. The proposed approach is illustrated by some numerical examples.     

A Variance Ratio Test of the Behaviour of Some FTSE Equity Indices Using Ranks and Signs

This study utilises tests based on ranks and signs suggested by Wright (2000) in addition to the traditional variance ratio test to examine the behaviour of some UK Financial Times Stock Exchange (FTSE) stock indices. The results suggest that the null hypothesis of martingale difference behaviour of the index returns series examined in the study is rejected. The use of the nonparametric based variance ratio tests provide stronger evidence against the martingale difference behaviour than the conventional variance ratio tests, under conditions of both homoskedasticity and heteroskedasticity for the examined series. Moreover, the application of Wrights variance ratio tests in a rolling window framework, indicates that the results for the FTSE returns are consistent neither with a linear AR assumption nor with the white noise hypothesis.We are grateful to Jonathan Wright for programming help. We also thank the editor and an anonymous referee for their constructive comments. All errors and omissions remain ours.     

p2: a random effects model with covariates for directed graphs

A random effects model is proposed for the analysis of binary dyadic data that represent a social network or directed graph, using nodal and/or dyadic attributes as covariates. The network structure is reflected by modeling the dependence between the relations to and from the same actor or node. Parameter estimates are proposed that are based on an iterated generalized least-squares procedure. An application is presented to a data set on friendship relations between American lawyers.     

Testing the Random Walk Behavior and Efficiency of the Gulf Stock Markets

Inferences drawn from tests of market efficiency are rendered imprecise in the presence of infrequent trading. As the observed index in thinly traded markets may not represent the true underlying index value, there is a systematic bias toward rejecting the efficient market hypothesis. For the three emerging Gulf markets examined in this paper, correction for infrequent trading significantly alters the results of market efficiency and random walk tests. The Beveridge–Nelson (1981) decomposition of index returns is done to estimate the underlying index.     

SECULAR MEAN REVERSION AND LONG‐RUN PREDICTABILITY OF THE STOCK MARKET

The empirical financial literature reports evidence of mean reversion in stock prices and the absence of out‐of‐sample return predictability over horizons shorter than 10 years. Anecdotal evidence suggests the presence of mean reversion in stock prices and return predictability over horizons longer than 10 years, but thus far, there is no empirical evidence confirming such anecdotal evidence. The goal of this paper is to fill this gap in the literature. Specifically, using 141 years of data, this paper begins by performing formal tests of the random walk hypothesis in the prices of the real S&P Composite Index over increasing time horizons of up to 40 years. Although our results cannot support the conventional wisdom that the stock market is safer for long‐term investors, our findings speak in favor of the mean reversion hypothesis. In particular, we find statistically significant in‐sample evidence that past 15‐17 year returns are able to predict the future 15‐17 year returns. This finding is robust to the choice of data source, deflator, and test statistic. The paper continues by investigating the out‐of‐sample performance of long‐horizon return forecasting based on the mean‐reverting model. These latter tests demonstrate that the forecast accuracy provided by the mean‐reverting model is statistically significantly better than the forecast accuracy provided by the naive historical‐mean model. Moreover, we show that the predictive ability of the mean‐reverting model is economically significant and translates into substantial performance gains.     

The right speed and its value

Slow investments cause substantial revenue losses, yet acceleration increases costs. This tradeoff implies that an optimal investment speed usually exists; it is faster the higher a firm's intrinsic speed capability. We hypothesize that it is a firm's intrinsic speed capability, rather than its speed relative to industry competitors per se, that boosts firm value. Using data on oil and gas facilities (1996–2005), we find that intrinsic speed capabilities augment firm value in a varied way: their value is larger with better corporate governance, lower cost of capital, and higher ability to draw value from R&D investment. Our work elevates the discussion of speed from a project‐level consideration to a firm‐level competitive advantage issue and raises the need to further explore its strategic value. Copyright © 2013 John Wiley & Sons, Ltd.     

On Families of Distributions with Shape Parameters

Univariate continuous distributions are one of the fundamental components on which statistical modelling, ancient and modern, frequentist and Bayesian, multi‐dimensional and complex, is based. In this article, I review and compare some of the main general techniques for providing families of typically unimodal distributions on with one or two, or possibly even three, shape parameters, controlling skewness and/or tailweight, in addition to their all‐important location and scale parameters. One important and useful family is comprised of the ‘skew‐symmetric’ distributions brought to prominence by Azzalini. As these are covered in considerable detail elsewhere in the literature, I focus more on their complements and competitors. Principal among these are distributions formed by transforming random variables, by what I call ‘transformation of scale’—including two‐piece distributions—and by probability integral transformation of non‐uniform random variables. I also treat briefly the issues of multi‐variate extension, of distributions on subsets of and of distributions on the circle. The review and comparison is not comprehensive, necessarily being selective and therefore somewhat personal. © 2014 The Authors. International Statistical Review © 2014 International Statistical Institute     

Revisiting Cash Endowment and House Money Effects in an Experimental Auction of a Novel Agri‐food Product in the Philippines

This study explores the effect of varying cash endowments on bidding behavior in auction experiments conducted in a developing country. Our results suggest that cash endowment levels can have different effects on bidding behavior under second price auction and random nth price auction. In contrast to past studies conducted in developed countries, we generally do not see the presence of positive house money effect in our results. If behavior varies significantly as the cash endowment is varied, then care must be taken when designing auction experiments or when comparing results to other experimental results and theoretical predictions.     

防内外部窃听的多播物理层安全算法

针对无线多播系统同时存在内、外部窃听者的复杂情况,提出随机化干扰的物理层多播安全传输算法。该算法基于收发天线构成信道的代数空间进行设计：一方面在内部窃听者的信道代数空间方向上不发送信息,另一方面在合法用户信道的正交方向上引入随机干扰信号。这样直接使得内部窃听者接收的信号受到能量削减的同时,非合法用户受到随机化干扰,最终实现了物理层多播信息的安全传输。理论分析和仿真结果表明,算法可同时保证系统内、外部窃听者极高的误码率,从而无法获取信息。