Do Islamic Stock Returns Hedge Against Inflation? A Wavelet Approach

This article makes an initial attempt to study the hedging effectiveness of Islamic stock returns against inflation for different investment horizons. We applied the wavelet analysis to measure the cross-correlations between the time series as a function of time-scales using data ranging from 2007 to early 2015. The main results tend to indicate the following: First, that for investment horizons not exceeding 3 years, the FTSE Bursa Malaysia Emas Shariah Index constituent returns may potentially hedge against inflation. Additionally, the hedging ability of stock returns was absent from 2008 to 2009 following the global financial crisis. Finally, a buy-and-hold strategy exceeding 3 years may erode investments. The results are plausible and have strong policy implications.     

Forecasting turning points in tourism growth

Tourism demand exhibits growth cycles, and it is important to forecast turning points in these growth cycles to minimise risks to destination management. This study estimates logistic models of Hong Kong tourism demand, which are then used to generate both short- and long-term forecasts of tourism growth. The performance of the models is evaluated using the quadratic probability score and hit rates. The results show that the ways in which this information is used are crucial to the models’ predictive power. Further, we investigate whether combining probability forecasts can improve predictive accuracy, and find that combination approaches, especially nonlinear combination approaches, are sensitive to the quality of forecasts in the pool. In addition, model screening can improve forecasting performance.     

Variations in farm consumption and their relationship to income: an empirical investigation of Illinois farm households

Empirical tests of household consumption have yielded mixed results regarding the validity of the life cycle/permanent income (LCPI) hypothesis. A significant problem with such studies is the difficulty in finding sufficient micro-level data on household expenditures. By using the recent rich quantity of such data in the Farm Business Farm Management (FBFM) data for Illinois farms from 1995 to 2009, the study reported here for farm households should provide more consistent results regarding the LCPI hypothesis. Applying an empirical model based on the LCPI hypothesis, this article identifies the determinants of farm consumption and the relationship to income. This study provides evidence that current income changes are not significant in explaining the consumption changes of farm households, thus supporting the LCPI hypothesis for farm households.     

Advertising to the masses: the effects of crowding on the attention to place-based advertising

Advertising situated in environments where people congregate or pass through on their way to somewhere else benefit from being placed in such high traffic areas. However, these strategically placed ads also suffer from conditions of human crowding that prevents them from being noticed and processed. We undertake a study of place-based advertising in a shopping mall using facial recognition software to determine the effect of human density on the attention directed to advertising. We find that as human density increases, attention to advertising decreases, but only to a point where it begins to increase again. Our research also finds that human density plays a moderating role on the motivation to process advertising.     

Does tourism-led growth hypothesis exist in Mauritius? Evidence from disaggregated tourism markets

We use the data of total tourism market and 10 major tourism markets in Mauritius to test the validity of tourism-led growth hypothesis in the country for the period 1980–2011. Using causality techniques, we confirm the hypothesis for the total tourism market. However, tourism-led growth exists in only 6 of the 10 markets. We conclude that not all tourism markets are contributing substantially to Mauritius’ economy.     

Celebrity endorsement in tourism: Attention,emotional arousal and familiarity

Celebrity endorsement in tourism is utilised by global marketing practitioners to attract tourists to visit destinations. Despite this, studies are yet to assess the efficacy of two specific types of celebrity endorsement, a celebrity from the host country (host celebrity) vs. a celebrity from the country-of-origin (origin celebrity). Utilising the match-up hypothesis, this research applied a quasi-experimental design, consisting of a mixed method approach, which combined eye-tracking and self-report data. Convergent results across three studies demonstrate that an origin celebrity elicits a higher intention to visit, mediated by the emotional arousal evoked from the endorsement. Eye-tracking analysis demonstrated that an origin celebrity elicits a higher degree of visual attention and emotional arousal when the advertised scenery is familiar. However, this promotion effect disappears in unfamiliar scenery. This research contributes to an evolving debate on celebrity endorsement in tourism, revealing the psychological and physiological mechanisms underpinning the effectiveness of destination marketing campaigns.     

一种混合多边缘型LDPC码密度进化算法

在二进制输入加性高斯白噪声信道下，研究了基于多边缘型低密度奇偶校验码（Multi-edge Low Density Parity Check，MET-LDPC）的密度进化算法。针对高斯近似算法在前期迭代中的不准确问题，提出了一种改进算法。在分析MET-LDPC码的密度进化的基础上，将全密度进化与高斯近似算法结合，通过设置切换限制条件，弥补早期迭代的不准确，提高编码阈值估计的准确性。仿真结果表明,与MET-LDPC全密度进化算法相比，所提算法可以有效提高编码阈值估计的准确性，对LDPC编码的设计有一定的参考价值。     

Forecasting dynamic return distributions based on ordered binary choice

We present a simple approach to the forecasting of conditional probability distributions of asset returns. We work with a parsimonious specification of ordered binary choice regressions that imposes a connection on sign predictability across different quantiles. The model forecasts the future conditional probability distributions of returns quite precisely when using a past indicator and a past volatility proxy as predictors. The direct benefits of the model are revealed in an empirical application to the 29 most liquid U.S. stocks. The forecast probability distribution is translated to significant economic gains in a simple trading strategy. Our approach can also be useful in many other applications in which conditional distribution forecasts are desired.