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The purpose of this paper is to test the market linkage and the strength of the linkage between the identity‐preserved (IP) non‐genetically modified organism (non‐GMO) and non‐IP conventional soybean futures markets at the Tokyo Grain Exchange (TGE) when effects from structural breaks are considered.

The Johansen method is used for testing the market linkage and the law of one price (LOP) test is performed to find out the strength of the linkage. The Bai‐Perron test is conducted on the price series to identify the structural breaks. After the breaks are statistically determined by the Bai‐Perron test the Johansen tests are conducted for every break period.

Market linkage exists between the non‐GMO and conventional soybean futures markets but the LOP test suggests that the two markets are not fully linked and the relative price of the two soybeans is not constant. The breaks identified in the study affected the market linkage; the price relationship is lost during the break periods.

The results of this study help explain the value of other new markets where the product traded is a close substitute for an existing market.

This is the first study to apply the market integration theory to an IP market. The TGE non‐GMO soybean contract is the first market price series with sufficient information to appropriately model a price integration linkage for an IP market. The result is valuable in the future when more markets for IP commodities are developed.

The purpose of this study is to examine the linkages between Australian house prices and stock prices under the Toda and Yamamoto test framework. Specifically, it investigated whether there is a capital switching effect between house prices and stock prices.

This study examined the linkages between house prices and stock prices under the Toda and Yamamoto test framework. To accommodate the impact of the global financial crisis (GFC), a sub-period analysis was undertaken. To assess the impact of investor structure, the tests were also performed for small cap stocks and large cap stocks individually.

The empirical results reveal a negative lead–lag relationship between house prices and stock prices in Australia, suggesting the existence of capital switching activities between housing and stocks. The impact of the GFC on the lead–lag relationship between house prices and stock prices is also documented. Before the crisis, a causality transmission was running from house prices to stock prices, whilst stock prices appeared to lead house prices after the crisis. The capital switching activities between housing and stocks are more evident for small cap stocks.

This study is the first to examine the linkages between house prices and stock prices under the Toda and Yamamoto test framework. This is the first study to explore the impacts of the GFC on the lead–lag relationship between the two asset prices under the capital switching framework. This study is also the first to provide empirical evidence regarding the existence of capital switching activities between housing and stocks. In addition, the impact of investor structure on the interrelationship between the two asset prices is examined for the first time under the capital switching framework.

This study explores the price linkage between the Chinese commodity futures market and other dominant futures markets, and examines the forces behind the price linkages. The contribution by the trading hour innovations in the United States (or United Kingdom) market to the overnight price changes in the Chinese market is larger in scale than the contribution by the daytime information from the Chinese market to the overnight returns of the corresponding US (or UK) market. Several futures have significant interactions of the domestic and foreign factors in the price linkages while the Chinese domestic factors explain better the global market price linkage in some futures (aluminum, gold, and corn), demonstrating the leading role of the Chinese futures markets in these world markets.

The purpose of this paper is on developing and implementing a model which provides a fuller and more comprehensive reflection of the interaction of house prices at the suburb level.

The authors examine how changes in housing prices evolve across space within the suburban context. In doing so, the authors developed a model which allows for suburbs to be connected both because of their geographic proximity but also by non-spatial factors, such as similarities in socioeconomic or demographic characteristics. This approach is applied to modelling home price dynamics in Melbourne, Australia, from 2007 to 2018.

The authors found that including both spatial and non-spatial linkages between suburbs provides a better representation of the data. It also provides new insights into the way spatial shocks are transmitted around the city and how suburban housing markets are clustered.

The authors have generalized the widely used SAR model and advocated building a spatial weights matrix that allows for both geographic and socioeconomic linkages between suburbs within the HOSAR framework. As the authors outlined, such a model can be easily estimated using maximum likelihood. The benefits of such a model are that it yields an improved fit to the data and more accurate spatial spill-over estimates.

The purpose of this paper is to investigate the continuing justification for linking the prices of European gas to those oil products.

The paper uses an analytic‐deductive approach supported by relevant analysis of data over a period of two decades.

Statistical analysis of the end‐uses of gas and oil products over the past two decades reveal that, with few exceptions, use of oil is increasing confined to transportation while gas is a utility fuel used to generate heat and power. The ability of end‐users to substitute oil products for gas – the principal justification for price linkage – has substantially diminished over the past two decades, and this trend is continuing. The implication of these findings is that nearly 20 percent of Europe's energy supplies are priced inappropriately with reference to a fuel which has little relevance to the supply/demand dynamics of natural gas. At levels of oil prices seen since 2003, this has significantly negative consequences for consumers. An important qualification to these findings is that in markets where prices have been set by gas to gas competition for many years – the UK and North America – a long‐term “natural correlation” between gas and oil prices has been observed.

The paper raises the important question facing European gas stakeholders and asks whether to remain with oil‐linked prices or move to spot market prices created at hubs in North West Europe.

The aim of this paper is to examine the dynamic relationships between Middle East stock markets.

Daily data from the Egyptian (CMA) and Israeli Tel Aviv Stock Exchange (TASE‐100) stock indices are considered. The paper employs a Bivariate cointegration GARCH(1,1) model to explain price discovery and lead‐lag relationships for the period July 1997 – August 2007.

Empirical results confirm that the Egyptian market plays a price discovery role, implying that CMA prices contain useful information about TASE‐100 prices. CMA market is more informationally efficient than TASE‐100 market. Further, CMA index reflects new information faster than TASE‐100 index.

Future research should examine the dynamic relationships between Middle East stock markets using intraday (high frequency) data and recent dynamic (long memory) methods.

The findings are helpful to financial managers and traders dealing with Middle East stock markets.

The contribution of this paper is to provide evidence on the stock market dynamics and financial linkages between two Middle East emerging markets using recent daily data and a modern econometric model. To the best of the author's knowledge, no previous study has tested the dynamic relationships between daily prices of CMA and TASE‐100.

Prior hospitality studies have reviewed review trustworthiness and perceived price as predictors of restaurant selection. However, the impacts of these two factors may vary by sales promotion and customer types. This study aims to determine whether sales promotions and customer type are the key elements that facilitate behavioral intentions by moderating the linkage between perceived price and behavioral intentions as well as the linkage between online review trustworthiness and behavioral intentions.

Analysis of the responses of 533 individuals familiar with the Michelin Guide for restaurants in Seoul provided evidence supporting a sales promotion theory wherein promotions signal benefits in consumers’ minds.

The findings show that when perceived price is positive and the trustworthiness of online reviews is high, repeat customers prefer mixed coupons to price discounts. Notably, the results indicate that when the trustworthiness of online reviews is high, first-time customers also prefer mixed coupons to price discounts. Furthermore, the findings suggest that negative evaluations of perceived price increase the impact of mixed coupons by signaling to first-time customers that given restaurants’ offerings provide monetary benefits regardless of their intentions to revisit said restaurants.

The study findings provide insights that should help managers better understand various levels of promotion. Managers can design their pricing strategies to strengthen customers’ motivations to visit their restaurants – the very thing customers often seek in sales promotions.

This study provides indisputable evidence for a sales promotion theory, wherein promotions signal benefits in consumers’ minds; however, it also shows that first-time and repeat customers do not respond equally to sales promotions.

This study aims to revisit the stock price–volume relations, providing new evidence from the emerging market of Qatar. In particular, three main issues are examined using both aggregate market- and sector-level data. First, the return–volume relation and whether or not this relation is asymmetric. Second, the common characteristics of return volatility; and third, the nature of the relation between trading volume and return volatility.

The study uses the OLS and VAR modeling approaches to examine the contemporaneous and dynamic (causal) relations between index returns and trading volume, respectively, while an EGARCH-X(1,1) model is used to analyze the volatility–volume relation. The data set comprises daily index observations and the corresponding trading volumes for the entire market and the individual seven sectors of the Qatar Exchange (i.e. banks and financial services, consumer goods and services, industrials, insurance, real estate, telecommunications and transportation).

The empirical analysis reports evidence of a positive contemporaneous return–volume relation in all sectors barring transportation and insurance. This relation appears to be asymmetric for all sectors. For the market and almost all sectors, there is no significant causality between returns and volume. By and large, these findings lend support for the implications of the mixture of distributions hypothesis (MDH). Lastly, the information content of lagged volume seems to have an important role in predicting the future dynamics of return volatility in all sectors, with the industrials being the exception.

The findings provide important implications for portfolio managers and investors, given that the volume of transactions is generally found to be informative about the price movement of sector indices. Specifically, tracking the behavior of trading volume over time can give a broad portrayal of the future direction of market prices and volatility of equity, thereby enriching the information set available to investors for decision-making.

Based on both market- and sector-level data from the emerging stock market of Qatar, this study attempts to fill an important void in the literature by examining the return–volume and volatility–volume linkages.

The purpose of this paper is to assess price linkages and patterns of transmission among producer and consumer markets for apple in Slovenia.

Non-linear error correction models are applied. Non-linearities are allowed by means of threshold and multivariate local linear regression estimation techniques. Monthly prices over the period 2000-2011 are used in the empirical application.

Both techniques provide evidence of non-linearities in price adjustments. Findings suggest that producer and consumer prices tend to increase rather than decrease. Results also indicate that parametric threshold approaches may have difficulties in adequately representing price behavior dynamics.

The main contribution of this work to the literature relies on the fact that this is the first attempt to assess vertical price transmission in the apple sector in Central and Eastern European Country markets. Further, it is the first attempt to use multivariate local linear regression techniques in this context.

This study aims to examine the spillover effects of the mean and volatility between oil prices and stock indices of six Gulf Cooperation Council (GCC) countries (UAE, Kuwait, Saudi Arabia, Qatar, Oman and Bahrain).

Over the period 2008–2019, a bivariate VARMA-GARCH-ADCC model was combined with the maximal overlap discrete wavelet transform technique filter to shed light on a wide range of possible spillover effects in the mean and variances of level prices at various time horizons.

The authors find that the spillover effects between oil prices and the GCC stock markets are time-varying and spread across various time horizons. Besides, oil prices and stock market indices are directly impacted by their own shocks and variations and indirectly influenced by other price volatilities and wavelet scales. The linkages in volatility spillovers between oil prices and the GCC stock markets occur in the short-term, midterm and long-term horizons. More specifically, the results also show that the asymmetric estimates are statistically significant for the associations between oil prices and each stock market in the GCC countries. This implies that negative shocks play a more vital role than positive shocks in driving the dynamic condition correlations between oil and stock markets under study.

The significant interrelatedness between oil prices and each stock market in the GCC countries has important implications for investors, portfolio managers, and other market participants. They can use the findings of this research to create the best oil-GCC stock portfolios and predict more precisely the volatility spillover patterns in constructing their hedging strategies.

In several ways, this study differs from previous research. First, while previous empirical studies of the dynamic link between oil prices and stock markets have focused primarily on developed or emerging markets, the focus of this is on six GCC countries. Second, the linkage between oil prices and stock markets is typically studied at the original data level in the time domain in relevant literature, while frequency information is overlooked. Therefore, the current study examines this relationship from a multiscale perspective. Third, in this paper, to capture a wide range of possible spillover effects in the mean and variance of level prices at multiple wavelet scales, the authors use a VARMA-GARCH-ADCC model in conjunction with wavelet multiresolution analysis. Additionally, this article also applies wavelet hedge ratio and wavelet hedge portfolio analysis at various time horizons.