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Builds on the work of Damodaran (1993) and Brisley and Theobald (19967) on measuring the speed with which stock markets convert information into price changes by using a simpler model of the price adjustment coefficient and applying it to 1988‐1966 data from the Hong Kong, US and Japanese markets and the Morgan Stanley Capital International indexes. Explains the methodology and presents the detailed results, which show that the Hong Kong adjustment is similar to the US and Japan for systematic and for all information; although the range of adjustment speeds depends on the sector and composition of the indexes. Makes many comparisons between the three markets and suggests that this method of describing market efficiency could provide a more consistent and objective ranking of worlds capital markets.

The purpose of the paper is to investigate the causal relationships and speed of adjustment of stock prices to changes in macroeconomic information (MEI) in Ghana from 1996 to 2018 using monthly data. The paper seeks to conduct the investigation at individual MEI level rather than the composite MEI.

Quantitative approach was used in this paper. Monthly data span of 1996–2018 was used. The delay and half-life technique was used to determine the speed with which the information resulting from the changes in the macroeconomic are evident in the stock price. Thereafter, Toda–Yamamoto Granger no-causality approach was used to examine the causal relationship amongst variables.

The paper revealed that although the market adjustment to MEI has improved, the speed is till slow. The exchange rate exhibited the slowest speed in respect of the market reaction while the market reaction to money supply was the fastest. Toda–Yamamoto Granger no-causality estimation also revealed a bi-directional causality between MEI (gross domestic product, interest rate and money supply) and stock price and uni-directional relationship flowing from MEI (the exchange rate and foreign direct investment) to stock price. The paper also found no causality between inflation and stock price.

The findings although revealed improved level of market efficiency in comparison with the earlier data, the speed of adjustment is still undesirable. Rigorous approach should be adopted for the implementation of major reforms such as alternative market so as to increase the number of share listing and to increase the scope of investors' participation to enhancing trading volume and marketability and ultimately speed up information diffusion.

The practical implication of the low level of information processing rate of Ghana Stock Exchange (averagely more than a month) is that astute investors and market analysts could employ MEI to outperform the market prior to their infusion onto the stock market.

This study is one of the few studies in the Ghanaian literature that has extended the investigation of the speed of adjustment beyond composite or aggregate macroeconomic level estimation to estimation at individual variable level. This contribution is very relevant since each macroeconomic variable has unique characteristics and require specific policy framework, it is important to consider the speed of adjustment from the perspective of each of the individual variables.

While price studies such as Jawadi et al. generally focus on the relationships between oil and stock markets through the study of oil price on stock markets, this paper takes a different perspective to the linkages between oil and stock markets. This study sets out to investigate the efficiency hypothesis for oil markets while testing for whether oil price dynamics depend on stock market fluctuations or not.

Using nonlinear econometric modeling, this paper investigates the oil market adjustment dynamics for four developed and emerging countries: France, the USA, Mexico and the Philippines. Our findings show strong evidence of significant linkages between oil and stock markets for all the countries under consideration.

As in Jawadi et al. who focus on stock price dynamics regarding oil price, the findings of this present paper, which focuses more on the oil industry, also point to an asymmetrical mean‐reversion between oil and stock markets that occurs in a nonlinear manner. They reject the informational efficiency hypothesis for oil markets. Indeed, while the previous literature often highlights the stock markets' dependence on the oil industry, this study contributes to the literature by concluding in favor of significant feedback from stock to oil markets, which is not compatible with the efficiency principle according to Fama.

This paper develops a new nonlinear framework that should improve the investigation of oil‐stock market linkages. Future research could check the forecasting properties of this model to forecast the future dynamics of oil prices.

This paper adds to the literature by suggesting that it is not only oil shocks that affect stock markets, but that the latter also have a strong nonlinear impact on oil markets, reducing the diversification benefits of oil‐stock portfolios.

To develop a methodology for faculty salary adjustment through market adjustment based on market demand for business PhDs and merit adjustment based on faculty members' performance levels in the areas of teaching, research and service.

The methodology is composed of two models: one for market adjustment and the other for merit adjustment. The market adjustment is handled through goal programming and the merit adjustment through data envelopment analysis (DEA).

The approach when applied to a sample of faculty salaries shows that the adjusted salary of each faculty member is higher than his/her current actual salary, and each faculty member in the particular discipline deserves a salary increase that reflects market demand and merit factors.

The DEA model used in this research does not impose restrictions on the weights. Realistically, one may impose bounds on the weights and exclude unreasonable solutions from DEA analysis and also set multiple goals instead of the single goal used in the goal programming model.

Based on a goal programming model that addresses the market demand and a DEA model that addresses the merit‐based performances, this methodology may be implemented as a solution procedure for restructuring faculty salaries.

The novelty in this approach is that DEA is being used as a benchmarking technique for merit adjustment of faculty salaries. In that sense, this research work may be the first, where benchmarking has been used in “faculty salary equity adjustment.”

Recent studies have reflected the need to investigate the development of market orientation in the transitional economies under conditions of economic decline and great systemic change. However, the relationship between the level of market orientation and firm’s competitiveness in a turbulent environment has not been analysed. Personal interviews conducted with 221 managers of Ukrainian enterprises provided data to investigate the level of the development of market orientation and competitiveness. Managers’ attitudes toward marketing are used to create a typology of marketing approaches in the Ukraine. Competitiveness is measured as a multi‐dimensional concept using variables of organisational adaptability to the changes in business environment, advantages across the marketing mix and performance indicators as the dimensions. The results of the study suggest that the level of a firm’s competitiveness in the turbulent environment of a transitional economy is associated with the level of the development of market orientation.

Shanghai is the most important economic centre in China. It also has the nation's largest modern office market in terms of floorspace and investment values. However, as with office markets in other cities and countries, the Shanghai market displays rental volatility. This paper aims to examine this issue.

Rental volatility is examined by econometrically constructing a long‐run equilibrium relationship between rent and underlying demand and supply side factors. In order to establish the validity of this model, it is tested for the presence of a cointegrating vector. From this a short‐run dynamic adjustment model is constructed. This is an error correction mechanism that links the short‐ and long‐run models. The impact of office vacancies, foreign direct investment, and changes in the real interest rate on the office market are explicitly considered.

The results indicate that both demand (as represented by gross domestic product (GDP)) and supply (stock) are significant determinants of rents. Space demand is found to be both price and income elastic. In the short‐run model the error correction term is significant and correctly signed. In comparison to other office markets, the Shanghai market adjusts rather slowly. Foreign direct investment is found to have a positive impact on long‐run rents and the vacancy rate is found to impact on short‐term rental adjustment.

The Shanghai office market is the most important in China. However, it has displayed significant rental volatility. This paper is the first to examine explicitly the rental adjustment process in this office market. The results suggest a market that is performing as expected by economic theory but which nevertheless displays relatively slow adjustment to market imbalances.

We highlight two mechanisms of limited attention for expert information intermediaries, i.e., analysts, and the effects of such limited attention on the market price discovery process. We approach analysts' limited attention from the perspective of day-to-day arrival of information and processing of tasks. We examine the attention-limiting role of competing tasks (number of earnings announcements and forecasts for portfolio firms) and distracting events (number of earnings announcements for non-portfolio firms) in analysts' forecast accuracy and the effects of such, on the subsequent price discovery process. Our results show that competing tasks worsen analysts' forecast accuracy, and competing task induced limited attention delays the market price adjustment process. On the other hand, distracting events can improve analysts' forecast accuracy and accelerate market price adjustments when such events relate to analysts' portfolio firms through industry memberships.

The role of money and monetary policy of the central bank in pursuing macroeconomic stability has significantly changed over the period since the end of World War II. Globalization, liberalization, integration, and transition processes generally shaped the crucial milestones of the macroeconomic development and substantial features of economic policy and its framework in Europe. Policy-driven changes together with variety of exogenous shocks significantly affected the key features of macroeconomic environment on the European continent that fashioned the framework and design of monetary policies.

This chapter examines the key basis of the central bank’s monetary policy on its way to pursue and preserve the internal and external stability of the purchasing power of money. Substantial elements of the monetary policy like objectives and strategies are not only generally introduced but also critically discussed according to their accuracy, suitability, and reliability in the changing macroeconomic conditions. Brief overview of the Eurozone common monetary policy milestones and the past Eastern bloc countries’ experience with a variety of exchange rate regimes provides interesting empirical evidence on origins and implications of vital changes in the monetary policy conduction in Europe and the Eurozone.

This paper aims to study how primary and secondary market investors react to intangibles information disclosed in Italian IPOs. Previous literature on intangibles information disclosure as a determinant of IPO underpricing has reported inconsistent results; moreover, an area that has remained unexplored is to what extent different categories of market investors react to such information disclosure.

Based on a sample of firms listed on the Italian Stock Exchange, the authors use factor analysis to uncover the most relevant intangible assets disclosed in IPO prospectuses; this information is then included in a series of regressions which read into the reaction of primary and secondary market investors by means of price variations.

Primary market investors are found to be more sensitive to information regarding the company’s attitude towards its human capital and to that describing its innovation capacity in terms of IT and R&D investment. Secondary market investors are more sensitive to strategic alliances, research and development and future plans.

The findings can be generalized, but the empirical evidence would be more relevant if tested in different geographical contexts (i.e. Europe and/or the USA).

The empirical results could help firms be more selective in their disclosure, thus possibly soothing management’s concerns regarding an overly extensive, and therefore risky, dissemination of non-financial information and avoiding them to incur unnecessary costs.

Being aware of how the stock market reacts to the information disclosed is crucial in determining new regulations and accounting standards.

The authors introduce an unbiased categorization of intangibles variables that supplants the multiple classifications proposed in the literature, and the authors set apart the reaction of primary and secondary market IPO investors to the intangible information disclosure.