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In recent years, the world food market has undergone an accelerated process of concentration and consolidation. These intensive processes increase the competitive advantage of operating activities on the global market and are the result of numerous changes in the period of new economy. What is the meaning of brand management and how is it dealt with in practice? What is the importance of positioning in the light of brand image and identity? Which are the ways to measure the brand strength with the aid of the brand potential index (BPI) and to identify the characteristics (key drivers) which have the greatest influence on brand strength? All these are questions for which this paper seeks to provide answers.

The answers to the research questions were gained using the GFK target positioning research with which a brand analysis of high‐volume products was carried out in the light of its key characteristics: brand as a product, opportunities and risks involved in the brand on the market, competition analysis, analysis of brand's personality, target group analysis (market segmentation), and marketing cluster analysis.

Based on the case study, the paper demonstrates the applicability of the research in the process of brand evaluation, determining the positioning and communication guidelines on the example of food products brands.

The paper is important in identifying the sources of brand value.

The use of weather derivatives is impaired with a basis risk which diminishes the hedging effectiveness and hinders the distribution of these risk management instruments in the agricultural sector. A frequently suggested approach to reduce the basis risk is the use of mixed indices composed of several weather variables. The purpose of this paper is to compare the hedging effectiveness of a simple temperature‐based and a simple precipitation‐based weather derivative with that of a derivative based on a mixed index of two weather variables.

The basis of this comparison are empirical yield time series of the winter wheat production of 32 farms located in central Germany, as well as daily temperature and precipitation data collected by selected weather stations over several years. Insurance is structured as an option on an accumulated weather index and priced by index‐value simulation. In addition, the bootstrapping method is used to improve statistical reliability. The hedging effectiveness is measured non‐parametrically regarding the relative reduction of the standard deviation of winter wheat revenues caused by using weather derivatives.

The results reveal that mixed index‐based weather derivatives have a significantly higher potential to reduce the risk of winter wheat revenues than simple index‐based weather derivatives. However, using mixed index‐based weather derivatives does not lead to a significantly higher hedging effectiveness than the simultaneous use of several simple index‐based weather derivatives. Moreover, simple index‐based weather derivatives may more easily raise the interest of other industries which could serve as potential trading partners for the agricultural sector.

The authors analyzed the hedging effectiveness of weather derivatives based on simple and mixed indices with regard to the production of winter wheat in Central Germany. To confirm that the present results are generalizable, further research is required for other types of production apart from winter wheat cultivation and with respect to other regions besides Germany.

The focus and results of the present study are very relevant for farmers as well as for potential providers of weather derivatives. The results reconfirm that weather derivative providers should better offer different weather derivatives based on a simple index than complex derivatives that are based on a mixed index.

To the best of the authors' knowledge, this paper is the first that provides a comparative impact analysis of simple and mixed index‐based weather derivatives conducted for real individual farms with regard to their hedging effectiveness.

This paper aims to expand foreign investors' understanding of potential return enhancement and risk diversification advantages offered by equity market of Pakistan through comparing its performance to performances in other markets and investigating what matters for investing in Pakistan's market.

Comparative analysis of Pakistan Stock Exchange is performed using data for 22 developed and 22 emerging markets over the period 1993–2019. Cross-sectional analysis is performed using data for 130 non-financial firms from Pakistan and Carhart (1997) and Fama and French (2015) models are applied. The role of liquidity with five-factor model is analyzed using turnover rate and Amihud (2002) illiquidity cost as liquidity measures.

Pakistan's equity offers substantial diversification benefits if added to developed market portfolios. However, observed large returns come together with inverted premia for most traditional factors indicating that investors may want to invest preferably in big stocks with low book-to-market and momentum. Finally, global investors can invest in high yielding stocks with low liquidity risk owing to positive connection between liquidity and returns.

This study will provide investment model for foreign investors to enhance their portfolio returns. Policy makers in Pakistan must identify regulatory steps to facilitate foreign investments.

To the best of the authors' knowledge, this is the first study which identifies efficiency gains offered by Pakistan's equity for global investors.

Index by subjects, compiled by K.G.B. Bakewell covering the following journals: Facilities Volumes 8‐17; Journal of Property Investment & Finance Volumes 8‐17; Property Management Volumes 8‐17; Structural Survey Volumes 8‐17.

Compiled by K.G.B. Bakewell covering the following journals published by MCB University Press: Facilities Volumes 8‐18; Journal of Property Investment & Finance Volumes 8‐18; Property Management Volumes 8‐18; Structural Survey Volumes 8‐18.

Compiled by K.G.B. Bakewell covering the following journals published by MCB University Press: Facilities Volumes 8‐17; Journal of Property Investment & Finance Volumes 8‐17; Property Management Volumes 8‐17; Structural Survey Volumes 8‐17.

Index by subjects, compiled by K.G.B. Bakewell covering the following journals: Facilities Volumes 8‐18; Journal of Property Investment & Finance Volumes 8‐18; Property Management Volumes 8‐18; Structural Survey Volumes 8‐18.

Compiled by K.G.B. Bakewell covering the following journals published by MCB University Press: Facilities Volumes 8‐18; Journal of Property Investment & Finance Volumes 8‐18; Property Management Volumes 8‐18; Structural Survey Volumes 8‐18.

Compiled by K.G.B. Bakewell covering the following journals published by MCB University Press: Facilities Volumes 8‐17; Journal of Property Investment & Finance Volumes 8‐17; Property Management Volumes 8‐17; Structural Survey Volumes 8‐17.

Compiled by K.G.B. Bakewell covering the following journals published by MCB University Press: Facilities Volumes 8‐18; Journal of Property Investment & Finance Volumes 8‐18; Property Management Volumes 8‐18; Structural Survey Volumes 8‐18.