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The purpose of this research is to determine whether the trading of equity index futures contracts on the South African Futures Exchange (SAFEX) results in an increase in the volatility of the underlying spot indices. Since equity index futures contracts were first listed in the USA in 1975, various studies have been undertaken to determine whether the volatility of shares in the underlying indices increases as a result of the trading of such futures contracts. These studies have lead to the development of two schools of thought: [a] Trading activity in equity index futures contracts leads to an increase in the volatility of index shares. [b] Trading activity in equity index futures contracts does not lead to an increase in the volatility of the index shares and could in fact lead to greater stability in equity markets. Although some evidence of higher volatility in expiration periods was found, volatility in the expiration periods was not consistently higher than in the corresponding pre‐expiration period.

In the build-up of an investment decision, the existence of both active and passive investment vehicles triggers a puzzle for investors. Indeed the confrontation between active and index replication equity funds in terms of risk-adjusted performance and alpha generation has been a bone of contention since the inception of these investment structures. Accordingly, the objective of this chapter is to distinctly underscore whether an investor should be concerned in choosing between active and diverse passive investment structures.

The survivorship bias-free dataset consists of 776 equity funds which are domiciled either in America or Europe, and are likewise exposed to the equity markets of the same regions. In addition to geographical segmentation, equity funds are also categorised by structure and management type, specifically actively managed mutual funds, index mutual funds and passive exchange traded funds (‘ETFs’). This classification leads to the analysis of monthly net asset values (‘NAV’) of 12 distinct equally weighted portfolios, with a time horizon ranging from January 2004 to December 2014. Accordingly, the risk-adjusted performance of the equally weighted equity funds’ portfolios is examined by the application of mainstream single-factor and multi-factor asset pricing models namely Capital Asset Pricing Model (Fama, 1968; Fama & Macbeth, 1973; Lintner, 1965; Mossin, 1966; Sharpe, 1964; Treynor, 1961), Fama French Three-Factor (1993) and Carhart Four-Factor (1997).

Solely examination of monthly NAVs for a 10-year horizon suggests that active management is equivalent to index replication in terms of risk-adjusted returns. This prompts investors to be neutral gross of fees, yet when considering all transaction costs it is a distinct story. The relatively heftier fees charged by active management, predominantly initial fees, appear to revoke any outperformance in excess of the market portfolio, ensuing in a Fool’s Errand Hypothesis. Moreover, both active and index mutual funds’ performance may indeed be lower if financial advisors or distributors of equity funds charge additional fees over and above the fund houses’ expense ratios, putting the latter investment vehicles at a significant handicap vis-à-vis passive low-cost ETFs. This chapter urges investors to concentrate on expense ratios and other transaction costs rather than solely past returns, by accessing the cheapest available vehicle for each investment objective. Put simply, the general investor should retreat from portfolio management and instead access the market portfolio using low-cost index replication structures via an execution-only approach.

The battle among actively managed and index replication equity funds in terms of risk-adjusted performance and alpha generation has been a grey area since the inception of mutual funds. The interest in the subject constantly lightens up as fresh instruments infiltrate financial markets. Indeed the mutual fund puzzle (Gruber, 1996) together with the enhanced growth of ETFs has again rejuvenated the active versus passive debate, making it worth a detailed analysis especially for the benefit of investors who confront a dilemma in choosing between the two management styles.

The purpose of this paper is to study performance and market timing ability of equity real estate investment trusts (REITs).

The authors use classical regression‐based framework and their multi‐index, multifactor, and conditional extensions to jointly detect asset selectivity and market timing ability of equity REITs and their subcategories. These results are then validated by a nonparametric test.

It is found that equity REITs in aggregate have some housing market timing ability. Various equity REIT subcategories perform differently: office REITs can discover underpriced properties, while retail, industrial, and office REITs have poor timing ability. Nonparametric tests confirm that equity REITs do not have ability to predict real estate market movements.

Research in REIT performance evaluation is still limited to the asset selectivity aspect. This paper intends to fill this gap by providing empirical evidence of market timing ability of equity REITs using an array of parametric and nonparametric methods.

The commodity and equity derivatives have a close resemblance between them in trade practices and mechanisms, which makes it easy for the investors to combine these two assets classes for building up their portfolio. The diversification of investment among asset classes builds some relation between them. The integration of market within a country is necessary to bring in a smooth and balanced economic growth. Thus, the purpose of this paper is to examine the spillover between the equity and commodity futures markets which will be helpful not only for the investors but also for the policy makers, producers and the regulators.

To examine the spillover between the equity and commodity market, the major benchmarking indices of these markets, namely COMDEX of MCX, Dhaanya of NCDEX and NIFTY 50 of NSE, were chosen. NIFTY 50 index was chosen as representative of equity market due to its composition of most active constituent stocks than any other broad market index of Indian stock market. As the commodity market indices are not been traded, their constituent commodities were taken for the study. Thus, 11 MCX-COMDEX constituents such as Gold, Silver, Copper, Zinc, Aluminum, Nickel, Lead, Crude oil, Natural gas, Kapaskhali and Mentha oil and eight NCDEX-Dhaanya constituents such as Castor seed, Chana, Cotton seed oilcake, Jeera, Mustard seed, Refined soy oil, Turmeric and Wheat futures prices were taken against the NIFTY 50 futures prices with daily trading data for ten years starting from January 1, 2006 till December 31, 2015 to analyze their spillover effect. The return series data were used to test the spillover between equity and commodity futures market as it gives the crux of investors’ diversification through the Vector Autoregression (VAR) model and verified with Impulse Response Function by testing the null hypothesis, H₀, that there is no return spillover between the equity and commodity futures market.

The investors move from equity to commodity when there is a threat in equity market and vice versa, thereby diversify their risk for those commodities which are vulnerable to global and domestic pressures in the economy. Investigating the spillover between equity and commodity market gives an insight of market integration effect. A nation can achieve its economic growth easily when its markets are integrated.

The commodity indices are still notional indices in the market; therefore, individual constituent commodities of commodities indices were considered with the benchmarking equity futures index, which is one of the limitations of the study.

The integration of market within a country is necessary to bring in a smooth and balanced economic growth.

Most of the past studies dealt only with few commodities and equities and not with the broad-based benchmarking indices. This paves way for enquiry into the commodity and equity markets integration with the major constituent commodities traded in the economy. Hence, this paper looks into the presence of spillover between the equity and commodity markets. The VAR model is verified with the impulse response function which explains the reaction of any dynamic system in response to a pulse change in another. The impulse response function is presented graphically for easy and better understanding.

There is ample evidence that financial market development leads to economic growth. If improving labor rights can be shown to positively influence equity markets, then that, in turn, will lead to economic growth. The finance literature has examined the impact of a broader metric, namely, the Economic Freedom Index, on equity returns worldwide, and the evidence is mixed. This study focuses on one dimension of economic freedom: labor rights. Specifically, the study analyzes the impact of labor rights on national equity market indexes using the Labor Rights Index developed by the Organization for Economic Co-operation and Development (OECD) and the Fraser Institute (FI). Using panel regression analysis for 49 countries (for the OECD Index) and 76 countries (for the FI Index) over the period 1985–2014, the study finds that changes in labor rights have a statistically significant positive impact on equity returns, after controlling for business-cycle effects and time-fixed effects. The study also finds significant differences in the labor–rights–equity returns relationship between developed and less developed economies.

Sport teams not only compete with other teams for the ultimate prize but also for a share of customer mind space. For winning fan loyalty and resultant economic success, management of sport teams need to focus on team-branding, and thus, developing and measuring a team’s brand equity becomes essential, which is the core purpose of this paper.

Current work builds upon previous efforts to develop a reliable and, more importantly, a parsimonious sport team brand-equity (STBE) index, as opposed to the usual multi-dimensional reflective scales, too complicated and not of much use to practitioners.

The authors propose that the STBE index having eight indicators is enough to capture the full domain of the concept and provide a snapshot about the ability of a team’s administration to create strong emotional bonds with its fans.

Apart from demographics of the respondents, an important drawback is that the STBE index is from the perspective of television or online viewers and not those watching live in stadiums. This work contributes to extant sports brand equity literature by proposing a simpler scale made of casual variables, as opposed to reflective scales running into large number of similar items, a first of its kind in this domain. The authors also are able to forward the growing call for developing more of such scales through this effort.

Not only can the present scale be easily used by sport-marketers and researchers, it will be especially useful for marketing managers who want to associate their brands with sport teams, as it affects performance of their own brand.

The work represents a novel effort for developing a team-based brand equity and, to the authors’ knowledge, has not been attempted in this literature before.

The purpose of this paper is to investigate the extent to which Chinese equity investors can benefit from diversifying their portfolio into Shariah-compliant (Islamic) indices. It examines three Islamic stock indices (FTSE Shariah China price index, MSCI China Islamic IMI price index and the DJ Islamic Greater China price index) and ten sectoral indices in Shanghai Stock Exchange as a sample.

The multivariate GARCH dynamic conditional correlations (MGARCH-DCC) is deployed to estimate the time-varying linkages of returns of the selected indices, covering approximately eight years daily data starting from 28 August 2009 to 29 September 2017.

In general, in terms of volatility, the results indicate that all Islamic Indices are less volatile than the conventional indices. From the correlation analysis, the results imply that Chinese conventional equity investors would benefit from Islamic stock indices, especially when they include DJ Islamic Greater China in their portfolio.

The findings of this paper may have several significant implications for the Chinese equity investors and fund managers for better understanding about co-movements of the Chinese conventional sectoral indices with the Shariah-compliant stock indices with the purpose of gaining higher risk-adjusted returns through portfolio diversification.

The aim of this study is to measure portfolio diversification benefits of the Turkey-based equity investors into top trading partner countries. Portfolio diversification benefits are analyzed from the viewpoint of two types of investors in Turkey: conventional equities investors and Islamic equity investors.

In order to evaluate the time-varying correlations of the trading partner country's stock index returns with the Turkish stock index returns, the multivariate-generalized autoregressive conditional heteroskedasticity–dynamic conditional correlation (GARCH-DCC) is applied based on daily data covering 13 years' period between January 22, 2008 and January 22, 2021.

The results revealed that the US stock indices provide the most diversified benefit for both conventional and Islamic Turkey-based equity investors. In general, Islamic indices exhibit relatively lower correlation with trading partners than conventional indices. Turkey and Russia are recorded as the most volatile indices.

The diversification potential in trading partners for Turkey-based Islamic equity investors has not been studied yet. This study is to fill in this gap in the literature and to give fruitful insights to both conventional and Islamic investors.

This study aims to compare the diversification risk of the crypto portfolio with those of equity portfolios. For this purpose, the hypothetical index was constructed with 20 cryptocurrencies that hold the highest market capitalization in the Coin Market Cap database, named as the Crypto-Index 20.

The portfolio diversification techniques were used to identify risk linked with the six largest European equity indexes and compared with the Crypto-Index 20. Indexes were considered as an independent portfolio while analysis was completed separately for each of them. Data concerning stock prices and their trade volume were collected from the Thomson Reuters Eikon database while crypto prices and their trade volume from the Coin Market Cap database. The diversification risk of the stock indexes was measured separately for each portfolio with the same risk techniques and the same methodological process.

Research results indicate that Crypto-Index 20 on average was 76 times riskier than FTSE 100, 55 times riskier than FTSE MIB, 44 times riskier than IBEX 35, 10 times riskier than CAC 40 and 9 times riskier than DAX and MDAX. Crypto-Index 20 comprises a stronger positive correlation and is exposed to higher volatility than six selected European equity indexes.

This research provides practical implications for the investors on the diversification benefits and risks attached to the cryptocurrencies portfolio by comparing it with the traditional equity portfolios. From a policy perspective, regulators might obtain information on the risk properties involved into cryptocurrencies and the possibility of creating an optimal portfolio.

This study aims to investigate the co-volatility patterns between cryptocurrencies and conventional asset classes across global markets, encompassing 26 global indices ranging from equities, commodities, real estate, currencies and bonds.

It used a multivariate factor stochastic volatility model to capture the dynamic changes in covariance and volatility correlation, thus offering empirical insights into the co-volatility dynamics. Unlike conventional research on price or return transmission, this study directly models the time-varying covariance and volatility correlation.

The study uncovers pronounced co-volatility movements between cryptocurrencies and specific indices such as GSCI Energy, GSCI Commodity, Dow Jones 1 month forward and U.S. 10-year TIPS. Notably, these movements surpass those observed with precious metals, industrial metals and global equity indices across various regions. Interestingly, except for Japan, equity indices in the USA, Canada, Australia, France, Germany, India and China exhibit a co-volatility movement. These findings challenge the existing literature on cryptocurrencies and provide intriguing evidence regarding their co-volatility dynamics.

This study significantly contributes to applying asset pricing models in cryptocurrency markets by explicitly addressing price and volatility dynamics aspects. Using the stochastic volatility model, the research adding methodological contribution effectively captures cryptocurrency volatility's inherent fluctuations and time-varying nature. While previous literature has primarily focused on bitcoin and a few other cryptocurrencies, this study examines the stochastic volatility properties of a wide range of cryptocurrency indices. Furthermore, the study expands its scope by examining global asset markets, allowing for a comprehensive analysis considering the broader context in which cryptocurrencies operate. It bridges the gap between traditional asset pricing models and the unique characteristics of cryptocurrencies.