Search results

On completion of this case study, students will be able to describe a circular economy and cross-marketing; discuss the common strategies under the circular economy paradigm; describe the benefits and risks of cross-marketing brand alliances and their strategic implications; examine the role of growth strategy in driving the growth of an organization; classify what constitutes the elements of a strategy for HelpUsGreen LLP; and discuss measures to be considered while selecting a partner for a cross-marketing brand alliance.

HelpUsGreen LLP was a start-up founded by Karan Rastogi in 2019, which manufactured incense sticks using the circular economy model. After deflecting from his earlier partner in 2019 and after approximately two years of effort, Rastogi expanded his business of making incense sticks using a circular economy model. Students through this case can step into the shoes of Rastogi, who, as of 9 January 2023, was in Kanpur and was in an urgent need to replicate a similar circular economy model in different cities. With over 21,060 tonnes of temple flower waste recycled, 210 tonnes of chemical pesticides offset and 100% natural products delivered, multiple opportunities emerged at the cross-marketing brand alliance and new product segment levels. Rastogi entered into several cross-marketing brand alliance arrangements and tasted success. Rastogi believed that choosing the right partner for cross-marketing was key to successful cooperation. Considering cross-marketing as a way forward, he urgently needed to develop a strategy that aligned with his mission to take HelpUsGreen LLP’s circular economy model to other parts of the country. Students should take into consideration the data regarding the processes at HelpUsGreen LLP that helped Rastogi restart from scratch and make assumptions to decide the growth route for entering different cities.

This case can be used as an introductory case in a post-graduate class on growth strategy for a business based on the circular economy model, as it delineates the challenges faced by a firm while creating a circular economy and managing its growth phase. The case can also be used in an entrepreneurship management course and a strategic management course. This case allows students to learn about the circular economy and challenges faced by the company during the growth phase. Thus, the case can be used for covering multiple perspectives related to growth strategy (e.g. the application of Ansoff matrix), for defining what is cross-marketing brand alliance and discussing what measures need to be considered while selecting a partner for cross-marketing brand alliance, and it is ideal for teaching the elements of strategy.

Teaching notes are available for educators only.

CSS 11: Strategy.

This study examines the bid/ask spread and its components in the KOSPI200 options market under the framework of the cross-market model, which utilizes the order flow information of both KOSPI200 futures and options markets. We also compare the results by the single-market model (MRR model; Madhavan et al., 1997) and by the cross-market model (Ryu (2011)’s extension). This comparison suggests that the cross-market approach can mitigate the underestimation of the permanent spread component of OTM options and the overestimation of the component of ITM options, which are often detected when we directly apply the single market model into the KOSPI200 options market where the ITM options are relatively illiquid while the OTM options are extremely liquid. We also find that the effect of the order flow information of the futures market on the option spread and its permanent spread component will vary depending on the option moneyness and the intraday time period. This implies that the order flow of the futures market has more significant effects if the degree of informed trading is relatively high.

This paper aims to examine the behaviour, both contemporaneous and causal, of stock and bond markets across four major international countries.

The authors generate volatility and correlations using the realised volatility approach and implement a general vector autoregression approach to examine causality and spillovers.

While results confirm that same asset-cross country return correlations and spillovers increase over time, the same in not true with variance and covariance behaviour. Volatility spillovers across countries exhibit a substantial amount of time variation; however, there is no evidence of trending in any direction. Equally, cross asset – same country correlations exhibit both negative and positive values. Further, the authors report an inverse relation between same asset – cross country return correlations and cross asset – same country return correlations, i.e. the stock return correlation across countries increases at the same time the stock and bond return correlation within each country declines. Moreover, the results show that the stock and bond return correlations exhibit commonality across countries. The results also demonstrate that stock returns lead movement in bond returns, while US stock and bond returns have predictive power other country stock and bond returns. In terms of the markets analysed, Japan exhibits a distinct nature compared with those of Germany, the UK and USA.

The results presented here provide a detailed characterisation of how assets interact both with each other and cross-countries and should be of interest to portfolio managers, policy-makers and those interested in modelling cross-market behaviour. Notably, the authors reveal key differences between the behaviour of stocks and bonds and across different countries.

The purpose of this paper is to investigate the dynamic relationship between Nigeria-US exchange rate (XR) and crude oil price (OILP) using daily data from 1 January 2001 to 31 December 2015.

The study uses alternative methods, including vector autoregressive-generalised autoregressive conditional heteroskedasticity (VAR-GARCH) within the framework of Baba-Engle-Kraft-Kroner model, constant conditional correlation (CCC)-GARCH and dynamic conditional correlation (DCC)-GARCH models.

The results from the VAR-GARCH model indicate unidirectional cross-market mean spillovers from oil market (OILM) to foreign exchange market (FXM). In addition, the results show a positive effect of OILP on XR, suggesting that an increase in OILP appreciates Nigerian currency relative to US dollar and a fall in OILP depreciates it. The authors find that the effects of cross-volatility spillovers between the OILM and FXM are bidirectional. The CCC results indicate positive correlations of returns of 16 per cent between the FXM and OILM. Finally, the DCCs results indicate positive correlations between the two markets since the fourth quarter of 2008 (the world financial crisis period) until the recent period of world oil glut and slow demand for crude oil.

Following the depreciation of the Nigerian currency vis-á-vis US dollar since the onset of the recent world oil glut and lower oil prices, Nigerian authorities should embark on subsidy reform, such as reduction in fuel subsidies. This may enable the release of fiscal resources that may be used to either rebuild fiscal space lost or finance investment in non-oil sectors in order to reduce overdependence on oil income. Lower fiscal revenues, coupled with the risk that crude oil maintains its low price for some time, imply that government should reduce its expenditure, and continue to draw on available accumulated funds from the excess crude account for some time until the real depreciation required for adjustment is achieved.

Studies on volatility spillovers between OILM and FXM are limited in the literature, particularly in Nigerian case. Moreover, the study employs different approaches for broader analysis. These alternative methods, a clear departure from the previous studies, provide comprehensive dynamic nature of the relationship between the FXM and OILM.

The outbreak of the coronavirus disease 2019 (COVID-19) pandemic is an unprecedented shock to the BRICS (Brazil, Russia, India, China, South Africa) economy and their financial markets have plummeted significantly due to it. This paper adds to the recent literature on contagion due to spillover by uniquely examining the presence of pairwise contagion or volatility transmissions in stock markets returns of India, Brazil, Russia, China and USA prior to and during COVID-19 pandemic period.

In this study, the generalised autoregressive conditional heteroskedasticity (GARCH) by Bollerslev (1986) under diagonal parameterization is used to estimate multivariate GARCH framework also known as BEKK (Baba EngleKraft and Kroner) model on stock market returns of BRIC nations and the US.

The empirical results show that the model captures the volatility spillovers and display statistical significance for own past mean and volatility with both short- and long-run persistence effects. Own volatility spillovers (Heatwave phenomenon) have been found to be highest for the US, China and Brazil compared to Russia and India. The coefficients indicate persistence of volatility for each country in terms of its own past errors. The highest and long-term spillover effect is found between US and Russia. The results recommend that Russia is least vulnerable to outside shocks. Finally after examining the pairwise results, it is suggested that the BRIC countries stock indices have exhibited volatility spillover due to the COVID-19 pandemic.

The study may be extended to include other emerging market economies under a dynamic framework.

Researchers and policymakers may draw useful insights on cross-market interdependencies regarding the spillovers in BRIC countries' stock markets. It also helps design international portfolio diversification strategies and in constructing optimal portfolios during COVID and in a post-COVID world.

COVID-19 has been an improbable event in the history of the world which can have a large impact on the financial economies across the emerging countries. This event can be deemed to be informative enough to measure the co-movements of the equity markets amongst cross-country return series, which has not been investigated so far for BRIC nations.

Investor sentiment (optimism or pessimism) may influence investors to follow others (herding) while taking their investment decisions. Herding may result in bubbles and crashes in the financial markets. The purpose of the study is to examine the presence of herding and the effects of investor sentiment on herding in China and Pakistan.

The investor sentiment is captured by five variables (trading volume, advance/decline ratio, weighted price-to-earnings ratio, relative strength index and interest rates) and a sentiment index developed through principal component analysis (PCA). The study uses daily prices of 2,184 firms from China and 568 firms from Pakistan for the period 2005 to 2018.

The study finds that herding prevails in China while reverse herding prevails in Pakistan. Interestingly, as investors become optimistic, herding in China and reverse herding in Pakistan decrease. This indicates that herding and reverse herding are greater during pessimistic periods. Further, the increase in herding in one market reduces herding in the other market. Moreover, optimistic sentiment in the Chinese market increases herding in the Pakistani market but the reverse is not true.

Considering the greater global financial liberalization, and better opportunities for emotion sharing, this study has important implications for regulators and investors. Market participants need to understand the prevalent irrational behavior before trading in the markets.

Since individual proxies may depict different picture of the relationship between sentiment and herding therefore the study also develops a sentiment index through PCA and incorporates this index in the analysis. Further, this study examines cross-country effects of herding and investor sentiment.

This paper aims to introduce a model-based stress-testing methodology for Islamic finance products. The importance of stress testing was indeed clearly underlined by the adverse developments in the global finance industry. One of the key takeaways was the need to strengthen the coverage of the capital framework. Cognisant of this fact, Basel III encapsulates provisions to enhance the financial sector’s ability to withstand shocks arising from possible stress events, thereby reducing adverse spillovers into the real economy. Similarly, the Islamic Financial Services Board requires Islamic financial institutions to run stress tests as part of capital planning.

The authors perform thorough backtests on Islamic and conventional portfolios under widely used risk models, which are characterised by an underlying conditional volatility framework and distribution, to identify the most suitable risk model specification. Associated with an appropriate initial shock and estimation window size, the paper also conducts a model-based stress test to examine whether the stress losses estimated by the selected models compare favourably to the historical shocks.

The results suggest that the model-based framework, when combined with an appropriate risk model and distribution, can successfully reproduce past stress periods. The conditional empirical risk model is the most effective one in both long and short portfolio cases – particularly when combined with a long-enough estimation window. The relative performance of normal vs heavy-tailed distributions and symmetric vs asymmetric risk models, on the other hand, is highly dependent on whether the portfolio is long or short. Finally, the authors find that the Islamic portfolio is generally associated with lower historical stress losses as compared to the conventional portfolio.

The model-based framework eliminates some of the key problems associated with traditional scenario-based approaches and is easily adaptable to Islamic finance.

This study aims to investigate the connectivity among four principal implied volatility (“fear”) markets in the USA.

The empirical analysis relies on daily data (“fear gauge indices”) for the period 2017–2023 and the quantile vector autoregressive (QVAR) approach that allows connectivity (that is, the network topology of interrelated markets) to be quantile-dependent and time-varying.

Extreme increases in fear are transmitted with higher intensity relative to extreme decreases in it. The implied volatility markets for gold and for stocks are the main risk connectors in the network and also net transmitters of shocks to the implied volatility markets for crude oil and for the euro-dollar exchange rate. Major events such as the COVID-19 pandemic and the war in Ukraine increase connectivity; this increase, however, is likely to be more pronounced at the median than the extremes of the joint distribution of the four fear indices.

This is the first work that uses the QVAR approach to implied volatility markets. The empirical results provide useful insights into how fear spreads across stock and commodities markets, something that is important for risk management, option pricing and forecasting.

This study aims to examine the existence of herding and the impact of economic and political factors in the Shariah-compliant stocks of Gulf Cooperation Council markets, namely, Bahrain, Kuwait, Oman, Qatar, Saudi Arabia and United Arab Emirates. This study also seeks to explore the existence of herding under market stress and cross-stocks herding between Shariah-compliant and conventional stocks.

The data period is from 1 January 2016 to 31 December 2021. Panel data regression and panel quantile regression are used to examine herding.

The results show that herding tends to exist in Shariah stocks before the pandemic but is more pronounced in both types of stocks during the pandemic. The empirical evidence shows that economic factors are significant to herding before and during pandemic, whereas the political factors are only shown to be significant before COVID-19. Conventional stocks are correlated to the herding of Shariah stocks but the Shariah stocks have no significant impact on the herding of conventional stocks. Panel quantile regression shows that herding exists in extreme conditions but not all markets perform similarly.

The results of this study imply that the political factor can lead investors to herd. This political factor represents information that is used by investors to herd, consistent with the prediction of information-based theory of herding. Hence, policymakers and regulators need to be wary of any change in the political factors as they may cause movement in stock prices that deviate from fundamental value because of investor herding.

The purpose of this study was to examine purchasing intentions in online sports ticketing websites. Based on previous research related to business-to-consumer (B2C) e-commerce, this study developed a conceptual model to test the effect of perceived risk, trust and the Technology Acceptance Model (TAM) on purchase intentions in online secondary ticket websites. College students (N = 251) from the northeastern region of the United States were chosen as the sample. Structural Equation Modeling (SEM) was used to investigate the proposed relationships among four major components (i.e. perceived risk, trust, TAM and behavioural intention). The results showed that there were positive effects of key TAM constructs (i.e. perceived usefulness and ease of use) and trust on purchasing intention, but perceived risk was not a significant indicator of purchase intention.