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Article
Publication date: 25 September 2020

Guilherme Cardoso, Karem Ribeiro and Luciano Carvalho

Risk management has been crucial to investors and regulators for pursuing market diversification opportunities and developing strategies to ensure market stability. This study…

Abstract

Purpose

Risk management has been crucial to investors and regulators for pursuing market diversification opportunities and developing strategies to ensure market stability. This study examines the dependence structures of volatility, related to co-movements and macroeconomic effects, among Latin American stock markets and the risk–return spectrum benefits in the Latin American market using time-varying returns and volatility forecasts within a multivariate structure.

Design/methodology/approach

The sample comprised the largest stock markets in Latin America during the period from January 2000 to December 2017 and copulas and multivariate models were applied.

Findings

The results indicated that the copula with the best fit for modeling the dependence structure of the markets was symmetric Joe-Clayton with time-varying parameters. The dependence volatility structure was higher in the positive (upper tail) than in the negative (lower tail) returns, which may indicate that the Latin American markets had diversification benefits during downturns. Evidence of market coupling was found during times of the global crisis (subprime crisis) in Latin America. The presence of monetary and temporal effects over the dependence structures suggests that investors may obtain gains in a multivariate structure with copula distributions.

Originality/value

The findings will be of interest to researchers and practitioners for several reasons. First, this study contributes to the growing literature on the relationship between market dependence and volatility. Second, it indicates that the Latin American markets may present diversification advantages during downturns. Third, it informs the influence of macroeconomic effects on Latin American markets. The models that included the nonnormal and asymmetric characteristics of the financial market yielded better results in terms of less information loss and data adherence.

Details

Managerial Finance, vol. 47 no. 4
Type: Research Article
ISSN: 0307-4358

Keywords

Article
Publication date: 9 February 2010

Ning Rong and Stefan Trück

The purpose of this paper is to provide an analysis of the dependence structure between returns from real estate investment trusts (REITS) and a stock market index. Further, the…

3707

Abstract

Purpose

The purpose of this paper is to provide an analysis of the dependence structure between returns from real estate investment trusts (REITS) and a stock market index. Further, the aim is to illustrate how copula approaches can be applied to model the complex dependence structure between the assets and for risk measurement of a portfolio containing investments in REIT and equity indices.

Design/methodology/approach

The usually suggested multivariate normal or variance‐ covariance approach is applied, as well as various copula models in order to investigate the dependence structure between returns of Australian REITS and the Australian stock market. Different models including the Gaussian, Student t, Clayton and Gumbel copula are estimated and goodness‐of‐fit tests are conducted. For the return series, both the Gaussian and a non‐parametric estimate of the distribution is applied. A risk analysis is provided based on Monte Carlo simulations for the different models. The value‐at‐risk measure is also applied for quantification of the risks for a portfolio combining investments in real estate and stock markets.

Findings

The findings suggest that the multivariate normal model is not appropriate to measure the complex dependence structure between the returns of the two asset classes. Instead, a model using non‐parametric estimates for the return series in combination with a Student t copula is clearly more suitable. It further illustrates that the usually applied variance‐covariance approach leads to a significant underestimation of the actual risk for a portfolio consisting of investments in REITS and equity indices. The nature of risk is better captured by the suggested copula models.

Originality/value

To the authors', knowledge, this is one of the first studies to apply and test different copula models in real estate markets. Results help international investors and portfolio managers to deepen their understanding of the dependence structure between returns from real estate and equity markets. Additionally, the results should be helpful for implementation of a more adequate risk management for portfolios containing investments in both REITS and equity indices.

Details

Journal of Property Investment & Finance, vol. 28 no. 1
Type: Research Article
ISSN: 1463-578X

Keywords

Article
Publication date: 6 January 2021

Liukai Wang, Fu Jia, Lujie Chen, Qifa Xu and Xiao Lin

This study aims to explore the dependence structure among Chinese firms across the emerging 5G industry at different stages and to provide some strategic insights for market…

Abstract

Purpose

This study aims to explore the dependence structure among Chinese firms across the emerging 5G industry at different stages and to provide some strategic insights for market participants.

Design/methodology/approach

This study adopt macroeconomic fundamentals and the log-returns of 45 listed firms in the Chinese 5G industry to construct the weighted adjacency matrix by measuring the correlation parameters and then use the triangulated maximally filtered graph (TMFG) algorithm to construct the dependence network. It analyses the topological structure of the constructed networks to obtain the dependence characteristics for each firm in the whole industrial supply chain at different levels.

Findings

The empirical results provide a comprehensive and concise snapshot of the industrial structure, across the whole 5G industry at different levels, rather than just a “one-to-one” pattern. Specifically, the dependence characteristics of different firms are heterogeneous, and most firms are highly connected with partners in the whole industrial supply chain, whereas a few firms that are weakly connected. Those closely connected firms are usually in the midstream. In addition, compared with firms at different levels, downstream firms usually have closer dependencies and stronger influence capabilities.

Practical implications

Regulators not only should promote stability development for those firms most intensely connected with whole industry chain but also protect those firms with weak link in the whole industry chain. Investors should better understand the embedded ties among different firms to obtain effective market information and can select multiple firms with fewer connections as backup to conduct joint investment for risk mitigation. Mangers should give priority to the central players/firms in the whole industrial supply chain and establish the alliances with closely connected firms.

Originality/value

This study contributes to both the information system and operation management literature by constructing a new network method, Copula-TMFG, to capture the dependence structure among Chinese firms in 5G industry, empirically providing some strategic insights for 5G industry stakeholders, such as regulators, investors and managers.

Details

Industrial Management & Data Systems, vol. 121 no. 2
Type: Research Article
ISSN: 0263-5577

Keywords

Article
Publication date: 6 November 2023

Fatma Hariz, Taicir Mezghani and Mouna Boujelbène Abbes

This paper aims to analyze the dependence structure between the Green Sukuk Spread in Malaysia and uncertainty factors from January 1, 2017, to May 23, 2023, covering two main…

Abstract

Purpose

This paper aims to analyze the dependence structure between the Green Sukuk Spread in Malaysia and uncertainty factors from January 1, 2017, to May 23, 2023, covering two main periods: the pre-COVID-19 and the COVID-19 periods.

Design/methodology/approach

This study contributes to the current literature by explicitly modeling nonlinear dependencies using the Regular vine copula approach to capture asymmetric characteristics of the tail dependence distribution. This study used the Archimedean copula models: Student’s-t, Gumbel, Gaussian, Clayton, Frank and Joe, which exhibit different tail dependence structures.

Findings

The empirical results suggest that Green Sukuk and various uncertainty variables have the strongest co-dependency before and during the COVID-19 crisis. Due to external uncertainties (COVID-19), the results reveal that global factors, such as the Infect-EMV-index and the higher financial stress index, significantly affect the spread of Green Sukuk. Interestingly, in times of COVID-19, its dependence on Green Sukuk and the news sentiment seems to be a symmetric tail dependence with a Student’s-t copula. This result is relevant for hedging strategies, as investors can enhance the performance of their portfolio during the COVID-19 crash period.

Originality/value

This study contributes to a better understanding of the dependency structure between Green Sukuk and uncertainty factors. It is relevant for market participants seeking to improve their risk management for Green Sukuk.

Details

Journal of Islamic Accounting and Business Research, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1759-0817

Keywords

Article
Publication date: 15 August 2016

Mingyuan Guo and Xu Wang

– The purpose of this paper is to analyse the dependence structure in volatility between Shanghai and Shenzhen stock market in China based on high-frequency data.

Abstract

Purpose

The purpose of this paper is to analyse the dependence structure in volatility between Shanghai and Shenzhen stock market in China based on high-frequency data.

Design/methodology/approach

Using a multiplicative error model (hereinafter MEM) to describe the margins in volatility of China’s Shanghai and Shenzhen stock market, this study adopts static and time-varying copulas, respectively, estimated by maximum likelihood estimation method to describe the dependence structure in volatility between Shanghai and Shenzhen stock market in China.

Findings

This paper has identified the asymmetrical dependence structure in financial market volatility more precisely. Gumbel copula could best fit the empirical distribution as it can capture the relatively high dependence degree in the upper tail part corresponding to the period of volatile price fluctuation in both static and dynamic view.

Originality/value

Previous scholars mostly use GARCH model to describe the margins for price volatility. As MEM can efficiently characterize the volatility estimators, this paper uses MEM to model the margins for the market volatility directly based on high-frequency data, and proposes a proper distribution for the innovation in the marginal models. Then we could use copula-MEM other than copula-GARCH model to study on the dependence structure in volatility between Shanghai and Shenzhen stock market in China from a microstructural perspective.

Details

China Finance Review International, vol. 6 no. 3
Type: Research Article
ISSN: 2044-1398

Keywords

Book part
Publication date: 20 January 2014

Jean-Marie Codron, Magali Aubert, Zouhair Bouhsina, Alejandra Engler, Iciar Pavez and Pablo Villalobos

While organization theories acknowledge the influence of specific assets on dependence and increasingly represent the latter as a structure of mutual dependence (dependence of A…

Abstract

While organization theories acknowledge the influence of specific assets on dependence and increasingly represent the latter as a structure of mutual dependence (dependence of A on B and dependence of B on A), there is, to the best of our knowledge, no empirical test concerning the impact of specific assets on a structure of dependence. Our chapter aims to fill this gap. It is all the more original in that it considers a case study where dependence changes sides according to the characteristics of the transaction. We examine the dependence between Chilean exporters and European importers when trading fresh produce. Such dependence originates with the need for just-in-time coordination and compliance with a compelling demand in a context of high price uncertainty.

Using a unique dataset from international trade in fresh produce between Chile and the rest of the world, we justify the use of a concentration sales ratio as a proxy for dependence and test the influence of a variety of specific assets on the side of dependence by using both categorical and dimensional approaches. Original findings show that certain transaction attributes have a strong influence on the side of dependence. In particular, the higher the frequency and the level of specific assets such as volume, niche varieties, and joint sales with other products, in the transaction, the greater the likelihood of a higher ratio of dependence for the importer rather than the exporter. Conversely, in the event of low levels of specific assets and less frequent operations, dependence tends to be greater on the side of the exporter.

Details

International Marketing in Rapidly Changing Environments
Type: Book
ISBN: 978-1-78190-896-9

Keywords

Article
Publication date: 23 February 2022

Fatma Houidi and Siwar Ellouze

The purpose of this paper is to examine the dependence structure between the US conventional stock market and each Islamic and conventional stock market provided by the Dow Jones…

Abstract

Purpose

The purpose of this paper is to examine the dependence structure between the US conventional stock market and each Islamic and conventional stock market provided by the Dow Jones index, namely, for the UK, Canada, Europe, the emerging countries and Asia-Pacific. This paper considers both the bearish and bullish market phases of the 2008 global financial crisis to analyze the financial contagion.

Design/methodology/approach

The authors implement the copula framework-based GJR-GARCH-t model for the period from December 31, 2004 to September 30, 2016.

Findings

The marginal models suggest a strong persistence of volatility in all stock markets. The dependence structure for stock market pairs under-consideration is not all strictly symmetrical. Moreover, the Islamic stock markets witness the same behavior as their conventional counterparts. Finally, the resilience and the decoupling hypotheses are not all around upheld by the empirical proof.

Originality/value

The findings of this paper are very important for global investors in their risk management during extreme market events. As the Sukuk is considered as a safe haven during crisis episodes, the investors are invited to take it into account for further portfolio diversification.

Details

International Journal of Islamic and Middle Eastern Finance and Management, vol. 15 no. 6
Type: Research Article
ISSN: 1753-8394

Keywords

Content available
Article
Publication date: 19 July 2022

Kasra Pourkermani

This research provides some evidence by the vine copula approach, suggesting the significant and symmetric causal relation between subsections of Baltic Exchange and hence…

Abstract

Purpose

This research provides some evidence by the vine copula approach, suggesting the significant and symmetric causal relation between subsections of Baltic Exchange and hence concluding that investing in different indexes, which is currently a risk diversification system, is not a correct risk reduction strategy.

Design/methodology/approach

The daily observations of Baltic Capesize Index (BCI), Baltic Handysize Index (BHSI), Baltic Dirty Tanker Index (BDTI) and Baltic LNG Tanker Index (BLNG) over an eight-year period have been used. After collecting data, calculating the return and estimating the marginal distribution of return rates for each of the indexes applying asymmetric power generalized autoregressive conditional heteroskedasticity and autoregressive moving average (APGARCH-ARMA), and with the assumption of skew student's t-distribution, the dependence of Baltic indexes was modeled based on Vine-R structures.

Findings

A positive and symmetrical correlation was observed between the study groups. High and low tail dependence is observed between all four indexes. In other words, the sector business groups associated with each of these indexes react similarly to the extreme events of other groups. The BHSI has a pivotal role in examining the dependency structure of Baltic Exchange indexes. That is, in addition to the direct dependence of Baltic groups, the dependence of each group on the BHSI can transmit accidents and shocks to other groups.

Practical implications

Since the Baltic Exchange indexes are tradable, these findings have implications for portfolio design and hedging strategies for investors in shipping markets.

Originality/value

Vine copula structures proves the causal relationship between different Baltic Exchange indexes, which are derived from different types of markets.

Details

Maritime Business Review, vol. 8 no. 3
Type: Research Article
ISSN: 2397-3757

Keywords

Book part
Publication date: 31 December 2010

Rania Hentati and Jean-Luc Prigent

Purpose – In this chapter, copula theory is used to model dependence structure between hedge fund returns series.Methodology/approach – Goodness-of-fit tests, based on the…

Abstract

Purpose – In this chapter, copula theory is used to model dependence structure between hedge fund returns series.

Methodology/approach – Goodness-of-fit tests, based on the Kendall's functions, are applied as selection criteria of the “best” copula. After estimating the parametric copula that best fits the used data, we apply previous results to construct the cumulative distribution functions of the equally weighted portfolios.

Findings – The empirical validation shows that copula clearly allows better estimation of portfolio returns including hedge funds. The three studied portfolios reject the assumption of multivariate normality of returns. The chosen structure is often of Student type when only indices are considered. In the case of portfolios composed by only hedge funds, the dependence structure is of Franck type.

Originality/value of the chapter – Introducing goodness-of-fit bootstrap method to validate the choice of the best structure of dependence is relevant for hedge fund portfolios. Copulas would be introduced to provide better estimations of performance measures.

Details

Nonlinear Modeling of Economic and Financial Time-Series
Type: Book
ISBN: 978-0-85724-489-5

Keywords

Article
Publication date: 4 May 2020

A. Ford Ramsey, Sujit K. Ghosh and Barry K. Goodwin

Revenue insurance is the most popular form of insurance available in the US federal crop insurance program. The majority of crop revenue policies are sold with a harvest price…

Abstract

Purpose

Revenue insurance is the most popular form of insurance available in the US federal crop insurance program. The majority of crop revenue policies are sold with a harvest price replacement feature that pays out on lost crop yields at the maximum of a realized or projected harvest price. The authors introduce a novel actuarial and statistical approach to rate revenue insurance policies with exotic price coverage: the payout depends on an order statistic or average of prices. The authors examine the price implications of different dependence models and demonstrate the feasibility of policies of this type.

Design/methodology/approach

Hierarchical Archimedean copulas and vine copulas are used to model dependence between prices and yields and serial dependence of prices. The authors construct several synthetic exotic price coverage insurance policies and evaluate the impact of copula models on policies covering different types of risk.

Findings

The authors’ findings show that the price of exotic price coverage policies is sensitive to the choice of dependence model. Serial dependence varies across the growing season. It is possible to accurately price exotic coverage policies and we suggest these add-ons as a possible avenue for developing private crop insurance markets.

Originality/value

The authors apply hierarchical Archimedean copulas and vine copulas that allow for flexibility in the modeling of multivariate dependence. Unlike previous research, which has primarily considered dependence across space, the form of exotic price coverage requires modeling serial dependence in relative prices. Results are important for this segment of the agricultural insurance market: one of the main areas that insurers can develop private products around the federal program.

Details

Agricultural Finance Review, vol. 80 no. 5
Type: Research Article
ISSN: 0002-1466

Keywords

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