Estimation of risk measures in energy portfolios using modern copula techniques

Jaschke, Stefan R.

doi:10.1016/j.csda.2014.01.019

Cited by 21 publications

(14 citation statements)

References 43 publications

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“…Empirical results are provided in section 3 and section 4 concludes. ¶In this context, Jäschke (2014) proposes novel bootstrap-based goodness-of-fit tests, which help to fit the appropriate copula to the data. See also Jäschke et al (2012) for a discussion of the drawbacks of previously used goodness-of-fit test for copulas.…”

Section: Introductionmentioning

confidence: 99%

“…§ Generally, the use of copula techniques in the context of oil prices is already established in the literature. For instance, see Jäschke (2014) for a study of the dependence structure between WTI and Brent crude oil spot log-returns using †Assuming that oil exporting countries reinvest their revenues in US dollar assets, the dollar will appreciate in the short-run. However, the long-run reaction of the US dollar against other currencies is less clear-cut and is determined by the weight of oil in US total imports compared to the US weights in OPEC imports (Coudert et al 2008).…”

Section: Introductionmentioning

confidence: 99%

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Oil price and FX-rates dependency

Beckmann

Berger

Czudaj

2015

Quantitative Finance

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Oil prices and exchange rates against the dollar have both experienced long swings over the recent decade. Regardless of the great amount of research, some issues are still open to debate. In this vein, this paper focuses on the evolution of the relationship between oil prices and dollar exchange rates of 12 oil exporting and oil importing countries based on a dynamic copula approach. We use daily data for two 5-year periods between 2003 and 2013, taking the collapse of Lehman Brothers as the dividing point. Our results have four main implications: first, the intensity of relationship between oil prices and FX-rates has increased over time even if the peak of the financial crisis is included. Second, the increased tail dependency shows that extreme events are likelier to occur simultaneously for both series. Third, the dependency has become more dynamic after the financial crisis and is therefore better characterized by time-varying copulas. Finally, currencies of oil importers and oil exporters display a different dependency structure against the US dollar in the case of rising oil prices with the latter appreciating and the former depreciating.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Oil price and FX-rates dependency

Beckmann

Berger

Czudaj

2015

Quantitative Finance

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“…For example, Melo Mendes and Aíube (2011) used the copula approach to model the serial dependence in financial return series. Righi and Ceretta (2011) examined the overall dependence between the U.S. and Brazilian stock markets while Aloui et al (2014), Hammoudeh et al (2014) and Jäschke (2014) have looked at cross dependencies within the energy and international stock markets.…”

Section: Introductionmentioning

confidence: 99%

Dependence Modeling and Portfolio Risk Estimation using GARCH-Copula Approach

Razak

Ismail²

2019

JSM

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Past studies have shown that linear correlation measure may result in misleading interpretations and implications of dependency when financial variables are involved. The copula approach can be adopted as an alternative for measuring dependence as it provides the solution to fat tail problems in multivariate cases which arises from the probability of large or extreme co-movements. Due to limited studies on copulas using Islamic financial data, this study set outs to obtain a clear picture on the dependence between Islamic and conventional stock markets in Malaysia. Firstly, we model the dependence between Islamic and conventional returns data using the copula-ARMA-GARCH models with normal and nonnormal error distributions, and secondly, we evaluate the portfolios of Islamic and conventional indices using recent risk measures. This paper shows that, by using the copula approach for measuring the dependency between two financial variables while maintaining their true nature as described by the ARMA-GARCH models, meaningful interpretation can be made about the association of the financial variables which reflects the real association between markets. Furthermore, this study proposes a set of procedures on how portfolio risks can be estimated using VaR based on the ARMA(p,q)-GARCH(1,1)-t-copula models including backtesting via simulation.

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“…In the literature, it has mainly been used to characterize the dependence structure among portfolio assets in both unconditional and conditional cases. For example, in the unconditional case, Jaschke [36] analyzed the dependence structure between WTI and Brent markets using different copula models. The comprehensive performance valuation on different copula-based risk estimates showed that Gumbel copula provided the best model fitting [36].…”

Section: Copula Model In the Energy Marketsmentioning

confidence: 99%

“…For example, in the unconditional case, Jaschke [36] analyzed the dependence structure between WTI and Brent markets using different copula models. The comprehensive performance valuation on different copula-based risk estimates showed that Gumbel copula provided the best model fitting [36]. Work by Anne-Laure Delatte [37] also showed that the dependence structure between the commodity and the stock markets was predominantly symmetric, as described by the Gaussian copula model [37].…”

Section: Copula Model In the Energy Marketsmentioning

confidence: 99%

Forecasting Energy Value at Risk Using Multiscale Dependence Based Methodology

Zha

Chen

et al. 2016

Entropy

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Abstract:In this paper, we propose a multiscale dependence-based methodology to analyze the dependence structure and to estimate the downside portfolio risk measures in the energy markets. More specifically, under this methodology, we formulate a new bivariate Empirical Mode Decomposition (EMD) copula based approach to analyze and model the multiscale dependence structure in the energy markets. The proposed model constructs the Copula-based dependence structure formulation in the Bivariate Empirical Mode Decomposition (BEMD)-based multiscale domain. Results from the empirical studies using the typical Australian electricity daily prices show that there exists a multiscale dependence structure between different regional markets across different scales. The proposed model taking into account the multiscale dependence structure demonstrates statistically significantly-improved performance in terms of accuracy and reliability measures.

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Estimation of risk measures in energy portfolios using modern copula techniques

Cited by 21 publications

References 43 publications

Oil price and FX-rates dependency

Oil price and FX-rates dependency

Dependence Modeling and Portfolio Risk Estimation using GARCH-Copula Approach

Forecasting Energy Value at Risk Using Multiscale Dependence Based Methodology

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