A dynamic conditional regime-switching GARCH CAPM for energy and financial markets

Urom, Christian; Chevallier, Julien; Zhu, Bangzhu

doi:10.1016/j.eneco.2019.104577

Cited by 10 publications

(7 citation statements)

References 96 publications

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“…Adcock [24] states that it's unnecessary to assume that returns follow a normal distribution to satisfy the CAPM axioms. He found that the family of Skewed-Normal distributions (described in Azzalini and Dalla Valle [25] ) is empirically important for UK stocks, and estimates of the CAPM β parameter change significantly when the sampling distribution allows for skewness.…”

Section: Kaplan and Petersonmentioning

confidence: 99%

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Estimating parameters of the CAPM under generalised asymmetric student-t distribution—The case of the Warsaw Stock Exchange sectoral indices

Pipień

2024

Financ. Stat. J.

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This paper analyses selected sub-indices listed on the Warsaw Stock Exchange (WSE) covering seven sectors: construction, IT, media, real estate, fuel, food, and telecommunications, from 3 January 2006 to 29 May 2020. We use daily, weekly, monthly, and quarterly data, resulting in 3600 daily, 751 weekly, 172 monthly, and 56 quarterly observations. The WIG index quotations were used to approximate the market portfolio and the Poland 10Y government bond yields for the risk-free rate. We have estimated the parameter β in CAPM regression using three different stochastic assumptions for the error term. The basic stochastic framework of the model utilises the generalised asymmetric student-t distribution (GAST). We have also estimated the parameter β based on the symmetric version of the GAST distribution and on the Gaussian one. These models can be treated as a special case of the basic framework. The estimates of the β parameter are influenced by the assumptions made about the error term. The data indicates that except for WIG-Paliwa, the Gaussian error term leads to larger β estimates than other non-Gaussian specifications. The inference about the shape parameters is not very certain, and the data does not strongly support the two-piece mechanism that enforces the asymmetry of the error term distribution. Furthermore, the estimates of the β parameter depend strongly on the frequency of the analysed series.

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Section: Kaplan and Petersonmentioning

confidence: 99%

“…The CAPM theory, which imposes a zero restriction on the intercept in the null hypothesis, has been studied for decades, as detailed by Jensen et al [45] . It's worth noting that the assumptions behind the CAPM theory do not require returns to be normally distributed, as stated by Adcock [24] .…”

Section: Empirical Insights Into Capm Regressionmentioning

confidence: 99%

Estimating parameters of the CAPM under generalised asymmetric student-t distribution—The case of the Warsaw Stock Exchange sectoral indices

Pipień

2024

Financ. Stat. J.

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“…There are many ways to measure risk spillovers in financial markets. The multivariate GARCH model and the Copula model are commonly applied in evaluating risk spillover (Han et al 2016 ; Chen et al 2020 ; Urom et al 2020 ; Ji et al 2020 ). However, the multivariate GARCH model has too many constraints and cannot explain the correlation between negative return and return fluctuation.…”

Section: Literature Reviewmentioning

confidence: 99%

Key market identification, mechanism transmission, and extreme shock during the risk spillover process: an empirical study of the G20 FOREX markets

et al. 2023

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The role of the G20 in global governance has been increasingly prominent in the context of the extensive spread of coronavirus disease 2019 and the aggravation of financial risk contagion. Detecting the risk spillovers among the G20 FOREX markets is crucial to maintain financial stability. Therefore, this paper first adopts a multi-scale approach to measure the risk spillovers among the G20 FOREX markets from 2000 to 2022. Furthermore, the key markets, the transmission mechanism, and the dynamic evolution are researched based on the network analysis. We derive the following findings: (1) The magnitude and volatility of the total risk spillover index of the G20 countries are highly associated with extreme global events. (2) The magnitude and volatility of risk spillovers among the G20 countries are asymmetric in the different extreme global events. (3) The key markets in the risk spillover process are identified, and the USA always occupies a core position in the G20 FOREX risk spillover networks. (4) In the core clique, the risk spillover effect is obviously high. In the clique hierarchy, as the risk spillover effect is transmitted downward, the risk spillovers present the decrease trends. (5) The density, transmission, reciprocity, and clustering degrees in the G20 risk spillover network during the COVID-19 period are much higher than that in other periods.

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“…In a traditional SML also, relying solely on the Korean stock market, he found empirically that actual betas were different from perceived betas, especially when the alleged betas were more than one. Urom et al (2020) examined a conditional one-factor model that can account for the spread in the average returns of portfolios sorted by book-to-market ratios over the long run.…”

Section: Review Of Literaturementioning

confidence: 99%

Testing The Validity of Postmodern Theory of Portfolio from Market Based Model: An Empirical Evidence from Emerging Economy of Pakistan

Rasheed

Hamid

Talha

et al. 2022

IJMRES

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This study is aimed to test the validity of the postmodern theory of portfolio with the help of the market-based model, and 100 companies’ data has been used for the period 1st Jan, 2005 to 1st Feb, 2021 for listed companies at PSX. The explanatory power of CAPM is tested with the risk measures beta, idiosyncratic risk, semivariance/downside risk (Yildiz & Erzurumlu, 2018) and value at risk (VaR). Results of the GARCH (1,1) model indicates that E(R) DR and E(R) VaR has a significant impact on volatility by adding the-se explanatory measures in the variance equation. Whereas risk parameters significantly impact volatility, as shown by adding explanatory measures in the mean equation. The estimated returns and risk indicators of both global and local companies have essential explanatory capacity. In contrast, results suggest that to the MSCI index, the downward market integration is greater, and T-Bill prices may be the dominating factor.

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A dynamic conditional regime-switching GARCH CAPM for energy and financial markets

Cited by 10 publications

References 96 publications

Estimating parameters of the CAPM under generalised asymmetric student-t distribution—The case of the Warsaw Stock Exchange sectoral indices

Estimating parameters of the CAPM under generalised asymmetric student-t distribution—The case of the Warsaw Stock Exchange sectoral indices

Key market identification, mechanism transmission, and extreme shock during the risk spillover process: an empirical study of the G20 FOREX markets

Testing The Validity of Postmodern Theory of Portfolio from Market Based Model: An Empirical Evidence from Emerging Economy of Pakistan

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