Modeling dependence dynamics through copulas with regime switching

Candido, Osvaldo; Ziegelmann, Flávio Augusto; Dueker, Michael J.

doi:10.1016/j.insmatheco.2012.01.001

Cited by 59 publications

(40 citation statements)

References 16 publications

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“…This section reviews very recent literature employing regime-switching approach briefly. First, using generalized autoregressive conditional heteroscedasticity (GARCH) and Markov switching models, Caporale et al [5] Silva Filho et al [10]. They found that significant effects of financial contagion from the Brexit to many other international countries.…”

Section: Literature Reviewmentioning

confidence: 99%

Value Premium and Portfolio Return Regime: Evidence from European Equities

Tsuji¹

2018

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This paper examines the profitability of four European higher return stock portfolios and their linkages between the value premium factor return, high-minus-low (HML), developed by Fama and French. Our fundamental analyses and quantitative examinations using Markov switching models derive the following findings. First, in the four higher return stock portfolios in Europe, the smallest and the highest momentum portfolio shows the highest return. Second, the second smallest and the highest book-to-market (BM) portfolio, the second smallest and the highest operating profitability portfolio, and the second smallest and the second lowest investment portfolio for Europe also demonstrate higher excess returns than the overall stock market in Europe. Furthermore, we also clarify that for all the four European stock portfolios, there clearly exist two regimes: one is positively associated with the value premium factor return, HML, and the other is negatively associated with HML. We further reveal that recently, for all the four portfolios, the high value premium factor loading regimes shift to the other regimes that are uncorrelated with HML. This indicates that, in the recent periods, hedging and risk-diversification effects can be recognized in investing value stocks and the four higher return stock portfolios in Europe.

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Section: Literature Reviewmentioning

confidence: 99%

Value Premium and Portfolio Return Regime: Evidence from European Equities

Tsuji¹

2018

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“…First, a time process needs to be specified. Patton (2006) andSilva Filho et al (2012) model the copula parameters varying through time according to an evolution equation in a bivariate context, which can be extended to a vine context. Second, a two-step IFM estimator may no longer be implemented and only a sequential estimation for the vine parameters can be performed.…”

Section: Some Pitfalls and Further Researchmentioning

confidence: 99%

Dependence Analysis of Ethanol, Sugar, Oil, BRL/Usd Exchange Rate and Bovespa: A Vine Copula Approach

Resende¹,

Candido²

2015

Econ. Apl.

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ResumoEste trabalho tem por objetivo analisar a relação de dependência entre o setor sucroalcooleiro (representado por Etanol e Açúcar), Petróleo, Taxa de Câmbio R$/US$ e o mercado acionário brasileiro (representado pelo ín-dice BOVESPA). A metodologia utilizada é baseada em pair-cópulas e são comparadas três especificações: Regular Vine, a forma mais geral, e dois casos particulares Vine Canônico e Drawable vine. Os resultados obtidos indicaram relações de dependência alinhadas com a literatura existente, mas mostraram que estas relações se alteram significativamente quando a dependência condicional é levada em conta.Palavras-chave: Commodities; Bio-combustíveis; Dependência multivariada; R-Vine cópulas. AbstractThe aim of this study is to assess the dependence relationship of the sugarcane sector (represented by Ethanol and Sugar), Oil, BRL/USD Exchange Rate and Brazilian stock market (represented by the BOVESPABolsa de Valores de São Paulo -Index). Our methodology is based on paircopulas constructions, in which tree specification are compared: Regular Vine, more general, and two particular cases, Canonical vine (C-vine) and Drawable vine (D-vine). Primary results are shown to be aligned with the existing literature but they can change significantly when conditional dependence is taken into account.

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“…The proposed variant model, on the other hand, differs from those based on copulas in the sense that besides allowing the dependence parameter to vary following a restricted ARMA process, as in Patton (2006), we also allow it to develop according to a hidden two-state first-order Markov chain, as in Silva Filho et al (2012). This approach allows us to capture non-linearities on the dependence structure over time.…”

Section: Facts About Financial Market Indexesmentioning

confidence: 99%

Assessing some stylized facts about financial market indexes: a Markov copula approach

Candido

Ziegelmann²

2014

Journal of Economic Studies

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Purpose – The aim of this paper is to measure and evaluate the relationship between returns-volatility and trading volume and returns and volatility of financial market indexes using time-varying copulas. Design/methodology/approach – The time dynamic dependence parameter is allowed to evolve according to a restricted ARMA-type equation which includes a constant term that is driven by a hidden two-state first-order Markov chain. Findings – In using this time dynamics in conjunction with non-elliptical distribution functions and tail dependence measure, the authors are allowing for (and focusing on) non-linearities in the returns-volume-volatility relationship. The results support the assumption that current trading volume provides information about future volatility as well as that there is a negative relationship between returns and their volatilities in financial market indexes. Originality/value – The authors provide an interesting empirical interpretation for the regimes the authors have identified: in the high dependence regime the sequential information arrival hypothesis and/or noise trading hypothesis are valid, consequently future volatility prediction is possible and persistent but does not last indefinitely; in the low dependence regime, the future volatility prediction is more unlikely to occur, since both trading volume and return negatives have a low (near zero) relation with future volatility.

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Modeling dependence dynamics through copulas with regime switching

Cited by 59 publications

References 16 publications

Value Premium and Portfolio Return Regime: Evidence from European Equities

Value Premium and Portfolio Return Regime: Evidence from European Equities

Dependence Analysis of Ethanol, Sugar, Oil, BRL/Usd Exchange Rate and Bovespa: A Vine Copula Approach

Assessing some stylized facts about financial market indexes: a Markov copula approach

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