Modeling the conditional distribution of interest rates as a regime-switching process

Gray, Stephen

doi:10.1016/0304-405x(96)00875-6

Cited by 1,255 publications

(1,100 citation statements)

References 23 publications

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“…Note that the variances in this specification are regime-independent whereas the covariances (or correlations) are both time-varying and regime-switching (We estimate the MS-DCC-GARCH model using the two-step approach of [53,62]. In the second step, we use the modified Hamilton filter proposed by [57] to solve the path-dependence problem [63][64][65] and estimate the regime-switching conditional covariances accordingly). As [57] note, the specification in which all parameters are regime dependent is highly unstable due to the large number of switching parameters.…”

Section: Methodsmentioning

confidence: 99%

Do Sustainable Stocks Offer Diversification Benefits for Conventional Portfolios? An Empirical Analysis of Risk Spillovers and Dynamic Correlations

2017

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This paper explores the potential diversification benefits of socially responsible investments for conventional stock portfolios by examining the risk spillovers and dynamic correlations between conventional and sustainability stock indexes from a number of regions. We observe significant unidirectional volatility transmissions from conventional to sustainable equities, suggesting that the criteria applied for socially responsible investments do not necessarily shield these securities from common market shocks. While significant dynamic correlations are observed between sustainable and conventional stocks, particularly in Europe, the analysis of both in-and out-of-sample dynamic portfolios suggests that supplementing conventional stock portfolios with sustainable counterparts improves the risk/return profile of stock portfolios in all regions. The findings overall suggest that sustainable investments can indeed provide diversification gains for conventional stock portfolios globally.

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Section: Methodsmentioning

confidence: 99%

Do Sustainable Stocks Offer Diversification Benefits for Conventional Portfolios? An Empirical Analysis of Risk Spillovers and Dynamic Correlations

2017

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“…We therefore maintain the simpler four-state model without ARCH effects. The absence of ARCH effects in our model can be explained by the fact that, at the monthly frequency, regime switching can capture volatility clustering through time-variations in the probabilities of (persistent) states with very different levels of volatility, see Gray (1996) and Timmermann (2000).…”

Section: Testing Restrictions and Arch Effectsmentioning

confidence: 99%

“…A number of papers have found evidence of regime switching dynamics in short-term US interest rates (e.g., Gray (1996), Ang and Bekaert (2002b), Bansal, Tauchen and Zhou (2004) and Guidolin and Timmermann (2007)). Furthermore, some studies have found that short-term rates are useful predictors of stock returns (e.g., Keim and Stambaugh, (1986)).…”

Section: Stochastic Short-term Interest Ratementioning

confidence: 99%

Size and Value Anomalies under Regime Shifts

Guidolin

Timmermann

2007

SSRN Journal

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This paper finds strong evidence of time-variations in the joint distribution of returns on a stock market portfolio and portfolios tracking size-and value effects. Mean returns, volatilities and correlations between these equity portfolios are found to be driven by underlying regimes that introduce short-run market timing opportunities for investors. The magnitude of the premia on the size and value portfolios and their hedging properties are found to vary across regimes. Regimes are shown to have a large impact on the optimal asset allocation -especially under rebalancing -and on investors' utility. Regimes also have a considerable impact on hedging demands, which are positive when the investor starts from more favorable regimes and negative when starting from bad states. Recursive out-of-sample forecasting experiments show that portfolio strategies based on models that account for regimes dominate single-state benchmarks.

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“…This probability is crucial, since all regime probabilities in the paper can be derived from it. Using similar techniques as in Gray (1996a), the following formula shows that this probability has a first-order recursive structure, which simplifies its computation substantially:…”

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confidence: 99%

Improving GARCH volatility forecasts with regime-switching GARCH

Klaassen

2002

Advances in Markov-Switching Models

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Many researchers use GARCH models to generate volatility forecasts. Using data on three major U.S. dollar exchange rates we show that such forecasts are too high in volatile periods. We argue that this is due to the high persistence of shocks in GARCH forecasts. To obtain more flexibility regarding volatility persistence, this paper generalizes the GARCH model by distinguishing two regimes with different volatility levels; GARCH effects are allowed within each regime. The resulting Markov regime-switching GARCH model improves on existing variants, for instance by making multi-periodahead volatility forecasting a convenient recursive procedure. The empirical analysis demonstrates that the model resolves the problem with the high single-regime GARCH forecasts and that it yields significantly better outof-sample volatility forecasts.Key words: GARCH, Markov-switching, variance, forecasting, exchange rates. JEL classification: C52, C53, F31. * Department of Economics, University of Amsterdam, Roetersstraat 11, 1018 WB Amsterdam, the Netherlands; tel: +31-20-5254191; fax: +31-20-5254254; E-mail: klaassen@fee.uva.nl. I thank Harry Huizinga, Frank de Jong, Michael McAleer, Bertrand Melenberg, Theo Nijman, Arthur van Soest, Kenneth West, the editors of this issue, James Hamilton and Baldev Raj, and two referees for very useful and constructive comments.

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Modeling the conditional distribution of interest rates as a regime-switching process

Cited by 1,255 publications

References 23 publications

Do Sustainable Stocks Offer Diversification Benefits for Conventional Portfolios? An Empirical Analysis of Risk Spillovers and Dynamic Correlations

Do Sustainable Stocks Offer Diversification Benefits for Conventional Portfolios? An Empirical Analysis of Risk Spillovers and Dynamic Correlations

Size and Value Anomalies under Regime Shifts

Improving GARCH volatility forecasts with regime-switching GARCH

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