Exact solutions for expected rates of return under Markov regime switching
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Exact solutions for expected rates of return under Markov regime switching implications for the equity premium puzzle by Andrew B. Abel

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Published by National Bureau of Economic Research in Cambridge, MA .
Written in English

Subjects:

  • Stocks -- Prices -- Mathematical models.,
  • Equilibrium (Economics) -- Mathematical models.

Book details:

Edition Notes

StatementAndrew B. Abel.
SeriesNBER working papers series -- working paper no. 4110, Working paper series (National Bureau of Economic Research) -- working paper no. 4110.
ContributionsNational Bureau of Economic Research.
The Physical Object
Pagination29 p. ;
Number of Pages29
ID Numbers
Open LibraryOL22439584M

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  Abstract. This paper derives simple closed-form solutions for expected rates of return on stocks and riskless one-period bills under the assumption that shocks to the growth rates of consumption and dividends are generated by a Markov regime-switching by: Get this from a library! Exact solutions for expected rates of return under Markov regime switching: implications for the equity premium puzzle. [Andrew B Abel; National Bureau of Economic Research.]. Downloadable! This paper derives simple closed-form solutions for expected rates of return on stocks and riskless one-period bills under the assumption that shocks to the growth rates of consumption and dividends are generated by a Markov regime-switching process. These closed-form solutions are used to show that the Markov regime-switching process exacerbates the equity premium puzzle and the. Exact Solutions for Expected Rates of Return Under Markov.

regime switching models. We are convinced that our finding, that is, stochastic ex-change rate under regime switching model, can sharply catch the regime switching time and period. Furthermore, two type of regimes: good and bad economic perfor-mance or normal and crisis periods, is better for most of the exchange rates studies than more regimes. Markov-switching model of exchange rates outperforms the random walk one. Plenty of followers use regime-switching models in exchange rate estimation and forecasting, and most of them find that these kinds of models either fit exchange rate data well or generate superior forecasts to a random walk model or other models. 1. A. In this document, I discuss in detail how to estimate Markov regime switching models with an example based on a US stock market index. See for example Kole and Dijk () for an application. Key words: Markov switching, Expectation Maximization, bull and bear markets JEL classi cation: C51, C58, A23 1 Speci cation We assume that the asset return Y. study of Taiwan’s business cycles based on a bivariate Markov switching model. Section 6 presents the Markov switching model of conditional variance. Section 7 is an empirical analysis of Taiwan’s short term interest rates. Section 8 concludes this note. Readers may also consult Hamilton () for a concise treatment of the Markov.

r t = μ S t + ε t ε t ∼ N (0, σ 2) where S t ∈ { 0, 1 }, and the regime transitions according to. P (S t = s t | S t − 1 = s t − 1) = [ p 00 p 10 1 − p 00 1 − p 10] We will estimate the parameters of this model by maximum likelihood: p 00, p 10, μ 0, μ 1, σ 2. The data used in this example can be found at Regime-Switching Models James D. Hamilton Department of Economics, University of California, San Diego La Jolla, CA [email protected] Prepared . tween a low and a high volatility regime, are analyzed. Both gaussian and fat-tailed conditional distribu-tions for the residuals are assumed, and the degrees of freedom can be state-dependent to model possible time-varying kurtosis. The empirical analysis demonstrates that Markov Regime-Switching . Switching mechanism governed by a Markovian state variable Features Characterizing distinct (mean or variance) patterns over time More flexible than models with structural changes Allowing for regime persistence (cf. random switching model) C.-M. Kuan (Finance & CRETA, NTU) Markov Switching Model 5 /