An Econometric Model of Nonlinear Dynamics in the Joint Distribution of Stock and Bond Returns

By Massimo Guidolin, Allan G. Timmermann. 2005

276 citations recorded by the source corpus.

This paper considers a variety of econometric models for the joint distribution of US stock and bond returns in the presence of regime switching dynamics. While simple two- or three-state models capture the univariate dynamics in bond and stock returns, a more complicated four state model with regimes characterized as crash, slow growth, bull and recovery states is required to capture their joint distribution. The transition probability matrix of this model has a very particular form. Exits from the crash state are almost always to the recovery state and occur with close to 50 percent chance suggesting a bounce-back effect from the crash to the recovery state.

Subfields: Economics and Econometrics, Finance

View Paper: https://www.semanticscholar.org/paper/2b9d41186cede4327d4feb4caac574fba3326586

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Citations in the corpus

Macro-Finance Determinants of the Long-Run Stock-Bond Correlation: The DCC-MIDAS Specification (2016, unknown): “State of economy variables: Ilmanen (2003), Guidolin and Timmermann (2006), and Aslanidis and Christiansen (2013) show that the general state of the macro economy provides information about the future stock-bond correlation.”
Inflation Bets or Deflation Hedges? The Changing Risks of Nominal Bonds (2013, unknown): “The nominal-real covariance has declined since the early 1980 s, driving down term premia.”
International Asset Allocation Under Regime Switching, Skew and Kurtosis Preferences (2005, background): “The decomposition in (32) shows that future moments of wealth depend on future portfolio choices, ωb.”
Asset Allocation Under Multivariate Regime Switching (2005, methodology): “Following Guidolin and Timmermann (2006b), we use a block bootstrap (with 50,000 independent trials) for the empirical distribution of −V Tτ to account for the fact that realized utility levels are likely to be serially dependent as time-variations in the conditional distribution of asset returns…”
Value Versus Growth: Time-Varying Expected Stock Returns (2011, background): “…asset allocation (e.g., Ang and Bekaert 2002a and Guidolin and Timmermann 2008b), interest rate dynamics (e.g., Ang and Bekaert 2002b), capital markets integration (e.g., Bekaert and Harvey 1995), and the joint distribution of stock and bond returns (e.g., Guidolin and Timmermann 2006).”
A model of carbon price interactions with macroeconomic and energy dynamics (2011, methodology): “As K rises, it becomes increasingly easy to fit complicated dynamics and deviations from the normal distribution in the returns (Guidolin and Timmermann, 2006).”
Modeling International Financial Returns with a Multivariate Regime Switching Copula (2009, unknown): “Regarding asymmetric dependence, Longin and Solnik (1995) analyze correlations between stock markets over a period of 30 years using the constant conditional correlation (CCC) model of Bollerslev (1990).”
Real-Time Price Discovery in Global Stock, Bond and Foreign Exchange Markets (2006, unknown): “See also the recent related empirical results in Guidolin and Timmermann (2005, 2006) .”
VOLATILITY AND CORRELATION FORECASTING (2006, background): “Guidolin and Timmermann (2005a) uncover VaR dynamics at horizons of up to two years.”