Member of Research Project HIAS Focuses on (1) : Kyuho Kang (Korea Univ.)

Friday, 16 March 2018 from to (Japan)
at Hitotsubashi University, IER Bld. ( 3F Conference Room )
2-1, Naka, Kunitachi Tokyo 186-8601 Japan

Macro Money Workshop
Economic Statistics Workshop

Toshiaki Watanabe (Institute of Economic Research)
Tomohito Okabe (Institute of Economics Research)

This paper proposes a new dynamic Nelson-Siegel (DNS) model with time-varying factor loadings and stochastic volatilities, in which the factors are instantaneously correlated. The proposed model is evaluated statistically and economically. For the statistical evaluation, we examine its out-of-sample yield curve density forecasting. The economic value of the model is analyzed in terms of the bond portfolio choice of a Bayesian risk-averse investor. According to our out-of-sample U.S. monthly yield curve density forecasting and bond portfolio optimization, our model results in substantially more accurate density forecasts and better portfolio performance than standard DNS models do. This finding suggests that incorporating time-varying factor loadings, stochastic volatilities, and factor shock correlations is essential for improving predictive accuracy and bond portfolio strategy.

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  • Friday, 16 March 2018
    • 17:10 - 18:40 Stochastic Volatility Dynamic Nelson-Siegel Model with Time-Varying Factor Loadings and Correlated Factor Shocks 1h30'
      Speaker: Kyu Ho Kang (Associate Professor at Korea University)