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Dynamic Asset Allocation: A Bayesian Approach, Yalan Feng

Dissertations, Theses, and Capstone Projects

The first half of this dissertation consists of two essays addressing dynamic asset allocation problem by exploring time-varying volatility and covariance between different assets.

In the first essay, I propose a time-varying Bayesian approach based on autoregressive models. To allow a parsimonious specification while improving predictive power, I specify a step function that considerably decreases the number of parameters to be estimated. To reduce data dimensionality, I use orthogonal portfolios instead of correlated assets in estimation and forecast. Finally, a Bayesian estimation is applied to dynamically update coefficients and error variance. I combine Bayesian time-varying autoregression with step function restriction …