Investors have increasing interests in sophisticated yet transparent analytic tools to handle model uncertainty, tail risk and market dynamics. This paper demonstrates how macroeconomic factor models, based on Bayesian model averaging (BMA), can help address the challenges in some specific...

All the financial practitioners are working in incomplete markets full of unhedgeable risk-factors. Making the situation worse, they are only equipped with the imperfect information on the relevant processes. In addition to the market risk, fund and insurance managers have to be prepared for...

We introduce an ensemble learning method based on Gaussian Process Regression (GPR) for predicting conditional expected stock returns given stock-level and macro-economic information. Our ensemble learning approach significantly reduces the computational complexity inherent in GPR inference and...

This paper shows how uncertainty about the type of return distribution (distribution uncertainty) can be incorporated in asset allocation decisions by using a novel, Bayesian semiparametric approach. To evaluate the economic importance of distribution uncertainty, the extent of changes in...

Do parameter uncertainties regarding different risk factors have symmetric effects on asset prices? In a general equilibrium setting where uncertainties regarding consumption and portfolio returns are of concern to investors but all the structural parameters of consumption and dividend growth...

For the popular mean-variance portfolio choice problem in the case without a risk-free asset, we develop a new portfolio strategy to mitigate estimation risk. We show that in both calibrations and real datasets, optimally combining the sample global minimum variance portfolio with a sample...

We propose a novel approach for measuring the impact of climate change on long-horizon equity risk and optimal portfolio choice. Our method combines historical data about the impact of climate change on return dynamics with prior beliefs elicited from the temperature long-run risk (LRR-T) model...

This paper examines the economic implications of new factor models and shows that the Hou, Xue, and Zhang (HXZ, 2015a) four-factor model outperforms the Fama and French (FF5, 2015a) five-factor model for investing in anomalies in- and out-of-sample. The difference in certainty-equivalent returns...

The evaluation of hedge fund performance is challenging given the flexible nature of hedge funds' strategies and their lack of operational transparency. As a result inference about skill is inevitably contaminated by the error in the benchmark model. To address this concern, we propose a model...