Using the Markowitz mean-variance portfolio optimization theory, researchers have shown that the traditional estimated return greatly overestimates the theoretical optimal return, especially when the dimension to sample size ratio p/n is large. Bai, Liu, and Wong (2009) propose a...

This paper proposes the spectral corrected methodology to estimate the Global Minimum Variance Portfolio (GMVP) for the high dimensional data. In this paper, we analysis the limiting properties of the spectral corrected GMVP estimator as the dimension and the number of the sample set increase to...

Markowitz mean-variance portfolios with sample mean and covariance as inputparameters feature numerous issues in practice. They perform poorly out of sampledue to estimation error, they experience extreme weights together with high sensitivityto change in input parameters. The heavy-tail...

In this paper, we propose a Markov Chain Quasi-Monte Carlo (MCQMC) approach for Bayesian estimation of a discrete-time version of the stochastic volatility (SV) model. The Bayesian approach represents a feasible way to estimate SV models. Under the conventional Bayesian estimation method for SV...

Modelling the dynamics of credit derivatives is a challenging task in finance and economics. This work studies risk of collateralized debt obligations (CDOs) by investigating the evolution of tranche spread surfaces and base correlation surfaces using a dynamic semiparametric factor model...

This paper considers the portfolio problem for high dimensional data when the dimension and size are both large.We analyze the traditional Markowitz mean-variance (MV) portfolio by large dimension matrix theory, and find the spectral distribution of the sample covariance is the main factor to...

Barberis, Shleifer and Vishny (1998) and others have developed Bayesian models to explain investors' behavioral biases by using the conservatism heuristics and the representativeness heuristics in making decisions. To extend their work, Lam, Liu, and Wong (2010) have developed a model of weight...

In this paper, we introduce a new pseudo-Bayesian model to incorporate the impact of a financial Crisis and establish some properties of stock returns and investors' behaviors during the financial crisis and during recovery after crisis. Our proposed model can be applied to investigate some...

Using the Markowitz mean-variance portfolio optimization theory, researchers have shown that the traditional estimated return greatly overestimates the theoretical optimal return, especially when the dimension to sample size ratio is large. Bai, Liu, and Wong (2006,2009a,b) propose...

This paper extends the work of Korkie and Turtle (2002) by first proving that the traditional estimate for the optimal return of self-financing portfolios always over-estimates from its theoretic value. To circumvent the problem, we develop a Bootstrap estimate for the optimal return of...