If the underlying asset price process is unknown, arbitrageurs may not have sufficient incentive and confidence to use the underlying asset to arbitrage options. The option market makers can hedge their portfolios of temporary option inventories without the underlying asset, but investors’ risk attitudes and heterogeneous expectations could become relevant to option pricing. This paper shows th...

This paper applies the mean-variance portfolio optimization (PO) approach and the stochastic dominance (SD) test to examine preferences for international diversification versus domestic diversification from American investors’ viewpoints. Our PO results imply that the domestic diversification strategy dominates the international diversification strategy at a lower risk level and the reverse is ...

Robust portfolios resolve the sensitivity issue identified as a concern in implementing mean-variance analysis. Because robust approaches are not widely used in practice due to a limited understanding regarding the portfolios constructed from these methods, we present an analysis of the composition of robust equity portfolios. We find that compared to the Markowitz mean-variance formulation, ro...

The impact of the management performance evaluation methods on the information quality in accounting will be studied in this paper. The information plays two roles in the market-oriented economies; first, it allows the investors to evaluate the potential opportunities of the investment (prospective role) and, secondly, it enables the investors to monitor how to allocate and use their capital by...

Asset allocation among diverse financial markets is essential for investors especially under situations such as the financial crisis of 2008. Portfolio optimization is the most developed method to examine the optimal decision for asset allocation. We employ the hidden Markov model to identify regimes in varied financial markets; a regime switching model gives multiple distributions and this inf...

The objective of this paper is to find out whether the expected potential gains from strategic asset allocation can be realized in an out-of-sample test. Firstly, we find that long-term investors should time the market if they use our proposed shrinkage prior. This prior downplays the predictability of asset returns and leads to superior out-of-sample results compared to a standard uniform prio...

The shrinkage method of Ledoit and Wolf (2003; 2004a; 2004b) has shown certain success in estimating a well-conditioned covariance matrix for high dimensional portfolios. This paper generalizes the shrinkage method of Ledoit and Wolf to a multivariate shrinkage setting, by which the well-conditioned covariance matrix is estimated using the weighted averaging of multiple priors, instead of singl...

To reduce risk, investors seek assets that have high expected return and are unlikely to move in tandem. Correlation measures are generally used to quantify the connections between equities. The 2008 financial crisis, and its aftermath, demonstrated the need for a better way to quantify these connections. We present a machine learning-based method to build a connectedness matrix to address the ...

In this paper, we apply particle swarm optimisation to the construction of optimal risky portfolios for financial investments. Constructing an optimal risky portfolio is a high-dimensional constrained optimisation problem where financial investors look for an optimal combination of their investments among different financial assets with the aim of achieving a maximum reward-to-variability ratio...