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Real Estate Investment Trusts is suggested as an attractive addition to mixed-asset portfolio. This study develops several hypothesized portfolio and tests whether REITs can actually increase diversification benefits of investors. We use mean-variance spanning test by Kan and Zhou (2008) to examine whether adding a REITs into portfolio can significantly expand efficient frontier in either global minimum variance portfolio or tangency portfolio. We assume our investors hold portfolio in the four markets, namely Japan, Singapore, Taiwan and US markets for period from March 2005 to February 2008. Three hypotheses are tested under various assumed conditions. The first hypothesis, which is REITs can provide diversification benefit, is confirmed in all these four markets. In addition, we find, for Taiwan domestic investors, holding international REITs in their portfolio rather than only Taiwan¡¦s REITs will provide more diversification benefit. The second hypothesis, which is holding period will affect diversification benefit, is not supported. However, this could be resulted from a test of short period in this study. The final hypothesis, which is different investment portfolio will affect the diversification benefit of RETIs for Taiwan domestic investors, is confirmed. Our results also suggest that expanding of efficient frontier are mainly from global minimum variance portfolio rather than tangency portfolio.

In contrast to the studies of constant or time-varying correlations between stock and bond returns, in this thesis, I explore the regime-dependent correlations between stock and bond returns. Specifically, I start with a comprehensive asset pricing model, i.e., a regime-switching multifactor model, and then investigate the regime-dependent correlations between stock and bond returns. Based on the BIC, the number of regimes in the regime-switching model is optimally determined to be two. For the two regimes, the directions of the regime-dependent correlations appear to be significantly different. Also, the magnitudes of the regime-dependent correlations are substantially larger in these two regimes than the correlation in the single regime. With my findings in the regime-dependent correlations, I then examine the performance of portfolio strategies. Throughout the in-sample and out-of-sample tests, I find that the two portfolio strategies, regime inferred portfolio and probability implied portfolio, can outperform the benchmark, S&P 500.

In this article, we consider the portfolio selection problem as a Bayesian decision problem. We compare the traditional mean–variance and mean–variance–skewness efficient portfolios. We develop bi-level programming problem to investigate the market’s preference for risk by using observed (market) weights. Numerical experiments are conducted on a portfolio formed by the 30 stocks in the Dow Jones Industrial Average. Numerical results show that the market’s preferences are better explained when skewness is included.

A passive investment management model was developed via a critical literature review of portfolio methodologies. This model was developed based on the fundamental models originated by both Markowitz and Sharpe. The passive model was automated via the development of a computer programme that can be used to generate the required outputs as suggested by Markowitz and Sharpe. For this computer programme MATLAB is chosen and the model’s logic is designed and validated. The demonstration of the designed programme using securities traded is performed on Johannesburg Securities Exchange. The selected portfolio has been sub-categorised into six components with a total of twenty- seven shares. The shares were grouped into different components due to the investors’ preferences and investment time horizon. The results demonstrate that a test portfolio outperforms a risk- free money market instrument (the government R194 bond), but not the All Share Index for the period under consideration. This design concludes the reason for this is due in part to the use of the error term from Sharpe’s single index model. An investor following the framework proposed by this design may use this to determine the risk- return relationship for selected portfolios, and hopefully, a real return.

The 2007-2008 financial crash and the looming climate change and global warming have heightened interest in sustainable investment. But whether the shift is as a result of the financial crash or a desire to preserve the environment, a sustainable investment might be desirable. However, to maintain this interest and to motivate investors in indulging in sustainability, there is the need to show the possibility of yielding positive returns. The main objective of the thesis is to investigate whether the sustainable investment can lead to higher returns. The thesis focuses primarily on incorporating sustainability into Markowitz portfolio optimization. It looks into the essence of sustainability and its impact on companies by comparing different concepts. The analysis is based on the 30 constituent stocks from the Dow Jones industrial average or simply the Dow. The constituents stocks of the Dow, from 2007-12-31 to 2018-12-31 are investigated. The thesis compares the cumulative return of the Dow with the sustainable stocks in the Dow based on their environmental, social and governance (ESG) rating. The results are then compared with the Dow Jones Industrial Average denoted by the symbol (^DJI) which is considered as the benchmark for my analysis. The constituent stocks are then optimized based on the Markowitz mean-variance framework and a conclusion is drawn from the constituent stocks, ESG, environmental, governance and social asset results. It was realized that the portfolio returns for stocks selected based on their environmental and governance ratings were the highest performers. This could be due to the fact that most investors base their investment selection on the environmental and governance performance of companies and the demand for stocks in that category could have gone up over the period, contributing significantly to their performance.

Transaction costs and resampling are two important issues that need great attention in every portfolio investment planning. In practice costs are incurred to rebalance a portfolio. Every investor tries to find a way of avoiding high transaction cost as much as possible. In this thesis, we investigated how transaction costs and resampling affect portfolio investment. We modified the basic mean-variance optimization problem to include rebalancing costs we incur on transacting securities in the portfolio. We also reduce trading as much as possible by applying the resampling approach any time we rebalance our portfolio. Transaction costs are assumed to be a percentage of the amount of securities transacted. We applied the resampling approach and tracked the performance of portfolios over time, assuming transaction costs and then no transaction costs are incurred. We compared how the portfolio is affected when we incorporated the two issues outlined above to that of the basic mean-variance optimization.

<p>There is a big interest for alternative investment strategies than investing in traditional asset classes. Commodities are having a boom dynamic with increasing prices. This thesis is therefore based on applying Modern Portfolio Theory concept to this alternative asset class.</p><p>In this paper we manage to create optimal portfolios of commodities for investors with known and unknown risk preferences. When comparing expected returns to actual returns we found that for the investor with the known risk preference almost replicated the return of the markets. The other investor with unknown risk preference also profited but not as efficient as the market portfolio.</p>

There is a big interest for alternative investment strategies than investing in traditional asset classes. Commodities are having a boom dynamic with increasing prices. This thesis is therefore based on applying Modern Portfolio Theory concept to this alternative asset class. In this paper we manage to create optimal portfolios of commodities for investors with known and unknown risk preferences. When comparing expected returns to actual returns we found that for the investor with the known risk preference almost replicated the return of the markets. The other investor with unknown risk preference also profited but not as efficient as the market portfolio.

MV is the traditional method to treat international portfolio selection problems, which bases its theory on the assumption of Normal Distribution. However, during economy recession the portfolio return turns out to be a fat tail distribution. Therefore, in this sense, we explore Roy’s SF criterion and apply the extreme theory to the historical data. We demonstrate how such portfolios would perform during the Asian Crisis, IT Bubble Bust and the Financial Crisis separately. We also compare the SF portfolio’s performance to the MV portfolio’s performance, therefore to check, SF and MV portfolio, which will outperform during bust and boom of the economy. The Asian Crisis was marked with great currency devaluation and lower currency return on equity. The Dot.Com Bubble Busts was known for its sharp plummet in the stock market, while, the Financial Crisis was known as the large falls in the US stock market and elsewhere. They are the extreme events of the world capital markets, which in some way contribute to the non-normal distribution. Simulated results over the 1997-2010 period which include six busts and booms: the Asian Crisis, period after Asian Crisis, IT Bubble Bust, period after IT Bubble Bust, The Financial Crisis and period after The Financial Crisis, indicate that SF portfolio outperforms MV portfolio during most of the times, this result is especially obvious for Indonesian and Thailand.