Ng, Hon Yip. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2008. / Includes bibliographical references (p. 79-83). / Abstracts in English and Chinese. / Chapter 1 --- Introduction --- p.1 / Chapter 2 --- Basic Concepts in Portfolio Theory --- p.8 / Chapter 2.1 --- Statistical Model --- p.8 / Chapter 2.2 --- Mean-Variance Optimization --- p.9 / Chapter 2.3 --- The Efficient Frontier --- p.11 / Chapter 2.4 --- The Tangency Portfolio and The Capital Market Line --- p.13 / Chapter 2.5 --- Mathematical Formulation of Portfolio Optimization --- p.17 / Chapter 3 --- Derivation of The Improved Estimator --- p.29 / Chapter 4 --- Simulation Study --- p.40 / Chapter 4.1 --- Procedure of Simulation --- p.40 / Chapter 4.2 --- Simulation Results --- p.46 / Chapter 4.2.1 --- Zero Correlation --- p.47 / Chapter 4.2.2 --- Positive Correlations --- p.50 / Chapter 4.2.3 --- Negative Correlations --- p.52 / Chapter 5 --- Conclusion and Future Direction --- p.56 / Chapter A --- Simulation results for p = 200 --- p.58 / Chapter B --- Simulation results for p = 400 --- p.61 / Chapter C --- Simulation results for p = 500 --- p.64 / Chapter D --- Simulation results for p = 200 with negative correlations --- p.67 / Chapter E --- Simulation results for p = 400 with negative correlations --- p.71 / Chapter F --- Simulation results for p = 500 with negative correlations --- p.75 / Bibliography --- p.79

<p>This paper is an empirical study on Harry Markowitz work on Modern Portfolio Theory. The model introduced by him assumes the normality of assets’ return. We examined the OMX Large Cap List1 by mathematical and statistical methods for normality of assets’ returns. We studied the effect of the parameters, Skewness and Kurtosis for different time series data. We tried to figure it out which data series is better to construct a portfolio and how these extra parameters can make us better informed in our investments.</p>

This paper is an empirical study on Harry Markowitz work on Modern Portfolio Theory. The model introduced by him assumes the normality of assets’ return. We examined the OMX Large Cap List1 by mathematical and statistical methods for normality of assets’ returns. We studied the effect of the parameters, Skewness and Kurtosis for different time series data. We tried to figure it out which data series is better to construct a portfolio and how these extra parameters can make us better informed in our investments.

The expected equity premium is an important parameter in many financial models, especially within portfolio optimization. A good forecast of the future equity premium is therefore of great interest. In this thesis we seek to forecast the equity premium, use it in portfolio optimization and then give evidence on how sensitive the results are to estimation errors and how the impact of these can be minimized. Linear prediction models are commonly used by practitioners to forecast the expected equity premium, this with mixed results. To only choose the model that performs the best in-sample for forecasting, does not take model uncertainty into account. Our approach is to still use linear prediction models, but also taking model uncertainty into consideration by applying Bayesian model averaging. The predictions are used in the optimization of a portfolio with risky assets to investigate how sensitive portfolio optimization is to estimation errors in the mean vector and covariance matrix. This is performed by using a Monte Carlo based heuristic called portfolio resampling. The results show that the predictive ability of linear models is not substantially improved by taking model uncertainty into consideration. This could mean that the main problem with linear models is not model uncertainty, but rather too low predictive ability. However, we find that our approach gives better forecasts than just using the historical average as an estimate. Furthermore, we find some predictive ability in the the GDP, the short term spread and the volatility for the five years to come. Portfolio resampling proves to be useful when the input parameters in a portfolio optimization problem is suffering from vast uncertainty.

There are several authors Markowitz (1991), Elton and Gruber (1997) that discuss the main issues that an investor faces when investing, for example how to allocate resources among the variety of different securities. These issues have led to the discussion of portfolio theories, especially the Modern Portfolio Theory (MPT), which is developed by Nobel Prize awarded economist Harry Markowitz. This theory is the philosophical opposite of tradi-tional asset picking. The purpose of this thesis is to investigate if an investor can apply MPT in order to achieve a higher return than investing in an index portfolio. Combining a strong portfolio that beats the market in the longrun would be the ultimate goal for most investors. The theories that are used to analyze the problem and the empirical findings provide the essential concepts such as standard deviation, risk and return of the portfolio. Further, diversification, correlation and covariance are used to achieve the optimal risky portfolio. There will be a walk-through of the MPT, with the efficient frontier as the graphical guide to express the optimal risky portfolio. The methodology constitutes as the frame for the thesis. The quantitative method is used since the data input is gathered from historical data. This thesis is based on existing theories, and the deductive approach aims to use these theories in order to accomplish a valid and accurate analysis. The benchmark that is used to compare the results from the portfolio is the Stockholm stock exchange OMX 30. This index mimics and reflects the market as a whole. The portfolio will be reweighed at a preplanned schedule, each quarter to constantly obtain an optimal risky portfolio. The finding from this study indicates that the actively managed portfolio outperforms the passive benchmark during the selected timeframe. The outcome someway differs when evaluating the risk adjusted result and becomes less significant. The risk adjusted result does not provide any strong evidence for a greater return than index. Finally, with this finding, the authors can conclude by stating that an actively managed optimal risky portfolio with guidance of the MPT can surpass the OMX 30 within the selected timeframe.

Non-arbitrage asset pricing has been an avenue of unending interest to financial academics and practitioners alike. With increased capital outflow being permitted by developing economies, investors now have easy access to securities issued by foreign firms. The issue investigated in this research is concerned with the persistent presence of arbitrage opportunities between depository receipts and domestic stocks of Indian firms during the recent financial crisis. Instead of being priced in parity with one another during the crisis, ADRs of Indian firms were overpriced by as much as 70% for months on end. This thesis investigates the reasons giving rise to this premium by analyzing causes like benefits from diversification and liquidity.

<p>There are several authors Markowitz (1991), Elton and Gruber (1997) that discuss the main issues that an investor faces when investing, for example how to allocate resources among the variety of different securities. These issues have led to the discussion of portfolio theories, especially the Modern Portfolio Theory (MPT), which is developed by Nobel Prize awarded economist Harry Markowitz. This theory is the philosophical opposite of tradi-tional asset picking.</p><p>The purpose of this thesis is to investigate if an investor can apply MPT in order to achieve a higher return than investing in an index portfolio. Combining a strong portfolio that beats the market in the longrun would be the ultimate goal for most investors.</p><p>The theories that are used to analyze the problem and the empirical findings provide the essential concepts such as standard deviation, risk and return of the portfolio. Further, diversification, correlation and covariance are used to achieve the optimal risky portfolio. There will be a walk-through of the MPT, with the efficient frontier as the graphical guide to express the optimal risky portfolio.</p><p>The methodology constitutes as the frame for the thesis. The quantitative method is used since the data input is gathered from historical data. This thesis is based on existing theories, and the deductive approach aims to use these theories in order to accomplish a valid and accurate analysis. The benchmark that is used to compare the results from the portfolio is the Stockholm stock exchange OMX 30. This index mimics and reflects the market as a whole. The portfolio will be reweighed at a preplanned schedule, each quarter to constantly obtain an optimal risky portfolio.</p><p>The finding from this study indicates that the actively managed portfolio outperforms the passive benchmark during the selected timeframe. The outcome someway differs when evaluating the risk adjusted result and becomes less significant. The risk adjusted result does not provide any strong evidence for a greater return than index. Finally, with this finding, the authors can conclude by stating that an actively managed optimal risky portfolio with guidance of the MPT can surpass the OMX 30 within the selected timeframe.</p>

<p>The expected equity premium is an important parameter in many financial models, especially within portfolio optimization. A good forecast of the future equity premium is therefore of great interest. In this thesis we seek to forecast the equity premium, use it in portfolio optimization and then give evidence on how sensitive the results are to estimation errors and how the impact of these can be minimized.</p><p>Linear prediction models are commonly used by practitioners to forecast the expected equity premium, this with mixed results. To only choose the model that performs the best in-sample for forecasting, does not take model uncertainty into account. Our approach is to still use linear prediction models, but also taking model uncertainty into consideration by applying Bayesian model averaging. The predictions are used in the optimization of a portfolio with risky assets to investigate how sensitive portfolio optimization is to estimation errors in the mean vector and covariance matrix. This is performed by using a Monte Carlo based heuristic called portfolio resampling.</p><p>The results show that the predictive ability of linear models is not substantially improved by taking model uncertainty into consideration. This could mean that the main problem with linear models is not model uncertainty, but rather too low predictive ability. However, we find that our approach gives better forecasts than just using the historical average as an estimate. Furthermore, we find some predictive ability in the the GDP, the short term spread and the volatility for the five years to come. Portfolio resampling proves to be useful when the input parameters in a portfolio optimization problem is suffering from vast uncertainty. </p>

壽險業具高財務槓桿之特性，其投資策略顯著影響公司清償能力及保戶權益，壽險公司資產負債管理亦攸關金融市場之穩定。本研究系統分析兩岸保險市場及資產配置行為，比較兩岸保險業尤其是壽險業資產配置之差異，並使用Markowitz之mean-variance模型，自金融市場、法規限制及資金經理人行為三者協動作用出發，假設模型限制條件，以數值結果闡釋不同因素對資產配置結果之影響程度，及形成兩岸壽險業最適資產配置差異之原因。 分析兩岸現況後可發現，兩岸壽險業投資雖均以固定收益資產為主，然大陸銀行存款比例過高，而台灣傾向於投資國外債券。結合模型數值結果，歸納所得之主要結論包括：（1）利率環境差異為影響兩岸壽險資產配置之基礎因素；（2）適當寬鬆之法律規範有利於投資收益之提高；（3）不動產及其他類型投資將成為兩岸壽險業主要投資收益來源；（4）大陸壽險業資產配置策略受金融市場影響顯著。據此，本研究建議：（1）台灣可適當放寬壽險業投資比例限制；（2）大陸需完善金融市場並增強透明度；（3）大陸監理機關應加強對壽險公司財務報表揭露與業務資訊公開之監管。

abstract: This thesis develops a low-investment marketing strategy that allows low-to-mid level farmers extend their commercialization reach by strategically sending containers of fresh produce items to secondary markets that present temporary arbitrage opportunities. The methodology aims at identifying time windows of opportunity in which the price differential between two markets create an arbitrage opportunity for a transaction; a transaction involves buying a fresh produce item at a base market, and then shipping and selling it at secondary market price. A decision-making tool is developed that gauges the individual arbitrage opportunities and determines the specific price differential (or threshold level) that is most beneficial to the farmer under particular market conditions. For this purpose, two approaches are developed; a pragmatic approach that uses historic price information of the products in order to find the optimal price differential that maximizes earnings, and a theoretical one, which optimizes an expected profit model of the shipments to identify this optimal threshold. This thesis also develops risk management strategies that further reduce profit variability during a particular two-market transaction. In this case, financial engineering concepts are used to determine a shipment configuration strategy that minimizes the overall variability of the profits. For this, a Markowitz model is developed to determine the weight assignation of each component for a particular shipment. Based on the results of the analysis, it is deemed possible to formulate a shipment policy that not only increases the farmer's commercialization reach, but also produces profitable operations. In general, the observed rates of return under a pragmatic and theoretical approach hovered between 0.072 and 0.616 within important two-market structures. Secondly, it is demonstrated that the level of return and risk can be manipulated by varying the strictness of the shipping policy to meet the overall objectives of the decision-maker. Finally, it was found that one can minimize the risk of a particular two-market transaction by strategically grouping the product shipments. / Dissertation/Thesis / M.S. Industrial Engineering 2011