Wang, Yang. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2011. / Includes bibliographical references (p. 72-74). / Abstracts in English and Chinese. / Chapter 1 --- Literature Review and Model Description --- p.1 / Chapter 1.1 --- Portfolio theory under mean-variance framework --- p.2 / Chapter 1.2 --- Portfolio theory under utility-maximizing framework --- p.5 / Chapter 1.3 --- Model Description --- p.11 / Chapter 2 --- Parameterized optimal rebalancing strategy --- p.14 / Chapter 2.1 --- An open-loop policy of the T-horizon model --- p.16 / Chapter 2.2 --- A closed-loop policy of the T-horizon model --- p.24 / Chapter 2.3 --- Illustrative numerical example --- p.36 / Chapter 3 --- Non-parameterized optimal rebalancing model --- p.46 / Chapter 3.1 --- T=2 period problem --- p.47 / Chapter 3.2 --- T=3 period problem --- p.55 / Chapter 4 --- s-S type policy --- p.59 / Chapter 4.1 --- Exponential K-convex function --- p.60 / Chapter 4.2 --- Revised multiperiod portfolio selection model --- p.62 / Chapter 5 --- Conclusion and summary of work --- p.70 / Bibliography --- p.71

Hlavním cílem této práce je poskytnout přehledné a ucelené informace o aplikaci portfolia managementu v projektovém řízení, zprostředkovat zkušenosti a doporučení ze zahraničních aplikací a také seznámit potencionální zájemce s návody, jak v případě zájmu postupovat při aplikaci v praxi. Práce vychází z obecného pohledu klasické teorie portfolia, na tuto část navazuje teoreticky zaměřený úsek věnující se teorii portfolio managementu. Poslední část je věnována aplikaci portfolia managementu a konkrétní ukázce implementace z praxe.

This thesis investigates different aspects of the impact of extreme downside risk on stock returns. We first investigate the impact at market level, where the return of the stock market index is expected to be positively correlated to its tail risk. More specifically, we incorporate Markov switching mechanism into the framework of Bali et al. (2009) to analyse the relationship between risk and returns under different market regimes. Interestingly, although highly significant in calm periods, the tail risk-return relationship cannot be captured during turbulent times. This is puzzling since this is the time when the distress risk is most prominent. We show that this pattern persists under different modifications of the framework, including expanding the set of state variables and accounting for the non-iid feature of return process. We suggest that this result is due to the leverage and volatility feedback effects. To better filter out these effects, we propose a simple but effective modification to the risk measures which reinstates the positive extreme risk-return relationship under any state of market volatility. The success of our method provides insights into how extreme downside risk is factored into expected returns. In the second investigation, this thesis explores the impact of extreme downside risk on returns in a security level analysis. We demonstrate that a stock with higher tail risk exposure tends to experience higher average returns. Motivated by the limitations of systematic extreme downside risk measures in the literature, we propose two groups of new ‘co-tail-risk’ measures constructed from two different approaches. The first group is the natural development of canonical downside beta and comoment measures, while the second group is based on the sensitivity of stock returns on innovations in market systematic crash risk. We utilise our new measures to investigate the asset pricing implication of extreme downside risk and show that they can capture a significant positive relationship between this risk and expected stock return. Moreover, our second group of ‘co-tail-risk’ measures show a highly consistent performance even in extreme settings such as low tail threshold and monthly sample estimation. The ability of this measure to generate a number of observations given limited return data solves one of the most challenging problems in tail risk literature. In the last investigation, this thesis examines the influence of extreme downside risk on portfolio optimisation. It is motivated by the evidence in Chapter 4 regarding the size pattern of the extreme downside risk impact on stock returns where the impact is larger for small stocks. Accordingly, portfolio optimisation practice that focuses on tail risk should be more effective when applied to small stocks. In comparing the performance of mean-Expected Tail Loss against that of mean-variance across size groups of Fama and French’s (1993) sorted portfolios, we confirm this conjecture. Moreover, we further investigate the performance of different switching approaches between mean-variance and mean-Expected Tail Loss to utilise the suitability of these optimisation methods for specific market conditions. However, our results reject the use of any switching method. We demonstrate the reason switching could not enhance performance is due to the invalidity of the argument regarding the suitability of any optimisation method for a specific market regime.

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

Researchers recommended investing according to the long only momentum (MOM) strategy to generate excess returns for private investors. The general problem of this study was that it was unclear when to enter and when to exit declining financial markets to avoid larger losses and to improve the overall performance with the MOM strategy. Therefore, it was important to understand the influence of a timing indicator on the MOM strategy. The purpose of this study was to examine the relationship between different moving average (MA) settings, the MOM strategy, and the performance of the returns from the construction of small U.S. stock portfolios. The research question was what MA setting as a strategy adjustment could improve the MOM strategy performance for small portfolios of U.S. stocks. A quasi-experimental research design was chosen to answer this research question. For the methods and analysis, simple- and exponential- MA, 2 econometric models, and abnormal Sharpe ratios were computed on the sample basis of 30 Dow Jones Industrial Average (DJIA) stocks. The computations allowed me to determine the optimal trading frequencies for the MA MOM strategy. The key result was that the MA MOM strategy could improve the MOM strategy on average by 0.16% per month. The optimal trading frequency for the MA MOM strategy with $5,000 was tri yearly through which (0.90 - 1.85 %) net monthly return could be achieved. The MOM strategy can be adjusted by a simple moving average (SMA) indicator on a 6 versus 36-month basis as a recommendation. This study might contribute to positive social change by adjusting the MOM strategy, which specifically impacts private investors in declining stock markets to improve the overall performance when trading the MA MOM strategy.

Credit derivatives are among the most criticized financial instruments in the current credit crises. Given their short history, finance professionals are still researching to discover effective ways to reduce the mark-to-market (MTM) volatility in credit derivatives, especially in turbulent market conditions. Many credit portfolios have been struggling to find out appropriate tools and techniques to help them navigate the current credit crises and hedge mark-to-market volatility in their portfolios. In this study we provide a tool kit to help reduce the pricing fluctuations in structured credit portfolios utilizing data analysis and statistical methods. In Chapter One we provide a snapshot of credit derivatives market by summarizing different types of credit derivatives; including single-name credit default swaps (CDS), market credit indices, bespoke portfolios, market index tranches, and bespoke tranches (synthetic CDOs). In Chapter Two we illustrate a method to calculate a stable hedge ratio (beta) by combining industry practices and statistical techniques. Choosing an appropriate hedge ratio is critical for funds that desire to hedge mark-to-market volatility. Many credit portfolios suffered 40%-80% market value losses in 2008 and 2009 due to the mark-to-market volatility in their long positions. In this chapter we introduce ten different betas in order to hedge a long bespoke portfolio by liquid market indices. We measure the effectives of these betas by two measures: Stability and mark-to-market volatility reduction. Among all betas we present, we deduct that the following betas are appropriate to be used as hedge ratios: Implied Beta, Quarterly Regression Beta on Spread Levels, Yearly Regression Betas on Spread Levels, Up Beta, and Down Beta. In Chapter Three we analyze the risk factors that impact the MTM volatility in CDS tranches; namely Spread Risk, Correlation Risk, Dispersion Risk, and Curve Risk. We focus our analysis in explaining the risks in the equity tranche as this is the riskiest tranche in the capital structure. We show that all four risks introduced are critical in explaining MTM volatility in equity tranches. We also perform multiple regression analysis to show the correlations between different risk factors. We show that, when combined, spread, correlation, and dispersion risks are the most important risk factors in analyzing MTM fluctuations in equity tranche. Curve risk can be used as an add-on risk to further explain local instances. After understanding various risk factors that impact the MTM changes in equity tranche, we put this knowledge to work to analyze two instances in 2008 in which we experienced significant spread widening in equity tranche. Both examples show that a good understanding of the risks that drive MTM changes in CDS tranches is critical in making informed trading decisions. In Chapter Four we focus on two topics: Portfolio Stratification and Index Selection. While portfolio stratification helps us better understand the composition of a portfolio, index selection shows us which indices are more suitable in hedging long bespoke positions. In stratifying a portfolio we define Class-A as the widest credits, Class-B as the middle tier, and Class-C as the tightest credits in a credit portfolio. By portfolio stratification we show that Class-A has significant impact on the overall portfolio. We use five different risk measures to analyze different properties of the three classes we introduce. The risk measures are Sum of Spreads (SOS), Sigma/Mu, Basis Point Volatility (BPVOL), Skewness, and Kurtosis. For all risk measures we show that there is high correlation between Class-A and the whole portfolio. We also show that it is critical to monitor the risks in Class-A to better understand the spread moves in the overall portfolio. In the second part of Chapter Four, we perform analysis to find out which credit index should be used in hedging a long bespoke portfolio. We compare four credit indices for their ability to track the bespoke portfolio on spread levels and on spread changes. Analysis show that CDX.HY and CDX IG indices fits the best to hedge our sample bespoke portfolio in terms of spread levels and spread changes, respectively. Finally, we perform multiple regression analysis using backward selection, forward selection, and stepwise regression methods to find out if we should use multiple indices in our hedging practices. Multiple regression analysis show that CDX.HY and CDX.IG are the best candidates to hedge the sample bespoke portfolio we introduced.

El presente trabajo tuvo como objetivo principal el desarrollo de una metodología para la empresa RENUSA, que le permita identificar, categorizar, priorizar y autorizar el portafolio de proyectos de tecnologías de la información. Esta empresa comercializa repuestos y realiza mantenimiento de autos. El resultado de la aplicación de la metodología es obtener el máximo beneficio financiero y no financiero. Así mismo se determinó el nivel actual organizacional de la gestión del portafolio de proyectos. Así mismo se desarrolló cuatro capítulos, donde en el primer capítulo se definieron los términos y conceptos que sirvieron en la comprensión de la metodología y su aplicación, así como también los principales estándares de evaluación del grado de madurez organizacional de la gestión de proyectos. En el segundo capítulo, se desarrolló la situación actual de la empresa, donde se comprendió los objetivos estratégicos de la empresa, la estructura organizacional, la cadena de suministro, entre otros. Luego se definió la situación problemática y los objetivos específicos de solución. En el tercer capítulo, se planteó los alcances de la metodología de gestión de portafolio de proyectos bajo la metodología del PMI, adecuado al nivel de madurez objetivo de la organización, bajo el estándar OPM3. Así mismo, se profundizó en el estudio de la herramienta de decisión AHP, la cual se usó en la etapa de priorización, para alinear el portafolio a los objetivos estratégicos de la empresa. Finalmente, en el último capítulo se mencionó las conclusiones obtenidas, luego de la evaluación a la empresa, y las recomendaciones respectivas que permitirán mejorar la gestión de portafolio de proyectos en la empresa RENUSA. / The main objective of this work was to develop a methodology for the RENUSA company, which allows it to identify, categorize, prioritize and authorize the portfolio of information technology projects. This company sells parts and performs car maintenance. The result of the application of the methodology is to obtain the maximum financial and non-financial benefit. Likewise, the current organizational level of project portfolio management was determined. Likewise, four chapters were developed, where in the first chapter were defined the terms and concepts that served in the understanding of the methodology and its application, as well as the principles of the evaluation of the degree of maturity of the organizational project management. In the second chapter, the current situation of the company is described, which includes the strategic objectives of the company, the organizational structure, the chain supply, among others. Then the problematic situation and the specific objectives of the solution are defined. In the third chapter, the scope of the management of the project portfolio management, under the PMI standard, was considered appropriate to the level of objective maturity of the organization, under the OPM3 standard. Likewise, it deepened in the study of the decision tool AHP, which was used in the prioritization stage, to align the portfolio to the strategic objectives of the company. Finally, in the last chapter the conclusions are mentioned, then to evaluate the company, and the recommendations, refers to the management of the project portfolio in the RENUSA company. / Trabajo de investigación

As the relative capital value of major real estate investment grows, and investment risk continues to centralise, the requirement to diversify this risk through shared ownership has increased. This international trend toward increased co-ownership has been manifested in cross border collaborations and, with this sharing of risks has come the dilemma of preserving the operational integrity of these assets and the capital value of the fractional interests created. This thesis considers the process of valuation of fractional interests, examining the methods employed in both the real estate and securities investment communities, and it identifies the shortcomings of the current unstructured approach to the problem. It reveals the impact of improperly structured agreements between co-owners on the value of their interests and illustrates the enormity of this in terms of the Australian publicly traded real estate securities sector. This thesis concludes that the current deficiencies in fractional interest valuation methodologies can be effectively addressed through the adoption, by professional real estate valuers, of a common approach to the investigation of the factors influencing the value of fractional interests and the terms of agreements which underlie these interests / Doctor of Philosophy (PhD)

"July 1982." Bibliography: leaves 177-186. Examines the performance and policies of the Composite Fund of the University of Adelaide. Using performance measures suggested by modern portfolio theory which take explicit account of risk. Results show slight superior performance 1978-1982. Examines efficiency of Australian share market and the consequences for investment strategy. Suggests a variety of policy measures as alternatives for the Fund and emphasizes the benefits of using analytical techniques and empirical investigation in the areas of investment policy, performance measurement and monitoring of risk.

This thesis presents two research projects examining the relationship between top management turnover (i.e. investment directors of funds management firms) and the performance of actively managed Australian institutional funds. Khorana (1996, 2001) studies this relationship from purely a performance perspective using U.S. managed funds. This thesis extends the work of Khorana (1996, 2001) by providing investors and other stakeholders with empirical evidence on performance, sources of performance and the dynamics of portfolios in the pre-and-post replacement periods. This issue is significant given the importance of executive management in the implementation of the institution's investment strategy, the sizeable assets under their control, as well as the overall success and profitability of the funds management operation. In addition, investors, asset consultants, managed fund ratings agencies and the financial media devote significant resources in scrutinizing the performance, organizational activities, leadership and human capital of investment management firms. Accordingly, the first research project examines the impact of performance and fund flow activity on top management turnover in both the pre-and-post replacement periods. The research documents that turnover of underperforming investment managers results in significantly higher performance in the post-replacement period, while turnover coinciding with outperforming managers delivers investors significantly lower returns (risk-adjusted). The evidence also identifies significant changes in portfolio risk associated with managerial turnover. Finally, the study finds that underperforming investment managers exhibit significantly lower fund flows prior to replacement. The second research project represents the first rigorous analysis of top management turnover with respect to monthly portfolio holdings for a sample of actively managed Australian equity funds. An examination of the dynamics of portfolios surrounding both the departure and the arrival dates of investment managers provides a finer decomposition in understanding investment performance, the sources of value added and the extent to which momentum strategies are executed both pre-and-post the turnover event. Accordingly, the study examines a manager's success or failure depending on 'winner' and 'loser' stock holdings, portfolio turnover, reliance on momentum strategies, variation in portfolio risk, stock preferences and fund flows for underperforming versus outperforming investment directors in the pre-and-post replacement periods. The research also documents that new investment managers of previously underperforming portfolios exhibit superior stock-selections skills in the post-replacement period, therefore reversing the portfolio's previously poor performance. The study finds that new investment managers liquidate 'loser' stocks (i.e. cleaning out the portfolio) as well as decreasing the portfolio's concentration (i.e. increases the portfolio's diversification and lowering tracking error). The results also indicate that underperforming investment managers in the pre-replacement period exhibit a preference for larger stocks (i.e. more liquid stocks with greater relative benchmark weights in the index), growth-oriented securities and a preference towards riding past period winners (i.e. following momentum strategies), however they are unable to successfully select and exploit momentum stocks. On the other hand, incoming managers of underperforming portfolios in the pre-replacement period do not show any particular stock size preference. The study also shows these managers prefer growth stocks, do not rely on momentum strategies, and yet still display superior returns in the post-replacement period. The study also documents that new investment managers of previously outperforming portfolios are unable to replicate the performance of the previous head of equities. In terms of stock preferences related to superior performing portfolios, the results show that departing investment managers prefer larger stocks and select stocks based on momentum strategies. On the other hand, incoming investment managers have a greater preference for smaller stocks, are less reliant on momentum strategies and prefer more volatile securities, however, these strategies do not provide superior returns relative to the pre-replacement period.