This thesis investigates the application of principal component analysis to the Australian stock market using ASX200 index and its constituents from April 2000 to February 2014. The first ten principal components were retained to present the major risk sources in the stock market. We constructed portfolio based on each of the ten principal components and named these “principal portfolios

Bakgrund: Avkastningsstiftelse är en mycket speciell organisationsform vars syfte är att förvalta ett givet kapital och bruka dess avkastning för att främja ett uppsatt ändamål. Kapitalförvaltningens utformning får således stor inverkan på i vilken utsträckning dessa stiftelser kan främja deras ändamål och därmed uppnå deras syften. Dessa ändamål är i majoriteten av fallen allmännyttiga varför stiftelser spelar en viktig roll som resurstillförare i samhället. En genomgång av forskningen inom området visade att tidigare studier främst fokuserat på stiftelser som väsen i Sverige eller deras roll inom filantropin varför vi fann det intressant att genomföra en studie med fokus på deras kapitalförvaltning. Syfte: Syftet med denna uppsats är att kartlägga och analysera svenska avkastningsstiftelsers kapitalförvaltning med fokus på investeringsprocessen och riskhantering, givet restriktioner och uppsatta mål. Genomförande: Studien är en kvalitativ flerfallstudie inom vilken åtta intervjuer genomfördes med personer med insyn i stiftelserna i urvalets kapitalförvaltning. Även dokumentstudier genomfördes, dels för att skapa studiens referensram och dels som ett komplement till empirin insamlad via intervjuerna. Den insamlade data analyserades sedan i relation till etablerad finansiell teori och beprövad erfarenhet med fokus på investeringsprocessen samt riskhantering. Slutsats: Undersökningen av avkastningsstiftelsernas praktiska kapitalförvaltning har visat att stiftelserna i överlag inte utformat sin kapitalförvaltning fullt ut i enlighet med teorin och den beprövade erfarenheten inom ramen för denna studie. Stiftelsers speciella situation och begränsningar anses generellt sett ej ligga till grund för detta. Möjliga skäl vilka diskuteras är misstro på modellernas funktionalitet, att förvaltarna fallit offer för psykologiska snedvridningar samt kostnadsaspekten. / Background: A Swedish grant making foundation is a very special organizational form with the purpose to manage a given amount of capital and use the capital returns to fulfill a certain purpose. The design of the portfolio management therefore has a large impact on to which extent these foundations can fulfill their purposes. The purposes are generally of benefit for the society, thus foundations play an important role as a contributor of resources to the Swedish society. In our review of previous research we found that earlier studies mainly focused on foundations as an organizational form in Sweden or on their role in philanthropy why we found it interesting to conduct a study focusing on their portfolio management. Purpose: The purpose of this study is to identify and analyze the portfolio management of Swedish grant making foundations focusing on the investment process and risk management, given constraints and set goals. Completion: This study is a qualitative multi-case study within which eight interviews were conducted with people with insight in the portfolio management of the foundations in the sample. Document studies were also conducted in order to create the frame of references of the study and as a complement to the information collected via the interviews. The collected data was then analyzed in relation to established financial theory and well-tried experience focusing on the investment process and risk management. Conclusion: The examination of the grant making foundations’ portfolio management showed that the foundations, in general, have not fully designed their portfolio management in accordance with the theoretical models and well-tried experience which are analyzed inrelation to in this study. The foundations’ special situation and restrictions are generally not found to be the basis for this. Possible reasons discussed were disbelief in the functionality of the models, the portfolio managers being victims to psychological biases and the cost issue.

No description available.

Optimal investment decisions often rely on assumptions about the models and their associated parameter values. Therefore, it is essential to assess suitability of these assumptions and to understand sensitivity of outcomes when they are altered. More importantly, appropriate approaches should be developed to achieve a robust decision. In this thesis, we carry out a sensitivity analysis on parameter values as well as model speci cation of an important problem in portfolio management, namely the optimal portfolio execution problem. We then propose more robust solution techniques and models to achieve greater reliability on the performance of an optimal execution strategy. The optimal portfolio execution problem yields an execution strategy to liquidate large blocks of assets over a given execution horizon to minimize the mean of the execution cost and risk in execution. For large-volume trades, a major component of the execution cost comes from price impact. The optimal execution strategy then depends on the market price dynamics, the execution price model, the price impact model, as well as the choice of the risk measure. In this study, rst, sensitivity of the optimal execution strategy to estimation errors in the price impact parameters is analyzed, when a deterministic strategy is sought to minimize the mean and variance of the execution cost. An upper bound on the size of change in the solution is provided, which indicates the contributing factors to sensitivity of an optimal execution strategy. Our results show that the optimal execution strategy and the e cient frontier may be quite sensitive to perturbations in the price impact parameters. Motivated by our sensitivity results, a regularized robust optimization approach is devised when the price impact parameters belong to some uncertainty set. We rst illustrate that the classical robust optimization might be unstable to variation in the uncertainty set. To achieve greater stability, the proposed approach imposes a regularization constraint on the uncertainty set before being used in the minimax optimization formulation. Improvement in the stability of the robust solution is discussed and some implications of the regularization on the robust solution are studied. Sensitivity of the optimal execution strategy to market price dynamics is then investigated. We provide arguments that jump di usion models using compound poisson processes naturally model uncertain price impact of other large trades. Using stochastic dynamic programming, we derive analytical solutions for minimizing the expected execution cost under jump di usion models and compare them with the optimal execution strategies obtained from a di usion process. A jump di usion model for the market price dynamics suggests the use of Conditional Value-at-Risk (CVaR) as the risk measure. Using Monte Carlo simulations, a smoothing technique, and a parametric representation of a stochastic strategy, we investigate an approach to minimize the mean and CVaR of the execution cost. The devised approach can further handle constraints using a smoothed exact penalty function.

This thesis investigates implications of interdependence between stock market prices in the context of several financial applications including: portfolio selection, tests of market efficiency and measuring the extent of integration among national stock markets. In Chapter 2, I note that volatility spillovers (transmissions of risk) have been found in numerous empirical studies but that no one, to my knowledge, has evaluated their effects in the general portfolio framework. I dynamically forecast two multivariate GARCH models, one that accounts for volatility spillovers and one that does not, and construct optimal mean-variance portfolios using these two alternative models. I show that accounting for volatility spillovers lowers portfolio risk with statistical significance and that risk-averse investors would prefer realised returns from portfolios based on the volatility spillover model. In Chapter 3, I develop a structural MGARCH model that parsimoniously specifies the conditional covariance matrix and provides an identification framework. Using the model to investigate interdependencies between size-sorted portfolios from the Australian Stock Exchange, I gain new insights into the issue of asymmetric dependence. My findings not only confirm the observation that small stocks partially adjust to market-wide news embedded in the returns to large firms but also present evidence that suggests that small firms in Australia fail to even partially adjust (with statistical significance) to large firms??? shocks contemporaneously. All adjustments in small capitalisation stocks occur with a lag. Chapter 4 uses intra-daily data and develops a new method for measuring the extent of stock market integration that takes into account non-instantaneous adjustments to overnight news. This approach establishes the amounts of time that the New York, Tokyo and London stock markets take to fully adjust to overnight news and then uses this This thesis investigates implications of interdependence between stock market prices in the context of several financial applications including: portfolio selection, tests of market efficiency and measuring the extent of integration among national stock markets. In Chapter 2, I note that volatility spillovers (transmissions of risk) have been found in numerous empirical studies but that no one, to my knowledge, has evaluated their effects in the general portfolio framework. I dynamically forecast two multivariate GARCH models, one that accounts for volatility spillovers and one that does not, and construct optimal mean-variance portfolios using these two alternative models. I show that accounting for volatility spillovers lowers portfolio risk with statistical significance and that risk-averse investors would prefer realised returns from portfolios based on the volatility spillover model. In Chapter 3, I develop a structural MGARCH model that parsimoniously specifies the conditional covariance matrix and provides an identification framework. Using the model to investigate interdependencies between size-sorted portfolios from the Australian Stock Exchange, I gain new insights into the issue of asymmetric dependence. My findings not only confirm the observation that small stocks partially adjust to market-wide news embedded in the returns to large firms but also present evidence that suggests that small firms in Australia fail to even partially adjust (with statistical significance) to large firms??? shocks contemporaneously. All adjustments in small capitalisation stocks occur with a lag. Chapter 4 uses intra-daily data and develops a new method for measuring the extent of stock market integration that takes into account non-instantaneous adjustments to overnight news. This approach establishes the amounts of time that the New York, Tokyo and London stock markets take to fully adjust to overnight news and then uses this

Thesis (Ph.D.)--University of Wollongong, 2007. / Typescript. Includes bibliographical references: leaf 303-338.

Univ., Diss.--St. Gallen, 2004.

Univ., Diss.--Zürich, 2007. / ALM = Asset- und Liability Management. - CVaR = Conditional Value-at-Risk.

Univ., Diss.--München, 2008.

Calif., Univ., Dep. of Management Science and Engineering, Diss.--Stanford, 2002. / Kopie, ersch. im Verl. UMI, Ann Arbor, Mich.