Browsing by Author "Ranasinghe, LP"

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item: Thesis-Full-text
Portfolio optimization through quadratic Programming when there is perturbation in the return matrix
Dharmathilaka, NT; Dissanayake, AR; Ranasinghe, LP
According to Finance the investor who invests in risky assets such as stocks, after forming a diversified portfolio or collection of securities; is interested in earning maximum return out of minimum risk, and it is more technically known as Portfolio Optimization(PO). The present problem is a Quadratic Programming problem is consisted of simultaneous variations of initial return vector of each company. In this study the main objective was to study the behavior of covariance-variance matrix, correlation matrix and the optimum weights vector when there is small perturbation in the mean return vector. Then fitting a model between perturbation values versus optimum weights was also performed. The results show that there is a significant variation of optimum weights when there is small perturbation in the return matrix. And there is no change in the covariance or correlation matrices. This is done under the assumption that there is no short selling. Apart from that results show that when there is perturbation in the return matrix the expected return of the portfolio is also changing. When the value of perturbation is increased individually for one company only, to drive away at least one company from the optimum weights (to zero the optimum weight of one company) it was observe that the perturbation value should be increased extensively for the SGX data sample. That means the weights are not very much sensitive to perturbations in the market. If negatively mean companies are removed and perturbation is done for positively mean companies the effort to remove at least one company from the optimum weights is less.
item: Thesis-Abstract
Portfolio optimization using quadratic programming
(2014-08-14) Ranasinghe, LP; Cooray, TMJA; Dissanayake, R
Investment analysis is concerned, portfolio optimization is very important in order to get maximum profit. In the proposed research the optimization will be done in two main steps. The first part is the modelling mean variance so called reward and risk. The second part is finding optimum solution. The data set published by the Colombo Stock Exchange was used for this research paper as the raw data. The following five companies are selected for the analysis without biases those are Commercial bank, John Keells, Lanka Hospital, The Sri Lanka Telecom and The United motors. These companies represent several fields in the Sri Lankan market such as banking, group of companies, health service, semi government companies, automobile sector. The objective of the research is to find the optimum allocation of the portfolio. The risk should be minimized and the reward should be maximized at the same time. As a strategy to do both of these simultaneously, the linear combination with controlling arbitrary constant is used. That particular linear combination is a convex quadratic function. In order to find the solution of this, the numerical method is used via MATLAB inbuilt'm file'. The developed model of the Markowitz portfolio optimization model1 could be formulated in order to find the optimum allocation of investment amounts for any number of investment channels. The model can be used by investment researchers and could be applied to gain an analytical idea about the efficient frontier. The model has a parameter that can change emphasis on risk minimization or reward maximization. The portfolio optimization finds the optimum allocation of money to be invested. The optimum allocation depends on several factors, according to Markowitz, the return as well as risk, should be considered simultaneously. The main model for this research is 'Markowitz Portfolio Selection Model'. The objective function of the above model consists a linear combination of risk and return. Since the risk is a quadratic expression, the objective function can also be considered as a quadratic function. Then the normal optimization cannot be applied and the non linear optimization (quadratic optimization) must be applied. The main constraint that can be identified is the budgetary constraint along with other limitations, such as boundary restraints. The model has the advantage of changing the budget at any time and the user can use the total budget as a unit, then the optimum allocation fractions, for each investment can be found. The optimization calculation is carried out through 'Matlab', computer aided calculation software. The output of the optimization model is the ratio of the total investment amount to be allocated, the allocated in the percentages of the total portfolio for Commercial Bank, John Keells, Lanka Hospital, Sri Lanka Telecom and United Motors respectively as 0%, 0%, 62%, 38%, and 0%. The minimum function value is - 0.0907, and the function stands for the linear combination of the risk and the reward.
item: Thesis-Full-text
Pragmatic portfolio optimization : gauging black-litterman model in emerging markets
Sivathas, K; Dissanayake, AR; Ranasinghe, LP
With the advent of modern portfolio theory1 in 1952 by Harry Markowitz, the investment management industry had witnessed an uprising. Yet the encountered shortfalls and rigidity of the methodologies lead to the development of Black- Litterman model by 1990s. The Black- Litterman model addressed those deficiencies and introduced the luxury of incorporating the unique views of Asset managers about the assets under management in their portfolios. This projected research efforts implementing the difficult phases of the Black-Litterman model and depicts its practical and pertinent nature by comparing to other portfolio allocation methods which uses the historical and CAPM methods. The modeling of mean variance (reward and risk) and then the portfolio allocation has been done using these three distinct methods. Thereafter the benevolent leads of the BL method over others have been discussed. To assess the BL model, eight stocks such as Samsung Electronics Co., Ltd (SAMSUNGKorea), China Mobile Communications Corporation (CHINA MOB- China), Naspers Limited (NASPERS-South Africa), Emaar Properties (EMAR- United Arab Emirates), Koc Holding AS (KCHOL- Turkey), Akbank (AK BANK- Turkey), Braskem SA (BRKM5- Brazil) and Taiwan Cement Corporation (TAIWAN CE- Taiwan) which comes under Emerging markets have been considered. For the analysis, the monthly stock closing prices published by Bloomberg L.P. have been taken. In addition to this the monthly closings of the MSCI Emerging Markets Index and US Treasury rates have been obtained to use respectively as the market benchmark and market risk free rate. Four outlooks/views about these stocks were evaluated and the vector of BL Expected Excess Return which is the weighted average of Equilibrium market return vector and the View vector have been established using the Black- Litterman model. The grandeur of the BL method that’s tailored portfolio weightages corresponding the Asset managers’ views was studied. The model has been implemented using the scientific software MATLAB. Other than the Black-Littreman methodology, the concepts of Markowitz portfolio theory, efficient frontier, CAPM returns, Portfolio expected returns, Portfolio variances and the Sharp ratios have been used to describe the portfolio dynamics. The portfolio weightages derived using BL Expected Excess Returns did accord with the four views. It has been clearly witnessed that the incorporation of View vector, had caused the Equilibrium market return vector to get adjusted with respect to the outlooks/views.
item: Thesis-Abstract
Preservation of architectural icon : symbiotic relationship between new and old
Ranasinghe, LP; Gamage, A
The constant urge for urbanization and high density living has its toll on the old and the more nostalgic buildings, that tells its own stay of means evolution. Thus, these two conflicting interests are forced to confront each other in the name of development. The obvious solution, therefore in this situation is the preservation/ conservation and finally reutilization of the old for the new. The inherent problem in this exercise is the reutilization of architectural icons, in ensuring this transformation of functions more meaningful. In other words, where posture symbiotic relationship between the old and the new does not exist the buildings lack meaning and eventually way lead to chaos due to conflicts between the icon and functions. Thus in conservation, it is essential that this relationship is upheld and maintained in striking at a perfect balance of elements and spaces between contrast and harmony that complements each other in conservation and reutilization of icons in the modern day context while ensuring the integrity of the icon.