Institutional-Repository, University of Moratuwa
Welcome to the University of Moratuwa Digital Repository, which houses postgraduate theses and dissertations, research articles presented at conferences by faculties and departments, university-published journal articles and research publications authored by academic staff. This online repository stores, preserves and distributes the University's scholarly work. This service allows University members to share their research with a larger audience.
 Research Publications |  Thesis & Dissertation |  E- Books |
 UoM Journal Publications |  UoM Conference Proceedings |  Articles published in Scimago's Q1 journals |  UoM Research Reports |  Other Articles authored by UoM staff |
Recent Submissions
item: Thesis-Abstract
Analysis of stock market reactions to quarterly financial results in banking sector of Colombo Stock Exchange
(2023) Perera, HPJ; Karunananda, GACM; Dencil , JADM
This research “Analysis of Stock Market Reactions to Quarterly Financial Results in Banking Sector” is completed by using daily stock prices of CSE in banking sector from 2013 to 2020. The aim of this research is to identify whether investors buy and increase the demand for a stock if the quarterly financial results give positive indications and vice-versa for negative indications. Hence the focus shall be to detect whether there is a discernable relationship between a company's financial success in a certain quarter and the subsequent returns observed in its return. Under this main objective, volatility pattern of the stock return was analyzed by using symmetric and asymmetric model. Apart from that, appropriate Generalized Autoregressive Conditional Heteroscedastic (GARCH) family models were built for S & P SL 20 companies in banking sector. This study was included five main banking sector companies in S & P SL 20 companies. This study finds that the market has weak-form efficiency. In that event (n=2), Mean equation shows that the effect of event has spread between -4% to +27% and also volatility of effect of event has spread between -10% to +10%. Considering other events, mean equation shows that the effect of event have spread between -7% to 10% and also volatility of effect has varied between -8 to 6%.Quarterly financial result shows the financial health and growth of the company. Quarterly financial results are helping investors to make smart strategic decisions.
item: Thesis-Abstract
Comparison of ARIMA and SAMA circular models for stock price prediction for selected companies
(2023) Chiranthi, KU; Edirisinghe, PM
In rapidly moving world, a complimentary source of income for any individual has become essential requirement. Investors are very fond of stock prices to make their benefits and so they more concern about the future of the stock market. The stock market is going increase because of investors for their submissive income. Selecting stocks for marketing is actually a rough job and person could not trade without having a clear analysis and the background study of the particular stock. Scientific forecasting techniques get hold on the place of lighthouse in share market investments and it is divided in to two parts as statistical techniques and soft computing techniques. This study is aimed on univariate statistical techniques with Auto Regressive Integrated Moving Average method(ARIMA) and Sama Circular Model(SCM). Literature revealed that some major weaknesses of ARIMA model and SCM minimizing those weaknesses.
This study is based on monthly stock prices and limited 5 years and 5 companies of listed companies of Colombo stock Exchange (CSE). Practical steps which need to be undertaken to use SCM and ARIMA models are used to stock price prediction. The results revealed that SCM is superior to ARIMA and SCM can be applied to every seasonal and cyclical variations.
item: Thesis-Abstract
Determinants of electricity demand in Sri Lanka, univariate and multivariate time series approach
(2024) Wickramanayake, MTAR; Talagala, PD
Studying energy consumption problems has become an important topic of research in recent decades. Efficient energy distribution planning necessitates accurate forecasts of future demand in order to achieve a balance between energy supply and demand. This study was conducted by focusing on developing a demand model for forecasting electricity demand in Sri Lanka. A univariate and multivariate model were focused on forecasting the electricity demand. Economic variables, including gross domestic product, foreign direct investment, inflation rate, population, average unit price, and number of consumer accounts, were used for the multivariate analysis. Data relevant to economic variables and electricity demand was collected from 1969 to 2020. Under the univariate analysis, naive, drift, and mean models were used as benchmark models, and exponential smoothing (ETS) and the ARIMA model were used further for the analysis. Under the multivariate analysis, the Granger causality test was used to identify the nature of the relationship between each economic variable and the electricity demand in Sri Lanka. A VAR modeling approach was used to build up a relationship model between the electricity demand and the selected economic variables under the Granger causality test. Forecast error was used to select the best model. According to the univariate analysis, as per the forecast error calculations, ARIMA(0,2,1) was found to be the best univariate model. The Granger Casualty test under the multivariate analysis indicated that foreign direct investment and average unit price Granger cause the electricity consumption in Sri Lanka. Based on an overall analysis of forecast errors, the VAR model demonstrates superior statistical fitness compared to both univariate and other multivariate analysis for predicting electricity demand in Sri Lanka.
item: Thesis-Abstract
Estimation of bearing capacity of driven piles using numerical modeling
(2024) Fernando, VNC; Priyankara, NH
Pilling is a blend of art and science. While choosing a suitable pile type and the installation method lie in the artistic aspect, scientific dimensions allow engineers to study the behavior of installed elements under different types of loading. The nature of the interaction between a pile and the soil it contacts is significantly influenced by the method of installation used. This interaction cannot be accurately predicted based solely on the physical properties of the materials involved. Different methods are used to determine the bearing capacity of piles, including static equations, dynamic equations, empirical methods, numerical methods, computer software programs, and pile static load tests. However, it is important to note that each of these approaches may yield different values for the bearing capacity of piles, and rarely do any two methods produce identical computed capacities. According to Randolph M. F. (1992), achieving precise estimates of axial pile capacity in various soil types is a challenge and often results in a margin of error of approximately ±30% During the last few decades, there has been swift and substantial progress in the analytical methods employed in pile design. This advancement not only validated traditional empirical approaches but also led to their replacement with more robust theoretical foundations. In intricate geotechnical projects, when dealing with complex load combinations or substantial interaction with adjacent structures, engineers often turn to the Finite Element Method (FEM) for analysis. However, an exception to this trend is observed in the design of driven piles or soil- displacement piles, where a different approach is typically employed to determine factors such as pile capacity and performance. In the modeling of displacement piles, it is essential to compile the installation effects resulting from different installing techniques with the most applicable constitutive model to obtain an accurate result by simulating real soil behavior. With the evolution of computational power, different numerical techniques can be employed successfully in standard FE analysis using soil parameters obtained from cost-effective site investigations to lead to a more realistic load- settlement response for driven piles or soil-displacement piles.
item: SRC-Report
Design and development of detection and extinguishing system for forest fire using sensor networks, aerial and ground robots [abstract]
(2017) Chathuranga, KVDS; Guha, P; Lalitharathne, , SWHMTD; Mukhija, P; Gopura, RARC
Forests are an important component in the ecosystem. Due to natural and human interventions, these forests can get destroyed. Forest fires are such cause where unimaginable damage to the eco system, and property is inflicted. Therefore, early detection and extinguishing such fires would be a benefit. This report presents such a detection and extinguishing system that uses wireless sensor network to predict and detect forest fires and an automated robot system to extinguish such fires.
Wireless sensor nodes with temperature sensors, humidity sensors, pressure sensors, CO2 sensors and LoRa module are distributed in a 2m×2m size grid and data obtained by that system is used to train an artificial neural network to classify if a fire is present in that particular grid or not. Construction and the operation of this sensor network is explained in this report.
Furthermore, the design and the evaluation of the ground robot used for extinguishing the forest fire is presented and an experiment conducted to validate the system is introduced. SRC/Grant Close/2019/V1 The sensor network can classify a fire starting in one of its grids with about 65% accuracy and the automated robot has the ability to extinguish such a fire.