13th Students’ Research Symposium 2023/2024
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Item The Month of the Year Effect of Stock Returns: Empirical Evidence from the Colombo Stock Exchange(Department of Finance, Faculty of Commerce and Management Studies, University of Kelaniya, Sri Lanka., 2025) Anubuddhika, D. G. J.; Madhushani, P. W. G.Introduction: The Efficient Market Hypothesis (EMH) assumes that stock prices fully reflect all the available information ensuring stock market efficiency. The prevalence of seasonal effects leads to market efficiencies, enabling investors to reap abnormal returns. The purpose of this study is to investigate the existence of the January effect of the All-Share Price Index (ASPI) on the Colombo Stock Exchange (CSE), which is supported by the previous findings considering how the most significant economic events in Sri Lanka affect this phenomenon. Methodology: This study examines the stock market anomalies focusing on 10 years of ASPI monthly returns from 2014–2024, which were converted into natural logarithm returns. To address the existence of ARCH effects in the residuals, such as GARCH and EGARCH, apart from the OLS regression model. Findings: Even though there is a negative January effect, the results indicate that there is a positive July effect for the full period, a positive April effect for the pre-crisis period and a significant negative March effect for the post- and recovery period (after 2022). Conclusion: According to the results, EMH is a contradiction as the results exhibit that there are anomalies during the full period, pre-crisis, and post-crisis period. In conclusion, CSE is not a weak form efficient suggesting that investors can earn abnormal returns by applying investment strategies observing historical stock patterns.Item The Impact of Exchange Rates on Stock Market Performance in Sri Lanka(Department of Finance, Faculty of Commerce and Management Studies, University of Kelaniya, Sri Lanka., 2025) Rajapaksha, R. A. R. A.; Gunasekara, A. L.Introduction: The relationship between exchange rates and stock market performance in developing economies is a topic of great interest to investors, researchers and policymakers. This paper examines the impact of exchange rates on the S&P SL20 index in Sri Lanka. This includes the exchange rate behavior of the USD, EUR, GBP, AUD and JPY against the Sri Lankan rupee. Apart from other factors in the economy, the behavior of exchange rates has made a difference in economic development and investor decisions. Therefore, the purpose of the research is to explore the relationship between exchange rates and the stock market in Sri Lanka in the short and long term. Methodology: This paper used monthly data from January 2010 to July 2024. After conducting unit root tests using ADF analysis for stationarity of all variables, the strength of association between the dependent and independent variables is measured through a correlation analysis. The ARDL model elaborates on the short- and long-run impacts, as well as using a GARCH model that captures the effect of the volatility of exchange rates on stock market returns. Descriptive statistics represent data development through the study period with the help of tables or graphs. Findings: Descriptive statistics show positive means for all variables but non-normal distributions with skewness and kurtosis. The ADF test confirmed stationarity, thus enabling further analysis. The USD has a significant negative impact, and both short- and long-run dynamics are highlighted through the ARDL model. The ARCH test does not show heterogeneity, while the GARCH model confirms volatility clusters and emphasizes the strong influence of the USD. The results emphasize that not all exchange rate movements have the same impact on the performance of the S&P SL20, and that some currencies strongly determine its performance. Conclusion: This paper highlights the relationship between exchange rates and stock market performance in Sri Lanka. Foreign exchange stability is important for market outcomes and suggests currency stabilization strategies that minimize market crashes. Investors should consider how to manage their investments against the exchange rate to maximize returns when investing in the stock market. Due to the large differences between past literature reviews and the current database and the differences in the variables considered, the current research is bound to shed new light on the short-run and long-run relationship.Item The Effect on Stock Market Volatility on Stock Prices By Using The Methods of Arch, Garch, And Egarch in Colombo Stock Exchange, Sri Lanka(Department of Finance, Faculty of Commerce and Management Studies, University of Kelaniya, Sri Lanka., 2025) Shajida, M. S. F.; Kethmi, G. A. P.Introduction: The purpose of the study is to examine the effect on stock market volatility on stock prices by using the methods of ARCH, GARCH, and EGARCH in Colombo Stock Exchange, Sri Lanka. Methodology: The researcher has chosen the S&P SL 20 Index in CSE, Sri Lanka for the study. In this regard, the secondary data was collected from the official website of CSE. Daily historical stock prices were the independent variables and forecasted stock volatility was the dependent variable. The model has been done using EViews 12 SV. 10 years span of data has been analyzed to find the most accurate forecasting model and the deviation between actual volatility and forecasted volatility. To check the accuracy between actual and the forecasted volatility, the error measurements called MAE, RMSE, MAPE, and TU were used. Findings: According to the study's findings, all three models confirmed that there is a significant relationship between actual and forecasted volatility, evident through the model's ability to capture key market patterns, including volatility clustering and persistence. While each model offers unique strengths, the ARCH model emerges as the most balanced option for general use. EGARCH is particularly useful in markets with asymmetrical responses, and GARCH provides reliable short-term forecasting but is less consistent overall. Conclusion: ARCH consistently performs well, making it the most balanced and reliable model overall. EGARCH effectively captures percentage errors and handles market asymmetries, proving useful for conditions requiring specific percentage accuracy. Finally, GARCH performs best in minimizing large deviations but falls short on other metrics, placing it behind ARCH and EGARCH in terms of consistent forecast reliability. The final result ranking emphasizes ARCH as the top choice for balanced accuracy, followed by EGARCH for specialized contexts, with GARCH providing strong but slightly less consistent performance.Item The Effect of Capital Structure on Firm Performance: Evidence from Listed Diversified Financials Sector Companies in Colombo Stock Exchange: Pre- Crisis vs. Economic Crisis(Department of Finance, Faculty of Commerce and Management Studies, University of Kelaniya, Sri Lanka., 2025) Ishanka, G. A. C.; Gunasekara, H. M. A. L.Introduction: This study investigates the impact of capital structure on the financial performance of diversified financial sector companies listed on the Colombo Stock Exchange (CSE) during pre-crisis (2014–2020) and crisis (2021–2023) periods. The objectives of the study are to evaluate the strength of the causal relationship between capital structure and firm performance of the listed diversified financial sector companies between the periods of 2014-2023 and to check whether there is a statistically significant impact between the capital structure and firm performance of the listed Diversified Financial sector companies before and during the economic crisis periods (2014-2023). This study addresses this gap by examining the effect of debt on three key performance metrics: Return on Capital Employed (ROCE), Return on Assets (ROA), and Tobin’s Q. Methodology: The research follows a quantitative approach using secondary data from 27 listed diversified financial firms. Panel data regression will be used for the analysis to evaluate the relationship between capital structure and firm performance, with firm age, size, tangibility, and sales growth as control variables. The economic crisis is incorporated as a dummy variable to assess its effect on firm performance. Descriptive statistics and t-tests are used to identify differences in firm performance between pre-crisis and crisis periods. Findings: The findings indicate a significant negative relationship between the debt-to-equity ratio and all three performance indicators (ROCE, ROA, and Tobin’s Q) and ROA, ROCE are significantly impacted by the Economic Crisis and Tobin’s Q is not impacted by the Economic Crisis. Conclusion: Capital Structure and Firm Performance is a highly discussed topic among researchers. However, studies done on specific sectors are very rare in the Sri Lankan context. Furthermore, the study has incorporated the economic crisis as well. Therefore, this study will provide insights into future research on this topic.Item The Effect of Capital Structure on Firm Performance: Evidence from Listed Capital Goods Sector in Colombo Stock Exchange: Pre-Crisis vs. Economic Crisis(Department of Finance, Faculty of Commerce and Management Studies, University of Kelaniya, Sri Lanka., 2025) Madhushika, N. G. S.; Gunasekara, H. M. A. L.Introduction: This study investigates the impact of capital structure on the financial performance of firms in the capital goods sector listed on the Colombo Stock Exchange (CSE) in Sri Lanka. The analysis covers the period from 2014 to 2023, distinguishing between the pre-crisis (2014-2020) and economic crisis (2021-2023) periods to understand the role of the economic crisis as a dummy variable. Firm performance is measured using Return on Assets (ROA), Return on Capital Employed (ROCE), and Tobin’s Q, while the debt-to-equity ratio serves as the independent variable. Control variables include firm size, age, tangibility, and sales growth. Methodology: Using a quantitative approach, secondary data from 22 listed firms were analyzed using panel data regression through descriptive analysis, correlation analysis, panel regression analysis, and t-tests. The study used a positivism approach. Random effect panel regression models were used to analyze the data. Findings: The findings indicate a significant negative relationship between the debt-to-equity ratio and all three performance indicators (ROCE, ROA, and Tobin’s Q) and ROA, ROCE are significantly statistically impacted by the Economic Crisis and Tobin’s Q is not statistically impacted by the Economic Crisis. Conclusion: The study concludes that higher debt ratios negatively affect firm performance, with this impact being more pronounced during an economic crisis. The findings highlight the need for firms to adopt timely capital structure decisions, especially in uncertain economic conditions.Item The Day of the Week Effect of Stock Returns: Empirical Evidence from the Colombo Stock Exchange(Department of Finance, Faculty of Commerce and Management Studies, University of Kelaniya, Sri Lanka., 2025) Rupasingha, P. H. P. H.; Madhushani, P. W. G.Introduction: The purpose of this study is to investigate the Day-of-the-Week Effect on stock returns in the Colombo Stock Exchange (CSE), examining whether specific days consistently exhibit abnormal returns. By analyzing the All-Share Price Index (ASPI) data from 2014 to 2024, the research explores how economic crises, such as the Easter Sunday Attack (2019), the COVID-19 pandemic, and Sri Lanka’s financial collapse (2022), influenced these anomalies. Methodology: Statistical techniques, including Ordinary Least Squares (OLS) regression and unit root tests, confirmed the presence of significant daily return patterns. The data sample consists of daily stock returns of all companies listed on the All Share Price Index (ASPI) from April 2014 to April 2024. The data was analyzed in two distinct periods: pre-crisis (2014–2019) and post-crisis recovery (2019–2024). Secondary data was used and retrieved from the CSE website. Findings: Mondays consistently recorded negative returns across all periods, suggesting a “Monday effect.” Thursdays showed the most significant positive returns, particularly during the post-crisis recovery period (2019–2024). Conclusion: The study confirms the existence of the day-of-the-week effect in the Colombo Stock Exchange, with distinct variations during economic crises and recovery periods. These findings underscore the need for further exploration into behavioural finance and its role in emerging markets. Future studies should include cross-market analyses to broaden understanding and applicability. The study provides recommendations to investors and policymakers; investors can understand these patterns and use them to enhance their trading strategies, optimizing buy-sell decisions based on predicted daily returns. Policymakers can gain insights into market inefficiencies and offer opportunities to improve regulatory frameworks and foster greater stability.Item Stock Split Announcements and Their Impact on the Short Run Stock Price Performance: An Analysis of the Pre and Post Pandemic Stock Split Announcements in the Colombo Stock Exchange(Department of Finance, Faculty of Commerce and Management Studies, University of Kelaniya, Sri Lanka., 2025) Ratnayake, D. M. W.; Kethmi, G. A. P.Introduction: This study was done in order to analyse the short-run impact of stock split announcements in the Colombo Stock Exchange of Sri Lanka through a comparison of announcements made during the Pre-Covid and Post-Covid periods. With the use of secondary data, the event study methodology was used to recognize the abnormal returns that have occurred due to the announcement of a stock split. The main objective of the study was to recognize whether there has been any change in how the market perceives stock split announcements and whether there has been any change in the Pre- and Post-Covid eras. The study has been able to unfold that the negative sentiment that was there towards stock split announcements in the Pre-Covid era has evolved towards a more positive sentiment in the Post-Covid era with the development of capital markets in Sri Lanka. Methodology: By constructing this study using the event study methodology, I have looked at the time period running up to the announcement and have analysed the post-announcement period as well by looking at the reaction of the split announcements on the average abnormal returns, cumulative average abnormal returns, and the t-statistic of the average abnormal returns. Through these avenues, the change in perception of these stock split announcements can be identified. Finding: While during the Pre-Covid era there has been a negative sentiment towards stock split announcements with negative Average Abnormal Returns of -0.64%, there has been a drastic change in the Average Abnormal Returns in the Post-Covid period indicating a return of 15%, showing a change in the perception that has evolved with the development of Sri Lankan capital markets. With various new developments in the economy and new innovations, the investor sentiment has also changed into seeing more opportunities with stock splits. Conclusion: Through the findings of this study, we can conclude that the stock split announcements in the Pre-Covid era, which were perceived to be negative by the market, have changed into a more positive perception during the Post-Covid period in creating more opportunities for market participants in the short run. With continuous analysis, it can be seen that the new developments and changes of the market have facilitated this sentiment, and for future research, a continuation of such trends can be analysed. Therefore, it is important to follow the impact of stock split announcements for short-run performance of stock prices.Item Impact of Behavioral Factors on Investment Decisions: Evidence from Western Province Investors in Colombo Stock Exchange (CSE)(Department of Finance, Faculty of Commerce and Management Studies, University of Kelaniya, Sri Lanka., 2025) Mendis, H. N. S.; Weligamage, S. S.Introduction: This study investigates the impact of behavioral factors on investment decisions among investors in the Western Province of Sri Lanka, specifically within the Colombo Stock Exchange (CSE). Behavioral finance, which integrates psychological insights into financial decision-making, challenges traditional financial theories that assume rational investor behavior. The primary objective is to examine how behavioural factors (such as representativeness, availability bias, anchoring, overconfidence, loss aversion, framing effects, mental accounting, and regret aversion) influence investment decisions. Methodology: A structured questionnaire was used to collect quantitative data from 100 investors, employing a snowball sampling method. The data were analyzed using exploratory factor analysis, descriptive factor analysis, and regression analysis to identify the relationships between behavioral factors and investment performance. Findings: It reveals that behavioral biases significantly impact investment decisions, leading to systematic errors and suboptimal outcomes. Overconfidence and anchoring biases were found to have a strong influence, while loss aversion and regret aversion also played critical roles in shaping investor behavior. The study concludes that understanding these factors can help improve investor education and decision-making strategies, ultimately contributing to better financial outcomes and market stability. Conclusion: The study concludes that behavioral factors significantly impact investment decisions among investors in the Colombo Stock Exchange (CSE). Key findings include that loss aversion and regret aversion lead to conservative investment practices and suboptimal outcomes. Overconfidence and anchoring biases result in reliance on easily recalled information or historical performance patterns, causing poor future predictions. Mental accounting influences decision-making by categorizing investments into different "buckets." The disposition effect shows that investors sell winning stocks too early and hold onto losing stocks for too long, negatively impacting performance. Understanding and mitigating these biases can improve investor education and decision-making strategies, contributing to better financial outcomes and market stability. The study highlights the need for tailored investor education programs and incorporating behavioral insights into advisory practices.Item Identifying the Relationship Between Dividend Policy and Stock Prices in the Banking Sector: Evidence from Colombo Stock Exchange(Department of Finance, Faculty of Commerce and Management Studies, University of Kelaniya, Sri Lanka., 2025) Hewawitharana, B. D.; Samarawickrama, A. J. P.Introduction: The banking industry supports investment activity, minimizes credit availability, and facilitates the flow of funds, making it the foundation of economic growth. This study aims to empirically test to identifying the relationship between dividend policy and stock prices in the banking sector. Methodology: The study adopts a quantitative approach using a panel dataset spanning 2011–2023 from seven banking companies on the CSE. Secondary data was obtained from the published annual reports. These firms were selected for their consistent dividend declarations over 13 years. Panel data regression models have been utilized to analyze the data as the Hausman test suggest the fixed effect model is the most appropriate for describing the relationship among the variables. EViews 12 analytical software has been used to analyze the data. Findings: The analysis revealed significant relationships between dividend policy and stock prices. Dividend payout ratios exhibited the most pronounced influence on stock prices, while dividend yields showed mixed results. Conclusion: Dividend policy serves as a critical determinant of stock price behavior in the banking sector, highlighting its importance as a strategic tool for both investors and corporate decision-makers. The findings emphasize the need for well-formulated dividend policies to enhance shareholder value, improve market perceptions, and provide guidance in volatile market conditions.Item A Comparative Analysis of the Impact of Firm-Specific and Macroeconomic Factors Influence Capital Structure Decisions: Evidence from Sri Lankan Manufacturing and Telecom Companies (2013-2023).(Department of Finance, Faculty of Commerce and Management Studies, University of Kelaniya, Sri Lanka., 2025) Begum, M. H. S.; Perera, L. A. S.Introduction: Optimal capital structure is important for the sound financial and future growth of any enterprise. This study aims to examine the significant impact of firm specific variables namely profitability, size, tangibility, liquidity and dividend payout policies in combination with macroeconomic variables consisting of; GDP growth rate, interest rate, inflation and exchange rate on the Manufacturing and Telecom firms of CSE for the year 2013-2023. Methodology: The analysis was carried out using panel data regression on a sample of 22 firms, 2 telecom firms and 20 manufacturing firms employing the criteria of market capitalization. All samples were chosen based on available ratios to accomplish the measurement of capital structure using the debt-to-equity ratio, and validity tests were applied to assess the accuracy of the calculations. In addition, the sectoral and combined examinations was conducted to look for difference and difference patterns. Findings: From the findings of the study show that this study finding of this manufacturing sectors represent firm specific characteristics, which show that tangibility and liquidity of the manufacturing firms have significant effects on capital structure decision and that firms with high tangible and high liquid assets utilize least debts. The level of profitability has a strong inverse relationship with leverage and strong positive relationship with dividend and interest rate that may be due to telecommunication infrastructure financing requirements. In the combined sector analysis, tangibility and liquidity are used as the major indexes, and the indexes of macroeconomic environment, including interest rate, exchange rate, inflation, and GDP growth had not been concluded to exert major influence over both sectors. It was also revealed that simply due to these observations, Firm size, Growth, GDP growth, Exchange rate and inflation rates held insignificant impacts across both sectors. Conclusion: This study has shown that firm specific characteristics organizational liquidity tangibility, Dividend and Profitability significantly affect capital structure decisions in the Manufacturing and Telecom industry of Sri Lanka aside from influence by the macroeconomic indicators namely the interest rates. The overall model also shows significance at the 1% level for both the telecom and the manufacturing sectors. These insights vindicate the essentiality of industry-specific financing to give firms the ability to improve their solvency and performance.