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Purpose: This study investigates internal/own shock in the domestic market and three external volatility spillovers from India, the UK, and the USA to the Sri Lanka stock market.

Need for the Study: The external market’s internal/own shocks and volatility spillovers influence portfolio choices in domestic stock market returns. Hence, it is required to investigate the internal shock in the domestic market and the external volatility spillovers from other countries.

Methodology: This study employs a quantitative method using ARMA(1,1)-GARCH(1,1) model. All Share Price Index (ASPI) is the proxy for the Colombo Stock Exchange (CSE) stock return. It uses daily time-series data from 1^st April 2010 to 21^st June 2023.

Findings: The findings revealed that internal/own and external shocks substantially impact the stock price volatility in CSE. Significant volatility clusters and persistence with extended memory in ASPI confirm internal/own shock in the market. Furthermore, CSE receives significant volatility shock from the USA, confirming external shock. This study’s findings highlight the importance of considering internal and external shocks in portfolio decision-making.

Practical Implications: Understanding the influence of internal shocks helps investors manage their portfolios and adapt to market volatility. Recognising significant volatility spillovers from external markets, especially the USA, informs diversification strategies. From a policy standpoint, the study emphasises the need for robust regulations and risk management measures to address shocks in domestic and global markets. This study adds value to the literature by assessing the sources of volatility shocks in the CSE, employing the ARMA-GARCH, a sophisticated econometrics model, to capture stock returns volatility, enhancing understanding of the CSE’s volatility dynamics.

Internationalization of capital markets gives opportunities to investors to invest their money in the country of their choice, not just in their own country. The relationships between international stock markets have become increasingly important in recent times. The purpose of this paper is to study the inter‐linkages between stock markets of India, Pakistan and Sri Lanka.

This paper studies the inter‐linkages between stock markets of India, Pakistan and Sri Lanka. Daily closing levels of the benchmark indices in the three countries are taken for a period of January 2003‐June 2010. While line charts, correlogram and unit‐root test are applied to check the stationary nature of the series; Granger's causality model, vector auto regression (VAR) model and variance decomposition analysis are performed to find out the linkages between the markets under study.

The paper concludes that while the National Stock Exchange (India) Granger causes Karachi Stock Exchange (Pakistan) and Colombo Stock Exchange (Sri Lanka), the vice versa is not true. These results of Granger's causality model are also confirmed by the VAR models.

Studies have been conducted in large numbers to test the linkages and integration between stock exchanges of the developed nations, namely the USA, Canada, Europe and Japan. Even the studies that have focused on the developing and under‐developed nations have studied the linkages of those with the developed nations. Little research has been conducted about the inter‐linkages between the nations from Asia. Even fewer studies have focused on stock exchanges in the South‐Asian region. This research paper focuses on the return from the benchmark stock exchanges from these three countries and also on the linkages between India, Pakistan and Sri Lanka.

This study examines return and volatility spillovers from the US and Japanese stock markets to three South Asian capital markets – (i) the Bombay Stock Exchange, (ii) the Karachi Stock Exchange and (iii) the Colombo Stock Exchange. We construct a univariate EGARCH spillover model that allows the unexpected return of any particular South Asian market to be driven by a local shock, a regional shock from Japan and a global shock from the USA. The study discovers return spillovers in all three markets, and volatility spillovers from the US to the Indian and Sri Lankan markets, and from the Japanese to the Pakistani market. Regional factors seem to exert an influence on these three markets before the Asian financial crisis but the global factor becomes more important in the post-crisis period.

The purpose of this paper is to examine the evolutionary nature of herding phenomenon in the context of a frontier stock market, the Colombo Stock Exchange of Sri Lanka.

This study applies the cross-sectional absolute deviation methodology for daily frequencies of data of all the common stocks listed during the period from April 2000 to March 2018. The regression coefficients are estimated by using both the ordinary least square and the quantile regression procedures.

The findings reveal significant changes to the pattern of herding over different market periods, each with specific characteristics. Herding is strongly evident in up and down market days in the 2000-2009 period, during which the market was highly uncertain with the impact of the political instability of the country due to the Civil War on the stock trading. Even after this Civil War period, herd tendency is strongly manifested toward the up market direction as a result of the investors’ optimism about the country’s economy and political stability, which caused to a speculative bubble in the market. After that, it is turned into negative herding due to the panic selling occurred in view of the uncertainty of the inflated prices, which led to a market crash. Notably, herding appears to be consistently absent over the period after the crash, despite the presence of herd motives such as high market uncertainties triggered by political instability and economic crisis during that period.

The findings suggest that herd behavior is an evolving phenomenon in financial markets. Consistent with the adaptive market hypothesis, the absence of herding evident after the market crash could be attributed to the investors’ learning of the irrationality of herding/negative herding for adapting to market conditions. As a result, herding and negative herding tendencies declined and disappeared at the aggregate market level.

This study contributes to the literature by providing novel evidence on the evolutionary nature of behavioral biases, particularly herding, as predicted by the adaptive market hypothesis. With the application of the quantile regression procedure, in addition to customary used ordinary least squares approach, it also provides robust evidence on this phenomenon.

The upsurge of globalization has made investors cautious toward investing decisions, and, resultantly, sophisticated techniques of forecasting and analyzing the stock markets have emerged. Particularly, this trend has gained momentum in emerging economies. One such trend is to overcome the investing risks associated with formation of rational bubbles. Bubbles are formed when asset prices inflate to a very high level temporarily, and they ultimately burst. Investors may take advantage of this short-lived phenomenon and gain high returns, but may also suffer as the entire investing value declines when the bubble bursts. The purpose of this paper is to identify rational bubbles in the emerging capital markets of South Asian region.

The monthly data have been obtained from June 1997 to February 2018 for Pakistan, Bombay, Dhaka and Colombo stock markets, and supremum-Augmented Dicky Fuller test developed by Phillips and Yu (2011) has been utilized to identify the rational bubbles.

The results revealed the presence of rational bubbles in South Asian equity markets. The current study is of significant nature for the facilitation of investors in future-making investing decisions concerning with the formation of rational bubbles.

Several studies have been conducted on stock markets of developed regions. Specific bubble episodes, which occurred previously, have helped the researchers and investors in gaining plenty of insights. A lot of studies have been conducted on the SAARC region as well. But they have used the conventional unit root test for bubble identification and not used as extensive data as, in this study, have been taken. This research is aimed to study equity prices of the four stock markets to establish the fact that if rational bubbles exist in the index, they are reflected in the returns or not.

This paper aims to examine the patterns of intellectual capital reporting (ICR) of large listed firms in a developing nation, Sri Lanka. The aim of this study is to highlight the differences in ICR practice between developing and developed nations.

The paper begins by examining each of the top 30 firms by market capitalization listed on the Colombo stock exchange in 1998/1999 and 1999/2000. Using the content analysis method, it reviews the annual reports of these firms to determine the types of intellectual capital (IC) items reported in Sri Lanka. It then compares these findings with a similar study undertaken in Australia during the same period.

The findings in this paper highlight the need for a uniform ICR definition and a reporting framework that provides comparative and consistent reporting under the auspices of a regulatory body. ICR differences were identified between Sri Lankan and Australian firms, and it is argued that these differences can be attributed to economic, social and political factors.

This paper highlights important policy issues for Australia, Sri Lanka and other nations. These issues are even more pertinent in the light of the gradual international adoption of the International Financial Reporting Standards (IFRSs), formulated by the International Accounting Standards Board (IASB).

Most papers on intellectual capital reporting have focused on firms in developed countries. This paper offers insights into comparative reporting practices between a developed and a developing country.

The purpose of this paper is to examine the causal relationships between stock prices and macroeconomic variables in Sri Lanka, in order to examine the validity of the semi‐strong form of the efficient market hypothesis.

The paper adopts unit roots and cointegration, error‐correction modelling, variance decomposition analysis, and impulse responses analysis to examine the causal relationship between six macroeconomic variables.

The results indicate that there are both short and long‐run causal relationships between stock prices and macroeconomic variables. These findings refute the validity of the semi‐strong version of the efficient market hypothesis for the Sri Lankan share market and have implications for investors, both domestic and international.

The paper addresses several methodological weaknesses in relation to unit root and cointegration tests which previous studies in the area of the paper have overlooked. Further, it uses more variables than those used in a previous study using Sri Lankan data.

Purpose: This chapter examines the effect of COVID-19 on the stock market volatility (SMV) in the Colombo Stock Exchange (CSE), Sri Lanka.

Need for the Study: The study is necessary to understand investor behaviour, market efficiency, and risk management strategies during a global crisis.

Methodology: Utilising daily All Share Price Index (ASPI) data from 2 January 2018 to 31 August 2021, the data are divided into subsamples corresponding to the pre-pandemic period, the pandemic period, and distinct waves of the pandemic. The impact of the pandemic is investigated using the Mann–Whitney U test, the Kruskal–Wallis test, and the Exponential Generalised Autoregressive Conditional Heteroscedasticity (EGARCH) model.

Findings: The pandemic considerably affected CSE – the Mann–Whitney U test produced different market returns during the pre-COVID and COVID eras. The Kruskal–Wallis test improved performance during COVID-19 but did not continue to do so across COVID-19 waves. The EGARCH model detected increased volatility and risk during the first wave, but the second and third waves outperformed the first. COVID-19 had a minimal overall effect on CSE market results. GARCH and Autoregressive Conditional Heteroskedasticity (ARCH) models identified long-term variance memory and volatility clustering. The News Impact Curve (NIC) showed that negative news had a more significant impact on market return volatility than positive news, even if the asymmetric term was not statistically significant.

Practical Implications: This study offers significant insight into how Sri Lanka’s SMV is affected by COVID-19. The findings help create efficient mitigation strategies to mitigate the negative consequences of future events.