Sustainability-related disclosure rules and financial market indicators: Searching for interconnections in developed and developing countries

The purpose of the paper is to select the right market proxy for calculating the expected return, since critically evaluating proxies or selecting the correct proxy market portfolio is essential for portfolio management because the change in the market portfolio proxy affects returns. In this study, monthly data of equity indices are evaluated to find out the better market proxy. The indices taken are BSE 30 (Sensex), Nifty 50, BSE 100, BSE 200, and BSE 500. The macroeconomic variables used in the study are industrial production index (IIP), consumer price index (CPI), money supply (M1), and exchange rate in India. To avoid the influence of COVID-19, the research period was from January 2013 to December 2019 to critically evaluate these proxies in order to find the most appropriate market proxy. This paper reveals a noteworthy relationship between stock market returns and macroeconomic factors, while suggesting that the BSE 500 is a better choice for all equity indices, as the index also shows a significant relationship with all macroeconomic variables. BSE500 is a composite index comprising all sectors with low, mid and large cap securities, therefore it reflects the impact of macroeconomic factors most efficiently, taking it as a market proxy. This study was carried out in the context of India and can be replicated for other countries.

The current empirical study attempts to analyze the impact of COVID-19 on the performance of the Indian stock market concerning two composite indices (BSE 500 and BSE Sensex) and eight sectoral indices of Bombay Stock Exchange (BSE) (Auto, Bankex, Consumer Durables, Capital Goods, Fast Moving Consumer Goods, Health Care, Information Technology, and Realty) of India, and compare the composite indices of India with three global indexes S&P 500, Nikkei 225, and FTSE 100. The daily data from January 2019 to May 2020 have been considered in this study. GLS regression has been applied to assess the impact of COVID-19 on the multiple measures of volatility, namely standard deviation, skewness, and kurtosis of all indices. All indices’ key findings show lower mean daily return than specific, negative returns in the crisis period compared to the pre-crisis period. The standard deviation of all the indices has gone up, the skewness has become negative, and the kurtosis values are exceptionally large. The relation between indices has increased during the crisis period. The Indian stock market depicts roughly the same standard deviation as the global markets but has higher negative skewness and higher positive kurtosis of returns, making the market seem more volatile.

The banking industry is one of the major industries in the Vietnamese stock market, so understanding how the industry index reacts to unusual events such as COVID-19’s impact is very important for the development of the Vietnamese stock market. This study examines the response of the banking sector index to three lockdown/blockage announcements to prevent the COVID-19 epidemic in Vietnam in 2020. Three times of lockdown/blockage: On February 13, 2020, blockade of Son Loi commune, Vinh Phuc province; on March 30, 2020, Vietnam announced the nationwide epidemic of COVID-19 and then nationwide lockdown, and on July 28, 2020, blockade in Da Nang. In the first case, the abnormal returns changed the sign around the notification date indicating that the stock price deviated from its fair value, but accumulating abnormal returns CAR (0;3] and CAR (0; 2] are both positive and statistically significant, which means that investors are more secure when the epidemic area is tightly controlled. The nationwide lockdown was the event that had the strongest impact on the stock price when both AR and CAR were negative and statistically significant before and after the date of the event’s announcement. Nationwide lockdown was the event that had the strongest impact on stock prices as both AR and CAR were negative in the days before and days after the event. This result supports the theory of imperfect substitution. Only AR [2] was positive and statistically significant, showing that the blockade event in Da Nang had a slight impact on the banking sector’s stock price.