Selection of the right proxy market portfolio for CAPM

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.

Nigerian economy depends on oil as the major source of revenue, failure to diversify the revenue base has raised questions about its sustainability and implication on the economy. This study uses market capitalization, broad money stock, credit to private sector, prime interest rate and deposit liability as proxies for the financial sector, while output in the manufacturing sector and manufacturing employment are used as proxies for manufacturing performance. The study examines the causal effects, shock effect and long-run impact using Granger Non-Causality, Vector Error Correction Model, and Dynamic Ordinary Least Square method, respectively. The results showed unidirectional causality, confirming the hypothesis of the ‘supply-leading view’ and ‘demand-following view’ except for market capitalization and output in the manufacturing sector, where independence was observed. The variance decomposition shows that the forecast error shock of credit to private sector and prime interest rate show more variations in manufacturing sector performance than other financial indicators. The long-run result using output in manufacturing sector as dependent variable shows a positive significant relationship with other financial sector indicators, except for broad money stock and deposit liability. This study recommended credit channel for transmission of monetary policy using interest rate to improve the performance of manufacturing sector, among others.

VUСA is a chaotic and rapidly changing business environment that, based on the variability, uncertainty, complexity and ambiguity of the modern world, transforms the approach of banks to the analysis of financial stability. The aim of the paper is to improve tools for monitoring the impact of VUCA-world conditions on the financial stability of banks, namely a model for studying and analyzing the impact of the modern business space “VUCA” on the financial stability of the country's banks. To test the model, the method of constructing regression equations in multifactor regression analysis is used. For this study, data from some Eastern European countries (Ukraine, Belarus, Latvia, Lithuania, Moldova) were used, and time series data were used for 10 years from 2010 to 2019.
Having considered the definition of “VUCA-world conditions”, the model of modern business space “VUCA” was developed when analyzing the activity of banks in the studied countries. Drivers, consequences, requirements and macroeconomic indicators of the countries’ activities in the VUСA-world conditions are determined. The VUCA-world conditions also consider the study of key macroeconomic indicators that allow building long-term relationships throughout the value chain. The analysis of the studied Eastern European countries showed that with the increase of factors of GDP growth, GNI per capita growth, research and development costs, foreign direct investment, and net inflow of 1%, the effective ratio of bank capital and assets also increases. The assessment, in contrast to the existing ones, makes it possible to consider the impact of the macroeconomic environment of banks on their financial stability.