There is an evident impact of telecommunication on financial inclusion in the case of several constructs irrespective of regional differences in India. Poor households suffer from inadequate access to financial services. Telecom plays an essential role in expanding financial services to rural areas and in helping people to improve their lives. Inclusive and holistic policies need to be promoted, which will simultaneously enhance telecommunication infrastructure and financial inclusion in India.

COVID-19 has impacted the world economy in an unprecedented manner; the financial markets indicate the same. This spontaneous event landed most of the stock markets into extreme volatility. Large capital outflow and extreme rapid fall were seen among almost all the world financial markets. Though similar trend prevailed everywhere during this pandemic, the impact could not be accumulated in absolute terms. Using the data of five stock markets, the current study endeavored to draw an impact of COVID-19 on major stock exchanges. The study uses wavelet coherency analysis on one-year daily data from June 2019 to May 2020 of five stock markets: Bombay Stock Exchange (BSE), London Stock Exchange (LSE), NASDAQ, Tokyo Stock Exchange (Nikkei), and Shanghai Stock Exchange. It is observed that there are time-variation and scale-variation in co-movements between the studied markets. During the crisis, the co-movement concentrates on a short time scale, even for two days. These results have significant implications for international investors, which will help them in portfolio diversification with time elements. All the stock markets under study have indicated co-movement at different time scales and frequencies with varying cross-power levels. However, the concentration of co-movement is found the most between the UK and the US stock markets. It is the least between Japan and the UK. In BSE, co-movement at shorter time scales started late. NASDAQ is leading only in one case, i.e., Shanghai Stock Exchange. BSE is not leading any stock index. LSE is in the leading position in all four cases. It has also been observed that co-movement started to concentrate at a shorter time scale as soon as the impact of the crisis increased.

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Seasonality in stock market is a well recognized postulation. The phenomenon stands for a regular or rhythmic pattern, apparent in stock returns. The present study investigates the persistence of such regularities in the form of weekend effect, monthly effect and holidays effect employing twelve-year data from 2000 to 2011 of S&P CNX Nifty. The article examines the survival of seasonalities in Indian stock market through Generalized Autoregressive Conditional Heteroskedasticity (GARCH) (1,1) model. The results indicate the occurrence of weekend effect in long run but reject the hypothesis of positive weekends and negative Mondays. On the contrary, the mean return on Tuesday is negative for the entire period. Instead of March effect, the study comes out with November effect and hence nullifies the ‘Tax-Loss Selling Hypothesis’. On dividing the entire period into three-year lags, anomalies instantaneously disappear confirming the fact that any seasonality takes some time to establish itself. Higher GARCH values validate that the Indian stock market is inefficient in its weak form and does not follow a random walk.

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