Technological Relationship Between Banknifty and Other Selected Sectorial Indices of NSE

Financial market of a country signifies the monetary strength of its economy. Smart monetary health of a rustic helps in enhancing the money flows and creates capital, that contributes to the event of the country. Post economic process innovate India he monetary market has entered into a replacement phase of worldwide integration and alleviation with variety of recent and innovative monetary instruments. The objective of the is to find the nature and extent of technical relationship between Nifty Bank on other selected sectorial indices of National Stock Exchange and to examine the risk and return factors of the sectorial indices. The major use of stock market indices are as a forecasting tool. Studying the historical performance of the stock market indices, you can forecast trends in the market. All the sectors of NSE are not considered in this study. Only five sectors other than bank nifty are considered. Six different sectors are compared individually with the Nifty Bank by the tools called correlation and Regression. Correlation and regression between the indices has been used to identify the relationship and extent of impact between Nifty Bank and other selected sectorial indices. From the results and findings of this study, one can understand that there is a significant relationship between Bank Nifty and other selected sectors (Energy, FMCG, IT, Media, Pharma) except Infrastructure. It is showing a poor relationship with Bank Nifty.

Factor Momentum Everywhere

In this article, the authors document robust momentum behavior in a large collection of 65 widely studied characteristic-based equity factors around the globe. They show that, in general, individual factors can be reliably timed based on their own recent performance. A time-series factor momentum portfolio that combines timing strategies of all factors earns an annual Sharpe ratio of 0.84. Factor momentum adds significant incremental performance to investment strategies that employ traditional momentum, industry momentum, value, and other commonly studied factors. The results demonstrate that the momentum phenomenon is driven in large part by persistence in common return factors and not solely by persistence in idiosyncratic stock performance.

Beta momentum strategy after extreme market movements

The authors adopt an event study method and empirically investigate the performance of a beta momentum strategy (long in past winners of small beta and short in past losers of large beta) after extreme market movements in 20 countries. The researchers find that the beta momentum strategy yields material abnormal returns after controlling for return factors of size (SMB), book-to-market (HML) and momentum (UMD). The results are consistent for both extreme market UP days or DOWN days and regardless of whether the extreme market movements are identified by three percent or two percent cut-off points. In addition, the results based on the beta momentum strategy are more consistent than those of conventional momentum and betting against beta (BAB) strategies over different test windows from (0, +1) days to (0, +90). Finally, the abnormal returns based on momentum, BAB, and our beta momentum strategies are statistically insignificant for the Asian and Australian subsamples, whereas the results are significant for the European and North American samples.