Nifty Bank Research Articles

Technical analysis on select stocks of banking sector

Technical Analysis is the forecasting of future financial price movements based on an examination of past price movements. Like weather forecasting, technical analysis does not result in absolute predictions about the future. Instead, technical analysis can help investors anticipate what is “likely” to happen to prices over time. Technical analysis uses a wide variety of charts that show price over time. This study is based on the analysis of four Nifty Bank Index stocks namely Axis Bank, Bank of Baroda, State Bank of India and ICICI bank listed in National Stock Exchange. Technical indicators such as Relative strength index (RSI), Rate of change (ROC) and Moving Average (MA) are used in the study. This paper aims at carrying out Technical Analysis of the securities of the selectedbanking stocks and to assist investment decisions in this Indian Market.

Pricing Efficiency of Equity Index Option Contracts: Evidence from National Stock Exchange of India

The present study examines the pricing efficiency of equity index options traded at National Stock Exchange of India by comparing the premium of options contracts traded on NIFTY, BANK NIFTY, CNXIT, NIFTY JUNIOR, and CNX100 indices with their respective theoretical price estimated by using Black-Scholes Model. 91-day T-Bill rate is used as risk-free rate and standard deviation computed on daily returns of the underlying index is used as volatility to estimate the theoretical prices. Pricing efficiency has been tested both for daily closing prices per se as well as for the In-the-Money, At-the-Money, and Out-of-the-Money options contracts. Mean Absolute Errors (MAE), Mean Squared Errors (MSE), Root Mean Squared Errors (RMSE), and Theils U statistics suggest that the premium of equity index options contracts do not follow Black-Scholes Model.

Weak-Form Efficiency of the Indian Stock Market: An Empirical Analysis

The present study attempts to verify weak form of efficient market hypothesis using daily data for the indices of Indian stock market, namely, NIFTY 50 (NSE-50), CNX 500 (NSE-500), CNX IT INDEX (NSE-IT), BANK NIFTY INDEX (NSE-BANK) and NIFTY MIDCAP 100 (NSE-MC100). For the analysis, the study employed GARCH (1, 1) model and EGARCH (1, 1) model over the sample period of 1, January 2010 to 5, November 2015. The study results exhibited that returns series are characterized by high persistence of volatility clusters and leverage effects over the sample period. The empirical findings show that the indices of National Stock Exchanges are not weak form efficient.

Testing Pricing Relationship between Bank Nifty futures & Bank Nifty Indices – Evidences from India

Today every investor wants to make more money with in a stipulated/short period. Large number of people involving in the buying & selling of securities in capital market. Capital market has governed by 3 largest stock exchanges namely NSE, BSE & MCX (SX). From the above stock exchanges induced by a number of creative financial instruments innovated by investors like equities, debentures, bonds, preference shares, mutual funds, ETF & Future and Options etc.., Each of the above classified securities are associated with risk & volatility. Volatility is the frequency of price changes/fluctuations happens at a stipulated period of time. In other words, it can be said that it gives the maximum possible chances to make a return for every investment. This volatility is playing a vital role of securities market to take a risk & return.

Long Run Relationship between Capital Market and Banking Sector ? A Cointegration on Federal Bank

This paper examines the long run relationship between the capital market and banking sector. India has a large investment contribution in capital market. It is vital to the functioning of an economy. The object of the study is to analyze the long run relationship between the stock price of federal bank and composite price of capital market represented by NIFTY. The data used for the purpose is secondary source. An empirical investigation is carried out using daily data of ten years ranging from 1 st January 2005 to 31 th December 2014. The data used in the present study have been taken from the official website of National Stock Exchange. The major statistical tools used in the study are Unit Root Test, Granger Causality /Block Exogenity Test, Cointegration analysis, Impulse Response function and Error Variance decomposition using the software E-views. Applying the Dickey Fuller Tests to determine the stationality it has been found that both time series are non stationary. Johnsen Cointegration analysis shows that there is unidirectional movement between NIFTY and Federal Bank index. To further investigate the lead lag relationship between the two by Granger Causality /Block Exogenaty test and to identify the short run relationship impulse response function and variance decomposition is conducted. From the study it is conclude that the effect in the banking sector leads to the movement of banking sector but no vice versa.

Effect of Return and Volatility Calculation on Option Pricing: Using BANKNIFTY

 Abstract—Predictability in the asset return and hence the volatility has remained a topic of great concern among the institutional and private investors. The underlying asset in our case is the Bank NIFTY futures. We have tried to predict the volatility using different methods using time series data which are based on historical approach. Then we applied Black- Scholes Option Pricing Model formulae to calculate the option price of Bank Nifty option. We then compared the prices with the actual market trading data of the Bank Nifty option.

Bank Nifty Index and Other Sectoral Indices of NSe- A Comparitive Study

Bank Nifty Index and Other Sectoral Indices of NSe- A Comparitive Study

A Study on Impact of Dividend on Nifty Bank Stocks

A Study on Impact of Dividend on Nifty Bank Stocks

Positive Feedback Strategy of FIIs in Indian Stock Market: A Sectoral Analysis

The Positive feedback hypothesis stipulates the strategy of rushing in when the markets are booming and rushing out when the markets are on the decline. The present study empirically documents the static and dynamic interaction between FII flows and returns of various indices of National Stock Exchange, using daily data for the variables from 2000 to 2009. Results indicate that there is evidence of positive feedback trading in Indian context in four selective indices viz. Bank Nifty, CNX Midcap, CNX Nifty Junior, and S&P CNX 500 out of fifteen sampled indices. It is also observed that FIIs are not only causating agents but also the effects of the stock return; and there is selective bidirectional relationship between net FII flows and returns of selected indices viz. CNX Midcap, CNX Nifty Junior, S&P CNX 500 and S&P CNX Nifty out of the (Fifteen) sampled indices.