scholarly journals Predictive Analytics in Stock Markets with Special Reference to BSE Sensex

2019 ◽  
Vol 8 (6S4) ◽  
pp. 615-619
Keyword(s):  
Stock Market ◽  
Predictive Analytics ◽  
Large Data ◽  
Business Environment ◽  
Market Returns ◽  
Stock Market Returns ◽  
Advanced Level ◽  
Random Walk Theory ◽  
Indian Stock Market ◽  
Near Future

Predictive analytics in finance is the art and science of using substantial quantities of data to find arrays. An Array can be termed as pattern or movement. Predictive analytics identifies patterns in large data volumes and helps to minimize future uncertainties. Predicting stock market returns is a puzzling task due to the multifaceted nature of the data. The present study is an applied application of the prediction and random walk theory on SENSEX behavior at an advanced level. Stock Market is the most dynamic element in the financial system and will play a crucial role in the progress of any country. The focus is on how much more on how to improve the forecasting models in terms of the performance of indices. The present model shows some commendable results in the prediction modelling reference to Indian stock market (BSE SENSEX). The designed model is also having utility for traders and investors estimating price movements of stocks at near future. Generally, the Fundamental Analysis comprises of evaluating the company’s profitability on the basis of its current business environment and financial performance in the future. Technical Analysis includes interpreting the charts and using statistical figures to identify the patterns in the stock market. A number of market indicators are believed to offer signals which are beneficial in anticipating future prices. For this purpose data of BSE Sensex data has been taken (January 2010- September 2018) from bseindia.com. The results exhibit that the Sensex would also gain momentum in the year 2019.

Relationship between Foreign Portfolio Investments (FPI), Domestic Institutional Investors, and Stock Market Returns in India

GIS Business ◽  
2017 ◽  
Vol 12 (6) ◽  
pp. 1-9
Author(s):  
Dhananjaya Kadanda ◽  
Krishna Raj
Keyword(s):  
Stock Market ◽  
Institutional Investors ◽  
Negative Relationship ◽  
Trading Strategies ◽  
Market Returns ◽  
Stock Market Returns ◽  
Foreign Portfolio Investment ◽  
Stock Market Return ◽  
Indian Stock Market ◽  
Feedback Trading

The present article attempts to understand the relationship between foreign portfolio investment (FPI), domestic institutional investors (DIIs), and stock market returns in India using high frequency data. The study analyses the trading strategies of FPIs, DIIs and its impact on the stock market return. We found that the trading strategies of FIIs and DIIs differ in Indian stock market. While FIIs follow positive feedback trading strategy, DIIs pursue the strategy of negative feedback trading which was more pronounced during the crisis. Further, there is negative relationship between FPI flows and DII flows. The results indicate the importance of developing strong domestic institutional investors to counteract the destabilising nature FIIs, particularly during turbulent times.

Stock Market Seasonality in an Emerging Market

2004 ◽  
Vol 29 (3) ◽  
pp. 35-42 ◽  
Author(s):  
S N Sarma
Keyword(s):  
Stock Market ◽  
Stock Markets ◽  
Abnormal Returns ◽  
Market Returns ◽  
Reform Era ◽  
Stock Market Returns ◽  
Active Strategy ◽  
Calendar Anomalies ◽  
Indian Stock Market ◽  
Daily Returns

The objective of this paper is to explore the day-of-the-week effect on the Indian stock market returns in the post-reform era. Till the late seventies, empirical studies provided ample evidence as to the informational efficiency of the capital markets advocating futility of information in consistently generating abnormal returns. However, later studies identified certain anomalies in the efficient market postulate. One major anomaly brought forth was the calendar-related abnormal rates of return. Various studies in this domain empirically demonstrated, through parametric and non-parametric tests on the stock returns data, that turn of the year, month, week, and holidays have consistently generated abnormal equity returns in both the developed and emerging markets unrelated to the attendant risks. Studies on the Indian stock markets' calendar anomalies, especially in the post-reform era, are very few. In an attempt to fill this gap, this study explores the Indian stock market's efficiency in the 'weak form' in the context of calendar anomalies, especially in respect of the weekend effect. Daily returns generated by the SENSEX, NATEX, and BSE200 during January 1st 1996 to August 10th 2002 comprising a total of 1,667 observations for each of the indices are considered for testing the seasonality. While most of the studies have considered the returns of one of the major indices based on the closing values, this study examines the multiple indices for possible seasonality. An analysis of returns' pattern of multiple indices is helpful in identifying the presence or otherwise of the stock market seasonality associated with various portfolios and for testing the efficacy of investment game based on the observed patterns of the returns. This study employed the daily mean index value for generating the daily returns to relax the implied assumption of the earlier studies — by considering the closing values of the indices — that trading is done at the closing values. A non-parametric test — Kruskall-Wallis test using 'H' statistic — is employed for testing the seasonality in the Indian stock market returns. The null hypothesis tested is that there are no differences in the mean daily returns across the weekdays. The major findings of the study are as follows: The Indian stock markets do manifest seasonality in their returns' pattern. The Monday-Tuesday, Monday-Friday, and Wednesday-Friday sets have positive deviations for all the indices. The Monday-Friday set for all the indices has the highest positive deviation thereby indicating the presence of opportunity to make consistent abnormal returns through a trading strategy of buying on Mondays and selling on Fridays. The above-mentioned active strategy is found to be beneficial in case of SENSEX The above-mentioned active strategy is found to be beneficial in case of SENSEX alone during the study period while for the others — NATEX and BSE200 — a passive ‘buy and hold’ strategy is more effective. The study concludes that the observed patterns are useful in timing the deals thereby exploring the opportunity of exploiting the observed regularities in the Indian stock market returns.

scholarly journals FIIs and Indian Stock Market: A Causality Investigation

2012 ◽  
Vol 14 (4) ◽  
pp. 5-24 ◽  
Author(s):  
Minakshi Paliwal ◽  
S. D. Vashishtha
Keyword(s):  
Stock Market ◽  
Capital Flows ◽  
Institutional Investors ◽  
Capital Gains ◽  
Market Returns ◽  
Causality Test ◽  
Stock Market Returns ◽  
Foreign Institutional Investors ◽  
And Performance ◽  
Indian Stock Market

While the volatility associated with portfolio capital flows is well known, there is also a concern that foreign institutional investors might introduce distortions in the host country markets due to the pressure on them to secure capital gains. In this context, present chapter attempts to find out the direction of causality between foreign institutional investors (FIIs) and performance of Indian stock market. To facilitate a better understanding of the causal linkage between FII flows and contemporaneous stock market returns (BSE National Index), a period of nineteen consecutive financial years ranging from January 1992 to December 2010 is selected. Granger Causality Test has been applied to test the direction of causality.

Are there Monthly and Turn-of-the-Month Effects in Indian Stock Market?: Evidence and Implications

Paradigm ◽  
2007 ◽  
Vol 11 (2) ◽  
pp. 16-22 ◽  
Author(s):  
Deepa Mangala ◽  
S.K. Sharma
Keyword(s):  
Stock Market ◽  
Strong Evidence ◽  
Stock Markets ◽  
Major Part ◽  
Market Returns ◽  
Stock Market Returns ◽  
International Stock Markets ◽  
Indian Stock Market ◽  
Daily Returns

The seasonal components of stock market returns have been extensively documented, yet the major part remains unexplained. The monthly effect has been reported in several international stock markets. The objective of this paper is to examine the existence of monthly effect and turn-of-the-month effect in Indian stock market by using S&P CNX Nifty index over the period from January 1994 to April 2005. The results reveal significantly high mean daily returns for days immediately before and during the first half of the month, especially, during the first few trading days of the month and indistinguishable from zero or even negative mean returns for the second half and the rest of the month. Turn-of-the-month is marked by abnormally high returns. This gives a strong evidence of existence of monthly effect and turn-of-the-month effect in Indian stock market.

Are there Monthly and Turn-of-the-Month Effects in Indian Stock Market?: Evidence and Implications

Paradigm ◽  
2007 ◽  
Vol 11 (2) ◽  
pp. 9-15
Author(s):  
Deepa Mangala ◽  
S.K. Sharma
Keyword(s):  
Stock Market ◽  
Strong Evidence ◽  
Stock Markets ◽  
Major Part ◽  
Market Returns ◽  
Stock Market Returns ◽  
International Stock Markets ◽  
Indian Stock Market ◽  
Daily Returns

The seasonal components of stock market returns have been extensively documented, yet the major part remains unexplained. The monthly effect has been reported in several international stock markets. The objective of this paper is to examine the existence of monthly effect and turn-of-the-month effect in Indian stock market by using S&P CNX Nifty index over the period from January 1994 to April 2005. The results reveal significantly high mean daily returns for days immediately before and during the first half of the month, especially, during the first few trading days of the month and indistinguishable from zero or even negative mean returns for the second half and the rest of the month. Turn-of-the-month is marked by abnormally high returns. This gives a strong evidence of existence of monthly effect and turn-of-the-month effect in Indian stock market.

scholarly journals Nexus between Stock Market Returns and Economic Variables: Evidence

2017 ◽  
Vol 4 (01) ◽  
Author(s):  
Vanitha Chawla ◽  
Shweta .
Keyword(s):  
Exchange Rate ◽  
Stock Market ◽  
Granger Causality ◽  
Granger Causality Test ◽  
Market Returns ◽  
Causality Test ◽  
Stock Market Returns ◽  
Macroeconomic Variables ◽  
Indian Stock Market ◽  
The Impact

The paper examines the impact of selected macroeconomic variables on the Indian stock market. The macroeconomic variables used in the study are interest rate, exchange rate, index of industrial production (IIP) and gold price. BSE Sensex is used as proxy for Indian stock market. We have used the monthly data for all the variables from January 2001 to December 2016. Regression analysis and Granger Causality test is used to establish the relationship between the stock market and macroeconomic variables. The results show significant impact of only exchange rate on stock returns. All the other variables have shown insignificant impact on the stock market returns. The results of Granger causality test show unidirectional relationship between exchange rate and stock prices and bi-directional relation between IIP and SENSEX.

scholarly journals Volatility Nexus Between Stock Market and Macroeconomic Variables in Bangladesh: an Extended GARCH Approach

2017 ◽  
Vol 64 (2) ◽  
pp. 233-243 ◽  
Author(s):  
Md. Abu Hasan ◽  
Anita Zaman
Keyword(s):  
Exchange Rate ◽  
Stock Market ◽  
Stock Returns ◽  
Stock Exchange ◽  
Market Returns ◽  
Stock Market Returns ◽  
Macroeconomic Variables ◽  
General Index ◽  
Indian Stock Market ◽  
The Garch Model

Abstract This paper examines the volatility of the Bangladesh stock market returns in response to the volatility of the macroeconomic variables employing monthly data of general index of Dhaka Stock Exchange (DSE) and four macroeconomic variables (Call Money Rate, Crude Oil Price, Exchange Rate and SENSEX of Bombay Stock Exchange) from January 2001 to December 2015. The results of GARCHS models reveal that the volatility of DSE return is significantly guided by the volatility of macroeconomic variables, such as, exchange rate and SENSEX. Specifically, volatility of the DSE is expected to 19% increase by 1% increase of exchange rate. Moreover, the volatility of the Bangladesh stock market returns is expected to dampen down by 2% with an increase in the volatility of Indian stock market of 1%. Thus, we can comment that adding exchange rate or stock returns of India in the GARCH model provides significant knowledge about the behaviour of the DSE volatility.

Sign in / Sign up

Export Citation Format

Share Document