scholarly journals STOCK PRICE SEASONALITY EFFECT AND TRADING STRATEGY – AN EMPIRICAL STUDY OF SELECTED IT COMPANIES IN INDIA

2012 ◽  
Vol 10 (2) ◽  
pp. 264-288 ◽  
Author(s):  
Sathya Swaroop Debasish
Keyword(s):  
Portfolio Management ◽  
Stock Price ◽  
Stock Exchange ◽  
Trading Strategy ◽  
Primary Objective ◽  
Price Series ◽  
Active Portfolio Management ◽  
Multiple Regression Technique ◽  
Indian Stock Market ◽  
Returns On Investment

The primary objective of the study is to investigate the existence of seasonality in stock price behavior in Indian stock market and more specifically in the IT sector. The period of the study is from 3rd November 1994 to 31st December 2010. The study has employed daily price series of selected seven IT companies obtained from the official website of National Stock Exchange (NSE). The study used multiple regression technique to examine the significance of the regression coefficient for investigating day of week effects and week of the month effect, and Kruskal Wallis for analysis of trading strategy. It is found that all the seven selected IT companies evidenced day of the week effect and mostly either on Monday, Tuesday or Wednesday. Only Patni and Wipro evidenced significant Thursday effect. Similarly, evidence on week of month effect mostly either on 1st week, 2nd week or 3rd week. This implies that active portfolio management taking into account the findings will provide superior returns on investment in the IT sector in India.

A Historical Data based Ensemble System for Efficient Stock Price Prediction

2019 ◽  
Vol 12 ◽  
Author(s):  
Vijay Kumar Dwivedi ◽  
Manoj Madhava Gore
Keyword(s):  
Stock Price ◽  
Prediction Models ◽  
Historical Data ◽  
Stock Exchange ◽  
Primary Objective ◽  
Lasso Regression ◽  
Stock Price Prediction ◽  
Price Prediction ◽  
Consistent Manner ◽  
Selection Operator

Background: Stock price prediction is a challenging task. The social, economic, political, and various other factors cause frequent abrupt changes in the stock price. This article proposes a historical data-based ensemble system to predict the closing stock price with higher accuracy and consistency over the existing stock price prediction systems. Objective: The primary objective of this article is to predict the closing price of a stock for the next trading in more accurate and consistent manner over the existing methods employed for the stock price prediction. Method: The proposed system combines various machine learning-based prediction models employing least absolute shrinkage and selection operator (LASSO) regression regularization technique to enhance the accuracy of stock price prediction system as compared to any one of the base prediction models. Results: The analysis of results for all the eleven stocks (listed under Information Technology sector on the Bombay Stock Exchange, India) reveals that the proposed system performs best (on all defined metrics of the proposed system) for training datasets and test datasets comprising of all the stocks considered in the proposed system. Conclusion: The proposed ensemble model consistently predicts stock price with a high degree of accuracy over the existing methods used for the prediction.

scholarly journals Random Walk Investigation in Indian Market with special reference to S&P Nifty – Fifty Stocks

2015 ◽  
Vol 4 (4) ◽  
pp. 52-61
Author(s):  
Tamilselvan Manickam ◽  
R Madhumitha
Keyword(s):  
Stock Market ◽  
Stock Exchange ◽  
Abnormal Returns ◽  
Empirical Support ◽  
Weak Form ◽  
Indian Market ◽  
Price Series ◽  
Stock Market Efficiency ◽  
Indian Stock Market ◽  
Weak Form Efficiency

The competence of a financial system is entirely depending upon the stock market efficiency. The gradual growth of equity investor’s participation is inevitable to enrich the overall growth of emerging economies.Hence the necessity is felt to provide an empirical support to the investing community. For the purpose, this study attempts to examine the weak-form efficiency of Indian stock market – National Stock Exchange (NSE). The study has used the daily closing price of the Nifty fifty stocks from 3rdJanuary 2011 to 24thApril 2015. To test the weak form efficiency both parametric and non-parametric tests called Autocorrelation, Augmented Dicky Fuller test, and Runs Test were performed.  The study reveals that 39 stocks of NSE-Nifty Fifty are found to be weak form inefficient, so that the investors can formulate trading strategies to gain abnormal returns. The Index and 10 stocks are found to be weak form efficient during the study period since the price series found to be autocorrelation existence.

scholarly journals Efficient Market Hypotheses Controversy and Nigerian Stock Exchange Relations

2020 ◽  
pp. 1-13
Keyword(s):  
Stock Market ◽  
Stock Price ◽  
Stock Exchange ◽  
Unit Root Test ◽  
General Meeting ◽  
Weak Form ◽  
Efficient Market Hypothesis ◽  
Annual Data ◽  
Efficient Market ◽  
Price Series

This study; Nigerian Stock Exchange and Efficient Market Hypothesis was done using All Share Index (ASI) with daily data from January 02, 2014 to May 20, 2019 (1333 observations) and annual data from 1985 to 2018 (34 observations) collected from the Nigeria Stock Market fact books. The study employed three analytical methods namely the unit root test, GARCH Model and the Autocorrelation cum patial autocorrelation method for the assessment of weak form hypothesis on the daily and annual all share index in the Nigerian Stock market. The results of these evaluations indicated a significant relationship between the price series and their lagged values implying that stock price series do not follow a random walk process in Nigerian stock market. Thus, affirming that the Nigeria Stock Exchange is not efficient in weak form. In the light of this, the researchers recommend that the supervisory and regulatory authorities should strengthen the Nigerian Stock Market through palliating its regulations pertaining to transparency of information management rules such as market barriers and stringent listing requirement, publication of accounts, notices of annual general meeting and the like.

Impact on Stock Price by the Inclusion to and Exclusion from CNX Nifty Index

2012 ◽  
Vol 13 (1) ◽  
pp. 39-50 ◽  
Author(s):  
M. Selvam ◽  
G. Indhumathi ◽  
J. Lydia
Keyword(s):  
Stock Market ◽  
Stock Prices ◽  
Stock Price ◽  
Research Study ◽  
Stock Exchange ◽  
Valuation Effect ◽  
Index Maintenance ◽  
Indian Stock Market ◽  
The Impact ◽  
Indian Perspective

Changes in an index are a regular phenomenon and they take place due to the inclusion and exclusion of stocks from the index. The inclusion or exclusion of stocks creates great impact on the value of the firm. However, these changes are simply a short-lived event with no permanent valuation effect. The present research study analyzed the impact of the inclusion into and exclusion of certain stocks from National Stock Exchange (NSE) S&P CNX Nifty index with Indian perspective. The study provides evidence on whether the announcements of Nifty index maintenance committee have any information content. This will also demonstrate the efficiency of Indian stock market with particular reference to NSE. The study revealed that on an average, no permanent effects were observed on stock prices. It is also found from the study that the NSE reacted unfavourably to the inclusion and exclusion of stocks and it is impossible to earn any excess returns where the particular stocks are included or excluded from the index.

scholarly journals Implementation of Fibonacci Retracements and Exponential Moving Average (EMA) Trading Strategy in Indonesia Stock Exchange

2021 ◽  
Vol 6 (4) ◽  
pp. 402-408
Author(s):  
Lusindah Lusindah ◽  
Erman Sumirat
Keyword(s):  
Stock Market ◽  
Stock Price ◽  
Stock Exchange ◽  
Moving Average ◽  
Time Frame ◽  
Trading Strategy ◽  
Individual Investors ◽  
Individual Investor ◽  
Back Testing ◽  
The Individual

Based on KSEI statistic data on March 2021, IDX individual stock market investor is increasing 199% compared to 2018 becoming 4,848,954 number of investors. 56.9% population of the individual investor is having ages that less than 30 years. In the period where IDX was bullish in November 2020 - January 2021, there is a phenomenon where stocks influencers appeared in social media and impacted to the stock price movement after the announcement is done by the influencer. In contrary, during bearish and sideways condition, those influencers were gone and changed with bad news that went viral where many individual investors are lost their capital in IDX. They lose money since they are gambling in the stock market without any analysis and no establishment of trading plan. This research is aimed as a strategy to individual investors in IDX to implement trading strategy based on Fibonacci retracements and projections, EMA lines, trendlines, stochastic, and volume. Back testing is conducted in IDX SMC Liquid index constituents during January 2018 until December 2020 period. By implementing this trading strategy, return generated is 164% for 3 years trading time frame. Author also found that this trading strategy is effective in bullish trend condition especially for individual investors that have long position.

Seasonality in Momentum Profits: Evidence from the Indian Stock Market

2015 ◽  
Vol 4 (3and4) ◽  
Author(s):  
Supriya Maheshwari ◽  
Raj S. Dhankar
Keyword(s):  
Stock Market ◽  
Stock Price ◽  
Stock Exchange ◽  
Practical Implementation ◽  
Momentum Strategies ◽  
Momentum Profits ◽  
Significant Difference ◽  
The Us ◽  
Show Evidence ◽  
Indian Stock Market

The paper investigates Indian momentum profitability along with its performance stability round the year using the stock price data from National Stock Exchange (NSE). Results show evidence in favour of momentum profitability over the sample period from 1997 to 2013. Moreover, the momentum performance is not specific to any particular month suggesting no influence of calendar on momentum anomaly in the Indian stock market, though momentum strategies performed differently in different calendar months, with particularly strong negative returns in the month of May. However, no statistically significant difference was observed among the mean monthly momentum returns across calendar months. Contrary to the US market findings, no January or similar April seasonality is observed in the Indian momentum profits suggesting some unique characteristics of Indian momentum profitability. In nutshell, the results from the study suggest support in favour of practical implementation of momentum strategies throughout the year in the Indian stock market.

scholarly journals Efficient Market Hypotheses Controversy and Nigerian Stock Exchange Relations

2020 ◽  
Vol 2 (1) ◽  
pp. 1-13
Author(s):  
Chukwu Agwu Ejem ◽  
Udochukwu Godfrey Ogbonna ◽  
Godwin Chigozie Okpara
Keyword(s):  
Stock Market ◽  
Stock Price ◽  
Stock Exchange ◽  
Unit Root Test ◽  
General Meeting ◽  
Weak Form ◽  
Efficient Market Hypothesis ◽  
Annual Data ◽  
Efficient Market ◽  
Price Series

This study; Nigerian Stock Exchange and Efficient Market Hypothesis was done using All Share Index (ASI) with daily data from January 02, 2014 to May 20, 2019 (1333 observations) and annual data from 1985 to 2018 (34 observations) collected from the Nigeria Stock Market fact books. The study employed three analytical methods namely the unit root test, GARCH Model and the Autocorrelation cum patial autocorrelation method  for the assessment of weak form hypothesis on the daily and annual all share index in the Nigerian Stock market. The results of these evaluations indicated a significant relationship between the price series and their lagged values implying that stock price series do not follow a random walk process in Nigerian stock market. Thus, affirming that the Nigeria Stock Exchange is not efficient in weak form.  In the light of this, the researchers recommend that the supervisory and regulatory authorities should strengthen the Nigerian Stock Market through palliating its regulations pertaining to transparency of information management rules such as market barriers and stringent listing requirement, publication of accounts, notices of annual general meeting and the like. JEL Classification: C1, C4, E6, G1

scholarly journals Unsupervised Learning Based Stock Price Recommendation using Collaborative Filtering

2019 ◽  
Vol 8 (11) ◽  
pp. 2051-2055
Keyword(s):  
Machine Learning ◽  
Stock Market ◽  
Collaborative Filtering ◽  
Portfolio Management ◽  
Recommender System ◽  
Stock Price ◽  
Stock Exchange ◽  
Performance Measure ◽  
Machine Learning Algorithms ◽  
Market Data

In this study, 17 stock market data were adopted for long term Prediction of stock price. Now days, Stock market data have got a significant role for invest finance in portfolio management. The various non-linear algorithms and statistical models are used for forecasting of financial data. In this article, we have used application of recommender system for this purpose. We primarily focused on use of machine learning algorithms for developing a stock market data recommender system. Machine learning has become a widely operational tool in financial recommendation systems. Here we considered the daily wise equity trading of Nifty 50 from National Stock Exchange (NSE) of 50 companies in 10 different sectors around 5986 days’ transactions as data. We adopted k-Nearest Neighbors classification algorithm to classify users based recommender system. Collaborative filtering method uses for recommend the stock, the performance measure through RMSE, and R2. The result also reveals that k-NN algorithm shown more accuracy as compare to other existing methods

scholarly journals Investors’ risk perception in the context of efficient market hypothesis: A conceptual framework for malaysian and indonesian stock exchange

2021 ◽  
Vol 124 ◽  
pp. 03002
Author(s):  
Syed Emad Azhar Ali ◽  
Fong-Woon Lai ◽  
Muhammad Kashif Shad
Keyword(s):  
Risk Perception ◽  
Market Efficiency ◽  
Stock Returns ◽  
Portfolio Management ◽  
Stock Exchange ◽  
Composite Index ◽  
Efficient Market Hypothesis ◽  
Primary Objective ◽  
Efficient Market ◽  
Share Prices

The advocates of the Efficient Market Hypothesis (EMH) theory postulates that share prices depict all the available information concerning its intrinsic worth. EMH espouses the Random Walk Theory i.e. future stock returns cannot be predicted based on past movement patterns. Contrary to that, there are believers of the Adaptive Market Hypothesis (AMH) who have questioned the adaptability of EMH and argues that market efficiency and investor’s risk perception varies across time, thus, stock returns can be predicted through active portfolio management. Various Studies have argued on market efficiency debate for developed markets, however, limited studies have examined the same for emerging markets such as Malaysia and Indonesia, which are most volatile among ASEAN-5 indices. Therefore, the primary objective of this study is to conceptualize the manifestation of efficient market hypothesis and investors’ risk perception in volatile markets of Malaysia (Kuala Lumpur Composite Index) and Indonesia (Jakarta Composite Index) by testing the 10 years (2010-2019) of daily, weekly and monthly data for the return predictability. The findings of this study will provide insight into stock market behavior to help investors to better strategize their portfolio investment positioning to reap the most efficient risk-based return.

scholarly journals Impact of merger & acquisition announcements on share price – a case of selected indian listed companies

2013 ◽  
Vol 1 (3) ◽  
pp. 384-391
Author(s):  
Poornima V ◽  
Chitra V
Keyword(s):  
Stock Price ◽  
Stock Exchange ◽  
Merger And Acquisition ◽  
Share Price ◽  
Stock Price Reaction ◽  
Study Methodology ◽  
Acquisition Announcements ◽  
Indian Stock Market ◽  
The Impact ◽  
Event Study Methodology

This study examines the impact of merger and acquisition announcements on share price towards acquiring companies during the year 2012 listed on National Stock Exchange, India. The investigation has been carried out using traditional event study methodology. The present study is an empirical analysis to examine the stock price reaction to information content of merger and acquisition announcements with a view of finding whether Indian stock market is semi-strong efficient or not. Impact has been analyzed between 7 days from the date of merger and acquisition announcement. The result divulges that around the announcement period the returns for the acquiring companies are higher. In the post merger announcement period there is an upward trend in the cumulative returnsimplying a positive result of the merger.

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