i-manager Publications

Online Share Trading - A Premium for Web Communities

D. Kesavaraja*, D. Jeyabharathi**, D. Sasireka***

* Lecturer, Department of Computer Science and Engineering, Dr. Sivanthi Aditanar College of Engineering, Tiruchendur, Tamil Nadu, India.

** Lecturer, Department of Computer Science and Engineering, Einstein College of Engineering, Tirunelveli, Tamil Nadu, India.

*** Lecturer, Department of Information Technology, PSN College of Engineering and Technology, Melathediyoor, Tamil Nadu, India.

Periodicity:December - February'2011
DOI : https://doi.org/10.26634/jmgt.5.3.1317

Abstract

The purpose of this research is to present a critical analysis on the effect of Online Share Trading (OST) benefits by Indian Web Communities. Online share trading mechanisms at the exchanges are often a hybrid of traditional share trading and recent share trading techniques. The traditional share trading is carried out through Stock Brokers, Face To Face , through telephones , through Agencies which often provide time mismatches , location constraints, busy phone lines, miss communication whereas in Online Share Trading (OST), enormous OST techniques are made possible through Internet and Web Technology.The critical success factor highly depends on the OST Websites associated with Web Communities. Different aspects of trading execution, which is the identification of special activities and desires of the web Community, are analyzed. This leads to analyze the factors as 1) Customer Satisfaction 2) Need to interact with share trading.On analyzing the research among the users and service providers, the web communities are benefited relative to the best, efficient, durable, and profitable, less time consuming, dynamic and user friendly which bring forth both satisfied services and customers.

Keywords

Online Share Trading,Web,Internet,Trade,Services.

How to Cite this Article?

D. Kesavaraja, D. Jeyabharathi and D. Sasireka (2011). Online Share Trading - A Premium For Web Communities. i-manager’s Journal on Management, 5(3), 48-58. https://doi.org/10.26634/jmgt.5.3.1317

References

[1]. K.K. Ang, and C. Quek. (2006). Stock Trading Using RSPOP: A Novel Rough Set-Based Neuro-Fuzzy Approach. IEEE Transactions on Neural Networks, Vol. 17, NO.5, pp.1301-1315.

[2]. J. W. Lee and J. Park. (2007). A Multiagent Approach to Q-Learning for Daily Stock Trading. IEEE Transactions on Systems, Man and Cybernetics- Part A: Systems and Humans, Vol. 37, No. 6, November, pp.864-877.

[3]. Hsin-Tsung Peng, Hahn-Ming Lee, Jan-Ming Ho, (2005). "Trading Decision Maker: Stock Trading Decision by Price Series Smoothing and Tendency Transition Inference," IEEE International Conference on e- Technology, e-Commerce and e-Service (EEE'05), pp.359-362.

[4]. Y. Chen, S. Mabu, K. Hirasawa and J. Hu. (2007). Genetic Network Programming with Sarsa Learning and Its Application to Creating Stock Trading Rules. IEEE Congress on Evolutionary Computation (CEC2007), pp. 220-227.

[5]. Alistair Fitt (2000).Online Share Investing A UK Guide, Pearson Education, December.

[6]. John White. (2003). Investing in Stocks and Shares A Step-by-step Guide to Making Money on the Stock Market.

[7]. Michael Becket (2009). How the Stock Market Works A Beginner's Guide to Investment.

[8]. Just Consult India Online 2007 Online Share Trading Report.

[9]. NSE Fact book 2007.

[10]. www.sharetradingeducation.com

[11]. www.bigsky.net.au/OnlineTrading

[12]. www.religareonline.com

[13]. South Indian Online Share Trading Financial Service by Navia 2009.

[14]. Richard Greenwood (2007) The Basics of Online Share Trading .

If you have access to this article please login to view the article or kindly login to purchase the article

Single Article

	North Americas,UK, Middle East,Europe		India	Rest of world
	USD	EUR	INR	USD-ROW
Online	15	15

ADD TO CART

Options for accessing this content:

If you would like institutional access to this content, please recommend the title to your librarian.
If you already have i-manager's user account: Login above and proceed to purchase the article.
New Users: Please register, then proceed to purchase the article.