Earticle

초록

영어

Stock markets are popular investment avenues to people who plan to receive premium returns compared to other financial instruments, but they are highly volatile and risky due to the complex financial dynamics and poor understanding of the market forces involved in the price determination. A system that can forecast, predict the stock prices and automatically create a portfolio of top performing stocks is of great value to individual investors who do not have sufficient knowledge to understand the complex dynamics involved in evaluating and predicting stock prices. In this paper the authors propose a Stock prediction, Portfolio Generation and Selection model based on Machine learning algorithms, Artificial neural networks (ANNs) are used for stock price prediction, Mathematical and Statistical techniques are used for Portfolio generation and Un-Supervised Machine learning based on K-Means Clustering algorithms are used for Portfolio Evaluation and Selection which take in to account the Portfolio Return and Risk in to consideration. The model presented here is limited to predicting stock prices on a long term basis as the inputs to the model are based on fundamental attributes and intrinsic value of the stock. The results of this study are quite encouraging as the stock prediction models are able predict stock prices at least a financial quarter in advance with an accuracy of around 90 percent and the portfolio selection classifiers are giving returns in excess of average market returns.

목차

ABSTRACT
Ⅰ. Introduction
Ⅱ. Literature Review
Ⅲ. Methods and Models
3.1. ANN Based Stock Prediction Model
3.2. Mathematical Model for Creating Stock Portfolios
3.3. Classification Model for Stock Portfolio Evaluation and Selection
Ⅳ. Data and Results
4.1. Attribute Selection and Analysis
4.2. Data Sources
4.3. Stock Prediction Results
4.4. Stock Portfolio Generation Results
Ⅴ. Findings and Implications
5.1. Major Findings of the Study
5.2. Implications of the Study
5.3. Limitations of the Study
5.4. Conclusions

키워드

저자

• Sandeep Patalay [ Research Scholar, Dept. of Management Studies, Vignan’s University, India ] Corresponding Author
• Madhusudhan Rao Bandlamudib [ Professor, Dept. of Management Studies, Vignan’s University, India ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  Asia Pacific Journal of Information Systems

• 간기

  계간

• pISSN

  2288-5404

• eISSN

  2288-6818

• 수록기간

  1990~2026

• 등재여부

  KCI 등재,SCOPUS

• 십진분류

  KDC 325 DDC 658