Portfolio Analysis of Major Mining Industries using Artificial Neural Networks

Rath, Sai Prasanna (2015) Portfolio Analysis of Major Mining Industries using Artificial Neural Networks. MTech thesis.

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Abstract

Mining industries are the backbone of Indian economy. Considering the role of mining in India, investing on mining industries will be highly profitable. The financial, technical analysis and price forecasting techniques help the people in clearing the ambiguity between different portfolio options for investment. These traditional techniques are more of theoretical derivation from the results so there is a need for a strong mathematical modelling of the past behaviour of the portfolio options which can then predict the future behaviour. Artificial neural network is one of the best choices available in such conditions. The main objective of any investor being to maximize the returns from his portfolio, artificial neural networks will play an important role in the portfolio analysis. The project work involved comparison of financial and technical analysis and use of Artificial Neural Network approach for analysing a portfolio in order to select a portfolio option to invest in near future. Here the portfolio options for three mining companies were pre-decided i.e. Coal India Limited, NMDC Limited Enterprises Limited. Then the financial and technical analyses were applied on the stocks of above mentioned companies. Trend lines were also fitted as per the past stock prices and forecasted over to the future. Next the artificial neural network models for each company were modelled over their daily and weekly data sets from October 2011- October 2014. The models were then tested on unknown data sets. An accuracy in the range of 86% - 93% was achieved on the testing data. Predictions were more accurate for a daily basis instead of weekly prediction. At last the results from traditional and ANN methods were combined. Financial ratios implied CIL and NMDC to be the preferable choice while technical indicators supported CIL and AEL. Finally the results from ANN were inferred and it was derived that the CIL stock could be the most preferable choice for investment in near future.

Item Type:Thesis (MTech)
Uncontrolled Keywords:Financial analysis, Portfolio, Neural network, Technical analysis
Subjects:Engineering and Technology > Mining Engineering > Mining Economics
Divisions: Engineering and Technology > Department of Mining Engineering
ID Code:9391
Deposited By:Mr. Sanat Kumar Behera
Deposited On:23 May 2018 16:47
Last Modified:23 May 2018 16:47
Supervisor(s):Tripathy, D P

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