The purpose of this research is to forecast the following day's closing price for a specific share of a company in the stock market using the "Hidden Markov Model". In this paper, the "Hidden Markov Model" is used to predict some of the stocks of interconnected airline markets. The researchers have developed the "Hidden Markov Model" for forecasting time series. As a result of its ability to model dynamic systems, this model is widely used for the
recognition of model and problem classifications.
In this article, the researchers examined trends in the historical data set. They inserted the appropriate neighboring prices to the datasets and predicted the next day's exchange. Data collection was secondary. The secondary market was collected from Southwest Airlines for 1.5 years (approximately) from September 17, 2002, to December 16, 2004. The observations of the input data are continuous rather than discrete. The sample size is 4 airline firms (British Airlines, Delta Airlines, Southwest Airlines, and Ryanair Holdings Ltd.)
The NIFTY IT index captures the performance of the Indian Information Technology (IT) companies. The NIFTY IT index consists of 10 companies listed on the National Stock Exchange (NSE). The IT sector in India has been recording tremendous growth over the years, where it accounts for a growth rate of 7.5 percent per annum.
Time series analysis is a statistical tool that can be used in forecasting the prices of financial assets. In the current study, the NIFTY IT index was forecasted from past data collected over a 10 year period spanning from 2011 to 2020. An ARIMA model is fit and used to forecast the NIFTY IT index. Forecasted values were different from actual prices, suggesting that more influencing independent variables must be include, to improve the model accuracy.
Table of Contents
1. INTRODUCTION
1.1 Introduction – Information Technology Industry and NIFTY IT
1.2 Impact of IT on the Indian Economy
1.3 Performance of IT industry in the Past Decade
2. DESIGN OF THE STUDY
2.1 Review of Literature
2.2 Statement of the Problem
2.3 Objectives
2.4 Hypothesis
2.5 Scope of the Study
2.6 Research Methodology
2.7 Research Tools
2.8 Data Collection Method
2.9 Plan of Analysis
2.10 Limitation of the Study
3. PROFILE OF THE COMPANY
3.1 Information Technology Industry
3.1.1 Introduction
3.1.2 Industry Structure of the IT Sector
3.1.3 Growth of IT Sector
3.1.4 Market Size of IT Industry
3.1.5 Challenges in IT industry
3.1.6 Government Regulations
3.1.7 Future Prospects of IT Industry
3.1.8 Future Trends in 2021
3.1.9 India’s IT Sector – Growing Opportunities for Investment
3.2 National Stock Exchange
3.3 NIFTY IT Index
3.4 Porter’s Five Force
3.5 Company Profile
4. DATA ANALYSIS
4.1 Summary Statistics
4.1.1 Normality Test
4.2 Time Series Plot
4.3 Dicky Fuller Test
4.4 Correlogram
4.5 Model 2: ARIMA
4.6 Hypothesis Testing
5. SUMMARY OF FINDINGS, CONCLUSION, SUGGESTION
5.1 Summary of Findings
5.2 Conclusion
5.3 Suggestions
Objectives and Topics
The primary objective of this research is to forecast the NIFTY IT index using historical weekly data from 2011 to 2020 through time series analysis. By applying statistical modeling techniques, the study aims to provide investors with a reliable tool for understanding price movements, volatility, and future trends within the Indian IT sector.
- Forecasting stock index prices using the ARIMA model.
- Evaluating the impact of the IT sector on the Indian economy.
- Analyzing the competitive landscape of major IT firms via SWOT analysis.
- Assessing market volatility and the effectiveness of time series forecasting techniques.
Excerpt from the Book
1.1 INTRODUCTION
The twenty-first century is known as the Digital age or age of information technology. The twenty-first century is known as the Digital age or age of information technology. Globally, India is a knowledge-based economy because of its impressive IT (Information Technology) sector or industry. In today's society, the use of information and communication (ICT) has made the world a better place to stay, making our lives easy than ever before. Today we use virtual technology from whether we want a piece of information or make a call to those that live miles away from us.
In India, two significant stock exchanges are present. These two stock exchanges are the Bombay Stock Exchange (BSE) SENSEX and National Stock Exchange (NSE), NIFTY. NIFTY is a benchmark index for the equity market of India. Stock market indices also provide a barometer to measure the direction or trend of market behavior. NIFTY 50 comprises 14 sectors of the country's economy and offers possible opportunities to the investment manager in one portfolio. NIFTY IT is one of those sectors. NIFTY 50 delivered negative returns in only two years since the beginning – in 2011 (-24.62%) due to high inflation, interest rate hike, rupee depreciation, and slowing economic growth and in 2015 (-4.06%) due to low corporate earnings and the Bharatiya Janata Party's loss in Delhi and Bihar state elections.
Summary of Chapters
1. INTRODUCTION: This chapter provides an overview of the role of the IT industry in the global and Indian economy, alongside a brief context on the importance of forecasting stock market indices.
2. DESIGN OF THE STUDY: This section details the research methodology, including the literature review, research objectives, hypothesis, data collection techniques, and the plan of analysis using the ARIMA model.
3. PROFILE OF THE COMPANY: This chapter covers the industry structure, growth factors, and SWOT analysis for major IT companies like TCS, Infosys, and HCL, providing a business context for the sector.
4. DATA ANALYSIS: This chapter presents the empirical results of the study, covering summary statistics, stationarity tests (Dicky-Fuller), and the implementation of the ARIMA model for index forecasting.
5. SUMMARY OF FINDINGS, CONCLUSION, SUGGESTION: This chapter synthesizes the results, concludes on the effectiveness of the model, and offers suggestions for future research and investor decision-making.
Keywords
NIFTY IT, Stock Market Prediction, Time Series Analysis, ARIMA Model, Indian IT Sector, Forecasting, Bombay Stock Exchange, National Stock Exchange, Market Capitalization, Volatility, Data Mining, Regression Analysis, Economic Growth, Investment Strategy, Financial Forecasting.
Frequently Asked Questions
What is the core purpose of this study?
The study aims to evaluate the effectiveness of the ARIMA model in forecasting the price movements of the NIFTY IT index in the Indian stock market.
Which indices were analyzed in this research?
The primary focus is on the NIFTY IT index, which captures the performance of leading IT companies listed on the National Stock Exchange (NSE).
What primary methodology is employed for forecasting?
The study utilizes Time Series Analysis, specifically the Autoregressive Integrated Moving Average (ARIMA) model, to predict future index prices based on historical trends.
How is the data collected for this research?
Secondary data was collected from various reliable sources, including annual reports of companies, official websites, and financial platforms like Moneycontrol and the NSE website.
What does the main body of the work cover?
The main body includes an industry overview, a detailed profile and SWOT analysis of key IT firms (TCS, Infosys, HCL), and the technical data analysis, including normality testing and the ARIMA modeling process.
What are the characterizing keywords of the research?
Key terms include NIFTY IT, Time Series Analysis, ARIMA Model, stock market prediction, volatility, and financial forecasting.
What were the results of the hypothesis testing in the study?
The study concluded that there is a significant difference between forecasted and actual values, suggesting that additional independent variables are required to improve model accuracy.
How did the COVID-19 pandemic affect the index performance?
The analysis shows a drastic downfall in the NIFTY IT index price during the 2020 crisis, falling from approximately 16,000 to 11,000.
- Citar trabajo
- Rajveer Rawlin (Autor), Dhanya ML (Autor), 2021, Forecasting India's NIFTY IT Index, Múnich, GRIN Verlag, https://www.grin.com/document/1034328
