E-ISSN:2583-0074

Research Article

Stock Exchange

Social Science Journal for Advanced Research

2025 Volume 5 Number 6 November
Publisherwww.singhpublication.com

Historical Analysis of the Index Nifty 50 Returns and its Potential to Create Wealth in Long Term

Singh C1*
DOI:10.5281/zenodo.17787083

1* Chitranjan Singh, HOD and Assistant Professor, Department of Commerce, Government Degree College, Vrindavan, Mathura, Uttar Pradesh, India.

Amsterdam Stock Exchange was the first stock exchange of the world and it was established in 1602.1 New York stock exchange of USA was established in 1792.2 Bombay stock exchange of India was established in 1975 3 and Nifty 50 was established in 1996.4 We observe Indian history of stock trading is not very old, it is very new when compared to other stock exchanges of the world. Study exhibits returns i.e. compounded annual growth rate CAGR and volatility of Nifty 50 to help investors to understand it in a simple way.

Keywords: BSE, NSE, CAGR, volatility, nifty 50, stock exchange

Corresponding Author How to Cite this Article To Browse
Chitranjan Singh, HOD and Assistant Professor, Department of Commerce, Government Degree College, Vrindavan, Mathura, Uttar Pradesh, India.
Email: 		Singh C, Historical Analysis of the Index Nifty 50 Returns and its Potential to Create Wealth in Long Term. Soc Sci J Adv Res. 2025;5(6):14-16.
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https://ssjar.singhpublication.com/index.php/ojs/article/view/303

Manuscript Received Review Round 1 Review Round 2 Review Round 3 Accepted
2025-10-01 2025-10-21 2025-11-07
Conflict of Interest Funding Ethical Approval Plagiarism X-checker Note
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© 2025 by Singh C and Published by Singh Publication. This is an Open Access article licensed under a Creative Commons Attribution 4.0 International License https://creativecommons.org/licenses/by/4.0/ unported [CC BY 4.0].

Soc Sci J Adv Res 2025;5(6)14
Download PDFBack To Article1. Introduction2. Objective of
the Study3. Data Collection4. Data Analysis5. Major Events
during life time of
Nifty 506. ConclusionReferences
Singh C. Historical Analysis of the Index Nifty 50 Returns

1. Introduction

This research paper covers study of nifty 50 index returns since its commencement to the December 2024. It also studies various ups and downs in the journey. Finally through statistical analysis it tries to understand volatility in its returns and understand how index can be used for long term wealth creation.

2. Objective of the Study

When compared to other stock exchanges of the world in India concept is new and only some decades old. This study provides returns CAGR and volatility to make it easy to understand. It will help to enhance knowledge of the investors as study discusses CAGR from the very inception of Nifty 50. It also throws light on volatility of the Nifty 50. Study also describes some major events happened during its inception to 2024.

3. Data Collection

the study is based on secondary data. Data has been collected from various websites including the official website of National stock exchange i.e. NSE.

Table 1: Closing Value of Nifty 50 at the end of every year from 1996 to 2024

Year EndClosing ValueYear EndClosing Value
1996899.120114,624.30
19971079.420125,905.10
1998884.2520136,304
19991,480.4020148,282.70
20001,263.5020157,946.30
20011,05920168,185.80
20021,093.50201710,530
20031,879.70201810,862.55
20042,080.50201912,168.45
20052,836.50202013,981.75
20063,966.40202117,354.05
20076,138.60202218,105.30
20082,959.10202321,731.40
20095,201202423,644.80
20106,134.50

https://www.niftyindices.com/reports/historical-data

4. Data Analysis

Data analysis has been done with the help of excel. Firstly CAGR has been calculated from the data.

Table 2: Calculation of CAGR for every year to 2024

Year EndClosing ValueCAGRYear EndClosing ValueCAGR
1996899.112.39%20114,624.3013.37%
19971079.412.11%20125,905.1012.26%
1998884.2513.47%20136,30412.77%
19991,480.4011.72%20148,282.7011.06%
20001,263.5012.98%20157,946.3012.88%
20011,05914.46%20168,185.8014.18%
20021,093.5014.99%201710,53012.25%
20031,879.7012.81%201810,862.5513.84%
20042,080.5012.92%201912,168.4514.21%
20052,836.5011.81%202013,981.7514.04%
20063,966.4010.43%202117,354.0510.86%
20076,138.608.26%202218,105.3014.28%
20082,959.1013.87%202321,731.408.80%
20095,20110.62%202423,644.800.00%
20106,134.5010.12%

After calculating CAGR average CAGR from 1996 to 2024 has been calculated. Standard deviation from the period 1996 to 2024 also been calculated. Calculation has been done in the following table, table 3-

Table 3: Calculation of average CAGR and standard deviation

Year EndCAGRYear EndCAGR
199612.39%201010.12%
199712.11%201113.37%
199813.47%201212.26%
199911.72%201312.77%
200012.98%201411.06%
200114.46%201512.88%
200214.99%201614.18%
200312.81%201712.25%
200412.92%201813.84%
200511.81%201914.21%
200610.43%202014.04%
20078.26%202110.86%
200813.87%202214.28%
200910.62%20238.80%
Average CAGR12.42%
Standard Deviation1.68%

From analysis we observe that average CAGR is of 12.42% per annum. This simply shows that in long run nifty 50 has provided roughly 12.5% return to its investors.

Standard deviation of the above CAGR is 1.68%. This shows that deviation is very less.


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Singh C. Historical Analysis of the Index Nifty 50 Returns

A standard deviation of 1.68 is a measure of how spread out a set of data is. It means that the values in the data set typically deviate from the mean by a value of 1.68. A low standard deviation means values are close to the mean, while a high one means values are more spread out. For a normal distribution, it would imply that roughly 95% of the data points fall between 1.68 standard deviations below and above the mean.

In finance, standard deviation is used to measure the volatility of an investment. A standard deviation of 1.68 would mean that an investment's returns have fluctuated by 1.68 on average over a specific period.

5. Major Events during life time of Nifty 50

Since its inception in 1996 Nifty 50 has witnessed many ups and downs. The worst year on Nifty 50 was 2008 in which it fell sharply due Global Financial Crisis. And interestingly 2009 was the best year as nifty 50 index recovered sharply.5

Life story of nifty 50 can be divided in to two phases viz. Bear phase and bull phase.

Some notable years of bear phase can be described as follows:

1996: nifty 50 witnessed a losing streak in the year of its inception for a straight 5 months.

2000-2001- In 2000 dot.com bubble got burst and all indices of the world seen sharp declines. Nifty 50 also experienced decline during this time.

2008: Nifty 50 plunged to its almost half value in the year of 2008 due to global financial crisis. Global financial crisis was started due to subprime mortgages in USA.

2011: Due to negative sentiments in the year 2011 nifty 50 witnessed a decline of more than 23%.

2020: Due to COVID-19 pandemic in the year 2020 nifty 50 lost its value heavily.

And notable years of bull phase can be discussed as follows:

2005 and 2006: Both years witnessed more than 35% growth in the index nifty 50.

2007: in the year 2007 returns of the index was more than 50%.

2009: 2009 was the best year ever. It witnessed more than 75% returns in it.

2017: in 2017 returns were more than 30% due to strong positive sentiments.

2020-21: nifty 50 index witnessed a v shaped recovery after post covid-19.

6. Conclusion

After analysis it is very obvious that if someone wants to invest for a long run one can invest in nifty 50 without much consideration. As in long run average CAGR is more than 12% per annum and standard deviation is very less.

It also has been observed that it entry in the market is at the time of crisis returns are better so one should not worry of crisis or fluctuation if investment is for long term.

References

1. https://en.wikipedia.org/wiki/Euronext_Amsterdam

2. https://en.wikipedia.org/wiki/New_York_Stock_Exchange

3. https://en.wikipedia.org/wiki/Bombay_Stock_Exchange

4. https://en.wikipedia.org/wiki/National_Stock_Exchange_of_India

5. https://en.wikipedia.org/wiki/Stock_market_crashes_in_India#:~:text=22%20Jan%202008%3A%20The%20Sensex,a%20loss%20of%20310%20points

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