INTRODUCTION
Sun TV Network Limited is one of India’s largest and most influential media and entertainment companies, headquartered in Chennai. Incorporated in 1993, the company operates a diversified portfolio spanning satellite television channels, FM radio stations, newspapers, magazines, and digital platforms. Sun TV Network is best known for its leadership in South Indian regional broadcasting, with channels catering to Tamil, Telugu, Kannada, and Malayalam audiences.
The company commands a dominant viewership share in regional television markets and has consistently demonstrated strong operating margins and cash flows. As a listed entity on the National Stock Exchange (NSE) and Bombay Stock Exchange (BSE), Sun TV Network Limited attracts significant investor interest as a defensive stock within the media and entertainment sector, owing to its relatively stable revenue streams and low dependence on economic cycles compared to other sectors
OBJECTIVE
To calculate the β (Beta) of Sun TV Network Limited and examine its statistical significance with respect to the NIFTY 50 index, thereby assessing the stock’s sensitivity to overall market movements.
DATA COLLECTION
Weekly historical price data for Sun TV Network Limited and the NIFTY 50 index was collected from the NSE website for the period 01 December 2024 to 30 November 2025.
The daily data was processed to extract Friday closing prices, and weekly returns were computed using percentage change methodology.
LITERATURE REVIEW
Prior research highlights the importance of benchmarking individual stock performance against broad market indices to understand systematic risk. Gupta (2024) notes that sector-specific stocks, particularly in media and consumer-oriented industries, often exhibit lower volatility compared to the broader market. Joshi (2023) emphasizes that investor sentiment and macroeconomic shocks significantly influence index movements, but individual stocks may react differently based on sectoral fundamentals.
Further, Joshi and Rohitraj (2024) and Patil and Saware (2024) demonstrate that Beta serves as a crucial measure of market risk, helping investors classify stocks as aggressive or defensive. Media stocks, in particular, are often characterized by lower beta values, reflecting their relatively stable demand and predictable revenue models. Regression-based beta estimation remains a widely accepted method to quantify this relationship between stock returns and market returns.
DATA ANALYSIS
Regression Equation :- y = 0.0529x + 0.0522
Where:–
y = Weekly return of Sun TV Network Limited
x = Weekly return of NIFTY 50
The regression equation indicates a very weak positive relationship between NIFTY 50 returns and Sun TV’s weekly returns.
Number of Observations = 48
β (Beta) = 0.0529
t-statistic for β = 0.2739
p-value = 0.7853
Since the p-value is greater than 0.05, beta is not statistically significant at the 5% level. This implies that changes in NIFTY 50 returns do not significantly explain movements in Sun TV’s stock returns during the study period.
R² = 0.0016
This indicates that only 0.16% of the variation in Sun TV’s weekly returns is explained by market movements, while 99.84% is influenced by firm-specific or other external factors not included in the model.
F-statistic = 0.075
Significance F = 0.7853
Since Significance F > 0.05, the overall regression model is not statistically significant.
CONCLUSION
The estimated β of Sun TV Network Limited is 0.0529, which is significantly less than 1, indicating that the stock is defensive in nature and exhibits very low sensitivity to market movements. However, the beta is statistically insignificant, suggesting that NIFTY 50 returns do not meaningfully predict Sun TV’s stock returns over the selected period.
From an investment perspective, Sun TV Network Limited may be considered suitable for risk-averse and long-term investors, as its returns appear to be driven more by internal business fundamentals rather than overall market volatility.
REFERENCES
Gupta, P. K. (2024). Analysing the dynamic interrelationship between Nifty-Fifty and sectoral indices daily returns of the National Stock Exchange. International Research Journal of Modernization in Engineering Technology and Science, 6(9).
Joshi, N. A. (2023). Impact of Covid-19 on performance on Indian stock indices: A study for NSE composite and sectoral indices. Copernican Journal of Finance & Accounting, 11(4), 125–146.
Joshi, A., & Rohitraj, S. (2024). Risk-return analysis of selected energy stocks with Nifty Energy and Nifty 50. Twenty Second AIMS International Conference on Management, 1843–1847.