# Relationship of reliance industry and nifty

Introduction:

Reliance Industries Limited is an Indian multinational conglomerate, headquartered in Mumbai. It has diverse businesses including energy, petrochemicals, natural gas, retail, telecommunications, mass media, and textiles.

Objective: Calculation of Beta of Reliance Industry and its significance.

Literature review:

Research shows that high-frequency data for publicly-listed Japanese manufacturing firms over the period 2000 to 2010 to show that a greater reliance on foreign market sales increases the conditional volatility of firms’ stock returns. The two margins of global engagement we consider, namely, exports and sales via foreign affiliates, have both a positive and economically significant effect on firm-level volatility, although an increase in the intensity of sales through foreign affiliates has a stronger effect on volatility than a similar change in firms’ export intensity.

The EC aims to return the European economy to sustainable growth and to enhance its shock absorbing capacity by reducing the reliance on bank finance and stimulating financial deepening and cross-border integration of Europeâ€™s capital markets. Financial diversification and integrated European capital markets are expected to improve risk sharing among households, supporting economic stability.

Data collection: The data was collected from the Yahoo finance website for the financial year 2022-2023, and only Friday closing prices were considered for the analysis. The Nifty 50 returns were taken as X, and the Company return was taken as Y. and hence the study is analyzing the relationship between Nifty 50 returns and company returns of some asset(s) during the specified time period.

Data Analysis:
Reliance Ltd Returns = -0.25 + 0.99 Nifty Returns
(5.24)

N= 51, R2= 0.35, F= 27.5, Significance Value = 3.27
t- Stat = 5.24

The above equation shows the relationship between Y and X. Positive sign means there is inverse relationship, which means if X rises and Y falls and Vise-Versa. In this equation b = 0.99. Figure in bracket is T-stat for b it is more than the table value. R2 = 35% of Y is explained by X. F = 27.5. The beta is 0.99 which means it is less than 1

Conclusion:
Here Beta is 0.99 which is less than 1 therefore it is good for long term investment

Refrences:

Sourafel Girma & Sandra Lancheros & Alejandro Riaño, 2015. “Global Engagement and Returns Volatility,” CESifo Working Paper Series 5650, CESifo.

Emiel F.S. van Bezooijen & J.A. Bikker, 2017. “Financial Structure and Macroeconomic Volatility: a Panel Data Analysis,” Working Papers 17-13, Utrecht School of Economics.