Relationship of Morgan Stanley With Nifty 50

Author: Meghna Undegaonkar [127] kohinoor business school

Introduction

Morgan Stanley is a leading global financial services firm providing investment banking, wealth management, and institutional securities services. 
As a publicly traded company, its stock performance is closely linked to market indices such as the Nifty 50. Understanding its Beta (β) value helps investors assess its volatility and correlation with market movements.

Objective

To determine the Beta (β) of Morgan Stanley and assess its significance in relation to Nifty 50.

Literature Review

1. Market Volatility and Beta Analysis

Misra and Mohapatra (2015) analyze the impact of market volatility on Beta values, particularly for financial institutions like Morgan Stanley. 
Their study highlights that global economic trends, interest rate changes, and monetary policies significantly influence stock movements and their correlation with major indices such as Nifty 50.

2. Stock Performance in Market Fluctuations

Gali (2021) examines how financial institutions, including investment banks like Morgan Stanley, respond to economic cycles. 
Using regression models and historical stock data, the study finds that investment banks exhibit unique volatility patterns, making their correlation with major indices like Nifty 50 less predictable during market fluctuations.

Data Collection

Data for Morgan Stanley and Nifty 50 was collected from NSE for the period 31-03-2024 to 20-03-2025. 
Weekly closing prices (Friday) were used to calculate returns. Morgan Stanleys weekly returns were regressed against Nifty 50s returns to determine Beta.

Data Analysis

Regression Equation

The regression equation describes the relationship between Morgan Stanleys returns (Y) and Nifty 50 returns (X):

Y = -0.0097 + (0.1145 * X)

Here,  
– Y represents Morgan Stanleys weekly return.  
– Xrepresents Nifty 50s weekly return.  
– The intercept (-0.0097) suggests a slight negative return when Nifty 50s return is zero.  
– The coefficient (0.1145) indicates that for every 1% change in Nifty 50s return, Morgan Stanleys return changes by 0.1145%, meaning it has a weak correlation with the market.

 

SUMMARY OUTPUT

Regression Statistics

Beta (β): 0.1145

R-Squared: 0.002

Adjusted R-Squared: -0.032

P-Value (Beta Significance): 0.804

ANOVA

F-Statistic: 0.06291

Significance F: 0.804

Regression Coefficients

Variable

Coefficient

Standard Error

t Stat

P-Value

Lower 95%

Upper 95%

Return_Nifty

0.1145

0.457

0.251

0.804

-0.819

1.049

 

Interpretation

The regression equation describes the relationship between Nifty 50 (X) and Morgan Stanley’s stock returns (Y), indicating that Morgan Stanley’s stock return is the dependent variable, while Nifty 50 is the independent variable.

• The intercept (-0.0097) suggests that when Nifty 50 remains unchanged, Morgan Stanleys stock return is slightly negative, indicating minimal independent movement.
• The Beta coefficient (0.1145) implies that for every 1% increase in Nifty 50Morgan Stanleys stock return is expected to increase by only 0.11%, indicating very weak market correlation.
• The R² value of 0.002 means that only 0.2% of Morgan Stanley’s stock return variations can be explained by changes in Nifty 50, confirming an extremely weak relationship.
• The F-statistic (0.06291) indicates that the model has low explanatory power, and the p-value (0.804) for the slope suggests that the relationship between Morgan Stanley and Nifty 50 is not statistically significant at conventional confidence levels.

This analysis indicates that Morgan Stanleys stock movements are largely independent of Nifty 50 trendsand do not closely follow broader market movements.

 

 

Conclusion

The Beta (β) value of 0.1145 indicates that Morgan Stanley has a very weak correlation with Nifty 50.
Its stock movements are largely independent of the overall market trends. The high p-value (0.804) suggests that the relationship between Morgan Stanley and Nifty 50 is not statistically significant.

References

1. Arun Kumar Misra & Sabyasachi Mohapatra, 2015. Indexing CNX NIFTY 50 Momentum Effects, Margin: The Journal of Applied Economic Research, National Council of Applied Economic Research, vol. 9(2), pages 157-178, May.

2. Srilakshminarayana Gali, 2021. The Behaviour of Extreme and Cumulative Stock Price Random Variables during Crisis Periods – A Study of Nifty 50 Stocks, Economic Research Guardian, Mutascu Publishing, vol. 11(1), pages 103-129, June.

 

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