Title: Relationship of Rolex rings Ltd. with Nifty 50
Author: Rutuja Vilas Gawade
Introduction: Rolex Rings is designs and manufactures hot forged rolled rings for bearing and automotive industries. It offers transmission components which includes gear blanks, ring gear, sun and pinion, shafts, and lock nuts; engine components which includes pulley, and cam lobs; chasis components which includes wheel hubs, gen2 and gen3 bearing components. Rolex Rings serves customers worldwide. Mr. Manesh D Madeka and Rupesh Dayashankar Madeka started the business under the partnership firm by the name of Rolex Industries in 1978.
Objective: Calculation of Beta (the change in Rolex rings with respect to change in nifty) and its significance.
Literature Review:
1. Demand for Value Added and Value-Added Exchange Rates
We examine the role of cross-border input linkages in governing how international relative price changes influence demand for domestic value added. We define a novel value-added real effective exchange rate (REER), which aggregates bilateral value-added price changes, and link this REER to demand for value added. Input linkages enable countries to gain competitiveness following depreciations by supply chain partners, and hence counterbalance beggar-thy-neighbor effects. Cross-country differences in input linkages also imply that the elasticity of demand for value added is country specific. Using global input-output data, we demonstrate these conceptual insights are quantitatively important and compute historical value-added REERs. ( Bems etal, 2015)
2. Real Exchange Rate Fluctuations and the Dynamics of Retail Trade Industries on the U.S.-Canada Border
This paper examines the effects of U.S.-Canadian real exchange rate movements on U.S. retail trade industries in states that border Canada. Using county level data, we focus on the effects on the number of establishments, employment, and payroll in two-digit and three-digit level retail trade industries. We expect fluctuations in the real exchange rate to affect these variables as movements in these relative price series impact on the incidence of cross-border shopping. This, in turn, affects the demand facing retailers located in each country. Our results suggest that for many of the industries in our sample, real exchange rates have a significant effect on these variables and these effects vary across industries. (Jeffrey Campbell, 2000)
Data Collection: Data was collected from NSE site historical data, then it was manipulated by finding the Friday closing price. After that weekly returns for nifty and Rolex rings was calculated which was written as X & Y. By doing regression through data analysis.
Data Analysis:
Equation Rolex rings Returns (Y)= 1.014 + 1.350 Nifty Returns (X) (4.447)
N= 51, R²= 0.287, F= 19.7811, Beta= 1.35.
The above equation shows the relationship between X & Y. (+) sign means there is a direct relationship which implies that if X rises, Y also rises & vice versa. In this equation b=1.35, that is if X rises by 1 unit, demand (Y) will rise by 1.35 units. Hence b is statistically significant at 5% significance level.
R²= 0.287 which means 28.7% of Y is explained by X, similarly F= 19.7811 which is also greater than table value. Hence overall model is statistically significant at 5% Significance level.
Conclusion: since it can be seen that value of b (beta) is more than 1 which implies that Rolex rings is good for short term investment.
References:
Mr. Rudolfs Bems & Robert C. Johnson, 2015. “Demand for Value Added and Value-Added Exchange Rates,” IMF Working Papers 2015/199, International Monetary Fund.
Jeffrey Campbell, 2000. “Real Exchange Rate Fluctuations and the Dynamics of Retail Trade Industries on the U.S.-Canada Border,” Econometric Society World Congress 2000 Contributed Papers 1224, Econometric Society.