{"id":20866,"date":"2024-03-29T08:49:25","date_gmt":"2024-03-29T03:19:25","guid":{"rendered":"http:\/\/www.sachdevajk.in\/?p=20866"},"modified":"2024-03-29T08:49:25","modified_gmt":"2024-03-29T03:19:25","slug":"relationship-of-nifty-50-index-with-symphony-ltd","status":"publish","type":"post","link":"http:\/\/www.sachdevajk.in\/?p=20866","title":{"rendered":"Relationship of Nifty 50 Index with Symphony ltd"},"content":{"rendered":"

Relationship of Nifty 50 Index with symphony ltd<\/strong><\/p>\n

Author: <\/strong>Shreyas Prabhu<\/p>\n

Introduction:<\/strong><\/p>\n

Symphony Limited is a leading company in the Indian automotive industry, specializing in the manufacture of high-performance tyres. It is based in Goa, India and was established in 1978. The company is known for its wide range of tyre products, including ultra-high-performance tyres, durable all-weather tyres, and sports tyres. Apollo is also committed to employing state-of-the-art technology and sustainable manufacturing processes. The company’s products are used in a variety of vehicles, from motorcycles and cars to buses and trucks.<\/p>\n

Objective:<\/strong> To find the Beta (\u03b2) of Symphony Limited and its significance<\/p>\n

\u00a0<\/p>\n

Data Collection:<\/strong><\/p>\n

Nifty 50 Index and Symphony Limited data was collected from the nseindia.com website for one year dating from 1st<\/sup> February 2023 to 31st<\/sup> January 2024. The historical data collected was manipulated using Microsoft Excel to get Friday closing prices of both, the index and the company. Weekly returns based on the closing prices were calculated using Excel tools and with the use of Regression analysis, weekly returns of Symphony Limited were regressed on weekly returns of Nifty 50 Index.<\/p>\n

\u00a0<\/p>\n

Data Analysis:<\/strong><\/p>\n

Equation of regression of weekly returns of Symphony Limited on weekly returns of Nifty 50 Index-<\/p>\n

Format of Regression equation is Y = \u03b1 + \u03b2(X)<\/p>\n

weekly returns of Symphony Limited = -0.123100963 + 0.528017358 \u00d7 weekly returns of Nifty 50 Index\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \u00a0(1.928811)<\/p>\n

Where,<\/p>\n

Number of Observations = 48,<\/p>\n

R Square = 0.074824787,<\/p>\n

F = 3.720312,<\/p>\n

P-value = 0.059938<\/p>\n

Interpretation-<\/p>\n