Impact of big match results on stock market value of principal sponsor.¶
By: Aayush Srivastava, Veldi Sushruth, E Akarsh Reddy
Disclaimer:¶
This study is meant for the sole purpose of analysis. This is NOT financial advice and cannot be interpreted as such under any circumstance. Neither the author(s) nor the contributor(s) will be responsible under any circumstance for any losses incurred by any individual, business, organization, partnership, company, society or any other third party. The values has been taken from reputable sources on the internet believed to be true, we wont be responsible for any data inconsistencies or misinformation. We have considered the matches that we perceived to be important. The results are primarly based on visual reference.
Brief:¶
We all know and love the beautiful game including us. Fortunately we also have a passion for the stock markets. And sitting in home during the Covid-19 pandemic we decided to find if there exists any relation between the two. Hence we decided to perform a simple study: Do the results of big football matches have an impact on the stock market value of principal sponsor?
Abstract:¶
Although we performed this study with high hopes of finding a positive relation between the result of the matches and variations in stock prices of principal sponsor, unfortunately we conclude that no such relationship exists neither positive nor negative, the variations seem to be influenced by other major factors beyond the scope of this study. Although we didn't find a relation between the match result and stock market value of the sponsor, we did find a possible relation between them before the match day.(This is just a hypothesis further research required to reach a conclusion.)
Analysis:¶
Loading and processing data:¶
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
rise=[0,0]
#This variable keeps a track if a temporary bubble is created after the match index 0 corresponds to false and index 1 corresponds to true
data=pd.read_excel('D:\Data Analysis\Football-Market 1\Football data.xlsx',sep='\s*,\s*')
data=data.dropna()
data['Id']=data.reset_index().index
data.head()
Helper functions:¶
x=['2 days prior','Match day','2 days after','Long Term Value']
def draw(i):
plt.plot(x,data.iloc[i][6:10])
plt.title('Plot')
plt.ylabel('Values')
plt.xlabel('Time')
info(i)
def info(i):
d=data.iloc[i]
print(' Date: '+str(d['Date']).split()[0])
print(' Club: '+d['Club'])
print(' Share Name: '+d['Share Name'])
print(' Currency: '+d['Currency'])
Visual Analysis:¶
draw(0)
Analysis: No rise observed.
rise[0]+=1
draw(1)
Analysis: Rise observed.
rise[1]+=1
draw(2)
Analysis: No rise observed.
rise[0]+=1
draw(3)
Analysis: No rise observed.
rise[0]+=1
draw(4)
Analysis: No rise observed.
rise[0]+=1
draw(5)
Analysis: No rise observed.
rise[0]+=1
draw(6)
Analysis: No rise observed.
rise[0]+=1
draw(7)
Analysis: Rise observed.
rise[1]+=1
draw(8)
Analysis: No rise observed.
rise[0]+=1
draw(9)
Analysis: No rise observed.
rise[0]+=1
draw(10)
Analysis: No rise observed.
rise[0]+=1
draw(11)
Analysis: No rise observed.
rise[0]+=1
draw(12)
Analysis: Rise observed.
rise[1]+=1
draw(13)
Analysis: Rise observed.
rise[1]+=1
draw(14)
Analysis: No rise observed.
rise[0]+=1
draw(15)
Analysis: No rise observed.
rise[0]+=1
draw(16)
Analysis: Rise observed.
rise[1]+=1
draw(17)
Analysis: Rise observed.
rise[1]+=1
draw(18)
Analysis: No rise observed.
rise[0]+=1
draw(19)
Analysis: Rise observed.
rise[1]+=1
draw(20)
Analysis: Rise observed.
rise[1]+=1
draw(21)
Analysis: Rise observed.
rise[1]+=1
draw(22)
Analysis: No rise observed.
rise[0]+=1
draw(23)
Analysis: Rise observed.
rise[1]+=1
draw(24)
Analysis: No rise observed.
rise[0]+=1
draw(25)
Analysis: No rise observed.
rise[0]+=1
draw(26)
Analysis: No rise observed.
rise[0]+=1
draw(27)
Analysis: Rise observed.
rise[1]+=1
draw(28)
Analysis: Rise observed.
rise[1]+=1
draw(29)
Analysis: No rise observed.
rise[0]+=1
draw(30)
Analysis: No rise observed.
rise[0]+=1
draw(31)
Analysis: Rise observed.
rise[1]+=1
Final Stats:¶
print('Rise occours:'+str(rise[1])+'/32')
print('Rise dose not occurs:'+str(rise[0])+'/32')
Result:¶
The price of the principal sponsor rises in about 59.3% of cases, and falls in about 40.6% of cases. The final stats suggest the there's no strong relation between the outcome of match and stock price of principal sponsor and the price depends on several other factors beyond the scope of this study.
Hence, we reject the hypothesis.