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Anakyse data. Calculate Granger Causality and R squared for multiple regression model

€30-250 EUR

Cancelled
Posted almost 5 years ago

€30-250 EUR

Paid on delivery
I have run a sentiment anlysis to get the average daily sentiment for tweets regarding Volkswagen from 2015-2018. I also have the excess return of Volkswagen over the DAX for each of these days. Now I want to see if the sentiment has an effect on the return during the next day. So I want to have the Granger Causality with a lag of 1 and 2 days. I also want to see whats the R squared if you use a multiple regression model. I uploaded a screenshot of the data frame I already have. timestamp is the day. Sentiment the avg sentiment of the day and excessreturn the excess return of this day. sentiment mean is important for days where there is no trading (weekends). I calculated the means over these days so that the mean sentiment from Firday until sunday can be used for the monday returns.
Project ID: 19278416

About the project

4 proposals
Remote project
Active 5 yrs ago

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4 freelancers are bidding on average €165 EUR for this job
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I am a statistician having more than 2 years of experience in the same field. I can help you in calculating r square as well as any kind of statistical models.
€250 EUR in 3 days
5.0 (121 reviews)
6.3
6.3
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HellO Sir, i am an expert in Mathematics, R Programming Language, SPSS Statistics, Statistical Analysis, Statistics. I can help you in this project. Please send me a message once. Thanks .
€155 EUR in 3 days
5.0 (6 reviews)
4.7
4.7
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HELLO! As an: - Bachelor of Applied Mathematics - Engineer in Statistics and Applied Economics - Microsoft Office Technician (Microsoft Graduate: MOS Diploma), - I have skills in programming language R, Python, Minitab, SPSS I am able, available and ready to do this kind of work in the best conditions, ---------------------------------------------------------------------------
€90 EUR in 5 days
4.8 (9 reviews)
3.1
3.1

About the client

Flag of GERMANY
Münster, Germany
0.0
0
Member since Apr 18, 2019

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