Extend your analysis of the Tesla stock price data by fitting some other distrib

Question

Extend your analysis of the Tesla stock price data by fitting some other distributions to the log-returns. Two possible distributions are the hyperbolic distribution and the skew hyperbolic Student's t-distribution. These are both distributions which have heavier tails than the normal distribution. There is an entry concerning the hyperbolic distribution in Wikipedia which you may consult. For the skew hyperbolic Student's t-distribution, see Aas & Haff (2006), Journal of Financial Econometrics, 4, pp. 275-309, which is available online from the library. Use the function hyperbFit from the package GeneralizedHyperbolic to fit the hyperbolic distribution to the log-returns. Examine the fit using plot. hyperbFit and check the goodness-of-fit using hyperbCvMTest. Use the function skewhypFit from the package SkewHyperbolic to fit the skew hyperbolic Student's t- distribution to the ling returns. Examine the fit using plot.skewhypFit. Unfortunately there is no goodness-of-fit test available for this distribution. Comment on the fits achieved. Note that there are help pages for the functions mentioned above. You may also wish to read the help for the function logHist which is used to draw the log-histogram which is one of the plots.

Explanation / Answer

Please provide data to solve the problem. since no data provided hence explaining the basics.

extend your analysis od the tesla stock price data by fitting some other distributions to the log returns. Two possible distributions are the hyperbolic distribution and the skew hyperbolic student's t distribution

Hyperbolic distribution::

The hyperbolic distribution is a continuous probability distribution characterized by the logarithm of the probability density function being a hyperbola. Thus the distribution decreases exponentially, which is more slowly than the normal distribution. It is therefore suitable to model phenomena where numerically large values are more probable than is the case for the normal distribution.

Hyperbfit:: Fits a hyperbolic distribution to data. Displays the histogram, log-histogram (both with fitted densities), Q-Q plot and P-P plot for the fit which has the maximum likelihood.
plot.hyperbfit:: plots the above

skew Student’s t-distributions"

skew the symmetric Student’s t-distribution by continuously piecing together two differently scaled halves of the symmetric base distribution

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