*
*
*
* Week 9 
*
*
*Load data, file -> import -> ASCII data created by spreadsheet
*
*insheet using FTSE100.csv
*

*Processing data

rename v1 price
generate time = _n
** flip around dimension
gen time2 = 6978 - time
drop time
rename time2 time
tsset time

*Generate returns
generate returns = price/L.price -1
generate lnreturns = ln(price/L.price)

*Graph returns
twoway (line returns time, yaxis(2)) (line lnreturns time, yaxis(2))
twoway (line price time)

*Histograms with densities
twoway (histogram price) (kdensity price)
twoway (histogram lnreturns) (kdensity lnreturns)

*install module for cdfplot
ssc install cdfplot
cdfplot lnreturns,normal

*Manual generation of normal distribution
su lnreturns
gen normalLogReturns= 0.0002308+ 0.0113213* invnorm(uniform())
su normalLogReturns

*Plot to see difference in densities
twoway(kdensity normalLogReturns ) (kdensity lnreturns )

*Autocorrelation function
ac lnreturns, recast(connected)

*Checking absolute returns
gen abslnreturns = abs(lnreturns)
ac abslnreturns, recast(connected)

*Skewness test for normality
*high joing prob, do not reject -> normally distributed
sktest lnreturns