from statsmodels import api as sm
from my_libs import *

Regress the SPY and VIX index

Need to translate the result into np.array
Need to change type to float

spy = get_price_data(["SPY"],method='day',back_day=20).dropna().Return.values.astype(float)
spy_ = spy*30

All price data of Close is actually Adj Close
Connection Successful
Finished SPY

Constructed a model of vix = intercept + b0 * spy + b1 * spy * 30

ip = pd.DataFrame({"spy":spy,"spy_":spy_})
dp = get_price_data(["^VIX"],method='day',back_day=20).dropna().Return.values.astype(float)

All price data of Close is actually Adj Close
Connection Successful
no data for ^VIX
'NoneType' object has no attribute 'index'
switching to realtimeday method
Finished ^VIX

ip = sm.add_constant(ip)

/home/ken/.local/lib/python2.7/site-packages/numpy/core/fromnumeric.py:2389: FutureWarning: Method .ptp is deprecated and will be removed in a future version. Use numpy.ptp instead.
  return ptp(axis=axis, out=out, **kwargs)

sm.OLS(dp,ip).fit().summary()

/home/ken/.local/lib/python2.7/site-packages/scipy/stats/stats.py:1416: UserWarning: kurtosistest only valid for n>=20 ... continuing anyway, n=13
  "anyway, n=%i" % int(n))

Dep. Variable:	y	R-squared:	0.737
Model:	OLS	Adj. R-squared:	0.713
Method:	Least Squares	F-statistic:	30.80
Date:	Sun, 04 Aug 2019	Prob (F-statistic):	0.000173
Time:	19:40:53	Log-Likelihood:	25.241
No. Observations:	13	AIC:	-46.48
Df Residuals:	11	BIC:	-45.35
Df Model:	1
Covariance Type:	nonrobust

	coef	std err	t	P>\|t\|	[0.025	0.975]
const	0.0033	0.011	0.305	0.766	-0.021	0.027
spy	-0.0109	0.002	-5.550	0.000	-0.015	-0.007
spy_	-0.3256	0.059	-5.550	0.000	-0.455	-0.196

Omnibus:	9.222	Durbin-Watson:	1.071
Prob(Omnibus):	0.010	Jarque-Bera (JB):	4.912
Skew:	-1.262	Prob(JB):	0.0858
Kurtosis:	4.641	Cond. No.	5.85e+17