quantopian curve fit gaussian + linear

start = '2008-01-01'
end = '2018-01-01'
price = get_pricing('AAPL', fields='price', start_date=start, end_date=end)
price.plot()

import numpy as np
import matplotlib.pyplot as plt
from scipy.optimize import curve_fit
import pandas as pd

def expfit(x, a, b, c, d, e, f):
    return  a*np.exp(-(b*x*x+c*x+d))+e*x+f

x = np.linspace(1,1+len(price),len(price))

params, params_covariance = curve_fit(expfit, x, price.values )

print params

y = expfit(x, *params)

f = pd.Series(y, index=price.index, name='exp fit')

pd.concat([price, f], axis=1).plot()

[  7.84216333e+01   5.57230815e-05  -7.13434301e-03   1.45807761e+00
   5.84734404e-02  -4.80640750e+00]

[  8.44865621e+00   1.29652892e-04  -1.37545875e-02  -1.42288153e+00

   -1.96774039e-02   6.58394726e+01]

reference:
https://chuanshuoge2.blogspot.com/2019/12/quantopian-curve-fit-gaussian.html