def main():
ticker = 'SPY'
root = './data'
path = make_dir(root)
# scraping
yf = YahooFinance(ticker)
chain = yf.get_chain()
spot = yf.get_spot()
array = qd.get('FRED/FEDFUNDS', rows=1, returns='numpy')
rate = array[0][1]
# option chain
oc = OptionChain(ticker,
chain).add_spot(spot).add_rate(rate,
name='Fed Funds Rate (%)')
oc.get_df().to_csv(f'{path}/option_chain.csv')
# call prices
call_prices = oc.get_price_mx()
call_prices.to_csv(f'{path}/call_prices.csv')
# implied vols
implied_vols = vol_surface(call_prices, spot, rate / 100)
implied_vols.to_csv(f'{path}/implied_vols.csv')
# interpolated surfaces
interp_linear = interpolate(implied_vols, 'linear')
interp_linear.to_csv(f'{path}/implied_vols_interpolated_lin.csv')
interp_cubic = interpolate(implied_vols, 'cubic')
interp_cubic.to_csv(f'{path}/implied_vols_interpolated_cub.csv')
# parametric models
model = DumasFlemingWhaley()
model.fit(implied_vols.reset_index())
model.get_surface().to_csv(f'{path}/implied_vols_parametric_dfw.csv')
# update repo
update_repo(root)
return
