def compute_scale(signal_level, ewma_level):
current_scaling = compute_scale_globals['current_scaling']
new_position_scaling = get_position_scaling(signal_level, current_scaling, ewma_level, threshold)
# updating for next step
compute_scale_globals['current_scaling'] = new_position_scaling
result = {
'band_inf': ewma_level + ((new_position_scaling - 1) * threshold),
'band_mid': ewma_level + (new_position_scaling * threshold),
'band_sup': ewma_level + ((new_position_scaling + 1) * threshold),
'scaling': -new_position_scaling
}
return result
def scale(row, cumul=cumul):
current_scaling = cumul['current_scaling']
price = row['price']
mu = row['mu']
sigma = 0.8 * row['sigma']
new_position_scaling = get_position_scaling(price, current_scaling, mu, sigma)
# updating for next step
cumul['current_scaling'] = new_position_scaling
result = {
'position_scaling': new_position_scaling,
'band_inf': mu + ((new_position_scaling + 1) * sigma),
'band_mid': mu + (new_position_scaling * sigma),
'band_sup': mu + ((new_position_scaling - 1) * sigma)
}
return pandas.Series(result)
