def port_average_directional_movement_index(asset_indicator, high_arr, low_arr,
close_arr, n, n_ADX):
"""Calculate the port Average Directional Movement Index for given data.
:param asset_indicator: the indicator of beginning of the stock
:param high_arr: high price of the bar, expect series from cudf
:param low_arr: low price of the bar, expect series from cudf
:param close_arr: close price of the bar, expect series from cudf
:param n: time steps to do EWM average
:param n_ADX: time steps to do EWM average of ADX
:return: Average Directional Movement Index in cudf.Series
"""
UpI, DoI = upDownMove(high_arr.data.to_gpu_array(),
low_arr.data.to_gpu_array())
tr = port_true_range(asset_indicator.to_gpu_array(),
high_arr.data.to_gpu_array(),
low_arr.data.to_gpu_array(),
close_arr.data.to_gpu_array())
ATR = PEwm(n, tr, asset_indicator).mean()
PosDI = division(PEwm(n, UpI, asset_indicator).mean(), ATR)
NegDI = division(PEwm(n, DoI, asset_indicator).mean(), ATR)
NORM = division(abs_arr(substract(PosDI, NegDI)), summation(PosDI, NegDI))
port_mask_nan(asset_indicator.data.to_gpu_array(), NORM, -1, 0)
ADX = cudf.Series(PEwm(n_ADX, NORM, asset_indicator).mean())
return ADX
def relative_strength_index(high_arr, low_arr, n):
"""Calculate Relative Strength Index(RSI) for given data.
:param high_arr: high price of the bar, expect series from cudf
:param low_arr: low price of the bar, expect series from cudf
:param n: time steps to do EWM average
:return: Relative Strength Index in cudf.Series
"""
UpI, DoI = upDownMove(high_arr.to_gpu_array(), low_arr.to_gpu_array())
UpI_s = shift(UpI, 1)
UpI_s[0] = 0
DoI_s = shift(DoI, 1)
DoI_s[0] = 0
PosDI = Ewm(n, UpI_s).mean()
NegDI = Ewm(n, DoI_s).mean()
RSI = division(PosDI, summation(PosDI, NegDI))
return cudf.Series(RSI, nan_as_null=False)
def port_relative_strength_index(asset_indicator, high_arr, low_arr, n):
"""Calculate Relative Strength Index(RSI) for given data.
:param high_arr: high price of the bar, expect series from cudf
:param low_arr: low price of the bar, expect series from cudf
:param n: time steps to do EWM average
:return: Relative Strength Index in cudf.Series
"""
UpI, DoI = upDownMove(high_arr.data.to_gpu_array(),
low_arr.data.to_gpu_array())
UpI_s = shift(UpI, 1)
UpI_s[0] = 0
UpI_s = cudf.Series(UpI_s) * (1.0 - asset_indicator)
DoI_s = shift(DoI, 1)
DoI_s[0] = 0
DoI_s = cudf.Series(DoI_s) * (1.0 - asset_indicator)
PosDI = PEwm(n, UpI_s, asset_indicator).mean()
NegDI = PEwm(n, DoI_s, asset_indicator).mean()
RSI = division(PosDI, summation(PosDI, NegDI))
return cudf.Series(RSI)
def average_directional_movement_index(high_arr, low_arr, close_arr, n, n_ADX):
"""Calculate the Average Directional Movement Index for given data.
:param high_arr: high price of the bar, expect series from cudf
:param low_arr: low price of the bar, expect series from cudf
:param close_arr: close price of the bar, expect series from cudf
:param n: time steps to do EWM average
:param n_ADX: time steps to do EWM average of ADX
:return: Average Directional Movement Index in cudf.Series
"""
UpI, DoI = upDownMove(high_arr.to_gpu_array(), low_arr.to_gpu_array())
last_ele = len(high_arr) - 1
tr = true_range(high_arr.to_gpu_array(), low_arr.to_gpu_array(),
close_arr.to_gpu_array())
ATR = Ewm(n, tr).mean()
PosDI = division(Ewm(n, UpI).mean(), ATR)
NegDI = division(Ewm(n, DoI).mean(), ATR)
NORM = division(abs_arr(substract(PosDI, NegDI)), summation(PosDI, NegDI))
NORM[last_ele] = math.nan
ADX = cudf.Series(Ewm(n_ADX, NORM).mean(), nan_as_null=False)
return ADX