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 port_trix(asset_indicator, close_arr, n):
"""Calculate the port trix.
:param asset_indicator: the indicator of beginning of the stock
:param close_arr: close price of the bar, expect series from cudf
:param n: time steps
:return: expoential weighted moving average in cu.Series
"""
EX1 = PEwm(n, close_arr, asset_indicator).mean()
EX2 = PEwm(n, EX1, asset_indicator).mean()
EX3 = PEwm(n, EX2, asset_indicator).mean()
return rate_of_change(cudf.Series(EX3), 2)
def port_mass_index(asset_indicator, high_arr, low_arr, n1, n2):
"""Calculate the port Mass 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 n1: n1 time steps
:param n1: n2 time steps
:return: Mass Index in cudf.Series
"""
Range = high_arr - low_arr
EX1 = PEwm(n1, Range, asset_indicator).mean()
EX2 = PEwm(n1, EX1, asset_indicator).mean()
Mass = division(EX1, EX2)
MassI = Rolling(n2, Mass).sum()
port_mask_nan(asset_indicator.data.to_gpu_array(), MassI, 0, n2 - 1)
return cudf.Series(MassI)
def port_true_strength_index(asset_indicator, close_arr, r, s):
"""Calculate port True Strength Index (TSI) for given data.
:param asset_indicator: the indicator of beginning of the stock
:param close_arr: close price of the bar, expect series from cudf
:param r: r time steps
:param s: s time steps
:return: True Strength Index in cudf.Series
"""
M = diff(close_arr, 1)
port_mask_nan(asset_indicator.data.to_gpu_array(), M, 0, 1)
aM = abs_arr(M)
EMA1 = PEwm(r, M, asset_indicator).mean()
aEMA1 = PEwm(r, aM, asset_indicator).mean()
EMA2 = PEwm(s, EMA1, asset_indicator).mean()
aEMA2 = PEwm(s, aEMA1, asset_indicator).mean()
TSI = division(EMA2, aEMA2)
return cudf.Series(TSI)
def port_exponential_moving_average(asset_indicator, close_arr, n):
"""Calculate the exponential weighted moving average for the given data.
:param close_arr: close price of the bar, expect series from cudf
:param n: time steps
:return: expoential weighted moving average in cu.Series
"""
EMA = PEwm(n, close_arr, asset_indicator).mean()
return cudf.Series(EMA)
def port_macd(asset_indicator, close_arr, n_fast, n_slow):
"""Calculate MACD, MACD Signal and MACD difference
:param close_arr: close price of the bar, expect series from cudf
:param n_fast: fast time steps
:param n_slow: slow time steps
:return: MACD MACDsign MACDdiff
"""
EMAfast = PEwm(n_fast, close_arr, asset_indicator).mean()
EMAslow = PEwm(n_slow, close_arr, asset_indicator).mean()
MACD = substract(EMAfast, EMAslow)
average_window = 9
MACDsign = PEwm(average_window, MACD, asset_indicator).mean()
MACDdiff = substract(MACD, MACDsign)
out = collections.namedtuple('MACD', 'MACD MACDsign MACDdiff')
return out(MACD=cudf.Series(MACD),
MACDsign=cudf.Series(MACDsign),
MACDdiff=cudf.Series(MACDdiff))
def port_chaikin_oscillator(asset_indicator, high_arr, low_arr, close_arr,
volume_arr, n1, n2):
"""Calculate port Chaikin Oscillator 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 volume_arr: volume the bar, expect series from cudf
:param n1: n1 time steps
:param n2: n2 time steps
:return: Chaikin Oscillator indicator in cudf.Series
"""
ad = (2.0 * close_arr - high_arr - low_arr) / (high_arr -
low_arr) * volume_arr
first = PEwm(n1, ad, asset_indicator).mean()
second = PEwm(n2, ad, asset_indicator).mean()
Chaikin = cudf.Series(substract(first, second))
return Chaikin
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 port_stochastic_oscillator_d(asset_indicator, high_arr, low_arr, close_arr,
n):
"""Calculate port stochastic oscillator D 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
:return: stochastic oscillator D in cudf.Series
"""
SOk = stochastic_oscillator_k(high_arr, low_arr, close_arr)
SOd = PEwm(n, SOk, asset_indicator).mean()
return cudf.Series(SOd)
def port_average_true_range(asset_indicator, high_arr, low_arr, close_arr, n):
"""Calculate the port Average True Range
See https://www.investopedia.com/terms/a/atr.asp for details
: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
:return: average true range indicator
"""
tr = port_true_range(asset_indicator.to_gpu_array(),
high_arr.to_gpu_array(), low_arr.to_gpu_array(),
close_arr.to_gpu_array())
ATR = PEwm(n, tr, asset_indicator).mean()
return cudf.Series(ATR, nan_as_null=False)
def port_coppock_curve(asset_indicator, close_arr, n):
"""Calculate port Coppock Curve for given data.
:param asset_indicator: the indicator of beginning of the stock
:param close_arr: close price of the bar, expect series from cudf
:param n: time steps
:return: Coppock Curve in cudf.Series
"""
M = diff(close_arr, int(n * 11 / 10) - 1)
N = shift(close_arr, int(n * 11 / 10) - 1)
port_mask_nan(asset_indicator.to_gpu_array(), M, 0, int(n * 11 / 10) - 1)
port_mask_nan(asset_indicator.to_gpu_array(), N, 0, int(n * 11 / 10) - 1)
ROC1 = division(M, N)
M = diff(close_arr, int(n * 14 / 10) - 1)
N = shift(close_arr, int(n * 14 / 10) - 1)
port_mask_nan(asset_indicator.to_gpu_array(), M, 0, int(n * 14 / 10) - 1)
port_mask_nan(asset_indicator.to_gpu_array(), N, 0, int(n * 14 / 10) - 1)
ROC2 = division(M, N)
Copp = PEwm(n, summation(ROC1, ROC2), asset_indicator).mean()
return cudf.Series(Copp, nan_as_null=False)