def __init__(self, ma_short, ma_long):
distance = MA(ma_short, 'close') - MA(ma_long, 'close')
indicator = DIFF(distance)
self.diff_distance = indicator
self.distance = distance
self.prev_distance = distance.shift(1)
self.cross = Cross.None_x
def SecurityRPS(window_min_max, window_ma, dependency):
RPS = (MSUM(1, dependency=dependency) -
MMIN(window=window_min_max, dependency=dependency)) / (
MMAX(window=window_min_max, dependency=dependency) -
MMIN(window=window_min_max, dependency=dependency))
RPS = MA(dependency=RPS, window=window_ma)
return RPS
def __init__(self, fast, slow, MACDLength, RSILength):
MACDValue = MACD(fast, slow, 'close')
AvgMACD = EMA(MACDLength, MACDValue)
self.moving_average = MA(25, 'close')
self.MACDDiff = MACDValue - AvgMACD
self.RSI = RSI(RSILength, 'close')
self.total_length = max(slow + MACDLength, RSILength)
self.count = 0
def __init__(self):
self.window = 10
self.ma = MA(self.window, 'close')
self.std = SQRT(VARIANCE(10, RETURNSimple('close')))
self.close = CLOSE()
self.pack = {'ta.xzce': 1,
'zc.xzce': 1,
'y.xdce': 1,
'ru.xsge': 1,
'a.xdce': 1,
'j.xdce': 1,
'jm.xdce': 1,
'ic.ccfx': 1,
'if.ccfx': 1,
'ih.ccfx': 1}
self.upper_direction = -1
self.lower_direction = 1
self.position_book = {}
self.order_queue = {}
def __init__(self):
self.window = 20
self.ma = MA(self.window, 'close')
self.var = SQRT(VARIANCE(20, RETURNSimple('close')))
self.close = CLOSE()
self.pack = {
'ta.xzce': 1,
'y.xdce': 1,
'ru.xsge': 1,
'a.xdce': 1,
'ic.ccfx': 1,
'if.ccfx': 1,
'ih.ccfx': 1
}
self.upper_direction = -1
self.lower_direction = 1
self.step = 0.005
self.profit_threshold = 0.005
self.position_book = {}
self.order_queue = {}
def __init__(self):
short_sma = MA(10, 'close')
long_sma = MA(30, 'close')
filter = (MAX(10, 'close') / MIN(10, 'close')) > 1.02
self.signal = (short_sma - long_sma)[filter]
def __init__(self):
self.short_sma = MA(10, 'close')
self.long_sma = MA(120, 'close')
def __init__(self):
filtering = (MAX(10, 'close') / MIN(10, 'close')) >= 1.02
indicator = MA(10, 'close') - MA(120, 'close')
self.signal = indicator[filtering]
from PyFin.Math.Accumulators import Latest
n = 3000
m = 3000
index = pd.date_range(dt.datetime(1990, 1, 1),
dt.datetime(1990, 1, 1) + dt.timedelta(days=m - 1))
index = np.repeat(index, n)
df = pd.DataFrame(np.random.randn(n * m, 3),
columns=['x', 'y', 'z'],
index=index)
df['c'] = matlib.repmat(np.linspace(0, n - 1, n, dtype=int), 1, m)[0]
start = dt.datetime.now()
t = MA(20, 'x') / MA(30, 'y')
res = t.transform(df, category_field='c')
print("Finance-Python (analysis): {0}s".format(dt.datetime.now() - start))
start = dt.datetime.now()
groups = df.groupby('c')
res = groups['x'].rolling(20).mean() / groups['y'].rolling(30).mean()
print("Pandas (group by): {0}s".format(dt.datetime.now() - start))
start = dt.datetime.now()
t = MovingAverage(20, 'x') / MovingAverage(30, 'x')
res = t.transform(df)
print("Finance-Python (accumulator): {0}s".format(dt.datetime.now() - start))
start = dt.datetime.now()
res = df['x'].rolling(20).mean() / df['x'].rolling(30).mean()
def __init__(self):
short_sma = MA(10, 'close')
long_sma = MA(60, 'close')
self.signal = short_sma - long_sma
# -*- coding: utf-8 -*-
u"""
Created on 2016-12-25
@author: cheng.li
"""
import datetime as dt
import pandas as pd
sample_data = pd.DataFrame(
data={'code': [1, 2, 1, 2, 1, 2],
'open': [2.0, 1.0, 1.5, 3.0, 2.4, 3.5],
'close': [1.7, 1.6, 0.9, 3.8, 1.6, 2.1]},
index=[dt.datetime(2016, 1, 1),
dt.datetime(2016, 1, 1),
dt.datetime(2016, 1, 2),
dt.datetime(2016, 1, 2),
dt.datetime(2016, 1, 3),
dt.datetime(2016, 1, 3)]
)
sample_data = sample_data[['code', 'open', 'close']]
if __name__ == '__main__':
from PyFin.api import MA
ts = MA(2, 'close')
res = ts.transform(sample_data, name='ma_2_no_code')
print(res)
def __init__(self):
self.signal = MA(10, 'close')