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strategy.py
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strategy.py
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import datetime
import numpy as np
import pandas as pd
import Queue
import talib
from abc import ABCMeta, abstractmethod
from event import SignalEvent
import matplotlib.pyplot as plt
import matplotlib.finance
import matplotlib.dates as mdates
import time
from collections import namedtuple
from matplotlib.finance import candlestick
import heapq
class Strategy(object):
"""
Strategy is an abstract base class providing an interface for
all subsequent (inherited) strategy handling objects.
The goal of a (derived) Strategy object is to generate Signal
objects for particular symbols based on the inputs of Bars
(OLHCVI) generated by a DataHandler object.
This is designed to work both with historic and live data as
the Strategy object is agnostic to the data source,
since it obtains the bar tuples from a queue object.
"""
__metaclass__ = ABCMeta
@abstractmethod
def calculate_signals(self,events):
raise NotImplementedError("Should implement calculate_signals()")
class BuyAndHoldStrategy(Strategy):
def __init__(self, bars, events):
"""
Initialises the buy and hold strategy.
Parameters:
bars - The DataHandler object that provides bar information
events - The Event Queue object.
"""
self.bars = bars
self.symbol_list = self.bars.symbol_list
self.events = events
# Once buy & hold signal is given, these are set to True
self.bought = self._calculate_initial_bought()
self.lock = False
self.close= np.array([])
self.high=np.array([])
self.low=np.array([])
self.open = np.array([])
self.counter=0
self.i=0
self.position = namedtuple('Position','direction')
self.position.direction = 'EXIT'
self.long_close_enter_price = 0
self.short_close_enter_price =0
self.stop_loss = 0.0030
self.temp_close=[]
self.fig=plt.figure(figsize=(18,10),dpi=80,facecolor='w',edgecolor='k')
self.ax1=self.fig.add_subplot(1,1,1)
self.ax1.cla()
plt.ion()
plt.show(False)
self.ax1.hold(True)
self.ema_short,self.ema_middle,self.ema_fast,self.close_plotting,self.time_stamp=[],[],[],[],[]
self.line1, = self.ax1.plot(self.time_stamp,self.close,alpha=0.8,color='blue',markerfacecolor='red')
self.line2, = self.ax1.plot(self.time_stamp,self.ema_short,alpha=0.8,color='green')
self.fig.show()
self.fig.canvas.draw()
self.background=self.fig.canvas.copy_from_bbox(self.ax1.bbox)
self.start_short_span=0
self.end_short_span=0
self.start_long_span=0
self.end_long_span=0
self.s=[]
# self.fig = plt.figure(num=1, figsize=(20,12), dpi=80,facecolor='w', edgecolor='k')
# self.ax1 = plt.subplot(1,1,1)
def _calculate_initial_bought(self):
"""
Adds keys to the bought dictionary for all symbols
and sets them to False.
"""
bought = {}
for s in self.symbol_list:
bought[s]= False
return bought
def around(self,a,decimals=4):
return np.around(a,decimals)
def calculate_signals(self, event):
"""
For "Buy and Hold" we generate a single signal per symbol
and then no additional signals. This means we are
constantly long the market from the date of strategy
initialisation.
Parameters
event - A MarketEvent object.
"""
#---------- WORKING ----------
#plt.xlabel("Dates")
# fig=plt.figure(figsize=(14,10),dpi=80,facecolor='w',edgecolor='k')
# ax1=fig.add_subplot(1,1,1)
# ax1.cla()
# plt.ion()
# plt.show(False)
# ax1.hold(True)
# ema_short,ema_middle,ema_fast,close,time_stamp=[],[],[],[],[]
# line1, = ax1.plot(time_stamp,close,alpha=0.8,color='blue',markerfacecolor='red')
# line2, = ax1.plot(time_stamp,ema_short,alpha=0.8,color='green')
# fig.show()
# fig.canvas.draw()
# background=fig.canvas.copy_from_bbox(ax1.bbox)
if event.type == 'MARKET':
for s in self.symbol_list:
bars = self.bars.get_latest_bars(s,N=1)
#if s == 'GBPEUR':
self.close = np.append(self.close,bars[0][5])
self.high = np.append(self.high,bars[0][3])
self.low = np.append(self.low,bars[0][4])
# print bars[0][1], type(bars[0][1])
# exit()
ema_10 = np.around(talib.EMA(self.close,timeperiod=10),decimals=4)
ema_25 = np.around(talib.EMA(self.close,timeperiod=25),decimals=4)
ema_50 = np.around(talib.EMA(self.close,timeperiod=50),decimals=4)
atr_22=np.around(talib.ATR(self.high,self.low,self.close,timeperiod=22),decimals=4)
min_22=np.around(talib.MIN(self.low,timeperiod = 22),decimals=4)
max_22=np.around(talib.MAX(self.high,timeperiod = 22),decimals=4)
ts_long = max_22 - atr_22*3.5
ts_short = min_22+atr_22*3.5
#--------PLOTTING----------------
#if bars[0][1].dayofweek<4:
self.time_stamp.append(bars[0][1])
self.close_plotting.append(bars[0][5])
#print bars[0][1],bars[0][1].dayofweek
self.ema_short.append(ema_10[-1])
if len(self.time_stamp)>250:
del self.time_stamp[0]
del self.close_plotting[0]
del self.ema_short[0]
xmin, xmax, ymin, ymax = [min(self.time_stamp) , max(self.time_stamp) , .82,1]
self.line1.set_xdata(self.time_stamp)
self.line1.set_ydata(self.close_plotting)
self.line2.set_xdata(self.time_stamp)
self.line2.set_ydata(self.ema_short)
plt.axis([xmin, xmax, ymin, ymax])
self.fig.canvas.restore_region(self.background) # restore background
self.ax1.draw_artist(self.line1) # redraw just the points
self.fig.canvas.blit(self.ax1.bbox)
#candlestick(self.ax1,bars)
#x=mdates.datestr2num(bars[0][1])
#plt.gca().xaxis.set_major_formatter(mdates.DateFormatter('%Y%m%d %H:%M:%S'))
#plt.gca().xaxis.set_major_locator(mdates.SecondLocator())
#print x
#ax1.autofmt_xdate()
# ax1.fmt_xdata =bars[0][1] #mdates.DateFormatter(bars[0][1])
# day = mdates.DayLocator()
# daysFmt=mdates.DateFormatter('%Y%m%d %H:%M:%S')
# ax1.xaxis.set_major_locator(day)
#
#
# plt.gcf().autofmt_xdate() #rotates labels
# #ax1.plot(bars[0][1])
# plt.gca().xaxis.set_major_formatter(mdates.DateFormatter('%Y%m%d'))
#plt.plot(atr_22,'g--')
# plt.draw()
y_min=0
y_max=0
# #plt.plot(atr_22,"#DDA0A0",label='ATR_22')
#plt.plot(min_22,"#DDA0A0",label='ATR_22')
#assert(len(self.a) == sma)
if bars is not None and bars != []:
if self.position.direction == 'EXIT':
if self.close[-1] < ema_50[-1]:
if ema_10[-1] < ema_50[-1] and pd.Series(ema_50).shift().values[-1] <= pd.Series(ema_10).shift().values[-1] and self.bought[s]==False:
self.short_close_enter_price = self.close[-1]
self.events.put(SignalEvent(bars[0][0], bars[0][1],'SHORT'))
#print self.i,' ENTER SHORT-->',bars[0][1],'close enter','-->',self.close[-1]
self.position.direction = 'SHORT'
self.bought[s]=True
self.temp_close.append(self.close[-1])
#print self.temp_close,self.close
#y_min=bars[0][1]
self.start_short_span=self.time_stamp[-1]
# p=plt.axvspan(self.start_span,self.time_stamp[-1])
#self.s.append(self.time_stamp[-1])
return
elif self.close[-1] > ema_50[-1]:
if ema_10[-1] > ema_50[-1] and pd.Series(ema_50).shift().values[-1] >= pd.Series(ema_10).shift().values[-1]:
self.long_close_enter_price = self.close[-1]
#self.bought[s] = True
self.events.put(SignalEvent(bars[0][0],bars[0][1],'LONG'))
self.position.direction ='LONG'
#print self.i,"ENTER LONG-->",bars[0][1], 'close enter','-->',self.close[-1]
self.bought[s]=True
self.temp_close.append(self.close[-1])
self.start_long_span=self.time_stamp[-1]
return
elif self.position.direction == 'SHORT' :
if self.close[-1] >= min(self.temp_close)+(0.0035/(1.1+((self.temp_close[0]-(min(self.temp_close)))*100))):
#print self.close[-1], self.temp_close[0], min(self.temp_close) ,min(self.temp_close)+(0.0040/(1.2+((self.temp_close[0]-(min(self.temp_close)))*100)))
self.position.direction='EXIT'
#print self.i,'EXIT SHORT',bars[0][1],'close enter','-->',self.close[-1]
self.bought[s]=False
self.events.put(SignalEvent(bars[0][0],bars[0][1],'EXIT'))
self.temp_close=[]
#y_max=bars[0][1]
#plt.axvspan(y_min,y_max,facecolor='g')
#plt.draw()
self.end_short_span=self.time_stamp[-1]
p=plt.axvspan(self.start_short_span,self.end_short_span,facecolor='r',alpha=.3)
return
elif self.position.direction == 'LONG' :
if self.close[-1] <= max(self.temp_close)-(0.0035/(1.1+(((max(self.temp_close)-self.temp_close[0]))*100))):
#if self.long_close_enter_price - self.close[-1] >=0.0020:
#assert(self.long_close_enter_price-self.close[-1]>=0.0020)
self.position.direction='EXIT'
self.long_close_enter_price = 0
self.bought[s]=False
self.events.put(SignalEvent(bars[0][0],bars[0][1],'EXIT'))
self.end_long_span=self.time_stamp[-1]
p=plt.axvspan(self.start_long_span,self.end_long_span,facecolor='g',alpha=.3)
#print self.i,'EXIT LONG', bars[0][1],'close exit','-->',self.close[-1]
self.temp_close=[]
return
self.i+=1
if self.position.direction=='SHORT' or self.position.direction=='LONG':
self.temp_close.append(self.close[-1])
elif self.position.direction == 'EXIT':
self.temp_close=[]
class PivotMA(Strategy):
def __init__(self,bars,events,plot=False):
self.bars = bars
self.symbol_list = self.bars.symbol_list
self.events = events
self.plot=plot
# Once buy & hold signal is given, these are set to True
self.bought = self._calculate_initial_bought()
self.lock = False
self.close= np.array([])
self.high=np.array([])
self.low=np.array([])
self.open = np.array([])
self.counter=0
self.i=0
self.position = namedtuple('Position','direction')
self.position.direction = 'EXIT'
self.long_close_enter_price = 0
self.short_close_enter_price =0
self.stop_loss = 0.0030
# keep closing price when in short
self.temp_close=[]
# FOR PIVOT POINTS
self.days=[]
self.previous_low=[]
self.previous_high=[]
self.previous_close=[]
self.min_previous_low=0
self.max_previous_high=0
self.last_close=0
self.pivot_points=np.array([])
self.hourly_pivot_points=np.array([])
if self.plot:
self.fig=plt.figure(figsize=(18,10),dpi=80,facecolor='w',edgecolor='k')
self.ax1=self.fig.add_subplot(1,1,1)
self.ax1.cla()
plt.ion()
plt.show(False)
self.ax1.hold(True)
#self.ema_short,self.ema_middle,self.ema_fast,self.close_plotting,self.time_stamp=[],[],[],[],[]
self.time_stamp,self.close_plotting,self.pivot_points_plotting,self.r1_plotting,self.s1_plotting=[],[],[],[],[]
self.line1, = self.ax1.plot(self.time_stamp,self.close_plotting,alpha=0.8,color='blue',markerfacecolor='red')
self.line2, = self.ax1.plot(self.time_stamp,self.pivot_points_plotting,alpha=0.8,color='green')
self.line3, = self.ax1.plot(self.time_stamp,self.r1_plotting,alpha=0.8,color='grey')
self.line4, = self.ax1.plot(self.time_stamp,self.s1_plotting,alpha=0.8,color='black')
self.fig.show()
self.fig.canvas.draw()
self.background=self.fig.canvas.copy_from_bbox(self.ax1.bbox)
self.start_short_span=0
self.end_short_span=0
def _calculate_initial_bought(self):
"""
Adds keys to the bought dictionary for all symbols
and sets them to False.
"""
bought = {}
for s in self.symbol_list:
bought[s]= False
return bought
def calculate_signals(self,event):
if event.type == 'MARKET':
for s in self.symbol_list:
bars = self.bars.get_latest_bars(s,N=1)
#if s == 'GBPEUR':
self.close = np.append(self.close,bars[0][5])
self.high = np.append(self.high,bars[0][3])
self.low = np.append(self.low,bars[0][4])
# atr_22=np.around(talib.ATR(self.high,self.low,self.close,timeperiod=22),decimals=4)
# min_22=np.around(talib.MIN(self.low,timeperiod = 22),decimals=4)
# max_22=np.around(talib.MAX(self.high,timeperiod = 22),decimals=4)
# ts_long = max_22 - atr_22*3.5
# ts_short = min_22+atr_22*3.5
self.days.append(bars[0][1].dayofweek)
if all(day==bars[0][1].dayofweek for day in self.days):
self.previous_high.append(self.high[-1])
self.previous_low.append(self.low[-1])
self.previous_close.append(self.close[-1])
else:
self.max_previous_high,self.min_previous_low= max(self.previous_high),min(self.previous_low)
self.last_close=self.previous_close[-1]
self.days=[]
self.previous_high=[]
self.previous_low=[]
self.previous_high.append(self.high[-1])
self.previous_low.append(self.low[-1])
# print bars[0][1],(self.max_previous_high+self.min_previous_low+self.last_close)/3
# print self.max_previous_high,self.min_previous_low,self.last_close
#---------------INDICATORS -------------------------
daily_pivot_point = (self.max_previous_high+self.min_previous_low+self.last_close)/3
self.pivot_points=np.append(self.pivot_points,daily_pivot_point)
R1=daily_pivot_point*2-self.min_previous_low
R2=daily_pivot_point+self.max_previous_high-self.min_previous_low
R3=self.max_previous_high+2*(daily_pivot_point-self.min_previous_low)
S1=daily_pivot_point*2-self.max_previous_high
S2=daily_pivot_point-self.max_previous_high+self.min_previous_low
S3=self.min_previous_low-2*(self.max_previous_high-daily_pivot_point)
hourly_pivot_point=(self.close[-1]+self.high[-1]+self.low[-1])/3
self.hourly_pivot_points=np.append(self.hourly_pivot_points,hourly_pivot_point)
MA_hourly_pivot_point_3= np.around(talib.SMA(np.array(self.hourly_pivot_points),timeperiod=3),decimals=4)
MA_hourly_pivot_point_5= np.around(talib.SMA(np.array(self.close),timeperiod=5),decimals=4)
if bars is not None and bars != []:
if self.position.direction == 'EXIT':
if ((R1-0.0010) <=self.high[-1] <= R1) or ((R2-0.0010) <=self.high[-1] <= R2) or ((R3-0.0010) <=self.high[-1] <= R3) :
if (MA_hourly_pivot_point_3[-1] < MA_hourly_pivot_point_5[-1] and MA_hourly_pivot_point_3[-2]>=MA_hourly_pivot_point_5[-2]) or (MA_hourly_pivot_point_3[-1] < MA_hourly_pivot_point_5[-1] and MA_hourly_pivot_point_3[-3]>=MA_hourly_pivot_point_5[-3]) and self.close[-1]<MA_hourly_pivot_point_3[-1] and self.close[-1]<MA_hourly_pivot_point_3[-1] and self.bought[s]==False:
self.short_close_enter_price = self.close[-1]
self.events.put(SignalEvent(bars[0][0], bars[0][1],'SHORT'))
#print self.i,' ENTER SHORT-->',bars[0][1],'close enter','-->',self.close[-1]
self.position.direction = 'SHORT'
self.bought[s]=True
self.temp_close.append(self.close[-1])
#print self.temp_close,self.close
return
elif ((S1+0.001)> self.low[-1] > S1) or ((S2+0.001)> self.low[-1] > S2) or ((S3+0.001)> self.low[-1] > S3):
if (MA_hourly_pivot_point_3[-1] < MA_hourly_pivot_point_5[-1] and MA_hourly_pivot_point_3[-2]>=MA_hourly_pivot_point_5[-2]) or (MA_hourly_pivot_point_3[-1] < MA_hourly_pivot_point_5[-1] and MA_hourly_pivot_point_3[-3]>=MA_hourly_pivot_point_5[-3]) and self.close[-1]>MA_hourly_pivot_point_3[-1]:
self.long_close_enter_price = self.close[-1]
#self.bought[s] = True
self.events.put(SignalEvent(bars[0][0],bars[0][1],'LONG'))
self.position.direction ='LONG'
#print self.i,"ENTER LONG-->",bars[0][1], 'close enter','-->',self.close[-1]
self.bought[s]=True
self.temp_close.append(self.close[-1])
return
elif self.position.direction == 'SHORT' :
if self.close[-1] >= self.temp_close[0]+ 0.0035 or self.close[-1] <= self.temp_close[0]-0.007:
#print self.close[-1], self.temp_close[0], min(self.temp_close) ,min(self.temp_close)+(0.0040/(1.2+((self.temp_close[0]-(min(self.temp_close)))*100)))
self.position.direction='EXIT'
#print self.i,'EXIT SHORT',bars[0][1],'close enter','-->',self.close[-1]
self.bought[s]=False
self.events.put(SignalEvent(bars[0][0],bars[0][1],'EXIT'))
self.temp_close=[]
return
elif self.position.direction == 'LONG' :
if self.close[-1] <= self.temp_close[0]-0.0035 or self.close[-1]>= self.temp_close[0]+0.007:
#if self.long_close_enter_price - self.close[-1] >=0.0020:
#assert(self.long_close_enter_price-self.close[-1]>=0.0020)
self.position.direction='EXIT'
self.long_close_enter_price = 0
self.bought[s]=False
self.events.put(SignalEvent(bars[0][0],bars[0][1],'EXIT'))
self.temp_close=[]
return
if self.plot:
self.time_stamp.append(bars[0][1])
self.close_plotting.append(bars[0][5])
#print bars[0][1],bars[0][1].dayofweek
self.pivot_points_plotting.append(daily_pivot_point)
self.r1_plotting.append(R1)
self.s1_plotting.append(S1)
if len(self.time_stamp)>250:
del self.time_stamp[0]
del self.close_plotting[0]
del self.pivot_points_plotting[0]
del self.r1_plotting[0]
del self.s1_plotting[0]
xmin, xmax, ymin, ymax = [min(self.time_stamp) , max(self.time_stamp) , .82,1]
self.line1.set_xdata(self.time_stamp)
self.line1.set_ydata(self.close_plotting)
self.line2.set_xdata(self.time_stamp)
self.line2.set_ydata(self.pivot_points_plotting)
self.line3.set_xdata(self.time_stamp)
self.line3.set_ydata(self.r1_plotting)
self.line4.set_xdata(self.time_stamp)
self.line4.set_ydata(self.s1_plotting)
plt.axis([xmin, xmax, ymin, ymax])
self.fig.canvas.restore_region(self.background) # restore background
self.ax1.draw_artist(self.line1) # redraw just the points
self.fig.canvas.blit(self.ax1.bbox)
if self.position.direction=='SHORT' or self.position.direction=='LONG':
self.temp_close.append(self.close[-1])
elif self.position.direction == 'EXIT':
self.temp_close=[]