class LiveTestStrat():
"""Same as Previous strat but this should use live prices
and trade the same stratey as Strategy()
"""
def __init__(self):
self.HZ = 1.0 / 1.0
self.local_strategies = [self.tsla]
# variables needed for tsla()
self.prices = AutoQueue(10)
self.boundary = 0.01
self.holding = False
self.volume = 0
def execute(self, portfolio):
while True:
for local_strategy in self.local_strategies:
local_strategy()
sleep(1.0 / self.HZ)
def tsla(self):
tsla = Security('TSLA')
price = tsla.get_price()
self.prices.put(price)
volume = tsla.security.get_volume()
# if volume != self.volume:
# print(volume)
# self.volume = volume
# else:
# return
# do things necessary for avg and stddev calc
# self.price_sum = self.prices.sum()
# self.price_sum_sq = self.prices.sum_sq()
# self.count = len(self.prices)
avg = self.prices.average()
var = self.prices.variance()
if price < avg * (1 - self.boundary):
# low price, want to buy
while portfolio.buy(tsla, 1):
pass
self.holding = True
elif price > avg * (1 + self.boundary):
# high price, want to sell_all
portfolio.sell_all(tsla)
self.holding = False
print(
f'Price: {price:.2f}\tAvg: {avg:.2f}\tvar: {var:.2f} <{time.asctime()}',
end='\r')
class Strategy():
def __init__(self):
# TODO framework to test different parameter in parallel
self.HZ = 14000.0
self.price_sum = 0
# perhaps make arg in Q(arg) an arg in __init__
self.prices = AutoQueue(10)
self.price_sum_sq = 0
self.count = 0
self.boundary = 0.025 # percent change from mean
# calculate average using a queue, be able to set size using some parameter
def execute(self, portfolio):
goog = TestSecurity("GOOG")
counter = 0
while counter < 949:
price = goog.get_price()
self.prices.put(price)
# do things necessary for avg and stddev calc
self.price_sum = self.prices.sum()
self.price_sum_sq = self.prices.sum_sq()
self.count = len(self.prices)
avg = self.prices.average()
var = self.prices.variance()
if price < avg * (1 - self.boundary):
# low price, want to buy
while portfolio.buy(goog, 1):
pass
self.holding = True
elif price > avg * (1 + self.boundary):
# high price, want to sell_all
portfolio.sell_all(goog)
self.holding = False
# print(f'Price: {price:.2f}\tAvg: {avg:.2f}\tvar: {var:.2f}')
counter += 1
sleep(1.0 / self.HZ)
print(portfolio)
class InterfaceEvents(Thread):
def __init__(self, udp_ip='127.0.0.1', udp_port='8888', message_size=16):
super(InterfaceEvents, self).__init__()
self.udp_ip = udp_ip
self.udp_port = udp_port
self.message_size = message_size
self.list_events = AutoQueue(maxsize=250)
self.list_events_time = AutoQueue(maxsize=250)
self.lock = Lock()
self.sock = socket.socket(socket.AF_INET, socket.SOCK_DGRAM) # UDP
self.sock.bind((self.udp_ip, self.udp_port))
# first message, with the sequence
first_message, addr = self.sock.recvfrom(
4096) # buffer size is 1024 bytes
self.frq_event, self.type_event, self.sequence_usage, self.sequence_training = self.decript_first_message(
first_message)
def get_nearest_message(self):
pass
def start(self):
super(InterfaceEvents, self).start()
def decript_first_message(self, m):
message_split_by_type = m.split(' DONE')
split_message = message_split_by_type[0].split(' ')
frq_event = split_message[0]
type_event = split_message[1]
sequence_usage = split_message[2:]
sequence_training = None
if type_event == 'T':
sequence_training_list = message_split_by_type[1].split(' ')[1:]
sequence_training = [[
sequence_training_list[2 * i],
sequence_training_list[2 * i + 1].split(',')
] for i in range(len(sequence_training_list) / 2)]
return frq_event, type_event, sequence_usage, sequence_training
def add_event_synchronicity(self, time_event, event):
self.lock.acquire()
self.list_events.put(event)
self.list_events_time.put(time_event)
self.lock.release()
def find_closest_event(self, datetime_window):
event_usage, event_training = '', ''
self.lock.acquire()
list_events_time = list(self.list_events_time)
list_events = list(self.list_events)
self.lock.release()
# search into the list of event and return the closest match
index_closest_after = bisect_left(list_events_time, datetime_window)
index_closest_before = index_closest_after - 1 # datetime are sorted in self.list_events_time
datetime_before = list_events_time[index_closest_before]
datetime_after = list_events_time[index_closest_before]
index_event_before = list_events[index_closest_before]
index_event_after = list_events[index_closest_before]
# linear interpolation to find closest match
percentage_closest = (datetime_window - datetime_before) / (
datetime_after - datetime_before)
index_event_closest = index_event_before + percentage_closest * (
index_event_after - index_event_before)
event_usage = self.sequence_usage[index_event_closest]
# TODO: add extraction of usage for training
return event_usage, event_training
def refresh(self):
while True:
data, addr = self.sock.recvfrom(
self.message_size) # buffer size is 1024 bytes
# data is a message with the structure:
# message: TEMPS_CLOCK,INDEX
# exemple: 2017-03-20 19:05:45.191179,42
split_message = data.split(',')
time_event = datetime.strptime(split_message[0],
'%Y-%m-%d %H:%M:%S.%f')
index_event = int(split_message[1])
event = self.sequence_usage[index_event]
# add event to a list
self.add_event_synchronicity(time_event, event)