class Simulator(object):
'''
simulation manager
'''
def __init__(self, instrument, strategies, start_date, end_date, opening_bal,time_stamp=None):
'''
constructs message queues
initialises brokers and traders
'''
self.instrument = instrument
self.start_date = start_date
self.end_date = end_date
self.opening_bal = opening_bal
self.datafeed = DataFeed(instrument)
self.orderQ = MsgQ()
self.receiptQ = MsgQ()
self.term_req_Q = MsgQ()
self.term_notice_Q = MsgQ()
self.broker = Broker(self.datafeed, self.orderQ, self.receiptQ, self.term_req_Q, self.term_notice_Q)
self.traders = []
for strategy in strategies:
trader = Trader(self.datafeed, self.broker, self.opening_bal, self.instrument, strategy, self.start_date, self.end_date)
self.traders.append(trader)
self.time_stamp = time_stamp
def run(self):
'''
simulate event series
'''
current_date = date(self.start_date.year, self.start_date.month, self.start_date.day)
length = self.end_date - self.start_date
d_total = length.days
display_int = d_total / 10
while (current_date <= self.end_date):
# PROCESS TRADING DAYS
if (self.datafeed.date_is_trading_day(current_date) == True):
self.broker.open_manage_and_close(current_date)
# book keeping
for trader in self.traders:
trader.ac.tally_individual_open_positions(current_date)
trader.ac.record_net_end_of_day_pos(current_date)
trader.ac.record_end_of_day_balances(current_date)
for trader in self.traders:
trader.execute_strategy(current_date)
#self.broker.log_closed_positions()
self.broker.log_all_positions(current_date)
# IGNORE NON-TRADING DAYS
else:
pass
current_date = current_date + timedelta(days=1)
elapsed = (self.end_date - current_date)
d_elapsed = elapsed.days
progress = (float(d_total) - float(d_elapsed)) / float(d_total) * 100.0
if (d_elapsed % display_int == 0):
print('%i/100' % int(progress))
self.traders[0].strategy.log_self()
def plot(self):
'''
analyse & report on simulation path and outcome
'''
d = date(self.start_date.year, self.start_date.month, self.start_date.day)
dates = []
prices = []
cash_bal = []
margin_bal = []
net_booked_position = []
net_open_position = []
daily_high = []
daily_low = []
mavg_band_ceiling = []
mavg_band_floor = []
trader = self.broker.traders[0]
ac = trader.ac
df = self.datafeed
pMin = None
pMax = None
while (d <= self.end_date):
# TRADING DAYS
if (self.datafeed.date_is_trading_day(d) == True):
dates.append(d)
mavg_top = df.n_day_moving_avg(None, d, 'high', Strategy.n)
mavg_bottom = df.n_day_moving_avg(None, d, 'low', Strategy.n)
mavg_band_ceiling.append(mavg_top)
mavg_band_floor.append(mavg_bottom)
pinfo = df.get_price_info(None, d)
prices.append(pinfo['close'])
daily_high.append(pinfo['high'])
daily_low.append(pinfo['low'])
s = str(d) + ',' + str(mavg_band_ceiling[len(mavg_band_ceiling) - 1]) + ',' + str(mavg_band_floor[len(mavg_band_floor) - 1]) + ',' + str(pinfo['close'])
logging.info(s)
cash_bal.append(ac.d_cash_bal[d])
margin_bal.append(ac.d_margin_bal[d])
net_booked_position.append(ac.d_net_booked_position[d])
net_open_position.append(ac.net_open_position[d])
if (pMin == None):
pMin = pinfo['low']
pMax = pinfo['high']
else:
if pinfo['low'] < pMin:
pMin = pinfo['low']
if pinfo['high'] > pMax:
pMax = pinfo['high']
# NON-TRADING DAYS
else:
pass
d = d + timedelta(days=1)
aDate = np.array(dates)
aPrice = np.array(prices)
fig = plt.figure(figsize=(20, 20))
ax = fig.add_subplot(111)
#ax.plot(aDate, aPrice, color='blue')
for series in [mavg_band_ceiling, mavg_band_floor]:
y = np.array(series)
t = np.array(dates)
ax.plot(t, y, color='red')
for series in [daily_high, daily_low]:
y = np.array(series)
t = np.array(dates)
ax.plot(t, y, color='blue')
plt.ylim([float(pMin), float(pMax)])
for series in [net_booked_position]:
y = np.array(series)
t = np.array(dates)
ax2 = ax.twinx()
ax2.plot(t, y, color='green')
ax.grid(False)
fig.autofmt_xdate(rotation=90)
fname = 'plot/plot_' + self.time_stamp
fig.savefig(fname)
