def main():
theMarket = Market(
data_path="data/%s_Candlestick_4_Hour_BID_01.08.2018-30.11.2018.csv" %
CURRENCY_PAIR) #, indicators={'ADX': 12})
MyRecord = Record()
MyOrderManager = OrderManager(market=theMarket, record=MyRecord)
MyTrader = SureFireTrader(orderManager=MyOrderManager)
SLTP_pips = [20, 25, 30]
start_order_type = ['BUY', 'SELL']
max_level_limit = [2, 3, 4]
window_size = 12
# Create a RL agent
with open("config/%s.json" % AGENT_METHOD, 'r') as fp:
agent_config = json.load(fp=fp)
with open("config/conv2d.json", 'r') as fp:
network_config = json.load(fp=fp)
agent = Agent.from_spec(
spec=agent_config,
kwargs=dict(
states=dict(type='float', shape=(window_size, window_size,
4)), #[Open, High, Low, Close]
actions=dict(
SLTP_pips=dict(type='int',
num_actions=len(SLTP_pips)), #[20,25,30]
start_order_type=dict(
type='int',
num_actions=len(start_order_type)), #['BUY','SELL']
max_level_limit=dict(
type='int', num_actions=len(max_level_limit)) #[2,3,4,5]
),
network=network_config))
if not os.path.exists("save_model/%s/trades" % AGENT_METHOD):
os.makedirs("save_model/%s/trades" % AGENT_METHOD)
reward_history = []
for episode in trange(100 + 1, ascii=True):
profit_history = []
this_reward_history = []
idle_count = 0
round_count = 0
episode_end = False
max_idle_limit = 12 #future action
MyRecord.reset()
MyOrderManager.reset()
theMarket.reset(start_index=window_size)
pbar = tqdm()
while (theMarket.next()): #main loop, essential
pbar.update(1) # simple-GUI
################### ROUTINES ###################
MyOrderManager.orders_check() #routine, after market.next
trade_status, other_detail = MyTrader.status_check(
) #routine, after orders_check
################################################
################### GET STATE ##################
ohlc = theMarket.get_ohlc(size=window_size)
indicators = theMarket.get_indicators(size=window_size)
O, H, L, C = gaf_encode(ohlc['Open']), gaf_encode(ohlc['High']), \
gaf_encode(ohlc['Low']),gaf_encode(ohlc['Close'])
#ADX = gaf_encode(indicators['ADX'])
state = np.stack((O, H, L, C), axis=-1)
################################################
################## TAKE ACTION #################
if trade_status == 'TRADE_OVER':
############ GET REWARD & TRAIN ################
if theMarket.get_current_index() > window_size:
'''
profit = sum(round(order['profit'],5) for order in other_detail if order['profit']>0)
loss = sum(round(order['profit'],5) for order in other_detail if order['profit']<0)
this_profit_factor = MyRecord.get_profit_factor()
this_trade_length = len(MyRecord.get_history())
reward = this_profit_factor*np.sqrt(this_trade_length)#SQN
'''
raw_reward = (MyRecord.get_net_profit() -
profit_history[-1]) / theMarket.get_pip()
penalty = 1.0 - 0.1 * len(other_detail)
if raw_reward > 0:
reward = raw_reward * penalty
else:
if len(other_detail) == 0:
reward = 0
else:
reward = -np.abs(other_detail[0]['TP'] -
other_detail[0]['price']
) / theMarket.get_pip()
if theMarket.get_current_index(
) >= theMarket.get_data_length(
) - max_idle_limit * max_level_limit[-1]:
episode_end = True
agent.observe(
reward=reward, terminal=episode_end
) # Add experience, agent automatically updates model according to batch size
this_reward_history.append(reward)
if episode_end == True:
if episode % 100 == 0:
this_dir = 'save_model/%s/%04d' % (AGENT_METHOD,
episode)
if not os.path.exists(this_dir):
os.makedirs(this_dir)
agent.save_model(this_dir + '/model')
pbar.close()
reward_history.append(this_reward_history)
with open(
'save_model/%s/trades/episode_%04d.pkl' %
(AGENT_METHOD, episode), 'wb') as f:
pickle.dump(MyRecord.get_history(), f, protocol=-1)
break
action = agent.act(state) # Get prediction from agent, execute
SL_pip = SLTP_pips[action['SLTP_pips']] * 2
TP_pip = SLTP_pips[action['SLTP_pips']]
MyTrader.set_max_level(
max_level_limit[action['max_level_limit']])
first_order_type = start_order_type[action['start_order_type']]
################################################
MyTrader.new_trade(SL_pip=SL_pip,
TP_pip=TP_pip,
start_order_type=first_order_type)
round_count += 1
idle_count = 0
logging.info(
"NewTradeStarted: current net profit=%f (price@%f)" %
(MyRecord.get_net_profit(), theMarket.get_market_price()))
elif trade_status == 'ADD_ORDER':
last_order = MyTrader.get_orders_detail()[-1]
if last_order['order_type'] == 'BUY':
price = last_order['price'] - theMarket.get_pip(TP_pip)
elif last_order['order_type'] == 'SELL':
price = last_order['price'] + theMarket.get_pip(TP_pip)
MyTrader.add_reverse_order(price=price,
SL_pip=SL_pip,
TP_pip=TP_pip)
idle_count = 0
elif trade_status == 'ERROR':
logging.warning("SureFireError: order issues...")
elif trade_status == 'NONE':
idle_count += 1
if idle_count >= max_idle_limit:
############ GET REWARD & TRAIN ################
'''
profit = sum(round(order['profit'],5) for order in other_detail if order['profit']>0)
loss = sum(round(order['profit'],5) for order in other_detail if order['profit']<0)
this_profit_factor = MyRecord.get_profit_factor()
this_trade_length = len(MyRecord.get_history())
reward = this_profit_factor*np.sqrt(this_trade_length)#SQN
'''
raw_reward = (MyRecord.get_net_profit() -
profit_history[-1]) / theMarket.get_pip()
penalty = 1.0 - 0.1 * len(other_detail)
if raw_reward > 0:
reward = raw_reward * penalty
else:
if len(other_detail) == 0:
reward = 0
else:
reward = -np.abs(other_detail[0]['TP'] -
other_detail[0]['price']
) / theMarket.get_pip()
if theMarket.get_current_index(
) >= theMarket.get_data_length(
) - max_idle_limit * max_level_limit[-1]:
episode_end = True
agent.observe(
reward=reward, terminal=episode_end
) # Add experience, agent automatically updates model according to batch size
this_reward_history.append(reward)
if episode_end == True:
if episode % 100 == 0:
this_dir = 'save_model/%s/%04d' % (AGENT_METHOD,
episode)
if not os.path.exists(this_dir):
os.makedirs(this_dir)
agent.save_model(this_dir + '/model')
pbar.close()
reward_history.append(this_reward_history)
with open(
'save_model/%s/trades/episode_%04d.pkl' %
(AGENT_METHOD, episode), 'wb') as f:
pickle.dump(MyRecord.get_history(), f, protocol=-1)
break
action = agent.act(
state) # Get prediction from agent, execute
SL_pip = SLTP_pips[action['SLTP_pips']] * 2
TP_pip = SLTP_pips[action['SLTP_pips']]
MyTrader.set_max_level(
max_level_limit[action['max_level_limit']])
first_order_type = start_order_type[
action['start_order_type']]
################################################
MyTrader.new_trade(SL_pip=SL_pip,
TP_pip=TP_pip,
start_order_type=first_order_type)
idle_count = 0
logging.info(
"NewTradeStarted: current net profit=%f (price@%f)" %
(MyRecord.get_net_profit(),
theMarket.get_market_price()))
################################################
profit_history.append(MyRecord.get_net_profit()) #for plotting
#MyRecord.show_details()
#print("Rounds of Tradings: %d\n"%round_count)
#with open('save_model/%s/trades/profit_history.pkl'%AGENT_METHOD, 'wb') as f:
#pickle.dump(profit_history,f,protocol=-1)
with open('save_model/%s/trades/reward_history.pkl' % AGENT_METHOD,
'wb') as f:
pickle.dump(reward_history, f, protocol=-1)
def main():
PROFIT_HIST = []
for arg_i in range(1, (len(sys.argv) // 3) + 2, 2):
_config = sys.argv[arg_i].split('\\')
AGENT_METHOD = _config[-2]
CURRENCY_PAIR = _config[-1]
theMarket = Market(
data_path="data/%s_Candlestick_4_Hour_BID_01.12.2018-31.12.2018.csv"
% CURRENCY_PAIR) #, indicators={'ADX': 12})
MyRecord = Record()
MyOrderManager = OrderManager(market=theMarket, record=MyRecord)
MyTrader = SureFireTrader(orderManager=MyOrderManager)
SLTP_pips = [20, 25, 30]
start_order_type = ['BUY', 'SELL']
max_level_limit = [2, 3, 4]
window_size = 12
# Create a RL agent
if AGENT_METHOD != "constant":
with open("config/%s.json" % AGENT_METHOD, 'r') as fp:
agent_config = json.load(fp=fp)
with open("config/conv2d.json", 'r') as fp:
network_config = json.load(fp=fp)
agent = Agent.from_spec(
spec=agent_config,
kwargs=dict(
states=dict(type='float',
shape=(window_size, window_size,
4)), #[Open, High, Low, Close]
actions=dict(
SLTP_pips=dict(
type='int',
num_actions=len(SLTP_pips)), #[20,25,30]
start_order_type=dict(
type='int', num_actions=len(
start_order_type)), #['BUY','SELL']
max_level_limit=dict(
type='int',
num_actions=len(max_level_limit)) #[2,3,4,5]
),
network=network_config))
the_episode = int(sys.argv[arg_i + 1])
agent.restore_model(sys.argv[arg_i] + '/%04d' % the_episode)
else:
agent = ConstantAgent(
states=dict(type='float',
shape=(window_size, window_size,
4)), #[Open, High, Low, Close]
actions=dict(
SLTP_pips=dict(type='int',
num_actions=len(SLTP_pips)), #[20,25,30]
start_order_type=dict(
type='int',
num_actions=len(start_order_type)), #['BUY','SELL']
max_level_limit=dict(
type='int', num_actions=len(max_level_limit)) #[2,3,4]
),
action_values={
'SLTP_pips': 2,
'max_level_limit': 2,
'start_order_type': 0
})
the_episode = 0
profit_history = []
idle_count = 0
round_count = 0
episode_end = False
max_idle_limit = 12 #future action
MyRecord.reset()
MyOrderManager.reset()
theMarket.reset(start_index=window_size)
#pbar = tqdm()
while (theMarket.next()): #main loop, essential
#pbar.update(1) # simple-GUI
################### ROUTINES ###################
MyOrderManager.orders_check() #routine, after market.next
trade_status, other_detail = MyTrader.status_check(
) #routine, after orders_check
################################################
################### GET STATE ##################
ohlc = theMarket.get_ohlc(size=window_size)
indicators = theMarket.get_indicators(size=window_size)
O, H, L, C = gaf_encode(ohlc['Open']), gaf_encode(ohlc['High']), \
gaf_encode(ohlc['Low']),gaf_encode(ohlc['Close'])
#ADX = gaf_encode(indicators['ADX'])
state = np.stack((O, H, L, C), axis=-1)
################################################
################## TAKE ACTION #################
if trade_status == 'TRADE_OVER':
############ GET REWARD & TRAIN ################
action = agent.act(state) # Get prediction from agent, execute
SL_pip = SLTP_pips[action['SLTP_pips']] * 2
TP_pip = SLTP_pips[action['SLTP_pips']]
MyTrader.set_max_level(
max_level_limit[action['max_level_limit']])
first_order_type = start_order_type[action['start_order_type']]
################################################
MyTrader.new_trade(SL_pip=SL_pip,
TP_pip=TP_pip,
start_order_type=first_order_type)
round_count += 1
idle_count = 0
logging.info(
"NewTradeStarted: current net profit=%f (price@%f)" %
(MyRecord.get_net_profit(), theMarket.get_market_price()))
elif trade_status == 'ADD_ORDER':
last_order = MyTrader.get_orders_detail()[-1]
if last_order['order_type'] == 'BUY':
price = last_order['price'] - theMarket.get_pip(TP_pip)
elif last_order['order_type'] == 'SELL':
price = last_order['price'] + theMarket.get_pip(TP_pip)
MyTrader.add_reverse_order(price=price,
SL_pip=SL_pip,
TP_pip=TP_pip)
idle_count = 0
elif trade_status == 'ERROR':
logging.warning("SureFireError: order issues...")
elif trade_status == 'NONE':
idle_count += 1
if idle_count >= max_idle_limit:
action = agent.act(
state) # Get prediction from agent, execute
SL_pip = SLTP_pips[action['SLTP_pips']] * 2
TP_pip = SLTP_pips[action['SLTP_pips']]
MyTrader.set_max_level(
max_level_limit[action['max_level_limit']])
first_order_type = start_order_type[
action['start_order_type']]
MyTrader.new_trade(SL_pip=SL_pip,
TP_pip=TP_pip,
start_order_type=first_order_type)
idle_count = 0
logging.info(
"NewTradeStarted: current net profit=%f (price@%f)" %
(MyRecord.get_net_profit(),
theMarket.get_market_price()))
################################################
profit_history.append(MyRecord.get_net_profit() *
10000) #for plotting
#pbar.close()
my_details = MyRecord.show_details()
print("Rounds of Tradings: %d\n" % round_count)
print('---')
PROFIT_HIST.append(profit_history)
if len(sys.argv) > 5:
df = pd.read_csv(sys.argv[5])
baseline = df['hist'].tolist()
plt.plot(range(len(baseline)), baseline, color='purple', linestyle=':')
plt.plot(range(len(PROFIT_HIST[0])), PROFIT_HIST[0])
plt.plot(range(len(PROFIT_HIST[1])), PROFIT_HIST[1])
plt.xlabel('timestep')
plt.ylabel('accumulated return')
plt.legend([
'baseline', sys.argv[1].split('\\')[-2],
sys.argv[3].split('\\')[-2]
],
loc='lower right',
fontsize='x-large')
plt.show()
else:
plt.plot(range(len(profit_history)), profit_history)
plt.xlabel('timestep')
plt.ylabel('accumulated return')
plt.show()
pd.DataFrame({
'hist': profit_history
}).to_csv('profit_history_test.csv', index=False)
def main():
AGENT_METHOD = sys.argv[1] # "ppo"
CURRENCY_PAIR = sys.argv[2] # "EURUSD"
theMarket = Market(data_path="data/%s_Candlestick_4_Hour_BID_01.12.2018-31.12.2018.csv"%CURRENCY_PAIR)#, indicators={'ADX': 12})
MyRecord = Record()
MyOrderManager = OrderManager(market=theMarket, record=MyRecord)
MyTrader = SureFireTrader(orderManager=MyOrderManager)
SLTP_pips = [20,25,30]
start_order_type = ['BUY','SELL']
max_level_limit = [2,3,4]
window_size = 12
output_record = {'episode':[], 'total_trades': [], 'win_trades': [],
'lose_trades': [], 'profit_factor': [], 'net_profit': [],
'max_drawdown': [], 'trading_rounds': []}
if AGENT_METHOD != "constant":
iter_range = range(0,100+1,100)
else:
iter_range = range(1)
for the_episode in iter_range:
# Create a RL agent
if AGENT_METHOD != "constant":
with open("config/%s.json"%AGENT_METHOD, 'r') as fp:
agent_config = json.load(fp=fp)
with open("config/conv2d.json", 'r') as fp:
network_config = json.load(fp=fp)
agent = Agent.from_spec(
spec=agent_config,
kwargs=dict(
states=dict(type='float', shape=(window_size,window_size,4)), #[Open, High, Low, Close]
actions=dict(
SLTP_pips=dict(type='int', num_actions=len(SLTP_pips)), #[20,25,30]
start_order_type=dict(type='int', num_actions=len(start_order_type)), #['BUY','SELL']
max_level_limit=dict(type='int', num_actions=len(max_level_limit)) #[2,3,4,5]
),
network=network_config
)
)
agent.restore_model("save_model"+"/"+AGENT_METHOD+"/"+'%04d'%the_episode)
else:
agent = ConstantAgent(
states=dict(type='float', shape=(window_size,window_size,4)), #[Open, High, Low, Close]
actions=dict(
SLTP_pips=dict(type='int', num_actions=len(SLTP_pips)), #[20,25,30]
start_order_type=dict(type='int', num_actions=len(start_order_type)), #['BUY','SELL']
max_level_limit=dict(type='int', num_actions=len(max_level_limit)) #[2,3,4]
),
action_values={'SLTP_pips': 2, 'max_level_limit': 2, 'start_order_type': 0}
)
profit_history = []
idle_count = 0
round_count = 0
episode_end = False
max_idle_limit = 12 #future action
MyRecord.reset()
MyOrderManager.reset()
theMarket.reset(start_index=window_size)
#pbar = tqdm()
while(theMarket.next()): #main loop, essential
#pbar.update(1) # simple-GUI
################### ROUTINES ###################
MyOrderManager.orders_check() #routine, after market.next
trade_status, other_detail = MyTrader.status_check() #routine, after orders_check
################################################
################### GET STATE ##################
ohlc = theMarket.get_ohlc(size=window_size)
indicators = theMarket.get_indicators(size=window_size)
O, H, L, C = gaf_encode(ohlc['Open']), gaf_encode(ohlc['High']), \
gaf_encode(ohlc['Low']),gaf_encode(ohlc['Close'])
#ADX = gaf_encode(indicators['ADX'])
state = np.stack((O,H,L,C),axis=-1)
################################################
################## TAKE ACTION #################
if trade_status == 'TRADE_OVER':
############ GET REWARD & TRAIN ################
action = agent.act(state) # Get prediction from agent, execute
SL_pip = SLTP_pips[action['SLTP_pips']]*2
TP_pip = SLTP_pips[action['SLTP_pips']]
MyTrader.set_max_level(max_level_limit[action['max_level_limit']])
first_order_type = start_order_type[action['start_order_type']]
################################################
MyTrader.new_trade(SL_pip=SL_pip, TP_pip=TP_pip, start_order_type=first_order_type)
round_count += 1
idle_count = 0
logging.info("NewTradeStarted: current net profit=%f (price@%f)"%(MyRecord.get_net_profit(), theMarket.get_market_price()))
elif trade_status == 'ADD_ORDER':
last_order = MyTrader.get_orders_detail()[-1]
if last_order['order_type'] == 'BUY':
price = last_order['price'] - theMarket.get_pip(TP_pip)
elif last_order['order_type'] == 'SELL':
price = last_order['price'] + theMarket.get_pip(TP_pip)
MyTrader.add_reverse_order(price=price, SL_pip=SL_pip, TP_pip=TP_pip)
idle_count = 0
elif trade_status == 'ERROR':
logging.warning("SureFireError: order issues...")
elif trade_status == 'NONE':
idle_count += 1
if idle_count >= max_idle_limit:
action = agent.act(state) # Get prediction from agent, execute
SL_pip = SLTP_pips[action['SLTP_pips']]*2
TP_pip = SLTP_pips[action['SLTP_pips']]
MyTrader.set_max_level(max_level_limit[action['max_level_limit']])
first_order_type = start_order_type[action['start_order_type']]
MyTrader.new_trade(SL_pip=SL_pip, TP_pip=TP_pip, start_order_type=first_order_type)
idle_count = 0
logging.info("NewTradeStarted: current net profit=%f (price@%f)"%(MyRecord.get_net_profit(), theMarket.get_market_price()))
################################################
profit_history.append(MyRecord.get_net_profit()) #for plotting
#pbar.close()
my_details = MyRecord.show_details()
print("Rounds of Tradings: %d\n"%round_count)
print('---')
output_record['episode'].append(the_episode)
output_record['trading_rounds'].append(round_count)
for k in my_details:
output_record[k].append(my_details[k])
plt.plot(range(len(profit_history)), profit_history)
plt.show()
for k in output_record:
plt.plot(output_record['episode'], output_record[k])
plt.title(k)
plt.show()
pd.DataFrame(output_record).to_csv('test_detail-episode.csv', index=False)
def OF():
OI = Market(
data_path="data/%s_Candlestick_4_Hour_BID_01.08.2018-30.11.2018.csv" %
Om)
Oa = Record()
Oo = OrderManager(market=OI, record=Oa)
OS = SureFireTrader(orderManager=Oo)
OP = [20, 25, 30]
OH = ['BUY', 'SELL']
Oy = [2, 3, 4]
Oc = 12
OR = ConstantAgent(states=Og(type='float', shape=(Oc, Oc, 4)),
actions=Og(SLTP_pips=Og(type='int', num_actions=OQ(OP)),
start_order_type=Og(type='int',
num_actions=OQ(OH)),
max_level_limit=Og(type='int',
num_actions=OQ(Oy))),
action_values={
'SLTP_pips': 0,
'max_level_limit': 0,
'start_order_type': 0
})
if not Ol.exists("save_model/constant/trades"):
Op("save_model/constant/trades")
if not Ol.exists('save_model/constant/0000'):
Op('save_model/constant/0000')
OR.save_model('save_model/constant/0000/model')
OM = []
OW = []
OL = []
Os = 0
OX = 0
OB = OY
OK = 12
Oa.reset()
Oo.reset()
OI.reset(start_index=Oc)
OD = tqdm()
while (OI.next()):
OD.update(1)
Oo.orders_check()
OJ, Oz = OS.status_check()
Oj = OI.get_ohlc(size=Oc)
Ok = OI.get_indicators(size=Oc)
O, H, L, C = gaf_encode(Oj['Open']), gaf_encode(
Oj['High']), gaf_encode(Oj['Low']), gaf_encode(Oj['Close'])
Or = On((O, H, L, C), axis=-1)
if OJ == 'TRADE_OVER':
if OI.get_current_index() > Oc:
Of = (Oa.get_net_profit() - OW[-1]) / OI.get_pip()
Ov = 1.0 - 0.1 * OQ(Oz)
if Of > 0:
Ou = Of * Ov
else:
if OQ(Oz) == 0:
Ou = 0
else:
Ou = -Ow(Oz[0]['TP'] - Oz[0]['price']) / OI.get_pip()
if OI.get_current_index(
) >= OI.get_data_length() - OK * Oy[-1]:
OB = OU
OR.observe(reward=Ou, terminal=OB)
OL.append(Ou)
if OB == OU:
OD.close()
OM.append(OL)
break
OT = OR.act(Or)
OE = OP[OT['SLTP_pips']] * 2
OG = OP[OT['SLTP_pips']]
OS.set_max_level(Oy[OT['max_level_limit']])
Oq = OH[OT['start_order_type']]
OS.new_trade(SL_pip=OE, TP_pip=OG, start_order_type=Oq)
OX += 1
Os = 0
Ot("NewTradeStarted: current net profit=%f (price@%f)" %
(Oa.get_net_profit(), OI.get_market_price()))
elif OJ == 'ADD_ORDER':
OA = OS.get_orders_detail()[-1]
if OA['order_type'] == 'BUY':
Oi = OA['price'] - OI.get_pip(OG)
elif OA['order_type'] == 'SELL':
Oi = OA['price'] + OI.get_pip(OG)
OS.add_reverse_order(price=Oi, SL_pip=OE, TP_pip=OG)
Os = 0
elif OJ == 'ERROR':
Ox("SureFireError: order issues...")
elif OJ == 'NONE':
Os += 1
if Os >= OK:
Of = (Oa.get_net_profit() - OW[-1]) / OI.get_pip()
Ov = 1.0 - 0.1 * OQ(Oz)
if Of > 0:
Ou = Of * Ov
else:
if OQ(Oz) == 0:
Ou = 0
else:
Ou = -Ow(Oz[0]['TP'] - Oz[0]['price']) / OI.get_pip()
if OI.get_current_index(
) >= OI.get_data_length() - OK * Oy[-1]:
OB = OU
OR.observe(reward=Ou, terminal=OB)
OL.append(Ou)
if OB == OU:
OD.close()
OM.append(OL)
break
OT = OR.act(Or)
OE = OP[OT['SLTP_pips']] * 2
OG = OP[OT['SLTP_pips']]
OS.set_max_level(Oy[OT['max_level_limit']])
Oq = OH[OT['start_order_type']]
OS.new_trade(SL_pip=OE, TP_pip=OG, start_order_type=Oq)
Os = 0
Ot("NewTradeStarted: current net profit=%f (price@%f)" %
(Oa.get_net_profit(), OI.get_market_price()))
OW.append(Oa.get_net_profit())
with OV('save_model/constant/trades/episode_0000.pkl', 'wb') as f:
ON(Oa.get_history(), f, protocol=-1)
with OV('save_model/constant/trades/profit_history.pkl', 'wb') as f:
ON(OW, f, protocol=-1)
with OV('save_model/constant/trades/reward_history.pkl', 'wb') as f:
ON(OM, f, protocol=-1)
Oa.show_details()
def Ql():
Qv=Market(data_path="data/%s_Candlestick_4_Hour_BID_01.08.2018-30.11.2018.csv"%QX)
QR=Record()
QH=OrderManager(market=Qv,record=QR)
QI=SureFireTrader(orderManager=QH)
Qd=[30,35,40,45,50]
QP=['BUY','SELL']
Qw=[1,2,3,4,5,6,7]
QN=24
with tX("config/%s.json"%Qt,'r')as fp:
QD=QC(fp=fp)
with tX("config/conv2d.json",'r')as fp:
Qc=QC(fp=fp)
QF=Qo(spec=QD,kwargs=tv(states=tv(type='float',shape=(QN,QN,4)),actions=tv(SLTP_pips=tv(type='int',num_actions=tR(Qd)),start_order_type=tv(type='int',num_actions=tR(QP)),max_level_limit=tv(type='int',num_actions=tR(Qw))),network=Qc))
if not QS.exists("save_model/%s/trades"%Qt):
Qx("save_model/%s/trades"%Qt)
QY=[]
for Qi in Qz(100+1,ascii=tH):
Qq=[]
Qm=[]
QA=0
QV=0
QB=tI
QK=12
QR.reset()
QH.reset()
Qv.reset(start_index=QN)
Qj=tqdm()
while(Qv.next()):
Qj.update(1)
QH.orders_check()
Qu,QE=QI.status_check()
QO=Qv.get_ohlc(size=QN)
Qf=Qv.get_indicators(size=QN)
O,H,L,C=gaf_encode(QO['Open']),gaf_encode(QO['High']), gaf_encode(QO['Low']),gaf_encode(QO['Close'])
Qh=Qs((O,H,L,C),axis=-1)
if Qu=='TRADE_OVER':
if Qv.get_current_index()>QN:
QJ=(QR.get_net_profit()-Qq[-1])/Qv.get_pip()
Qr=1.0-0.1*tR(QE)
if QJ>0:
Qa=QJ*Qr
else:
if tR(QE)==0:
Qa=0
else:
Qa=-QM(QE[0]['TP']-QE[0]['price'])/Qv.get_pip()
if Qv.get_current_index()>=Qv.get_data_length()-QK*Qw[-1]:
QB=tH
QF.observe(reward=Qa,terminal=QB)
Qm.append(Qa)
if QB==tH:
if Qi%100==0:
QT='save_model/%s/%04d'%(Qt,Qi)
if not QS.exists(QT):
Qx(QT)
QF.save_model(QT+'/model')
Qj.close()
QY.append(Qm)
with tX('save_model/%s/trades/episode_%04d.pkl'%(Qt,Qi),'wb')as f:
tQ(QR.get_history(),f,protocol=-1)
break
QG=QF.act(Qh)
Qe=Qd[QG['SLTP_pips']]*2
Qy=Qd[QG['SLTP_pips']]
QI.set_max_level(Qw[QG['max_level_limit']])
Qk=QP[QG['start_order_type']]
QI.new_trade(SL_pip=Qe,TP_pip=Qy,start_order_type=Qk)
QV+=1
QA=0
Qb("NewTradeStarted: current net profit=%f (price@%f)"%(QR.get_net_profit(),Qv.get_market_price()))
elif Qu=='ADD_ORDER':
QW=QI.get_orders_detail()[-1]
if QW['order_type']=='BUY':
Qn=QW['price']-Qv.get_pip(Qy)
elif QW['order_type']=='SELL':
Qn=QW['price']+Qv.get_pip(Qy)
QI.add_reverse_order(price=Qn,SL_pip=Qe,TP_pip=Qy)
QA=0
elif Qu=='ERROR':
Qp("SureFireError: order issues...")
elif Qu=='NONE':
QA+=1
if QA>=QK:
QJ=(QR.get_net_profit()-Qq[-1])/Qv.get_pip()
Qr=1.0-0.1*tR(QE)
if QJ>0:
Qa=QJ*Qr
else:
if tR(QE)==0:
Qa=0
else:
Qa=-QM(QE[0]['TP']-QE[0]['price'])/Qv.get_pip()
if Qv.get_current_index()>=Qv.get_data_length()-QK*Qw[-1]:
QB=tH
QF.observe(reward=Qa,terminal=QB)
Qm.append(Qa)
if QB==tH:
if Qi%100==0:
QT='save_model/%s/%04d'%(Qt,Qi)
if not QS.exists(QT):
Qx(QT)
QF.save_model(QT+'/model')
Qj.close()
QY.append(Qm)
with tX('save_model/%s/trades/episode_%04d.pkl'%(Qt,Qi),'wb')as f:
tQ(QR.get_history(),f,protocol=-1)
break
QG=QF.act(Qh)
Qe=Qd[QG['SLTP_pips']]*2
Qy=Qd[QG['SLTP_pips']]
QI.set_max_level(Qw[QG['max_level_limit']])
Qk=QP[QG['start_order_type']]
QI.new_trade(SL_pip=Qe,TP_pip=Qy,start_order_type=Qk)
QA=0
Qb("NewTradeStarted: current net profit=%f (price@%f)"%(QR.get_net_profit(),Qv.get_market_price()))
Qq.append(QR.get_net_profit())
with tX('save_model/%s/trades/reward_history.pkl'%Qt,'wb')as f:
tQ(QY,f,protocol=-1)
def fi():
fj = fn[1].split('\\')
fd = fj[-2]
fW = fj[-1]
fh = Market(
data_path="data/%s_Candlestick_4_Hour_BID_01.12.2018-31.12.2018.csv" %
fW)
fs = Record()
fr = OrderManager(market=fh, record=fs)
fE = SureFireTrader(orderManager=fr)
fI = [20, 25, 30]
fx = ['BUY', 'SELL']
fB = [2, 3, 4]
fY = 12
fP = {
'episode': [],
'total_trades': [],
'win_trades': [],
'lose_trades': [],
'profit_factor': [],
'net_profit': [],
'max_drawdown': [],
'trading_rounds': []
}
if fd != "constant":
fA = fR(0, 100 + 1, 100)
else:
fA = fR(1)
for fa in fA:
if fd != "constant":
with fD("config/%s.json" % fd, 'r') as fp:
fk = fV(fp=fp)
with fD("config/conv2d.json", 'r') as fp:
fF = fV(fp=fp)
fo = fL(spec=fk,
kwargs=fy(states=fy(type='float', shape=(fY, fY, 4)),
actions=fy(
SLTP_pips=fy(type='int', num_actions=fm(fI)),
start_order_type=fy(type='int',
num_actions=fm(fx)),
max_level_limit=fy(type='int',
num_actions=fm(fB))),
network=fF))
fo.restore_model(fn[1] + '/%04d' % fa)
else:
fo = ConstantAgent(
states=fy(type='float', shape=(fY, fY, 4)),
actions=fy(SLTP_pips=fy(type='int', num_actions=fm(fI)),
start_order_type=fy(type='int', num_actions=fm(fx)),
max_level_limit=fy(type='int', num_actions=fm(fB))),
action_values={
'SLTP_pips': 2,
'max_level_limit': 2,
'start_order_type': 0
})
fQ = []
fz = 0
fN = 0
fK = fp
fg = 12
fs.reset()
fr.reset()
fh.reset(start_index=fY)
while (fh.next()):
fr.orders_check()
fw, fl = fE.status_check()
fT = fh.get_ohlc(size=fY)
fc = fh.get_indicators(size=fY)
O, H, L, C = gaf_encode(fT['Open']), gaf_encode(
fT['High']), gaf_encode(fT['Low']), gaf_encode(fT['Close'])
fG = fU((O, H, L, C), axis=-1)
if fw == 'TRADE_OVER':
fX = fo.act(fG)
fS = fI[fX['SLTP_pips']] * 2
ft = fI[fX['SLTP_pips']]
fE.set_max_level(fB[fX['max_level_limit']])
fb = fx[fX['start_order_type']]
fE.new_trade(SL_pip=fS, TP_pip=ft, start_order_type=fb)
fN += 1
fz = 0
fq("NewTradeStarted: current net profit=%f (price@%f)" %
(fs.get_net_profit(), fh.get_market_price()))
elif fw == 'ADD_ORDER':
fO = fE.get_orders_detail()[-1]
if fO['order_type'] == 'BUY':
fH = fO['price'] - fh.get_pip(ft)
elif fO['order_type'] == 'SELL':
fH = fO['price'] + fh.get_pip(ft)
fE.add_reverse_order(price=fH, SL_pip=fS, TP_pip=ft)
fz = 0
elif fw == 'ERROR':
fJ("SureFireError: order issues...")
elif fw == 'NONE':
fz += 1
if fz >= fg:
fX = fo.act(fG)
fS = fI[fX['SLTP_pips']] * 2
ft = fI[fX['SLTP_pips']]
fE.set_max_level(fB[fX['max_level_limit']])
fb = fx[fX['start_order_type']]
fE.new_trade(SL_pip=fS, TP_pip=ft, start_order_type=fb)
fz = 0
fq("NewTradeStarted: current net profit=%f (price@%f)" %
(fs.get_net_profit(), fh.get_market_price()))
fQ.append(fs.get_net_profit())
fe = fs.show_details()
fv("Rounds of Tradings: %d\n" % fN)
fv('---')
fP['episode'].append(fa)
fP['trading_rounds'].append(fN)
for k in fe:
fP[k].append(fe[k])
'''
for k in output_record:
plt.plot(output_record['episode'], output_record[k])
plt.title(k)
plt.show()
'''
fC(fP).to_csv('test_detail-episode.csv', index=fp)