def sell(open_p,close_p,low_p,high_p,volume):
sell=[0]
rsi=RSI(close_p)
for i in range(1,len(close_p)):
if rsi[i]>50:
sell.append(1)
else:
sell.append(0)
return sell
def buy(open_p,close_p,low_p,high_p,volume):
buy=[0]
strend=supertrend(close_p,high_p,low_p)
rsi=RSI(close_p)
for i in range(1,len(close_p)):
if rsi[i]<50 :
buy.append(1)
else:
buy.append(0)
return buy
def seguimiento_boll(ohlc_5m, ohlc_1m, ohlc_10s, res_max_1min, res_min_1min, res_max_5min, res_min_5min, res_max_30m,
res_min_30m, sop_min_1min, sop_max_1min, sop_min_5min, sop_max_5min, sop_min_30m, sop_max_30m,
bollinger_1m, tipo_de_operacion, par, monto, client, request, contador):
print("seguimiento bollinger")
tiempo_de_operacion = "6"
if tipo_de_operacion == "ventac":
adx_1m = ADX(ohlc_1m)
rsi_1m = RSI(ohlc_1m, periodo=7)
ichimoku_10s = ichimoku(ohlc_10s)
tiempo_limite = time.time() + 600
while (adx_1m["ADX"].iloc[-1] < 32.0) and (rsi_1m.iloc[-1] < 70) and \
(ohlc_10s['c'].iloc[-1] > bollinger_1m["BB_dn"].iloc[-1]) and time.time() < tiempo_limite:
try:
ohlc_10s = pd.read_csv("datos_10s.csv", index_col="time")
ichimoku_10s = ichimoku(ohlc_10s)
except:
pass
starttime = time.time()
adx_10s = ADX(ohlc_10s)
print("posible venta")
print(f"precio: {ohlc_10s['c'].iloc[-1]}\n", f"tenkan-sen: {ichimoku_10s['tenkan-sen'].iloc[-1]}\n",
f"kijun-sen: {ichimoku_10s['kijun-sen'].iloc[-1]}")
if (ichimoku_10s["tenkan-sen"].iloc[-1] > ichimoku_10s["kijun-sen"].iloc[-1]) and \
(ichimoku_10s["Senkou span A"].iloc[-26] > ichimoku_10s["Senkou span B"].iloc[-26]) and \
(ohlc_10s['o'].iloc[-1] > ichimoku_10s["kijun-sen"].iloc[-1] > ohlc_10s['c'].iloc[-1] or
ohlc_10s['o'].iloc[-2] > ichimoku_10s["kijun-sen"].iloc[-2] > ohlc_10s['c'].iloc[-2]) and \
(ichimoku_10s["tenkan-sen"].iloc[-2] > ichimoku_10s["tenkan-sen"].iloc[-1]) and \
(adx_10s["ADX"].iloc[-2] > adx_10s["ADX"].iloc[-1]):
if contador.return_estrategia("venta", "estrategia4"):
ejecucion("ventac", par, tiempo_de_operacion, monto)
live_price_data = client.request(request)
precio = (float(live_price_data["prices"][0]["closeoutBid"])
+ float(live_price_data["prices"][0]["closeoutAsk"])) / 2
time.sleep(int(tiempo_de_operacion) * 60)
live_price_data = client.request(request)
precio2 = (float(live_price_data["prices"][0]["closeoutBid"])
+ float(live_price_data["prices"][0]["closeoutAsk"])) / 2
ichi_1m = ichimoku(ohlc_1m)
rsi_5m = RSI(ohlc_5m)
adx_5m = ADX(ohlc_5m)
with open("datos estrategia 4.txt", "at") as fichero_est_4:
fichero_est_4.write(f"\nprecio anterior: {ohlc_10s.iloc[-2]} \n"
f"precio actual: {ohlc_10s.iloc[-1]} \n"
f"ichimoku 1m sspan A: {ichi_1m['Senkou span A'].iloc[-2]}, {ichi_1m['Senkou span A'].iloc[-1]} \n"
f"ichimoku 1m sspan B: {ichi_1m['Senkou span B'].iloc[-2]}, {ichi_1m['Senkou span B'].iloc[-1]} \n"
f"ichimoku 1m sspan A -26: {ichi_1m['Senkou span A'].iloc[-26]} \n"
f"ichimoku 1m sspan B -26: {ichi_1m['Senkou span B'].iloc[-26]} \n"
f"tenkan-sen 1m: {ichi_1m['tenkan-sen'].iloc[-2]}, {ichi_1m['tenkan-sen'].iloc[-1]} \n"
f"kijun-sen 1m: {ichi_1m['kijun-sen'].iloc[-2]}, {ichi_1m['kijun-sen'].iloc[-1]} \n"
f"rsi 1m: {rsi_1m.iloc[-2]}, {rsi_1m.iloc[-1]} \n"
f"adx 1m: {adx_1m['ADX'].iloc[-2]}, {adx_1m['ADX'].iloc[-1]} \n"
f"DI+ 1m: {adx_1m['DI+'].iloc[-2]}, {adx_1m['DI+'].iloc[-1]} \n"
f"DI- 1m: {adx_1m['DI-'].iloc[-2]}, {adx_1m['DI-'].iloc[-1]} \n"
f"rsi 5m: {rsi_5m.iloc[-2]}, {rsi_5m.iloc[-1]} \n"
f"adx 5m: {adx_5m['ADX'].iloc[-2]}, {adx_5m['ADX'].iloc[-1]} \n"
f"DI+ 5m: {adx_5m['DI+'].iloc[-2]}, {adx_5m['DI+'].iloc[-1]} \n"
f"DI- 5m: {adx_5m['DI-'].iloc[-2]}, {adx_5m['DI-'].iloc[-1]} \n"
f"en resistencia 1m: {res_max_1min > ohlc_10s['c'].iloc[-1] > res_min_1min} \n"
f"en resistencia 5m: {res_max_5min > ohlc_10s['c'].iloc[-1] > res_min_5min} \n"
f"en resistencia 30m: {res_max_30m > ohlc_10s['c'].iloc[-1] > res_min_30m} \n"
f"sobre resistencia 1m: {res_max_1min <= ohlc_10s['c'].iloc[-1]} \n"
f"sobre resistencia 5m: {res_max_5min <= ohlc_10s['c'].iloc[-1]} \n"
f"venta \n")
if precio >= precio2:
print("operacion ganada, disminuyendo martingala")
cambio_de_monto(monto, "disminuir")
contador.sumar_estrategia("venta")
return
elif precio < precio2:
print("operacion perdida, aumentando martingala")
cambio_de_monto(monto, "aumentar")
tiempo_limite = time.time() + 600
else:
try:
if (f"{(int(time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(time.time()))[14:16]) - 1):02}" !=
ohlc_1m.iloc[-1].name[14:16]):
try:
ExtraccionOanda(client, 500, 'M1', par)
except Exception as e:
print(f"excepcion {e}: {type(e)}")
client = oandapyV20.API(
access_token="e51f5c80499fd16ae7e9ff6676b3c53f-3ac97247f6df3ad7b2b3731a4b1c2dc3",
environment="practice")
ohlc_1m = pd.read_csv("datos_M1.csv", index_col="time")
adx_1m = ADX(ohlc_1m)
rsi_1m = RSI(ohlc_1m, periodo=7)
res_max_1m, res_min_1min, sop_min_1m, sop_max_1min = calcular_rango_sop_res(ohlc_1m, 120)
except Exception as e:
print(f"excepcion {e}: {type(e)}")
print("error en lectura de datos m1 seguimiento ichimoku")
try:
if ((int(time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(time.time()))[15:16])) == 1 or (
int(time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(time.time()))[15:16])) == 6) and \
(ohlc_5m.iloc[-1].name[
14:16] != f"{int(time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(time.time()))[14:16]) - 1:02}"):
try:
ExtraccionOanda(client, 500, 'M5', par)
except Exception as e:
print(f"excepcion {e}: {type(e)}")
client = oandapyV20.API(
access_token="e51f5c80499fd16ae7e9ff6676b3c53f-3ac97247f6df3ad7b2b3731a4b1c2dc3",
environment="practice")
ohlc_5m = pd.read_csv("datos_M5.csv", index_col="time")
res_max_5min, res_min_5min, sop_min_5min, sop_max_5min = \
calcular_rango_sop_res(ohlc_5m, 50)
except Exception as e:
print(f"excepcion {e}: {type(e)}")
print("error en lectura de datos m5 seguimiento ichimoku")
time.sleep(10 - ((time.time() - starttime) % 10))
elif tipo_de_operacion == "comprac":
adx_1m = ADX(ohlc_1m)
rsi_1m = RSI(ohlc_1m, periodo=7)
ichimoku_10s = ichimoku(ohlc_10s)
tiempo_limite = time.time() + 600
while (adx_1m["ADX"].iloc[-1] < 32.0) and (rsi_1m.iloc[-1] < 70) and \
(ohlc_10s['c'].iloc[-1] < bollinger_1m["BB_up"].iloc[-1]) and time.time() < tiempo_limite:
try:
ohlc_10s = pd.read_csv("datos_10s.csv", index_col="time")
ichimoku_10s = ichimoku(ohlc_10s)
except:
pass
starttime = time.time()
adx_10s = ADX(ohlc_10s)
print("posible compra")
print(f"precio: {ohlc_10s['c'].iloc[-1]}\n", f"tenkan-sen: {ichimoku_10s['tenkan-sen'].iloc[-1]}\n",
f"kijun-sen: {ichimoku_10s['kijun-sen'].iloc[-1]}")
if (ichimoku_10s["tenkan-sen"].iloc[-1] < ichimoku_10s["kijun-sen"].iloc[-1]) and \
(ichimoku_10s["Senkou span A"].iloc[-26] < ichimoku_10s["Senkou span B"].iloc[-26]) and \
(ohlc_10s['o'].iloc[-1] < ichimoku_10s["kijun-sen"].iloc[-1] < ohlc_10s['c'].iloc[-1] or
ohlc_10s['o'].iloc[-2] < ichimoku_10s["kijun-sen"].iloc[-2] < ohlc_10s['c'].iloc[-2]) and \
(ichimoku_10s["tenkan-sen"].iloc[-2] < ichimoku_10s["tenkan-sen"].iloc[-1]) and \
(adx_10s["ADX"].iloc[-2] > adx_10s["ADX"].iloc[-1]):
if contador.return_estrategia("compra", "estrategia4"):
ejecucion("comprac", par, tiempo_de_operacion, monto)
live_price_data = client.request(request)
precio = (float(live_price_data["prices"][0]["closeoutBid"])
+ float(live_price_data["prices"][0]["closeoutAsk"])) / 2
time.sleep(int(tiempo_de_operacion) * 60)
live_price_data = client.request(request)
precio2 = (float(live_price_data["prices"][0]["closeoutBid"])
+ float(live_price_data["prices"][0]["closeoutAsk"])) / 2
ichi_1m = ichimoku(ohlc_1m)
rsi_5m = RSI(ohlc_5m)
adx_5m = ADX(ohlc_5m)
with open("datos estrategia 4.txt", "at") as fichero_est_4:
fichero_est_4.write(f"\nprecio anterior: {ohlc_10s.iloc[-2]} \n"
f"precio actual: {ohlc_10s.iloc[-1]} \n"
f"ichimoku 1m sspan A: {ichi_1m['Senkou span A'].iloc[-2]}, {ichi_1m['Senkou span A'].iloc[-1]} \n"
f"ichimoku 1m sspan B: {ichi_1m['Senkou span B'].iloc[-2]}, {ichi_1m['Senkou span B'].iloc[-1]} \n"
f"ichimoku 1m sspan A -26: {ichi_1m['Senkou span A'].iloc[-26]} \n"
f"ichimoku 1m sspan B -26: {ichi_1m['Senkou span B'].iloc[-26]} \n"
f"tenkan-sen 1m: {ichi_1m['tenkan-sen'].iloc[-2]}, {ichi_1m['tenkan-sen'].iloc[-1]} \n"
f"kijun-sen 1m: {ichi_1m['kijun-sen'].iloc[-2]}, {ichi_1m['kijun-sen'].iloc[-1]} \n"
f"rsi 1m: {rsi_1m.iloc[-2]}, {rsi_1m.iloc[-1]} \n"
f"adx 1m: {adx_1m['ADX'].iloc[-2]}, {adx_1m['ADX'].iloc[-1]} \n"
f"DI+ 1m: {adx_1m['DI+'].iloc[-2]}, {adx_1m['DI+'].iloc[-1]} \n"
f"DI- 1m: {adx_1m['DI-'].iloc[-2]}, {adx_1m['DI-'].iloc[-1]} \n"
f"rsi 5m: {rsi_5m.iloc[-2]}, {rsi_5m.iloc[-1]} \n"
f"adx 5m: {adx_5m['ADX'].iloc[-2]}, {adx_5m['ADX'].iloc[-1]} \n"
f"DI+ 5m: {adx_5m['DI+'].iloc[-2]}, {adx_5m['DI+'].iloc[-1]} \n"
f"DI- 5m: {adx_5m['DI-'].iloc[-2]}, {adx_5m['DI-'].iloc[-1]} \n"
f"en soporte 1m: {sop_min_1min < ohlc_10s['c'].iloc[-1] < sop_max_1min} \n"
f"en soporte 5m: {sop_min_5min < ohlc_10s['c'].iloc[-1] < sop_max_5min} \n"
f"en soporte 30m: {sop_min_30m < ohlc_10s['c'].iloc[-1] < sop_max_30m} \n"
f"debajo soporte 1m: {ohlc_10s['c'].iloc[-1] <= sop_min_1min} \n"
f"debajo soporte 5m: {ohlc_10s['c'].iloc[-1] <= sop_min_5min} \n"
f"compra \n")
if precio <= precio2:
print("operacion ganada, disminuyendo martingala")
cambio_de_monto(monto, "disminuir")
contador.sumar_estrategia("compra")
return
elif precio > precio2:
print("operacion perdida, aumentando martingala")
cambio_de_monto(monto, "aumentar")
tiempo_limite = time.time() + 600
else:
try:
if (f"{(int(time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(time.time()))[14:16]) - 1):02}" !=
ohlc_1m.iloc[-1].name[14:16]):
try:
ExtraccionOanda(client, 500, 'M1', par)
except Exception as e:
print(f"excepcion {e}: {type(e)}")
client = oandapyV20.API(
access_token="e51f5c80499fd16ae7e9ff6676b3c53f-3ac97247f6df3ad7b2b3731a4b1c2dc3",
environment="practice")
ohlc_1m = pd.read_csv("datos_M1.csv", index_col="time")
adx_1m = ADX(ohlc_1m)
rsi_1m = RSI(ohlc_1m, periodo=7)
res_max_1m, res_min_1min, sop_min_1m, sop_max_1min = calcular_rango_sop_res(ohlc_1m, 120)
except Exception as e:
print(f"excepcion {e}: {type(e)}")
print("error en lectura de datos m1 seguimiento ichimoku")
try:
if ((int(time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(time.time()))[15:16])) == 1 or (
int(time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(time.time()))[15:16])) == 6) and \
(ohlc_5m.iloc[-1].name[
14:16] != f"{int(time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(time.time()))[14:16]) - 1:02}"):
try:
ExtraccionOanda(client, 500, 'M5', par)
except Exception as e:
print(f"excepcion {e}: {type(e)}")
client = oandapyV20.API(
access_token="e51f5c80499fd16ae7e9ff6676b3c53f-3ac97247f6df3ad7b2b3731a4b1c2dc3",
environment="practice")
ohlc_5m = pd.read_csv("datos_M5.csv", index_col="time")
res_max_5min, res_min_5min, sop_min_5min, sop_max_5min = \
calcular_rango_sop_res(ohlc_5m, 50)
except Exception as e:
print(f"excepcion {e}: {type(e)}")
print("error en lectura de datos m5 seguimiento ichimoku")
time.sleep(10 - ((time.time() - starttime) % 10))
def trials(mu, theta2, lmbd, sigma2, EMitr, k, n, max_capital, num_agents,
mode, err, alpha, trl):
rng = np.random.RandomState(trl)
idx = rng.randint(0, n, size=(k))
beta = np.zeros((n, 1))
beta[idx, :] = mu + np.sqrt(theta2) * rng.randn(k, 1)
# #%% LATSI:
func_class = LATSI(beta, mu, theta2, sigma2, lmbd, EMitr, err, num_agents,
alpha, trl)
worker_manager = WorkerManager(func_caller=func_class,
worker_ids=num_agents,
poll_time=1e-15,
trialnum=trl)
options = Namespace(max_num_steps=max_capital,
num_init_evals=num_agents,
num_workers=num_agents,
mode=mode,
GP=func_class)
beta_hats = Bayesian_optimizer(worker_manager, func_class,
options).optimize(max_capital)
full_recovery_rate_latsi = []
partial_recovery_rate_latsi = []
for i in range(max_capital):
beta_hat = beta_hats[i]
est = (np.round(beta_hat) > (mu / 2))
real = (beta > 0)
partial_recovery_rate_latsi.append(np.sum(est == real) / (n))
correct_LATSI = 0.0
if (np.all(est == real)):
correct_LATSI = 1.0
full_recovery_rate_latsi.append(correct_LATSI)
# # # #%% SPATS:
func_class = SPATS(beta, mu, theta2, sigma2, lmbd, EMitr, num_agents, trl)
worker_manager = WorkerManager(func_caller=func_class,
worker_ids=num_agents,
poll_time=1e-15,
trialnum=trl)
options = Namespace(max_num_steps=max_capital,
num_init_evals=num_agents,
num_workers=num_agents,
mode=mode,
GP=func_class)
beta_hats = Bayesian_optimizer(worker_manager, func_class,
options).optimize(max_capital)
full_recovery_rate_spats = []
partial_recovery_rate_spats = []
for i in range(max_capital):
beta_hat = beta_hats[i]
est = (np.round(beta_hat) > (mu / 2))
real = (beta > 0)
partial_recovery_rate_spats.append(np.sum(est == real) / (n))
correct_spats = 0.0
if (np.all(est == real)):
correct_spats = 1.0
full_recovery_rate_spats.append(correct_spats)
# #%% RSI:
func_class2 = RSI(beta, mu, theta2, sigma2, lmbd, EMitr, err, trl)
worker_manager = WorkerManager(func_caller=func_class2,
worker_ids=num_agents,
poll_time=1e-15,
trialnum=trl)
options = Namespace(max_num_steps=max_capital,
num_init_evals=num_agents,
num_workers=num_agents,
mode=mode,
GP=func_class2)
beta_hats = Bayesian_optimizer(worker_manager, func_class2,
options).optimize(max_capital)
full_recovery_rate_rsi = []
partial_recovery_rate_rsi = []
for i in range(max_capital):
beta_hat = beta_hats[i]
est = (np.round(beta_hat) > (mu / 2))
real = (beta > 0)
partial_recovery_rate_rsi.append(np.sum(est == real) / (n))
correct_rsi = 0.0
if (np.all(est == real)):
correct_rsi = 1.0
full_recovery_rate_rsi.append(correct_rsi)
return [
full_recovery_rate_spats, full_recovery_rate_rsi,
full_recovery_rate_latsi, partial_recovery_rate_spats,
partial_recovery_rate_rsi, partial_recovery_rate_latsi
]
def seguimiento_ichimoku2(ohlc_5m, ohlc_1m, ohlc_10s, par, tipo_de_operacion, res_max_30m, res_min_30m, sop_min_30m,
sop_max_30m, res_max_5m, res_min_5m, sop_min_5m, sop_max_5m, res_max_1m, res_min_1m,
sop_min_1m, sop_max_1m, monto, client, request, contador):
print("estamos en seguimiento")
tiempo_de_operacion = "3"
if tipo_de_operacion == "compraf":
adx_5m = ADX(ohlc_5m)
rsi_5m = RSI(ohlc_5m)
ichimoku_1m = ichimoku(ohlc_1m)
tiempo_limite = time.time() + 600
while (adx_5m["ADX"].iloc[-1] > 20.0) and (rsi_5m.iloc[-1] > 30.0) and \
(ichimoku_1m["Senkou span A"].iloc[-26] < ohlc_10s['c'].iloc[-1] > ichimoku_1m["Senkou span B"].iloc[
-26]) and (time.time() < tiempo_limite):
starttime = time.time()
try:
ohlc_10s = pd.read_csv("datos_10s.csv", index_col="time")
res_max_10s, res_min_10s, sop_min_10s, sop_max_10s = calcular_rango_sop_res(ohlc_10s, 30)
ichimoku_10s = ichimoku(ohlc_10s)
except Exception as e:
print(f"excepcion {e}: {type(e)}")
print("reintentando lectura ohlc_10s")
ohlc_10s = pd.read_csv("datos_10s.csv", index_col="time")
res_max_10s, res_min_10s, sop_min_10s, sop_max_10s = calcular_rango_sop_res(ohlc_10s, 30)
ichimoku_10s = ichimoku(ohlc_10s)
print("posible compra, low 10s: ", ohlc_10s['l'].iloc[-1], " soporte max 10s: ", sop_max_10s)
if (ohlc_10s['l'].iloc[-1] <= sop_max_10s or ohlc_10s['l'].iloc[-2] <= sop_max_10s) or \
(ohlc_10s['l'].iloc[-1] <= sop_max_1m):
while ohlc_10s['c'].iloc[-1] < ichimoku_10s['kijun-sen'].iloc[-1] or \
ohlc_10s['c'].iloc[-1] < ichimoku_10s['tenkan-sen'].iloc[-1]:
try:
ohlc_10s = pd.read_csv("datos_10s.csv", index_col="time")
ichimoku_10s = ichimoku(ohlc_10s)
res_max_10s, res_min_10s, sop_min_10s, sop_max_10s = calcular_rango_sop_res(ohlc_10s, 30)
time.sleep(10)
except Exception as e:
print(f"excepcion {e}: {type(e)}")
print("reintentando lectura ohlc_10s")
ohlc_10s = pd.read_csv("datos_10s.csv", index_col="time")
ichimoku_10s = ichimoku(ohlc_10s)
res_max_10s, res_min_10s, sop_min_10s, sop_max_10s = calcular_rango_sop_res(ohlc_10s, 30)
if (ichimoku_10s["Senkou span B"].iloc[-26] > ohlc_10s['c'].iloc[-1] <
ichimoku_10s["Senkou span A"].iloc[-26] <
ichimoku_10s["Senkou span B"].iloc[-26]) \
and (ichimoku_10s['tenkan-sen'].iloc[-2] < ichimoku_10s['tenkan-sen'].iloc[-1]) \
and (ohlc_10s['o'].iloc[-1] < ichimoku_10s['kijun-sen'].iloc[-1] < ohlc_10s['c'].iloc[-1]):
if contador.return_estrategia("compra", "estrategia3") < 2:
ejecucion(tipo_de_operacion, par, tiempo_de_operacion, monto)
live_price_data = client.request(request)
precio = (float(live_price_data["prices"][0]["closeoutBid"])
+ float(live_price_data["prices"][0]["closeoutAsk"])) / 2
if (f"{(int(time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(time.time()))[14:16]) - 1):02}" !=
ohlc_1m.iloc[-1].name[14:16]):
try:
ExtraccionOanda(client, 500, 'M1', par)
except Exception as e:
print(f"excepcion {e}: {type(e)}")
client = oandapyV20.API(
access_token="e51f5c80499fd16ae7e9ff6676b3c53f-3ac97247f6df3ad7b2b3731a4b1c2dc3",
environment="practice")
if ((int(time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(time.time()))[15:16])) == 1 or (
int(time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(time.time()))[15:16])) == 6) and \
(ohlc_5m.iloc[-1].name[
14:16] != f"{int(time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(time.time()))[14:16]) - 1:02}"):
try:
ExtraccionOanda(client, 500, 'M5', par)
except Exception as e:
print(f"excepcion {e}: {type(e)}")
client = oandapyV20.API(
access_token="e51f5c80499fd16ae7e9ff6676b3c53f-3ac97247f6df3ad7b2b3731a4b1c2dc3",
environment="practice")
time.sleep(int(tiempo_de_operacion) * 60)
live_price_data = client.request(request)
precio2 = (float(live_price_data["prices"][0]["closeoutBid"])
+ float(live_price_data["prices"][0]["closeoutAsk"])) / 2
ohlc_1m = pd.read_csv("datos_M1.csv", index_col="time")
ichimoku_1m = ichimoku(ohlc_1m)
adx_1m = ADX(ohlc_1m)
rsi_1m = RSI(ohlc_1m)
ohlc_5m = pd.read_csv("datos_M5.csv", index_col="time")
adx_5m = ADX(ohlc_5m)
rsi_5m = RSI(ohlc_5m)
ichi_5m = ichimoku(ohlc_5m)
with open("datos estrategia 3.txt", "at") as fichero_est_3:
fichero_est_3.write(f"\nprecio anterior: {ohlc_10s.iloc[-2]} \n"
f"precio actual: {ohlc_10s.iloc[-1]} \n"
f"adx 5m: {adx_5m['ADX'].iloc[-2]}, {adx_5m['ADX'].iloc[-1]} \n"
f"DI+ 5m: {adx_5m['DI+'].iloc[-2]}, {adx_5m['DI+'].iloc[-1]} \n"
f"DI- 5m: {adx_5m['DI-'].iloc[-2]}, {adx_5m['DI-'].iloc[-1]} \n"
f"rsi 5m: {rsi_5m.iloc[-2]}, {rsi_5m.iloc[-1]} \n"
f"adx 1m: {adx_1m['ADX'].iloc[-2]}, {adx_1m['ADX'].iloc[-1]} \n"
f"DI+ 1m: {adx_1m['DI+'].iloc[-2]}, {adx_1m['DI+'].iloc[-1]} \n"
f"DI- 1m: {adx_1m['DI-'].iloc[-2]}, {adx_1m['DI-'].iloc[-1]} \n"
f"rsi 1m: {rsi_1m.iloc[-2]}, {rsi_1m.iloc[-1]} \n"
f"ichimoku 1m sspan A: {ichimoku_1m['Senkou span A'].iloc[-2]}, {ichimoku_1m['Senkou span A'].iloc[-1]} \n"
f"ichimoku 1m sspan B: {ichimoku_1m['Senkou span B'].iloc[-2]}, {ichimoku_1m['Senkou span B'].iloc[-1]} \n"
f"ichimoku tenkan 1m: {ichimoku_1m['tenkan-sen'].iloc[-2]}, {ichimoku_1m['tenkan-sen'].iloc[-1]} \n"
f"ichimoku kijun 1m: {ichimoku_1m['kijun-sen'].iloc[-2]}, {ichimoku_1m['kijun-sen'].iloc[-1]} \n"
f"ichimoku 10s sspan A: {ichimoku_10s['Senkou span A'].iloc[-2]}, {ichimoku_10s['Senkou span A'].iloc[-1]} \n"
f"ichimoku 10s sspan B: {ichimoku_10s['Senkou span B'].iloc[-2]}, {ichimoku_10s['Senkou span B'].iloc[-1]} \n"
f"ichimoku 10s sspan A -26: {ichimoku_10s['Senkou span A'].iloc[-26]} \n"
f"ichimoku 10s sspan B -26: {ichimoku_10s['Senkou span B'].iloc[-26]} \n"
f"tenkan-sen 10s: {ichimoku_10s['tenkan-sen'].iloc[-2]}, {ichimoku_10s['tenkan-sen'].iloc[-1]} \n"
f"kijun-sen 10s: {ichimoku_10s['kijun-sen'].iloc[-2]}, {ichimoku_10s['kijun-sen'].iloc[-1]} \n"
f"compra \n")
if precio <= precio2:
print("operacion ganada, disminuyendo martingala")
cambio_de_monto(monto, "disminuir")
contador.sumar_estrategia("compra")
return
elif precio > precio2:
print("operacion perdida, aumentando martingala")
cambio_de_monto(monto, "aumentar")
tiempo_limite = time.time() + 600
elif (ichimoku_10s["Senkou span B"].iloc[-26] < ohlc_10s['c'].iloc[-1] > ichimoku_10s["Senkou span A"].iloc[-26] >
ichimoku_10s["Senkou span B"].iloc[-26]) \
and (ichimoku_10s['tenkan-sen'].iloc[-2] <= ichimoku_10s['tenkan-sen'].iloc[-1]) \
and (ohlc_10s['o'].iloc[-1] < ichimoku_10s['tenkan-sen'].iloc[-1] < ohlc_10s['c'].iloc[-1] or
ohlc_10s['o'].iloc[-1] < ichimoku_10s['kijun-sen'].iloc[-1] < ohlc_10s['c'].iloc[-1]):
if contador.return_estrategia("compra", "estrategia3") < 2:
ejecucion(tipo_de_operacion, par, tiempo_de_operacion, monto)
live_price_data = client.request(request)
precio = (float(live_price_data["prices"][0]["closeoutBid"])
+ float(live_price_data["prices"][0]["closeoutAsk"])) / 2
if (f"{(int(time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(time.time()))[14:16]) - 1):02}" !=
ohlc_1m.iloc[-1].name[14:16]):
try:
ExtraccionOanda(client, 500, 'M1', par)
except Exception as e:
print(f"excepcion {e}: {type(e)}")
client = oandapyV20.API(
access_token="e51f5c80499fd16ae7e9ff6676b3c53f-3ac97247f6df3ad7b2b3731a4b1c2dc3",
environment="practice")
if ((int(time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(time.time()))[15:16])) == 1 or (
int(time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(time.time()))[15:16])) == 6) and \
(ohlc_5m.iloc[-1].name[
14:16] != f"{int(time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(time.time()))[14:16]) - 1:02}"):
try:
ExtraccionOanda(client, 500, 'M5', par)
except Exception as e:
print(f"excepcion {e}: {type(e)}")
client = oandapyV20.API(
access_token="e51f5c80499fd16ae7e9ff6676b3c53f-3ac97247f6df3ad7b2b3731a4b1c2dc3",
environment="practice")
time.sleep(int(tiempo_de_operacion) * 60)
live_price_data = client.request(request)
precio2 = (float(live_price_data["prices"][0]["closeoutBid"])
+ float(live_price_data["prices"][0]["closeoutAsk"])) / 2
ohlc_1m = pd.read_csv("datos_M1.csv", index_col="time")
ichimoku_1m = ichimoku(ohlc_1m)
adx_1m = ADX(ohlc_1m)
rsi_1m = RSI(ohlc_1m)
ohlc_5m = pd.read_csv("datos_M5.csv", index_col="time")
adx_5m = ADX(ohlc_5m)
rsi_5m = RSI(ohlc_5m)
ichi_5m = ichimoku(ohlc_5m)
with open("datos estrategia 3.txt", "at") as fichero_est_3:
fichero_est_3.write(f"\nprecio anterior: {ohlc_10s.iloc[-2]} \n"
f"precio actual: {ohlc_10s.iloc[-1]} \n"
f"adx 5m: {adx_5m['ADX'].iloc[-2]}, {adx_5m['ADX'].iloc[-1]} \n"
f"DI+ 5m: {adx_5m['DI+'].iloc[-2]}, {adx_5m['DI+'].iloc[-1]} \n"
f"DI- 5m: {adx_5m['DI-'].iloc[-2]}, {adx_5m['DI-'].iloc[-1]} \n"
f"rsi 5m: {rsi_5m.iloc[-2]}, {rsi_5m.iloc[-1]} \n"
f"adx 1m: {adx_1m['ADX'].iloc[-2]}, {adx_1m['ADX'].iloc[-1]} \n"
f"DI+ 1m: {adx_1m['DI+'].iloc[-2]}, {adx_1m['DI+'].iloc[-1]} \n"
f"DI- 1m: {adx_1m['DI-'].iloc[-2]}, {adx_1m['DI-'].iloc[-1]} \n"
f"rsi 1m: {rsi_1m.iloc[-2]}, {rsi_1m.iloc[-1]} \n"
f"ichimoku 1m sspan A: {ichimoku_1m['Senkou span A'].iloc[-2]}, {ichimoku_1m['Senkou span A'].iloc[-1]} \n"
f"ichimoku 1m sspan B: {ichimoku_1m['Senkou span B'].iloc[-2]}, {ichimoku_1m['Senkou span B'].iloc[-1]} \n"
f"ichimoku tenkan 1m: {ichimoku_1m['tenkan-sen'].iloc[-2]}, {ichimoku_1m['tenkan-sen'].iloc[-1]} \n"
f"ichimoku kijun 1m: {ichimoku_1m['kijun-sen'].iloc[-2]}, {ichimoku_1m['kijun-sen'].iloc[-1]} \n"
f"ichimoku 10s sspan A: {ichimoku_10s['Senkou span A'].iloc[-2]}, {ichimoku_10s['Senkou span A'].iloc[-1]} \n"
f"ichimoku 10s sspan B: {ichimoku_10s['Senkou span B'].iloc[-2]}, {ichimoku_10s['Senkou span B'].iloc[-1]} \n"
f"ichimoku 10s sspan A -26: {ichimoku_10s['Senkou span A'].iloc[-26]} \n"
f"ichimoku 10s sspan B -26: {ichimoku_10s['Senkou span B'].iloc[-26]} \n"
f"tenkan-sen 10s: {ichimoku_10s['tenkan-sen'].iloc[-2]}, {ichimoku_10s['tenkan-sen'].iloc[-1]} \n"
f"kijun-sen 10s: {ichimoku_10s['kijun-sen'].iloc[-2]}, {ichimoku_10s['kijun-sen'].iloc[-1]} \n"
f"compra \n")
if precio <= precio2:
print("operacion ganada, disminuyendo martingala")
cambio_de_monto(monto, "disminuir")
contador.sumar_estrategia("compra")
return
elif precio > precio2:
print("operacion perdida, aumentando martingala")
cambio_de_monto(monto, "aumentar")
tiempo_limite = time.time() + 600
try:
if (f"{(int(time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(time.time()))[14:16]) - 1):02}" !=
ohlc_1m.iloc[-1].name[14:16]):
try:
ExtraccionOanda(client, 500, 'M1', par)
except Exception as e:
print(f"excepcion {e}: {type(e)}")
client = oandapyV20.API(
access_token="e51f5c80499fd16ae7e9ff6676b3c53f-3ac97247f6df3ad7b2b3731a4b1c2dc3",
environment="practice")
ohlc_1m = pd.read_csv("datos_M1.csv", index_col="time")
ichimoku_1m = ichimoku(ohlc_1m)
res_max_1m, res_min_1m, sop_min_1m, sop_max_1m = calcular_rango_sop_res(ohlc_1m, 10)
if ((int(time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(time.time()))[15:16])) == 1 or (
int(time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(time.time()))[15:16])) == 6) and \
(ohlc_5m.iloc[-1].name[
14:16] != f"{int(time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(time.time()))[14:16]) - 1:02}"):
try:
ExtraccionOanda(client, 500, 'M5', par)
except Exception as e:
print(f"excepcion {e}: {type(e)}")
client = oandapyV20.API(
access_token="e51f5c80499fd16ae7e9ff6676b3c53f-3ac97247f6df3ad7b2b3731a4b1c2dc3",
environment="practice")
ohlc_5m = pd.read_csv("datos_M5.csv", index_col="time")
res_max_5m, res_min_5m, sop_min_5m, sop_max_5m = calcular_rango_sop_res(ohlc_5m, 50)
adx_5m = ADX(ohlc_5m)
rsi_5m = RSI(ohlc_5m)
except Exception as e:
print(f"excepcion {e}: {type(e)}")
print("hubo un error en la lectura de datos 1m o 5m en seguimiento ichimoku 2")
time.sleep(10 - ((time.time() - starttime) % 10))
if res_max_5m > ohlc_10s['c'].iloc[-1] > res_min_5m or res_max_30m > ohlc_10s['c'].iloc[-1] > res_min_30m:
print("se sale del seguimiento porque hay una resistencia cercana")
else:
print("se sale del seguimiento porque se ejecutó operacion o",
adx_5m["ADX"].iloc[-1] > 20.0, rsi_5m.iloc[-1] > 30.0,
ichimoku_1m["Senkou span A"].iloc[-26] < ohlc_10s['c'].iloc[-1] >
ichimoku_1m["Senkou span B"].iloc[-26])
elif tipo_de_operacion == "ventaf":
adx_5m = ADX(ohlc_5m)
rsi_5m = RSI(ohlc_5m)
ichimoku_1m = ichimoku(ohlc_1m)
tiempo_limite = time.time() + 600
while (adx_5m["ADX"].iloc[-1] > 20.0) \
and (rsi_5m.iloc[-1] < 70.0) and (ichimoku_1m["Senkou span A"].iloc[-26] > ohlc_10s['c'].iloc[-1] <
ichimoku_1m["Senkou span B"].iloc[-26]) and (time.time() < tiempo_limite):
starttime = time.time()
try:
ohlc_10s = pd.read_csv("datos_10s.csv", index_col="time")
res_max_10s, res_min_10s, sop_min_10s, sop_max_10s = calcular_rango_sop_res(ohlc_10s, 30)
ichimoku_10s = ichimoku(ohlc_10s)
except Exception as e:
print(f"excepcion {e}: {type(e)}")
print("reintentando lectura ohlc_10s")
ohlc_10s = pd.read_csv("datos_10s.csv", index_col="time")
res_max_10s, res_min_10s, sop_min_10s, sop_max_10s = calcular_rango_sop_res(ohlc_10s, 30)
ichimoku_10s = ichimoku(ohlc_10s)
print("posible venta, high 10s: ", ohlc_10s['h'].iloc[-1], " resistencia menor 10s: ", res_min_10s)
if (ohlc_10s['h'].iloc[-1] >= res_min_10s or ohlc_10s['h'].iloc[-2] >= res_min_10s) or \
(ohlc_10s['h'].iloc[-1] >= res_min_1m):
while ohlc_10s['c'].iloc[-1] > ichimoku_10s['kijun-sen'].iloc[-1] or \
ohlc_10s['c'].iloc[-1] > ichimoku_10s['tenkan-sen'].iloc[-1]:
try:
ohlc_10s = pd.read_csv("datos_10s.csv", index_col="time")
ichimoku_10s = ichimoku(ohlc_10s)
res_max_10s, res_min_10s, sop_min_10s, sop_max_10s = calcular_rango_sop_res(ohlc_10s, 30)
time.sleep(10)
except Exception as e:
print(f"excepcion {e}: {type(e)}")
print("reintentando lectura ohlc_10s")
ohlc_10s = pd.read_csv("datos_10s.csv", index_col="time")
ichimoku_10s = ichimoku(ohlc_10s)
res_max_10s, res_min_10s, sop_min_10s, sop_max_10s = calcular_rango_sop_res(ohlc_10s, 30)
if (ichimoku_10s["Senkou span B"].iloc[-26] < ohlc_10s['c'].iloc[-1] > ichimoku_10s["Senkou span A"].iloc[-26] >
ichimoku_10s["Senkou span B"].iloc[-26]) \
and (ichimoku_10s['tenkan-sen'].iloc[-2] > ichimoku_10s['tenkan-sen'].iloc[-1]) \
and (ohlc_10s['o'].iloc[-1] > ichimoku_10s['kijun-sen'].iloc[-1] > ohlc_10s['c'].iloc[-1]):
if contador.return_estrategia("venta", "estrategia3"):
ejecucion(tipo_de_operacion, par, tiempo_de_operacion, monto)
live_price_data = client.request(request)
precio = (float(live_price_data["prices"][0]["closeoutBid"])
+ float(live_price_data["prices"][0]["closeoutAsk"])) / 2
if (f"{(int(time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(time.time()))[14:16]) - 1):02}" !=
ohlc_1m.iloc[-1].name[14:16]):
try:
ExtraccionOanda(client, 500, 'M1', par)
except Exception as e:
print(f"excepcion {e}: {type(e)}")
client = oandapyV20.API(
access_token="e51f5c80499fd16ae7e9ff6676b3c53f-3ac97247f6df3ad7b2b3731a4b1c2dc3",
environment="practice")
if ((int(time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(time.time()))[15:16])) == 1 or (
int(time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(time.time()))[15:16])) == 6) and \
(ohlc_5m.iloc[-1].name[
14:16] != f"{int(time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(time.time()))[14:16]) - 1:02}"):
try:
ExtraccionOanda(client, 500, 'M5', par)
except Exception as e:
print(f"excepcion {e}: {type(e)}")
client = oandapyV20.API(
access_token="e51f5c80499fd16ae7e9ff6676b3c53f-3ac97247f6df3ad7b2b3731a4b1c2dc3",
environment="practice")
time.sleep(int(tiempo_de_operacion) * 60)
live_price_data = client.request(request)
precio2 = (float(live_price_data["prices"][0]["closeoutBid"])
+ float(live_price_data["prices"][0]["closeoutAsk"])) / 2
ohlc_1m = pd.read_csv("datos_M1.csv", index_col="time")
ichimoku_1m = ichimoku(ohlc_1m)
adx_1m = ADX(ohlc_1m)
rsi_1m = RSI(ohlc_1m)
ohlc_5m = pd.read_csv("datos_M5.csv", index_col="time")
adx_5m = ADX(ohlc_5m)
rsi_5m = RSI(ohlc_5m)
ichi_5m = ichimoku(ohlc_5m)
with open("datos estrategia 3.txt", "at") as fichero_est_3:
fichero_est_3.write(f"\nprecio anterior: {ohlc_10s.iloc[-2]} \n"
f"precio actual: {ohlc_10s.iloc[-1]} \n"
f"adx 5m: {adx_5m['ADX'].iloc[-2]}, {adx_5m['ADX'].iloc[-1]} \n"
f"DI+ 5m: {adx_5m['DI+'].iloc[-2]}, {adx_5m['DI+'].iloc[-1]} \n"
f"DI- 5m: {adx_5m['DI-'].iloc[-2]}, {adx_5m['DI-'].iloc[-1]} \n"
f"rsi 5m: {rsi_5m.iloc[-2]}, {rsi_5m.iloc[-1]} \n"
f"adx 1m: {adx_1m['ADX'].iloc[-2]}, {adx_1m['ADX'].iloc[-1]} \n"
f"DI+ 1m: {adx_1m['DI+'].iloc[-2]}, {adx_1m['DI+'].iloc[-1]} \n"
f"DI- 1m: {adx_1m['DI-'].iloc[-2]}, {adx_1m['DI-'].iloc[-1]} \n"
f"rsi 1m: {rsi_1m.iloc[-2]}, {rsi_1m.iloc[-1]} \n"
f"ichimoku 1m sspan A: {ichimoku_1m['Senkou span A'].iloc[-2]}, {ichimoku_1m['Senkou span A'].iloc[-1]} \n"
f"ichimoku 1m sspan B: {ichimoku_1m['Senkou span B'].iloc[-2]}, {ichimoku_1m['Senkou span B'].iloc[-1]} \n"
f"ichimoku tenkan 1m: {ichimoku_1m['tenkan-sen'].iloc[-2]}, {ichimoku_1m['tenkan-sen'].iloc[-1]} \n"
f"ichimoku kijun 1m: {ichimoku_1m['kijun-sen'].iloc[-2]}, {ichimoku_1m['kijun-sen'].iloc[-1]} \n"
f"ichimoku 10s sspan A: {ichimoku_10s['Senkou span A'].iloc[-2]}, {ichimoku_10s['Senkou span A'].iloc[-1]} \n"
f"ichimoku 10s sspan B: {ichimoku_10s['Senkou span B'].iloc[-2]}, {ichimoku_10s['Senkou span B'].iloc[-1]} \n"
f"ichimoku 10s sspan A -26: {ichimoku_10s['Senkou span A'].iloc[-26]} \n"
f"ichimoku 10s sspan B -26: {ichimoku_10s['Senkou span B'].iloc[-26]} \n"
f"tenkan-sen 10s: {ichimoku_10s['tenkan-sen'].iloc[-2]}, {ichimoku_10s['tenkan-sen'].iloc[-1]} \n"
f"kijun-sen 10s: {ichimoku_10s['kijun-sen'].iloc[-2]}, {ichimoku_10s['kijun-sen'].iloc[-1]} \n"
f"venta \n")
if precio >= precio2:
print("operacion ganada, disminuyendo martingala")
cambio_de_monto(monto, "disminuir")
contador.sumar_estrategia("venta")
return
elif precio < precio2:
print("operacion perdida, aumentando martingala")
cambio_de_monto(monto, "aumentar")
tiempo_limite = time.time() + 600
elif (ichimoku_10s["Senkou span B"].iloc[-26] > ohlc_10s['c'].iloc[-1] <
ichimoku_10s["Senkou span A"].iloc[-26] < ichimoku_10s["Senkou span B"].iloc[-26]) \
and (ichimoku_10s['tenkan-sen'].iloc[-2] >= ichimoku_10s['tenkan-sen'].iloc[-1]) \
and (ohlc_10s['o'].iloc[-1] > ichimoku_10s['tenkan-sen'].iloc[-1] > ohlc_10s['c'].iloc[-1] or
ohlc_10s['o'].iloc[-1] > ichimoku_10s['kijun-sen'].iloc[-1] > ohlc_10s['c'].iloc[-1]):
if contador.return_estrategia("venta", "estrategia3"):
ejecucion(tipo_de_operacion, par, tiempo_de_operacion, monto)
live_price_data = client.request(request)
precio = (float(live_price_data["prices"][0]["closeoutBid"])
+ float(live_price_data["prices"][0]["closeoutAsk"])) / 2
if (f"{(int(time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(time.time()))[14:16]) - 1):02}" !=
ohlc_1m.iloc[-1].name[14:16]):
try:
ExtraccionOanda(client, 500, 'M1', par)
except Exception as e:
print(f"excepcion {e}: {type(e)}")
client = oandapyV20.API(
access_token="e51f5c80499fd16ae7e9ff6676b3c53f-3ac97247f6df3ad7b2b3731a4b1c2dc3",
environment="practice")
if ((int(time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(time.time()))[15:16])) == 1 or (
int(time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(time.time()))[15:16])) == 6) and \
(ohlc_5m.iloc[-1].name[
14:16] != f"{int(time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(time.time()))[14:16]) - 1:02}"):
try:
ExtraccionOanda(client, 500, 'M5', par)
except Exception as e:
print(f"excepcion {e}: {type(e)}")
client = oandapyV20.API(
access_token="e51f5c80499fd16ae7e9ff6676b3c53f-3ac97247f6df3ad7b2b3731a4b1c2dc3",
environment="practice")
time.sleep(int(tiempo_de_operacion) * 60)
live_price_data = client.request(request)
precio2 = (float(live_price_data["prices"][0]["closeoutBid"])
+ float(live_price_data["prices"][0]["closeoutAsk"])) / 2
ohlc_1m = pd.read_csv("datos_M1.csv", index_col="time")
ichimoku_1m = ichimoku(ohlc_1m)
adx_1m = ADX(ohlc_1m)
rsi_1m = RSI(ohlc_1m)
ohlc_5m = pd.read_csv("datos_M5.csv", index_col="time")
adx_5m = ADX(ohlc_5m)
rsi_5m = RSI(ohlc_5m)
ichi_5m = ichimoku(ohlc_5m)
with open("datos estrategia 3.txt", "at") as fichero_est_3:
fichero_est_3.write(f"\nprecio anterior: {ohlc_10s.iloc[-2]} \n"
f"precio actual: {ohlc_10s.iloc[-1]} \n"
f"adx 5m: {adx_5m['ADX'].iloc[-2]}, {adx_5m['ADX'].iloc[-1]} \n"
f"DI+ 5m: {adx_5m['DI+'].iloc[-2]}, {adx_5m['DI+'].iloc[-1]} \n"
f"DI- 5m: {adx_5m['DI-'].iloc[-2]}, {adx_5m['DI-'].iloc[-1]} \n"
f"rsi 5m: {rsi_5m.iloc[-2]}, {rsi_5m.iloc[-1]} \n"
f"adx 1m: {adx_1m['ADX'].iloc[-2]}, {adx_1m['ADX'].iloc[-1]} \n"
f"DI+ 1m: {adx_1m['DI+'].iloc[-2]}, {adx_1m['DI+'].iloc[-1]} \n"
f"DI- 1m: {adx_1m['DI-'].iloc[-2]}, {adx_1m['DI-'].iloc[-1]} \n"
f"rsi 1m: {rsi_1m.iloc[-2]}, {rsi_1m.iloc[-1]} \n"
f"ichimoku 1m sspan A: {ichimoku_1m['Senkou span A'].iloc[-2]}, {ichimoku_1m['Senkou span A'].iloc[-1]} \n"
f"ichimoku 1m sspan B: {ichimoku_1m['Senkou span B'].iloc[-2]}, {ichimoku_1m['Senkou span B'].iloc[-1]} \n"
f"ichimoku tenkan 1m: {ichimoku_1m['tenkan-sen'].iloc[-2]}, {ichimoku_1m['tenkan-sen'].iloc[-1]} \n"
f"ichimoku kijun 1m: {ichimoku_1m['kijun-sen'].iloc[-2]}, {ichimoku_1m['kijun-sen'].iloc[-1]} \n"
f"ichimoku 10s sspan A: {ichimoku_10s['Senkou span A'].iloc[-2]}, {ichimoku_10s['Senkou span A'].iloc[-1]} \n"
f"ichimoku 10s sspan B: {ichimoku_10s['Senkou span B'].iloc[-2]}, {ichimoku_10s['Senkou span B'].iloc[-1]} \n"
f"ichimoku 10s sspan A -26: {ichimoku_10s['Senkou span A'].iloc[-26]} \n"
f"ichimoku 10s sspan B -26: {ichimoku_10s['Senkou span B'].iloc[-26]} \n"
f"tenkan-sen 10s: {ichimoku_10s['tenkan-sen'].iloc[-2]}, {ichimoku_10s['tenkan-sen'].iloc[-1]} \n"
f"kijun-sen 10s: {ichimoku_10s['kijun-sen'].iloc[-2]}, {ichimoku_10s['kijun-sen'].iloc[-1]} \n"
f"venta \n")
if precio >= precio2:
print("operacion ganada, disminuyendo martingala")
cambio_de_monto(monto, "disminuir")
contador.sumar_estrategia("venta")
return
elif precio < precio2:
print("operacion perdida, aumentando martingala")
cambio_de_monto(monto, "aumentar")
tiempo_limite = time.time() + 600
try:
if (f"{(int(time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(time.time()))[14:16]) - 1):02}" !=
ohlc_1m.iloc[-1].name[14:16]):
try:
ExtraccionOanda(client, 500, 'M1', par)
except Exception as e:
print(f"excepcion {e}: {type(e)}")
client = oandapyV20.API(
access_token="e51f5c80499fd16ae7e9ff6676b3c53f-3ac97247f6df3ad7b2b3731a4b1c2dc3",
environment="practice")
ohlc_1m = pd.read_csv("datos_M1.csv", index_col="time")
ichimoku_1m = ichimoku(ohlc_1m)
res_max_1m, res_min_1m, sop_min_1m, sop_max_1m = calcular_rango_sop_res(ohlc_1m, 10)
if ((int(time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(time.time()))[15:16])) == 1 or (
int(time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(time.time()))[15:16])) == 6) and \
(ohlc_5m.iloc[-1].name[
14:16] != f"{int(time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(time.time()))[14:16]) - 1:02}"):
try:
ExtraccionOanda(client, 500, 'M5', par)
except Exception as e:
print(f"excepcion {e}: {type(e)}")
client = oandapyV20.API(
access_token="e51f5c80499fd16ae7e9ff6676b3c53f-3ac97247f6df3ad7b2b3731a4b1c2dc3",
environment="practice")
ohlc_5m = pd.read_csv("datos_M5.csv", index_col="time")
res_max_5m, res_min_5m, sop_min_5m, sop_max_5m = calcular_rango_sop_res(ohlc_5m, 50)
adx_5m = ADX(ohlc_5m)
rsi_5m = RSI(ohlc_5m)
except Exception as e:
print(f"excepcion {e}: {type(e)}")
print("hubo un error en la lectura de datos 1m o 5m en seguimiento ichimoku 2")
time.sleep(10 - ((time.time() - starttime) % 10))
if sop_max_5m > ohlc_10s['c'].iloc[-1] > sop_min_5m or sop_max_30m > ohlc_10s['c'].iloc[-1] > sop_min_30m:
print("Se sale del seguimiento porque hay un soporte cercano")
else:
print("se sale del seguimiento porque se ejecutó operacion o ",
adx_5m["ADX"].iloc[-1] > 20.0, rsi_5m.iloc[-1] < 70.0,
ichimoku_1m["Senkou span A"].iloc[-26] > ohlc_10s['c'].iloc[-1] <
ichimoku_1m["Senkou span B"].iloc[-26])
def __init__(self, StockCode, StartDate, EndDate):
log_txt.insert(INSERT, 'getting price list\n')
try:
df = get_pse_data(StockCode, StartDate, EndDate)
except Exception as e:
log_txt.insert(INSERT, 'Get pse data error: {e}\n'.format(e=e))
log_txt.insert(INSERT, 'price list obtained')
# Derive the 30 day SMA of JFC's closing prices
ma30 = df.close.rolling(30).mean()
ma100 = df.close.rolling(100).mean()
# Combine the closing prices with the 30 day SMA
data = pd.concat([df.close, ma30, ma100], axis=1).dropna()
data.columns = [
'Closing Price', 'Simple Moving Average (30 day)',
'Simple Moving Average (100 day)'
]
#Create a new dataframe
signal = pd.DataFrame(index=df['close'].index)
signal['close'] = data['Closing Price']
signal['SMA30'] = data['Simple Moving Average (30 day)']
signal['SMA100'] = data['Simple Moving Average (100 day)']
log_txt.insert(INSERT, 'calculate RSI\n')
v_RSI = RSI.getRSI(self, signal)
log_txt.insert(INSERT, 'done calculating RSI\n')
log_txt.insert(INSERT, 'calculate moving averages\n')
MA = MovingAverage.buy_sell(signal)
log_txt.insert(INSERT, 'done calculating moving averages\n')
try:
signal['Buy_Signal_Price_MA'] = MA[0]
signal['Sell_Signal_Price_MA'] = MA[1]
signal['Buy_Signal_Price_RSI'] = v_RSI[0]
signal['Sell_Signal_Price_RSI'] = v_RSI[1]
except Exception as e:
log_txt.insert(INSERT,
'Get buy and sell data error: {e}\n'.format(e=e))
# Visually Show The Stock buy and sell signals
# Create the title
title = 'Adj. Close Price History Buy / Sell Signals '
# Get the stocks
my_stocks = signal
ticker = "close"
# Create and plot the graph
try:
plt.figure(figsize=(12.2, 4.5)) # width = 12.2in, height = 4.5
plt.scatter(my_stocks.index,
my_stocks['Buy_Signal_Price_MA'],
color='green',
label='Buy Signal MA',
marker='^',
alpha=1)
plt.scatter(my_stocks.index,
my_stocks['Sell_Signal_Price_MA'],
color='darkred',
label='Sell Signal MA',
marker='v',
alpha=1)
plt.scatter(my_stocks.index,
my_stocks['Buy_Signal_Price_RSI'],
color='blue',
label='Buy Signal RSI',
marker='^',
alpha=1)
plt.scatter(my_stocks.index,
my_stocks['Sell_Signal_Price_RSI'],
color='red',
label='Sell Signal RSI',
marker='v',
alpha=1)
plt.plot(
my_stocks[ticker], label=ticker, alpha=0.35
) # plt.plot( X-Axis , Y-Axis, line_width, alpha_for_blending, label)
plt.plot(my_stocks['SMA30'], label='SMA30', alpha=0.35)
plt.plot(my_stocks['SMA100'], label='SMA100', alpha=0.35)
plt.title(title)
plt.xlabel('Date', fontsize=18)
plt.ylabel('Adj. Close Price PHP', fontsize=18)
plt.legend(loc='upper left')
except Exception as e:
log_txt.insert(INSERT, 'Plotting data error: {e}\n'.format(e=e))
try:
plt.show()
except Exception as e:
log_txt.insert(INSERT, 'Plotting data error: {e}\n'.format(e=e))
log_txt.insert(INSERT, 'Produced graph\n')
def seguimiento_div(ohlc_5m, ohlc_1m, ohlc_10s, par, tipo_de_divergencia,
punto_max_min_macd, punto_ultimo, monto, client, request,
contador):
print("estamos en seguimiento divergencia")
tiempo_de_operacion = "5"
if tipo_de_divergencia == "bajista":
punto_max_macd = punto_max_min_macd
punto_ultimo_macd = punto_ultimo
adx_1m = ADX(ohlc_1m)
rsi_1m = RSI(ohlc_1m)
res_max_1m, res_min_1m, sop_min_1m, sop_max_1m = calcular_rango_sop_res(
ohlc_1m, 10)
adx_5m = ADX(ohlc_5m)
rsi_5m = RSI(ohlc_5m)
tiempo_limite = time.time() + 600
while punto_ultimo_macd < punto_max_macd and time.time(
) < tiempo_limite:
starttime = time.time()
try:
ohlc_10s = pd.read_csv("datos_10s.csv", index_col="time")
adx_10s = ADX(ohlc_10s)
ichimoku_10s = ichimoku(ohlc_10s)
res_max_10s, res_min_10s, sop_min_10s, sop_max_10s = calcular_rango_sop_res(
ohlc_10s, 30)
except Exception as e:
print(f"excepcion {e}: {type(e)}")
print("reintentando lectura ohlc_10s")
ohlc_10s = pd.read_csv("datos_10s.csv", index_col="time")
res_max_10s, res_min_10s, sop_min_10s, sop_max_10s = calcular_rango_sop_res(
ohlc_10s, 30)
try:
print(adx_1m["ADX"].iloc[-1])
print("posible venta, high 10s: ", ohlc_10s['h'].iloc[-1],
" resistencia menor 10s: ", res_min_10s)
if (ohlc_10s['h'].iloc[-1] <= res_min_10s or ohlc_10s['h'].iloc[-2] <= res_min_10s) or \
(ohlc_10s['h'].iloc[-1] <= res_min_1m):
while ohlc_10s['c'].iloc[-1] > ichimoku_10s[
'kijun-sen'].iloc[
-1] and punto_ultimo_macd < punto_max_macd:
try:
ohlc_10s = pd.read_csv("datos_10s.csv",
index_col="time")
ichimoku_10s = ichimoku(ohlc_10s)
res_max_10s, res_min_10s, sop_min_10s, sop_max_10s = calcular_rango_sop_res(
ohlc_10s, 30)
print(ohlc_10s['c'].iloc[-1], "kijun sen: ",
ichimoku_10s['kijun-sen'].iloc[-1])
time.sleep(10)
if ((int(time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(time.time()))[15:16])) == 1 or (
int(time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(time.time()))[
15:16])) == 6) and \
(ohlc_5m.iloc[-1].name[
14:16] != f"{int(time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(time.time()))[14:16]) - 1:02}"):
try:
ExtraccionOanda(client, 500, 'M5', par)
ohlc_5m = pd.read_csv("datos_M5.csv",
index_col="time")
punto_ultimo_macd = MACD(
ohlc_5m)["MACD"].iloc[-1]
except Exception as e:
print(f"excepcion {e}: {type(e)}")
client = oandapyV20.API(
access_token=
"e51f5c80499fd16ae7e9ff6676b3c53f-3ac97247f6df3ad7b2b3731a4b1c2dc3",
environment="practice")
except Exception as e:
print(f"excepcion {e}: {type(e)}")
print("reintentando lectura ohlc_10s")
ohlc_10s = pd.read_csv("datos_10s.csv",
index_col="time")
ichimoku_10s = ichimoku(ohlc_10s)
res_max_10s, res_min_10s, sop_min_10s, sop_max_10s = calcular_rango_sop_res(
ohlc_10s, 30)
if (ichimoku_10s["tenkan-sen"].iloc[-1] > ichimoku_10s["kijun-sen"].iloc[-1]) and \
(ichimoku_10s["Senkou span A"].iloc[-26] > ichimoku_10s["Senkou span B"].iloc[-26]) and \
(ohlc_10s['o'].iloc[-1] > ichimoku_10s["kijun-sen"].iloc[-1] > ohlc_10s['c'].iloc[-1] or
ohlc_10s['o'].iloc[-2] > ichimoku_10s["kijun-sen"].iloc[-2] > ohlc_10s['c'].iloc[-2]) and \
(ichimoku_10s["tenkan-sen"].iloc[-2] > ichimoku_10s["tenkan-sen"].iloc[-1]) and \
(adx_10s["ADX"].iloc[-2] > adx_10s["ADX"].iloc[-1]):
ejecucion("ventac", par, tiempo_de_operacion, monto)
live_price_data = client.request(request)
precio = (float(
live_price_data["prices"][0]["closeoutBid"]) +
float(live_price_data["prices"][0]
["closeoutAsk"])) / 2
if (f"{(int(time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(time.time()))[14:16]) - 1):02}"
!= ohlc_1m.iloc[-1].name[14:16]):
try:
ExtraccionOanda(client, 500, 'M1', par)
ohlc_1m = pd.read_csv("datos_M1.csv",
index_col="time")
adx_1m = ADX(ohlc_1m)
rsi_1m = RSI(ohlc_1m)
punto_ultimo_macd = MACD(
ohlc_1m)["MACD"].iloc[-1]
except Exception as e:
print(f"excepcion {e}: {type(e)}")
client = oandapyV20.API(
access_token=
"e51f5c80499fd16ae7e9ff6676b3c53f-3ac97247f6df3ad7b2b3731a4b1c2dc3",
environment="practice")
time.sleep(int(tiempo_de_operacion) * 60)
live_price_data = client.request(request)
precio2 = (float(
live_price_data["prices"][0]["closeoutBid"]) +
float(live_price_data["prices"][0]
["closeoutAsk"])) / 2
adx_10s = ADX(ohlc_10s)
rsi_10s = RSI(ohlc_10s)
with open("datos divergencias.txt",
"at") as fichero_div:
fichero_div.write(
f"precio anterior: {ohlc_1m.iloc[-2]} \n"
f"precio actual: {ohlc_1m.iloc[-1]} \n"
f"adx 5m: {adx_5m['ADX'].iloc[-2]} {adx_5m['ADX'].iloc[-1]} \n"
f"DI+ 5m: {adx_5m['DI+'].iloc[-2]}, {adx_5m['DI+'].iloc[-1]} \n"
f"DI- 5m: {adx_5m['DI-'].iloc[-2]}, {adx_5m['DI-'].iloc[-1]} \n"
f"rsi 5m: {rsi_5m.iloc[-2]} {rsi_5m.iloc[-1]} \n"
f"adx 1m {adx_1m['ADX'].iloc[-2]} {adx_1m['ADX'].iloc[-1]} \n"
f"DI+ 1m: {adx_1m['DI+'].iloc[-2]}, {adx_1m['DI+'].iloc[-1]} \n"
f"DI- 1m: {adx_1m['DI-'].iloc[-2]}, {adx_1m['DI-'].iloc[-1]} \n"
f"rsi 1m {rsi_1m.iloc[-2]} {rsi_1m.iloc[-1]} \n"
f"adx 10s {adx_10s['ADX'].iloc[-2]} {adx_10s['ADX'].iloc[-1]} \n"
f"DI+ 10s: {adx_10s['DI+'].iloc[-2]}, {adx_10s['DI+'].iloc[-1]} \n"
f"DI- 10s: {adx_10s['DI-'].iloc[-2]}, {adx_10s['DI-'].iloc[-1]} \n"
f"rsi 10s: {rsi_10s.iloc[-2]} {rsi_10s.iloc[-1]} \n"
"venta \n")
if precio >= precio2:
print("operacion ganada, disminyendo martingala")
cambio_de_monto(monto, "disminuir")
contador.sumar_estrategia("venta")
return
elif precio < precio2:
print("operacion perdida, aumentando martingala")
cambio_de_monto(monto, "aumentar")
tiempo_limite = time.time() + 600
except Exception as e:
print(f"excepcion {e}: {type(e)}")
ohlc_10s = pd.read_csv("datos_10s.csv", index_col="time")
ohlc_1m = pd.read_csv("datos_M1.csv", index_col="time")
time.sleep(10 - ((time.time() - starttime) % 10))
if (f"{(int(time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(time.time()))[14:16]) - 1):02}" != \
ohlc_1m.iloc[-1].name[14:16]):
try:
ExtraccionOanda(client, 500, 'M1', par)
ohlc_1m = pd.read_csv("datos_M1.csv", index_col="time")
adx_1m = ADX(ohlc_1m)
rsi_1m = RSI(ohlc_1m)
punto_ultimo_macd = MACD(ohlc_1m)["MACD"].iloc[-1]
res_max_1m, res_min_1m, sop_min_1m, sop_max_1m = calcular_rango_sop_res(
ohlc_1m, 10)
except Exception as e:
print(f"excepcion {e}: {type(e)}")
client = oandapyV20.API(
access_token=
"e51f5c80499fd16ae7e9ff6676b3c53f-3ac97247f6df3ad7b2b3731a4b1c2dc3",
environment="practice")
if ((int(time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(time.time()))[15:16])) == 1 or (
int(time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(time.time()))[15:16])) == 6) and \
(ohlc_5m.iloc[-1].name[
14:16] != f"{int(time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(time.time()))[14:16]) - 1:02}"):
try:
ExtraccionOanda(client, 500, 'M5', par)
ohlc_5m = pd.read_csv("datos_M5.csv", index_col="time")
adx_5m = ADX(ohlc_5m)
rsi_5m = RSI(ohlc_5m)
except Exception as e:
print(f"excepcion {e}: {type(e)}")
client = oandapyV20.API(
access_token=
"e51f5c80499fd16ae7e9ff6676b3c53f-3ac97247f6df3ad7b2b3731a4b1c2dc3",
environment="practice")
time.sleep(10 - ((time.time() - starttime) % 10))
print("Se sale del seguimiento porque se ejecuto o",
punto_ultimo_macd < punto_max_macd, punto_ultimo_macd,
punto_max_macd)
elif tipo_de_divergencia == "alcista":
punto_min_macd = punto_max_min_macd
punto_ultimo_macd = punto_ultimo
adx_1m = ADX(ohlc_1m)
rsi_1m = RSI(ohlc_1m)
res_max_1m, res_min_1m, sop_min_1m, sop_max_1m = calcular_rango_sop_res(
ohlc_1m, 10)
adx_5m = ADX(ohlc_5m)
rsi_5m = RSI(ohlc_5m)
tiempo_limite = time.time() + 600
while punto_ultimo_macd > punto_min_macd and time.time(
) < tiempo_limite:
starttime = time.time()
try:
ohlc_10s = pd.read_csv("datos_10s.csv", index_col="time")
adx_10s = ADX(ohlc_10s)
ichimoku_10s = ichimoku(ohlc_10s)
res_max_10s, res_min_10s, sop_min_10s, sop_max_10s = calcular_rango_sop_res(
ohlc_10s, 30)
except Exception as e:
print(f"excepcion {e}: {type(e)}")
print("reintentando lectura ohlc_10s")
ohlc_10s = pd.read_csv("datos_10s.csv", index_col="time")
res_max_10s, res_min_10s, sop_min_10s, sop_max_10s = calcular_rango_sop_res(
ohlc_10s, 30)
try:
print(adx_1m["ADX"].iloc[-1])
print("posible compra, low 10s: ", ohlc_10s['l'].iloc[-1],
" soporte max 10s: ", sop_max_10s)
if (ohlc_10s['l'].iloc[-1] <= sop_max_10s or ohlc_10s['l'].iloc[-2] <= sop_max_10s) or \
(ohlc_1m['l'].iloc[-1] <= sop_max_1m):
while ichimoku_10s["kijun-sen"].iloc[-1] > ohlc_10s[
'c'].iloc[
-1] and punto_ultimo_macd > punto_min_macd:
try:
ohlc_10s = pd.read_csv("datos_10s.csv",
index_col="time")
ichimoku_10s = ichimoku(ohlc_10s)
res_max_10s, res_min_10s, sop_min_10s, sop_max_10s = calcular_rango_sop_res(
ohlc_10s, 30)
print(ohlc_10s['c'].iloc[-1], "kijun sen: ",
ichimoku_10s['kijun-sen'].iloc[-1])
time.sleep(10)
if ((int(time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(time.time()))[15:16])) == 1 or (
int(time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(time.time()))[
15:16])) == 6) and \
(ohlc_5m.iloc[-1].name[
14:16] != f"{int(time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(time.time()))[14:16]) - 1:02}"):
try:
ExtraccionOanda(client, 500, 'M5', par)
ohlc_5m = pd.read_csv("datos_M5.csv",
index_col="time")
punto_ultimo_macd = MACD(
ohlc_5m)["MACD"].iloc[-1]
except Exception as e:
print(f"excepcion {e}: {type(e)}")
client = oandapyV20.API(
access_token=
"e51f5c80499fd16ae7e9ff6676b3c53f-3ac97247f6df3ad7b2b3731a4b1c2dc3",
environment="practice")
except Exception as e:
print(f"excepcion {e}: {type(e)}")
print("reintentando lectura ohlc_10s")
ohlc_10s = pd.read_csv("datos_10s.csv",
index_col="time")
ichimoku_10s = ichimoku(ohlc_10s)
res_max_10s, res_min_10s, sop_min_10s, sop_max_10s = calcular_rango_sop_res(
ohlc_10s, 30)
if (ichimoku_10s["tenkan-sen"].iloc[-1] < ichimoku_10s["kijun-sen"].iloc[-1]) and \
(ichimoku_10s["Senkou span A"].iloc[-26] < ichimoku_10s["Senkou span B"].iloc[-26]) and \
(ohlc_10s['o'].iloc[-1] < ichimoku_10s["kijun-sen"].iloc[-1] < ohlc_10s['c'].iloc[-1] or
ohlc_10s['o'].iloc[-2] < ichimoku_10s["kijun-sen"].iloc[-2] < ohlc_10s['c'].iloc[
-2]) and \
(ichimoku_10s["tenkan-sen"].iloc[-2] < ichimoku_10s["tenkan-sen"].iloc[-1]) and \
(adx_10s["ADX"].iloc[-2] > adx_10s["ADX"].iloc[-1]):
ejecucion("comprac", par, tiempo_de_operacion, monto)
live_price_data = client.request(request)
precio = (float(
live_price_data["prices"][0]["closeoutBid"]) +
float(live_price_data["prices"][0]
["closeoutAsk"])) / 2
if (f"{(int(time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(time.time()))[14:16]) - 1):02}" != \
ohlc_1m.iloc[-1].name[14:16]):
try:
ExtraccionOanda(client, 500, 'M1', par)
ohlc_1m = pd.read_csv("datos_M1.csv",
index_col="time")
adx_1m = ADX(ohlc_1m)
rsi_1m = RSI(ohlc_1m)
except Exception as e:
print(f"excepcion {e}: {type(e)}")
client = oandapyV20.API(
access_token=
"e51f5c80499fd16ae7e9ff6676b3c53f-3ac97247f6df3ad7b2b3731a4b1c2dc3",
environment="practice")
time.sleep(int(tiempo_de_operacion) * 60)
live_price_data = client.request(request)
precio2 = (float(
live_price_data["prices"][0]["closeoutBid"]) +
float(live_price_data["prices"][0]
["closeoutAsk"])) / 2
adx_10s = ADX(ohlc_10s)
rsi_10s = RSI(ohlc_10s)
with open("datos divergencias.txt",
"at") as fichero_div:
fichero_div.write(
f"precio anterior: {ohlc_1m.iloc[-2]} \n"
f"precio actual: {ohlc_1m.iloc[-1]} \n"
f"adx 5m: {adx_5m['ADX'].iloc[-2]} {adx_5m['ADX'].iloc[-1]} \n"
f"DI+ 5m: {adx_5m['DI+'].iloc[-2]}, {adx_5m['DI+'].iloc[-1]} \n"
f"DI- 5m: {adx_5m['DI-'].iloc[-2]}, {adx_5m['DI-'].iloc[-1]} \n"
f"rsi 5m: {rsi_5m.iloc[-2]} {rsi_5m.iloc[-1]} \n"
f"adx 1m {adx_1m['ADX'].iloc[-2]} {adx_1m['ADX'].iloc[-1]} \n"
f"DI+ 1m: {adx_1m['DI+'].iloc[-2]}, {adx_1m['DI+'].iloc[-1]} \n"
f"DI- 1m: {adx_1m['DI-'].iloc[-2]}, {adx_1m['DI-'].iloc[-1]} \n"
f"rsi 1m {rsi_1m.iloc[-2]} {rsi_1m.iloc[-1]} \n"
f"adx 10s {adx_10s['ADX'].iloc[-2]} {adx_10s['ADX'].iloc[-1]} \n"
f"DI+ 10s: {adx_10s['DI+'].iloc[-2]}, {adx_10s['DI+'].iloc[-1]} \n"
f"DI- 10s: {adx_10s['DI-'].iloc[-2]}, {adx_10s['DI-'].iloc[-1]} \n"
f"rsi 10s: {rsi_10s.iloc[-2]} {rsi_10s.iloc[-1]} \n"
"compra \n")
if precio >= precio2:
print("operacion ganada, disminyendo martingala")
cambio_de_monto(monto, "disminuir")
contador.sumar_estrategia("venta")
return
elif precio < precio2:
print("operacion perdida, aumentando martingala")
cambio_de_monto(monto, "aumentar")
tiempo_limite = time.time() + 600
except Exception as e:
print(f"excepcion {e}: {type(e)}")
ohlc_10s = pd.read_csv("datos_10s.csv", index_col="time")
ohlc_1m = pd.read_csv("datos_M1.csv", index_col="time")
time.sleep(10 - ((time.time() - starttime) % 10))
if (f"{(int(time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(time.time()))[14:16]) - 1):02}" != \
ohlc_1m.iloc[-1].name[14:16]):
try:
ExtraccionOanda(client, 500, 'M1', par)
ohlc_1m = pd.read_csv("datos_M1.csv", index_col="time")
adx_1m = ADX(ohlc_1m)
rsi_1m = RSI(ohlc_1m)
punto_ultimo_macd = MACD(ohlc_1m)["MACD"].iloc[-1]
res_max_1m, res_min_1m, sop_min_1m, sop_max_1m = calcular_rango_sop_res(
ohlc_1m, 10)
except Exception as e:
print(f"excepcion {e}: {type(e)}")
client = oandapyV20.API(
access_token=
"e51f5c80499fd16ae7e9ff6676b3c53f-3ac97247f6df3ad7b2b3731a4b1c2dc3",
environment="practice")
if ((int(time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(time.time()))[15:16])) == 1 or (
int(time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(time.time()))[15:16])) == 6) and \
(ohlc_5m.iloc[-1].name[
14:16] != f"{int(time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(time.time()))[14:16]) - 1:02}"):
try:
ExtraccionOanda(client, 500, 'M5', par)
ohlc_5m = pd.read_csv("datos_M5.csv", index_col="time")
adx_5m = ADX(ohlc_5m)
rsi_5m = RSI(ohlc_5m)
except Exception as e:
print(f"excepcion {e}: {type(e)}")
client = oandapyV20.API(
access_token=
"e51f5c80499fd16ae7e9ff6676b3c53f-3ac97247f6df3ad7b2b3731a4b1c2dc3",
environment="practice")
time.sleep(10 - ((time.time() - starttime) % 10))
print("Se sale del seguimiento porque se ejecuto o",
punto_ultimo_macd > punto_min_macd, punto_ultimo_macd,
punto_min_macd)
def influxQuery5m(client,
max_points,
min_points,
measurements,
interfaces,
start_time="now()"):
for measure in measurements:
if (measurements[measure]["name"] == "arp_packets"
or measurements[measure]["name"] == "ping_packets"
or measurements[measure]["name"] == "dns_packets"
or measurements[measure]["name"] == "dns_errors"):
doSum = True
else:
doSum = False
num_den = measure.split()
numerator = num_den[0]
denumerator2 = None
if (len(num_den) >= 2):
denumerator = num_den[1]
if len(num_den) == 3:
denumerator2 = num_den[2]
else:
denumerator = numerator
key = numerator.split(':')[0]
hosts = client.query(
'SHOW TAG VALUES ON "ntopng" FROM "autogen"."%s" WITH KEY = "%s" LIMIT %s'
% (numerator, key, str(cf.limitRSI)))
m_numerator = []
m_denumerator = []
m_denumerator2 = []
s_clause = ""
for metric in measurements[measure]["metrics"][0]:
m_numerator.append(metric)
s_clause += "NON_NEGATIVE_DERIVATIVE(LAST(" + metric + "), 1s) AS " + metric + ", "
if (m_numerator[0].find("flows") == -1):
for metric in measurements[measure]["metrics"][1]:
m_denumerator.append(metric)
s_clause += "NON_NEGATIVE_DERIVATIVE(LAST(" + metric + "), 1s) AS " + metric + ", "
if (denumerator2 != None):
for metric in measurements[measure]["metrics"][2]:
m_denumerator2.append(metric)
s_clause += "NON_NEGATIVE_DERIVATIVE(LAST(" + metric + "), 1s) AS " + metric + ", "
else:
m_denumerator = m_numerator
s_clause = s_clause[slice(len(s_clause) - 2)]
f_clause = """"ntopng"."autogen".""" + '"' + numerator + '"'
if (denumerator != numerator):
f_clause += """, "ntopng"."autogen".""" + '"' + denumerator + '"'
if (denumerator2 != None):
f_clause += """, "ntopng"."autogen".""" + '"' + denumerator2 + '"'
p2p_metric = ''
if (numerator.find("unreachable") != -1):
if (m_numerator[0].find("server") != -1):
p2p_metric = "bytes_sent"
else:
p2p_metric = "bytes_rcvd"
ips = hosts.get_points()
for ip in ips:
if isLocalHost(ip['value']):
continue
for ifid in interfaces:
#key
host_interface_measure = ip[
'value'] + "|" + ifid + "|" + measurements[measure]["name"]
if (start_time == "now()"
and host_interface_measure in hostRSI):
w_clause = start_time + " - 5m"
min_points = 1
else:
if (start_time == "now()"):
max_points = 2 * min_points
w_clause = start_time + " - " + str(
(max_points - 1) * 5) + "m AND time < " + start_time
results = client.query(
""" SELECT %s
FROM %s
WHERE time >= %s AND "%s"='%s' AND "ifid"='%s'
GROUP BY time(5m) fill(none) """ %
(s_clause, f_clause, w_clause, key, ip['value'], ifid))
n_points = list(results.get_points(measurement=numerator))
if (numerator == denumerator):
d_points = n_points
else:
d_points = list(
results.get_points(measurement=denumerator))
if denumerator2 != None:
d2_points = list(
results.get_points(measurement=denumerator2))
if len(d_points) == 0:
d_points = d2_points
m_denumerator = []
elif len(d2_points) == 0:
d2_points = d_points
m_denumerator2 = []
dim_numerator = len(n_points)
dim_denumerator = len(d_points)
dim_denumerator2 = len(
d2_points) if denumerator2 != None else dim_numerator
if (min(dim_numerator, dim_denumerator, dim_denumerator2) <
min_points):
continue
if (dim_numerator != dim_denumerator):
if dim_denumerator > dim_numerator:
d_points = d_points[-dim_numerator:]
else:
n_points = n_points[-dim_denumerator:]
#by reference changes
dim_denumerator2 = len(
d2_points) if denumerator2 != None else dim_denumerator
if (dim_denumerator2 != dim_denumerator
and denumerator2 != None):
if dim_denumerator2 > dim_denumerator:
d2_points = d2_points[-dim_denumerator:]
else:
n_points = n_points[-dim_denumerator2:]
d_points = d_points[-dim_denumerator2:]
if p2p_metric:
results = client.query(
""" SELECT NON_NEGATIVE_DIFFERENCE(SUM("%s")) AS "%s"
FROM "ntopng"."autogen"."host:p2p"
WHERE time >= %s AND "%s"='%s' AND "ifid"='%s'
GROUP BY time(5m) fill(0) """ %
(p2p_metric, p2p_metric, w_clause, key, ip['value'],
ifid))
p2p_points = list(
results.get_points(measurement="host:p2p"))
p2p_non_zero_points = []
for i in range(len(p2p_points)):
if (p2p_points[i][p2p_metric] != 0):
p2p_non_zero_points.append(p2p_points[i]['time'])
series = []
seriesDate = []
for i in range(len(n_points)):
sum_numerator = 0
sum_denumerator = 0
if (n_points[i]['time'] != d_points[i]['time']):
break
if (denumerator2 != None):
if d_points[i]['time'] != d2_points[i]['time']:
break
if (p2p_metric != ''):
if n_points[i]['time'] in p2p_non_zero_points:
break
try:
for x in m_numerator:
sum_numerator += n_points[i][x]
for x in m_denumerator:
sum_denumerator += d_points[i][x]
for x in m_denumerator2:
sum_denumerator += d2_points[i][x]
except TypeError: #portability
continue
if (sum_denumerator >= measurements[measure]["minValue"][1]
or sum_numerator >=
measurements[measure]["minValue"][0]):
if doSum:
sum_denumerator += sum_numerator
if sum_denumerator != 0:
ratioValue = truncate(sum_numerator /
sum_denumerator)
else:
continue
if measurements[measure]["name"].find("size") != -1:
thVal = cf.packet_size_threshold
else:
thVal = cf.ratio_threshold
if (not checkThreshold(
ratioValue, measurements[measure]["name"],
ip['value'], ifid, statsThreshold,
n_points[i]['time'], "ip", thVal) or
(doSum and
measurements[measure]["name"] != "dns_errors")):
continue
series.append(ratioValue)
if (len(series) >= min_points
or w_clause == "now()-5m"):
seriesDate.append(n_points[i]['time'])
if (w_clause != "now() - 5m"):
if (len(series) >= min_points):
if (start_time == "now()"):
rsi = RSI(series[-min_points:], min_points - 1,
ip['value'],
measurements[measure]["name"], ifid,
seriesDate[0] + "|wu", statsRSI)
hostRSI.update({host_interface_measure: rsi})
else:
rsi = RSI(series[:min_points], min_points - 1,
ip['value'],
measurements[measure]["name"], ifid,
seriesDate[0] + "|wu", statsRSI)
test_series = series[min_points:]
for i in range(len(test_series)):
rsi.next(test_series[i], seriesDate[i + 1],
statsRSI)
else:
if (len(series) >= 1):
hostRSI[host_interface_measure].next(
series[-1], seriesDate[-1], statsRSI)
import pandas as pnd
import numpy as np
from RSI import RSI
import matplotlib.pyplot as plt
Data = pnd.read_pickle('CompanyDataUpdated.pkl')
Period = 14
StockNames = list(Data.keys())
LowRsiLim = 20
HighRsiLim = 80
for StockName in StockNames:
Time = Data[StockName].index
Rsi = RSI(Data, StockName, Period)
LowRsi = np.zeros(Time.size) + LowRsiLim
HighRsi = np.zeros(Time.size) + HighRsiLim
if Rsi[-1] < 40:
fig, ax1 = plt.subplots()
ax1.plot(Time, Rsi, 'red')
ax1.plot(Time, LowRsi, 'black')
ax1.plot(Time, HighRsi, 'black')
ax1.set_xlabel('time')
ax1.set_ylabel('RSI', color='red')
ax1.tick_params(axis='y', labelcolor='red')
ax2 = ax1.twinx()
ax2.plot(Time, Data[StockName]['Close'], color='blue')
ax2.set_ylabel('Price', color='blue')
ax2.tick_params(axis='y', labelcolor='blue')