| Overall Statistics |
|
Total Trades 49 Average Win 0.91% Average Loss -0.81% Compounding Annual Return -17.667% Drawdown 9.500% Expectancy -0.131 Net Profit -2.818% Sharpe Ratio -0.53 Probabilistic Sharpe Ratio 24.040% Loss Rate 59% Win Rate 41% Profit-Loss Ratio 1.13 Alpha -0.132 Beta 0.937 Annual Standard Deviation 0.205 Annual Variance 0.042 Information Ratio -0.736 Tracking Error 0.182 Treynor Ratio -0.116 Total Fees $485.67 Estimated Strategy Capacity $450000.00 Lowest Capacity Asset TMF UBTUG7D0B7TX Portfolio Turnover 37.51% |
from AlgorithmImports import *
import math
import pandas as pd
from cmath import sqrt
from clr import AddReference
AddReference("System")
AddReference("QuantConnect.Algorithm")
AddReference("QuantConnect.Common")
from System import *
from QuantConnect import *
from QuantConnect.Algorithm import *
from QuantConnect.Data.Custom import *
from QuantConnect.Python import PythonData
class IntelligentSkyDoge(QCAlgorithm):
def Initialize(self):
self.cash = 100000
self.buffer_pct = 0.06 # CHANGE YOUR THRESHOLD HERE
self.SetStartDate(2023, 4, 1)
self.SetEndDate(2023, 5, 24)
self.SetCash(self.cash)
self.equities = ['VCIT', 'UDN', 'SARK','AMD','FNGU','TSLL','AEHR','MSTR','TARK','XLY','QQQE','VOOG','VOOV','VTV','HIBL','XLK','XLP','SVXY','QID','TBF','TSLA','LQD','VTIP','EDV','STIP','SPTL','IEI','USDU','SQQQ','VIXM','SPXU','QQQ','BSV','TQQQ','SPY','DBC','SHV','IAU','VEA','UTSL','UVXY','UPRO','EFA','EEM','TLT','SHY','GLD','SLV','USO','WEAT','CORN','SH','DRN','PDBC','COMT','KOLD','BOIL','ESPO','PEJ','UGL','URE','VXX','UUP','BND','BIL','DUST','JDST','JNUG','GUSH','DBA','DBB','COM','PALL','AGQ','BAL','WOOD','URA','SCO','UCO','DBO','TAGS','CANE','REMX','COPX','IEF','SPDN','CHAD','DRIP','SPUU','INDL','BRZU','ERX','ERY','CWEB','CHAU','KORU','MEXX','EDZ','EURL','YINN','YANG','TNA','TZA','SPXL','SPXS','MIDU','TYD','TYO','TMF','TMV','TECL','TECS','SOXL','SOXS','LABU','LABD','RETL','DPST','DRV','PILL','CURE','FAZ','FAS','EWA','EWGS','EWG','EWP','EWQ','EWU','EWJ','EWI','EWN','ECC','NURE','VNQI','VNQ','VDC','VIS','VGT','VAW','VPU','VOX','VFH','VHT','VDE','SMH','DIA','UDOW','PSQ','SOXX','VTI','COST','UNH','SPHB','BTAL','VIXY','WEBL','WEBS','UBT','PST','TLH','QLD','SQM','SSO','SD','DGRO','SCHD','SGOL','TIP','DUG','EWZ','TBX','VGIT','VGLT','CCOR','LBAY','NRGD','PHDG','SPHD','COWZ','CTA','DBMF','GDMA','VIGI','AGG','NOBL','FAAR','BITO','FTLS','MORT','FNDX','GLL','NTSX','RWL','VLUE','IJR','SPYG','VXUS','AAL','AEP','AFL','C','CMCSA','DUK','EXC','F','GM','GOOGL','INTC','JNJ','KO','MET','NWE','OXY','PFE','RTX','SNY','SO','T','TMUS','VZ','WFC','WMT','AMZN','MSFT','NVDA','TSM','BA','CB','COKE','FDX','GE','LMT','MRK','NVEC','ORCL','PEP','V','DBE','BRK-B','CRUS','INFY','KMLM','NSYS','SCHG','SGML','SLDP','ARKQ','XLU','XLV','ULTA','AAPL','AMZU','BAD','DDM','IYH','JPM','PM','XOM']
self.MKT = self.AddEquity("SPY", Resolution.Daily).Symbol
self.mkt = []
for equity in self.equities:
self.AddEquity(equity, Resolution.Minute)
self.Securities[equity].SetDataNormalizationMode(DataNormalizationMode.Adjusted)
self.PT1 = 0.72
self.PT2 = 0.0
self.PT3 = 0.22
self.HT50 = {str(i).zfill(2): 0 for i in range(1, 21)}
self.HTS50 = {str(i).zfill(2): [] for i in range(1, 21)}
self.Schedule.On(self.DateRules.EveryDay("SPY"),
self.TimeRules.BeforeMarketClose("SPY", 2),
self.FunctionBeforeMarketClose)
def RSI(self, equity, period):
extension = min(period*5, 250)
r_w = RollingWindow[float](extension)
history = self.History(equity, extension - 1, Resolution.Daily)
for historical_bar in history:
r_w.Add(historical_bar.Close)
while r_w.Count < extension:
current_price = self.Securities[equity].Price
r_w.Add(current_price)
if r_w.IsReady:
average_gain = 0
average_loss = 0
gain = 0
loss = 0
for i in range(extension - 1, extension - period -1, -1):
gain += max(r_w[i-1] - r_w[i], 0)
loss += abs(min(r_w[i-1] - r_w[i], 0))
average_gain = gain/period
average_loss = loss/period
for i in range(extension - period - 1, 0, -1):
average_gain = (average_gain*(period-1) + max(r_w[i-1] - r_w[i], 0))/period
average_loss = (average_loss*(period-1) + abs(min(r_w[i-1] - r_w[i], 0)))/period
if average_loss == 0:
return 100
else:
rsi = 100 - (100/(1 + average_gain / average_loss))
return rsi
else:
return None
def CumReturn(self, equity, period):
history = self.History(equity, period, Resolution.Daily)
closing_prices = pd.Series([bar.Close for bar in history])
current_price = self.Securities[equity].Price
closing_prices = closing_prices.append(pd.Series([current_price]))
first_price = closing_prices.iloc[0]
if first_price == 0:
return None
else:
return_val = (current_price / first_price) - 1
return return_val
def STD(self, equity, period):
r_w = RollingWindow[float](period + 1)
r_w_return = RollingWindow[float](period)
history = self.History(equity, period, Resolution.Daily)
for historical_bar in history:
r_w.Add(historical_bar.Close)
while r_w.Count < period + 1:
current_price = self.Securities[equity].Price
r_w.Add(current_price)
for i in range (period, 0, -1):
daily_return = (r_w[i-1]/r_w[i] - 1)
r_w_return.Add(daily_return)
dfstd = pd.DataFrame({'r_w_return':r_w_return})
if r_w.IsReady:
std = dfstd['r_w_return'].std()
if std == 0:
return 0
else:
return std
else:
return 0
def MaxDD(self, equity, period):
history = self.History(equity, period - 1, Resolution.Daily)
closing_prices = pd.Series([bar.Close for bar in history])
current_price = self.Securities[equity].Price
closing_prices = closing_prices.append(pd.Series([current_price]))
rolling_max = closing_prices.cummax()
drawdowns = (rolling_max - closing_prices) / rolling_max
max_dd = drawdowns.min()
return max_dd
def SMA(self, equity, period):
r_w = RollingWindow[float](period)
history = self.History(equity, period - 1, Resolution.Daily)
for historical_bar in history:
r_w.Add(historical_bar.Close)
while r_w.Count < period:
current_price = self.Securities[equity].Price
r_w.Add(current_price)
if r_w.IsReady:
sma = sum(r_w) / period
return sma
else:
return 0
def IV(self, equity, period):
r_w = RollingWindow[float](period + 1)
r_w_return = RollingWindow[float](period)
history = self.History(equity, period, Resolution.Daily)
for historical_bar in history:
r_w.Add(historical_bar.Close)
while r_w.Count < period + 1:
current_price = self.Securities[equity].Price
r_w.Add(current_price)
for i in range (period, 0, -1):
if r_w[i] == 0:
return 0
else:
daily_return = (r_w[i-1]/r_w[i] - 1)
r_w_return.Add(daily_return)
dfinverse = pd.DataFrame({'r_w_return':r_w_return})
if r_w.IsReady:
std = dfinverse['r_w_return'].std()
if std == 0:
return 0
else:
inv_vol = 1 / std
return inv_vol
else:
return 0
def SMADayRet(self, equity, period):
r_w = RollingWindow[float](period + 1)
r_w_return = RollingWindow[float](period)
history = self.History(equity, period, Resolution.Daily)
for historical_bar in history:
r_w.Add(historical_bar.Close)
while r_w.Count < period + 1:
current_price = self.Securities[equity].Price
r_w.Add(current_price)
for i in range (period, 0, -1):
if r_w[i] == 0:
return None
daily_return = (r_w[i-1]/r_w[i] - 1)
r_w_return.Add(daily_return)
if r_w.IsReady:
smareturn = sum(r_w_return) / period
return smareturn
else:
return 0
def EMA(self, equity, period):
extension = period + 50
r_w = RollingWindow[float](extension)
history = self.History(equity, extension - 1, Resolution.Daily)
for historical_bar in history:
r_w.Add(historical_bar.Close)
while r_w.Count < extension:
current_price = self.Securities[equity].Price
r_w.Add(current_price)
if r_w.IsReady:
total_price = 0
for i in range(extension - 1, extension - period - 2, -1):
total_price += r_w[i]
average_price = total_price/period
for i in range(extension - period - 2, -1, -1):
average_price = r_w[i]*2/(period+1) + average_price*(1-2/(period+1))
return average_price
else:
return None
def OnData (self, data):
pass
def FunctionBeforeMarketClose(self):
mkt_price = self.History(self.MKT, 2, Resolution.Daily)['close'].unstack(level= 0).iloc[-1]
self.mkt.append(mkt_price)
mkt_perf = self.cash * self.mkt[-1] / self.mkt[0]
self.Plot('Strategy Equity', self.MKT, mkt_perf)
self.HolyGrailSimplified()
#self.V15A()
self.v41Pops()
self.ExecuteTrade()
def HolyGrailSimplified(self):
if self.Securities['SPY'].Price > self.SMA('SPY', 200):
if self.RSI('QQQ', 10) > 79:
equities = ["UVXY", "SQQQ"]
returns = {}
for equity in equities:
returns[equity] = self.RSI(equity, 13)
s_e = sorted([item for item in returns.items() if item[1] is not None], key = lambda x: x[1], reverse = True)
t3e = s_e[:1]
for i in self.HT50.keys():
if self.HT50[i] == 0:
self.HT50[i] = self.PT1
self.HTS50[i].append(t3e[0][0])
break
else:
if self.RSI('SPY', 10) > 79:
equities = ["UVXY", "SPXS"]
returns = {}
for equity in equities:
returns[equity] = self.RSI(equity, 13)
s_e = sorted([item for item in returns.items() if item[1] is not None], key = lambda x: x[1], reverse = True)
t3e = s_e[:1]
for i in self.HT50.keys():
if self.HT50[i] == 0:
self.HT50[i] = self.PT1
self.HTS50[i].append(t3e[0][0])
break
else:
equities = ["TECL", "STIP"]
returns = {}
for equity in equities:
returns[equity] = self.RSI(equity, 11)
s_e = sorted([item for item in returns.items() if item[1] is not None], key = lambda x: x[1], reverse = False)
t3e = s_e[:1]
for i in self.HT50.keys():
if self.HT50[i] == 0:
self.HT50[i] = self.PT1
self.HTS50[i].append(t3e[0][0])
break
else:
if self.RSI('TQQQ', 10) < 31:
equities = ["TECL", "SHY"]
returns = {}
for equity in equities:
returns[equity] = self.RSI(equity, 11)
s_e = sorted([item for item in returns.items() if item[1] is not None], key = lambda x: x[1], reverse = False)
t3e = s_e[:1]
for i in self.HT50.keys():
if self.HT50[i] == 0:
self.HT50[i] = self.PT1
self.HTS50[i].append(t3e[0][0])
break
else:
if self.RSI('UPRO', 10) < 31:
equities = ["UPRO", "SHY"]
returns = {}
for equity in equities:
returns[equity] = self.RSI(equity, 11)
s_e = sorted([item for item in returns.items() if item[1] is not None], key = lambda x: x[1], reverse = False)
t3e = s_e[:1]
for i in self.HT50.keys():
if self.HT50[i] == 0:
self.HT50[i] = self.PT1
self.HTS50[i].append(t3e[0][0])
break
else:
if self.CumReturn('TQQQ', 6) < -0.11:
self.BuythedipsV2()
else:
if self.Securities['QLD'].Price > self.SMA('QLD', 20):
equities = ["TECL", "STIP"]
returns = {}
for equity in equities:
returns[equity] = self.RSI(equity, 11)
s_e = sorted([item for item in returns.items() if item[1] is not None], key = lambda x: x[1], reverse = False)
t3e = s_e[:1]
for i in self.HT50.keys():
if self.HT50[i] == 0:
self.HT50[i] = self.PT1
self.HTS50[i].append(t3e[0][0])
break
else:
self.Substrategy5()
self.Substrategy6()
def BuythedipsV2(self):
if self.CumReturn('TQQQ', 5) > 0.055:
equities = ["UVXY", "SQQQ"]
returns = {}
for equity in equities:
returns[equity] = self.RSI(equity, 11)
s_e = sorted([item for item in returns.items() if item[1] is not None], key = lambda x: x[1], reverse = True)
t3e = s_e[:1]
for i in self.HT50.keys():
if self.HT50[i] == 0:
self.HT50[i] = self.PT1
self.HTS50[i].append(t3e[0][0])
break
if self.CumReturn('SQQQ', 1) > 0.028:
self.Substrategy1()
self.Substrategy2()
else:
self.HoldStocksBondsSOXLSHVTECLSTIP()
def Substrategy1(self):
equities = ["TECL", "UDN"]
returns = {}
for equity in equities:
returns[equity] = self.RSI(equity, 11)
s_e = sorted([item for item in returns.items() if item[1] is not None], key = lambda x: x[1], reverse = False)
t3e = s_e[:1]
for i in self.HT50.keys():
if self.HT50[i] == 0:
self.HT50[i] = self.PT1 * 0.5
self.HTS50[i].append(t3e[0][0])
break
def Substrategy2(self):
equities = ["TECL", "TMV"]
returns = {}
for equity in equities:
returns[equity] = self.RSI(equity, 11)
s_e = sorted([item for item in returns.items() if item[1] is not None], key = lambda x: x[1], reverse = True)
t3e = s_e[:1]
for i in self.HT50.keys():
if self.HT50[i] == 0:
self.HT50[i] = self.PT1 * 0.5
self.HTS50[i].append(t3e[0][0])
break
def HoldStocksBondsSOXLSHVTECLSTIP(self):
self.Substrategy3()
self.Substrategy4()
def Substrategy3(self):
equities = ["SOXL", "SHV"]
returns = {}
for equity in equities:
returns[equity] = self.RSI(equity, 11)
s_e = sorted([item for item in returns.items() if item[1] is not None], key = lambda x: x[1], reverse = False)
t3e = s_e[:1]
for i in self.HT50.keys():
if self.HT50[i] == 0:
self.HT50[i] = self.PT1 * 0.68
self.HTS50[i].append(t3e[0][0])
break
def Substrategy4(self):
equities = ["TECL", "STIP"]
returns = {}
for equity in equities:
returns[equity] = self.RSI(equity, 11)
s_e = sorted([item for item in returns.items() if item[1] is not None], key = lambda x: x[1], reverse = False)
t3e = s_e[:1]
for i in self.HT50.keys():
if self.HT50[i] == 0:
self.HT50[i] = self.PT1 * 0.32
self.HTS50[i].append(t3e[0][0])
break
def Substrategy5(self):
if self.SMADayRet('TLT', 20) > self.SMADayRet('UDN', 20):
equities = ["TLT", "SQQQ"]
returns = {}
for equity in equities:
returns[equity] = self.RSI(equity, 11)
s_e = sorted([item for item in returns.items() if item[1] is not None], key = lambda x: x[1], reverse = True)
t3e = s_e[:1]
for i in self.HT50.keys():
if self.HT50[i] == 0:
self.HT50[i] = self.PT1 * 0.5
self.HTS50[i].append(t3e[0][0])
break
else:
equities = ["UUP", "SQQQ"]
returns = {}
for equity in equities:
returns[equity] = self.RSI(equity, 10)
s_e = sorted([item for item in returns.items() if item[1] is not None], key = lambda x: x[1], reverse = False)
t3e = s_e[:1]
for i in self.HT50.keys():
if self.HT50[i] == 0:
self.HT50[i] = self.PT1 * 0.5
self.HTS50[i].append(t3e[0][0])
break
def Substrategy6(self):
equities = ["UGL", "SQQQ"]
returns = {}
for equity in equities:
returns[equity] = self.RSI(equity, 12)
s_e = sorted([item for item in returns.items() if item[1] is not None], key = lambda x: x[1], reverse = False)
t3e = s_e[:1]
for i in self.HT50.keys():
if self.HT50[i] == 0:
self.HT50[i] = self.PT1 * 0.5
self.HTS50[i].append(t3e[0][0])
break
def V15A(self):
if self.RSI('SPY', 6) > 75:
equities = ["UVXY", "VIXY"]
returns = {}
for equity in equities:
returns[equity] = self.RSI(equity, 5)
s_e = sorted([item for item in returns.items() if item[1] is not None], key = lambda x: x[1], reverse = False)
t3e = s_e[:1]
for i in self.HT50.keys():
if self.HT50[i] == 0:
self.HT50[i] = self.PT2
self.HTS50[i].append(t3e[0][0])
break
else:
if self.RSI('BIL', 5) < self.RSI('VCIT', 4):
for i in self.HT50.keys():
if self.HT50[i] == 0:
self.HT50[i] = self.PT2
self.HTS50[i].append('SOXL')
break
else:
if self.SMADayRet('VIXY', 5) > self.SMADayRet('BND', 5):
equities = ["UVXY", "VIXY", "IEF"]
returns = {}
for equity in equities:
returns[equity] = self.MaxDD(equity, 3)
s_e = sorted([item for item in returns.items() if item[1] is not None], key = lambda x: x[1], reverse = True)
t3e = s_e[:1]
for i in self.HT50.keys():
if self.HT50[i] == 0:
self.HT50[i] = self.PT2
self.HTS50[i].append(t3e[0][0])
break
else:
if self.SMADayRet('EDV', 11) < 0:
equities = ["SVXY", "TMF"]
returns = {}
for equity in equities:
returns[equity] = self.RSI(equity, 21)
s_e = sorted([item for item in returns.items() if item[1] is not None], key = lambda x: x[1], reverse = False)
t3e = s_e[:1]
for i in self.HT50.keys():
if self.HT50[i] == 0:
self.HT50[i] = self.PT2
self.HTS50[i].append(t3e[0][0])
break
else:
equities = ["SVXY", "TMV"]
returns = {}
for equity in equities:
returns[equity] = self.RSI(equity, 21)
s_e = sorted([item for item in returns.items() if item[1] is not None], key = lambda x: x[1], reverse = False)
t3e = s_e[:1]
for i in self.HT50.keys():
if self.HT50[i] == 0:
self.HT50[i] = self.PT2
self.HTS50[i].append(t3e[0][0])
break
def v41Pops(self):
if self.RSI('QQQE', 10) > 79:
equities = ["UVXY", "VIXY"]
returns = {}
for equity in equities:
returns[equity] = self.RSI(equity, 13)
s_e = sorted([item for item in returns.items() if item[1] is not None], key = lambda x: x[1], reverse = False)
t3e = s_e[:1]
for i in self.HT50.keys():
if self.HT50[i] == 0:
self.HT50[i] = self.PT3
self.HTS50[i].append(t3e[0][0])
break
else:
if self.RSI('VTV', 10) > 79:
equities = ["UVXY", "VIXY"]
returns = {}
for equity in equities:
returns[equity] = self.RSI(equity, 13)
s_e = sorted([item for item in returns.items() if item[1] is not None], key = lambda x: x[1], reverse = False)
t3e = s_e[:1]
for i in self.HT50.keys():
if self.HT50[i] == 0:
self.HT50[i] = self.PT3
self.HTS50[i].append(t3e[0][0])
break
else:
if self.RSI('VOX', 10) > 79:
equities = ["UVXY", "VIXY"]
returns = {}
for equity in equities:
returns[equity] = self.RSI(equity, 13)
s_e = sorted([item for item in returns.items() if item[1] is not None], key = lambda x: x[1], reverse = False)
t3e = s_e[:1]
for i in self.HT50.keys():
if self.HT50[i] == 0:
self.HT50[i] = self.PT3
self.HTS50[i].append(t3e[0][0])
break
else:
if self.MaxDD('SPY', 9) < 0:
equities = ["UVXY", "VIXY"]
returns = {}
for equity in equities:
returns[equity] = self.RSI(equity, 13)
s_e = sorted([item for item in returns.items() if item[1] is not None], key = lambda x: x[1], reverse = False)
t3e = s_e[:1]
for i in self.HT50.keys():
if self.HT50[i] == 0:
self.HT50[i] = self.PT3
self.HTS50[i].append(t3e[0][0])
break
else:
if self.RSI('TECL', 10) > 79:
equities = ["UVXY", "VIXY"]
returns = {}
for equity in equities:
returns[equity] = self.RSI(equity, 13)
s_e = sorted([item for item in returns.items() if item[1] is not None], key = lambda x: x[1], reverse = False)
t3e = s_e[:1]
for i in self.HT50.keys():
if self.HT50[i] == 0:
self.HT50[i] = self.PT3
self.HTS50[i].append(t3e[0][0])
break
else:
if self.RSI('VOOG', 10) > 79:
equities = ["UVXY", "VIXY"]
returns = {}
for equity in equities:
returns[equity] = self.RSI(equity, 13)
s_e = sorted([item for item in returns.items() if item[1] is not None], key = lambda x: x[1], reverse = False)
t3e = s_e[:1]
for i in self.HT50.keys():
if self.HT50[i] == 0:
self.HT50[i] = self.PT3
self.HTS50[i].append(t3e[0][0])
break
else:
if self.RSI('VOOV', 10) > 79:
equities = ["UVXY", "VIXY"]
returns = {}
for equity in equities:
returns[equity] = self.RSI(equity, 13)
s_e = sorted([item for item in returns.items() if item[1] is not None], key = lambda x: x[1], reverse = False)
t3e = s_e[:1]
for i in self.HT50.keys():
if self.HT50[i] == 0:
self.HT50[i] = self.PT3
self.HTS50[i].append(t3e[0][0])
break
else:
if self.RSI('XLP', 10) > 75:
equities = ["UVXY", "VIXY"]
returns = {}
for equity in equities:
returns[equity] = self.RSI(equity, 13)
s_e = sorted([item for item in returns.items() if item[1] is not None], key = lambda x: x[1], reverse = False)
t3e = s_e[:1]
for i in self.HT50.keys():
if self.HT50[i] == 0:
self.HT50[i] = self.PT3
self.HTS50[i].append(t3e[0][0])
break
else:
if self.RSI('TQQQ', 10) > 79:
equities = ["UVXY", "VIXY"]
returns = {}
for equity in equities:
returns[equity] = self.RSI(equity, 13)
s_e = sorted([item for item in returns.items() if item[1] is not None], key = lambda x: x[1], reverse = False)
t3e = s_e[:1]
for i in self.HT50.keys():
if self.HT50[i] == 0:
self.HT50[i] = self.PT3
self.HTS50[i].append(t3e[0][0])
break
else:
if self.RSI('XLY', 10) > 80:
equities = ["UVXY", "VIXY"]
returns = {}
for equity in equities:
returns[equity] = self.RSI(equity, 13)
s_e = sorted([item for item in returns.items() if item[1] is not None], key = lambda x: x[1], reverse = False)
t3e = s_e[:1]
for i in self.HT50.keys():
if self.HT50[i] == 0:
self.HT50[i] = self.PT3
self.HTS50[i].append(t3e[0][0])
break
else:
if self.RSI('FAS', 10) > 80:
equities = ["UVXY", "VIXY"]
returns = {}
for equity in equities:
returns[equity] = self.RSI(equity, 13)
s_e = sorted([item for item in returns.items() if item[1] is not None], key = lambda x: x[1], reverse = False)
t3e = s_e[:1]
for i in self.HT50.keys():
if self.HT50[i] == 0:
self.HT50[i] = self.PT3
self.HTS50[i].append(t3e[0][0])
break
else:
if self.RSI('SPY', 10) > 80:
equities = ["UVXY", "VIXY"]
returns = {}
for equity in equities:
returns[equity] = self.RSI(equity, 13)
s_e = sorted([item for item in returns.items() if item[1] is not None], key = lambda x: x[1], reverse = False)
t3e = s_e[:1]
for i in self.HT50.keys():
if self.HT50[i] == 0:
self.HT50[i] = self.PT3
self.HTS50[i].append(t3e[0][0])
break
else:
if self.CumReturn('TQQQ', 6) < -0.12:
if self.CumReturn('QQQ', 1) > 0.018:
equities = ["UVXY", "VIXY"]
returns = {}
for equity in equities:
returns[equity] = self.RSI(equity, 13)
s_e = sorted([item for item in returns.items() if item[1] is not None], key = lambda x: x[1], reverse = False)
t3e = s_e[:1]
for i in self.HT50.keys():
if self.HT50[i] == 0:
self.HT50[i] = self.PT3
self.HTS50[i].append(t3e[0][0])
break
else:
self.V15B()
else:
self.V15B()
def V15B(self):
if self.RSI('SPY', 6) > 75:
equities = ["UVXY", "VIXY"]
returns = {}
for equity in equities:
returns[equity] = self.RSI(equity, 5)
s_e = sorted([item for item in returns.items() if item[1] is not None], key = lambda x: x[1], reverse = False)
t3e = s_e[:1]
for i in self.HT50.keys():
if self.HT50[i] == 0:
self.HT50[i] = self.PT3
self.HTS50[i].append(t3e[0][0])
break
else:
if self.RSI('BIL', 5) < self.RSI('VCIT', 5):
for i in self.HT50.keys():
if self.HT50[i] == 0:
self.HT50[i] = self.PT3
self.HTS50[i].append('SOXL')
break
else:
if self.RSI('SVXY', 11) > 60:
equities = ["TMF", "BIL"]
returns = {}
for equity in equities:
returns[equity] = self.RSI(equity, 10)
s_e = sorted([item for item in returns.items() if item[1] is not None], key = lambda x: x[1], reverse = False)
t3e = s_e[:1]
for i in self.HT50.keys():
if self.HT50[i] == 0:
self.HT50[i] = self.PT3
self.HTS50[i].append(t3e[0][0])
break
else:
if self.SMADayRet('VIXM', 10) > self.SMADayRet('SVXY', 5):
equities = ["UVXY", "VIXY", "IEF"]
returns = {}
for equity in equities:
returns[equity] = self.MaxDD(equity, 3)
s_e = sorted([item for item in returns.items() if item[1] is not None], key = lambda x: x[1], reverse = True)
t3e = s_e[:1]
for i in self.HT50.keys():
if self.HT50[i] == 0:
self.HT50[i] = self.PT3
self.HTS50[i].append(t3e[0][0])
break
else:
if self.SMADayRet('EDV', 11) < 0:
equities = ["SVXY", "TMF"]
returns = {}
for equity in equities:
returns[equity] = self.RSI(equity, 21)
s_e = sorted([item for item in returns.items() if item[1] is not None], key = lambda x: x[1], reverse = False)
t3e = s_e[:1]
for i in self.HT50.keys():
if self.HT50[i] == 0:
self.HT50[i] = self.PT3
self.HTS50[i].append(t3e[0][0])
break
else:
equities = ["SVXY", "TMV"]
returns = {}
for equity in equities:
returns[equity] = self.RSI(equity, 21)
s_e = sorted([item for item in returns.items() if item[1] is not None], key = lambda x: x[1], reverse = False)
t3e = s_e[:1]
for i in self.HT50.keys():
if self.HT50[i] == 0:
self.HT50[i] = self.PT3
self.HTS50[i].append(t3e[0][0])
break
def ExecuteTrade(self):
group = {
'HTS': [self.HTS50[i][0] if len(self.HTS50[i]) == 1 else self.HTS50[i] for i in self.HTS50],
'HT': [self.HT50[i] for i in self.HT50]
}
df = pd.DataFrame(group)
df = pd.concat([df])
df['HTS'] = df['HTS'].astype(str)
result = df.groupby(['HTS']).sum().reset_index()
for equity in self.equities:
if all(not pd.isnull(result.iloc[i, 0]) and not equity == result.iloc[i, 0] for i in range(len(result))):
if self.Portfolio[equity].HoldStock:
self.Liquidate(equity)
output = "*****"
for i in range(len(result)):
if result.iloc[i, 0]:
percentage = round(result.iloc[i, 1] * 100, 2)
output += "{}: {}% - ".format(result.iloc[i, 0], percentage)
output = output.rstrip(" - ")
self.Log(output)
for i in range(len(result)):
if not result.iloc[i, 1] == 0 and not result.iloc[i, 0] == 'BIL':
percentage_equity = self.Portfolio[result.iloc[i, 0]].HoldingsValue / self.Portfolio.TotalPortfolioValue
quantity = (result.iloc[i, 1] - percentage_equity) * self.Portfolio.TotalPortfolioValue / self.Securities[result.iloc[i, 0]].Price
if result.iloc[i, 1] < percentage_equity and abs(result.iloc[i, 1] / percentage_equity - 1) > self.buffer_pct:
self.SetHoldings(result.iloc[i, 0], result.iloc[i, 1])
#self.MarketOnCloseOrder(result.iloc[i, 0], quantity)
else:
pass
for i in range(len(result)):
if not result.iloc[i, 1] == 0 and not result.iloc[i, 0] == 'BIL':
percentage_equity = self.Portfolio[result.iloc[i, 0]].HoldingsValue / self.Portfolio.TotalPortfolioValue
quantity = (result.iloc[i, 1] - percentage_equity) * self.Portfolio.TotalPortfolioValue / self.Securities[result.iloc[i, 0]].Price
if result.iloc[i, 1] > percentage_equity and abs(percentage_equity / result.iloc[i, 1] - 1) > self.buffer_pct:
self.SetHoldings(result.iloc[i, 0], result.iloc[i, 1])
#self.MarketOnCloseOrder(result.iloc[i, 0], quantity)
else:
pass
self.HT50 = {str(i).zfill(2): 0 for i in range(1, 21)}
self.HTS50 = {str(i).zfill(2): [] for i in range(1, 21)}