| Overall Statistics |
|
Total Trades 369 Average Win 0.94% Average Loss -0.25% Compounding Annual Return 12.275% Drawdown 6.500% Expectancy 2.056 Net Profit 140.765% Sharpe Ratio 1.064 Probabilistic Sharpe Ratio 53.834% Loss Rate 36% Win Rate 64% Profit-Loss Ratio 3.77 Alpha 0.085 Beta 0.015 Annual Standard Deviation 0.082 Annual Variance 0.007 Information Ratio -0.091 Tracking Error 0.173 Treynor Ratio 5.756 Total Fees $1045.23 Estimated Strategy Capacity $13000000.00 Lowest Capacity Asset BIL TT1EBZ21QWKL Portfolio Turnover 4.42% |
from AlgorithmImports import *
from datetime import datetime, timedelta
class CustomDataWeighAlgorithm(QCAlgorithm):
def Initialize(self):
self.SetStartDate(2016,1, 1)
self.SetEndDate(2023, 8, 1)
self.SetCash(100000)
# Define the symbol and "type" of our generic data:
self.AddData(Weigh, "Weigh")
self.symbols = "SPY", "SPXL", "UVXY", "SSO","BIL","TQQQ","QLD","UUP","SOXL"
# Inizializza un dizionario per memorizzare le allocazioni iniziali degli asset
#self.AddRiskManagement(MaximumDrawdownPercentPerSecurity(0.10))
# Aggiungi tutti gli asset con risoluzione giornaliera (daily)
for symbol in self.symbols:
self.AddEquity(symbol, Resolution.Daily)
def OnData(self, data):
if not data.ContainsKey("Weigh"):
return
index_data = data["Weigh"]
#self.AddRiskManagement(MaximumDrawdownPercentPerSecurity(0.10))
# Stampa i valori degli indici
self.Debug(f"Data Time: {index_data.Time}, SPY: {index_data['SPY']}")
self.Debug(f"Data Time: {index_data.Time}, SPXL: {index_data['SPXL']}")
self.Debug(f"Data Time: {index_data.Time}, UVXY: {index_data['UVXY']}")
self.Debug(f"Data Time: {index_data.Time}, SSO: {index_data['SSO']}")
self.Debug(f"Data Time: {index_data.Time}, BIL: {index_data['BIL']}")
self.Debug(f"Data Time: {index_data.Time}, TQQQ: {index_data['TQQQ']}")
self.Debug(f"Data Time: {index_data.Time}, QLD: {index_data['QLD']}")
self.Debug(f"Data Time: {index_data.Time}, USD: {index_data['USD']}")
self.Debug(f"Data Time: {index_data.Time}, SOXL: {index_data['SOXL']}")
#self.SetHoldings("MDY",index_data['QQQ'])
self.SetHoldings("UVXY",index_data['UVXY']*0.95)
self.SetHoldings("SPY",index_data['SSO']*0.95)
self.SetHoldings("BIL",index_data['BIL']*0.95)
self.SetHoldings("QQQ",index_data['QLD']*0.95)
self.SetHoldings("SMH",index_data['USD']*0.95)
# self.SetHoldings("QQQ",index_data['QQQ'])
def BeforeClose(self):
# Put the code you want to execute before market close here
pass
class Weigh(PythonData):
'''Weigh Custom Data Class'''
def GetSource(self, config, date, isLiveMode):
return SubscriptionDataSource("https://www.dropbox.com/scl/fi/c8fclsnt05pyxp5j6rzf0/Weightss_0.csv?rlkey=9259nmjn0xp2u6pnsui9ad1kt&dl=1", SubscriptionTransportMedium.RemoteFile)
def Reader(self, config, line, date, isLiveMode):
if not (line.strip() and line[0].isdigit()):
return None
index = Weigh()
index.Symbol = config.Symbol
try:
# Example File Format:
data = line.split(',')
index.Time = datetime.strptime(data[0], "%Y-%m-%d")
index.EndTime = index.Time + timedelta(days=1)
index.Value = data[4]
index["SPY"] = float(data[1])
index["SPXL"] = float(data[2])
index["UVXY"] = float(data[3])
index["SSO"] = float(data[4])
index["BIL"] = float(data[5])
index["TQQQ"] = float(data[6])
index["QLD"] = float(data[7])
index["USD"] = float(data[8])
index["SOXL"] = float(data[9])
# index["QQQ"] = float(data[5])
except ValueError as e:
self.Debug(f"Errore nella lettura dei dati: {str(e)}")
return None
return index