| Overall Statistics |
|
Total Orders 1024 Average Win 0.15% Average Loss -0.09% Compounding Annual Return -5.792% Drawdown 4.400% Expectancy -0.048 Start Equity 100000 End Equity 97791.37 Net Profit -2.209% Sharpe Ratio -1.691 Sortino Ratio -3.233 Probabilistic Sharpe Ratio 11.428% Loss Rate 66% Win Rate 34% Profit-Loss Ratio 1.77 Alpha -0.12 Beta 0.168 Annual Standard Deviation 0.056 Annual Variance 0.003 Information Ratio -2.643 Tracking Error 0.095 Treynor Ratio -0.56 Total Fees $1409.69 Estimated Strategy Capacity $4200000.00 Lowest Capacity Asset AAPL R735QTJ8XC9X Portfolio Turnover 372.08% |
from AlgorithmImports import *
class TopCryptoStrategy(QCAlgorithm):
def Initialize(self):
self.SetStartDate(2023, 12, 10) # Set Start Date
self.SetCash(100000) # Set Strategy Cash
# Define the symbols
self.crypto_symbols = ["BTC"]
self.stock_symbols = ["AAPL"]
self.SetBenchmark("SPY")
# Attempt to add each cryptocurrency and stock
self.active_symbols = []
'''for symbol in self.crypto_symbols:
try:
self.AddCrypto(symbol, Resolution.Daily)
self.active_symbols.append(symbol)
except Exception as e:
self.Debug(f"Unable to add symbol: {symbol}. Exception: {e}")'''
for symbol in self.stock_symbols:
try:
self.AddEquity(symbol, Resolution.MINUTE)
self.active_symbols.append(symbol)
except Exception as e:
self.Debug(f"Unable to add symbol: {symbol}. Exception: {e}")
# Define the technical indicators
self.supertrend1 = {}
self.supertrend2 = {}
#self.rsi = {}
#self.ema100 = {}
#self.weekly_twap = {}
self.entry_prices = {}
for symbol in self.active_symbols:
self.supertrend1[symbol] = self.STR(symbol, 10, 2.5, MovingAverageType.Wilders)
self.supertrend2[symbol] = self.STR(symbol, 10, 3, MovingAverageType.Wilders)
#self.rsi[symbol] = self.RSI(symbol, 10, MovingAverageType.Wilders, Resolution.Daily)
#self.ema100[symbol] = self.EMA(symbol, 100, Resolution.Daily)
#self.weekly_twap[symbol] = self.WeeklyTwap(symbol, 5)
self.entry_prices[symbol] = None
self.SetWarmUp(100, Resolution.MINUTE) # Warm up period for 100 days
def WeeklyTwap(self, symbol, num_weeks):
twap = self.SMA(symbol, num_weeks * 5, Resolution.MINUTE) # Assuming 5 trading days per week
return twap
def OnData(self, data):
if self.IsWarmingUp:
return
for symbol in self.active_symbols:
if not data.Bars.ContainsKey(symbol):
continue
bar = data.Bars[symbol]
# Get current values
current_price = bar.Close
supertrend1 = self.supertrend1[symbol].Current.Value
supertrend2 = self.supertrend2[symbol].Current.Value
#rsi = self.rsi[symbol].Current.Value
#ema100 = self.ema100[symbol].Current.Value
#weekly_twap = self.weekly_twap[symbol].Current.Value
# Define factor based on asset type
#factor = 1.2 if symbol in self.crypto_symbols else 1.04
# Entry condition
if self.entry_prices[symbol] is None:
if (current_price > supertrend1 and
current_price > supertrend2 ): # Use appropriate factor
self.Debug(f"{symbol}: Supertrend1={supertrend1}, Supertrend2={supertrend2}")
self.SetHoldings(symbol, 0.5)
self.entry_prices[symbol] = current_price
# Exit condition
elif current_price < supertrend1 and current_price < supertrend2:
self.Liquidate(symbol)
self.entry_prices[symbol] = None