| Overall Statistics |
|
Total Orders 0 Average Win 0% Average Loss 0% Compounding Annual Return 0% Drawdown 0% Expectancy 0 Start Equity 100000 End Equity 100000 Net Profit 0% Sharpe Ratio 0 Sortino Ratio 0 Probabilistic Sharpe Ratio 0% Loss Rate 0% Win Rate 0% Profit-Loss Ratio 0 Alpha 0 Beta 0 Annual Standard Deviation 0 Annual Variance 0 Information Ratio 0 Tracking Error 0 Treynor Ratio 0 Total Fees $0.00 Estimated Strategy Capacity $0 Lowest Capacity Asset Portfolio Turnover 0% |
# region imports
from AlgorithmImports import *
# endregion
class SquareBrownJellyfish(QCAlgorithm):
def Initialize(self):
self.SetStartDate(2024, 5, 9)
self.SetEndDate(2024, 5, 9)
self.SetCash(100000)
self.AddUniverse(self.MyCoarseFilterFunction)
self.volumeBySymbol = {}
def MyCoarseFilterFunction(self, coarse): # and f.volume > 1000000
filtered = [f for f in coarse if f.has_fundamental_data and f.price > 10 and f.operation_ratios.roe.one_year > 0.1 and f.market_cap > 300000000 and f.earning_ratios.diluted_eps_growth.one_year > 0.1]
for x in filtered:
if x.Symbol not in self.volumeBySymbol:
self.volumeBySymbol[x.Symbol] = SymbolData(x.Symbol, self)
self.volumeBySymbol[x.Symbol].Update(x.EndTime, x.price, x.volume)
# sortBySMAVolume = sorted(self.volumeBySymbol.items(), key=lambda x: x[1].sma50.Current.Value, reverse=True)[:1000]
symbols = [x[0] for x in self.volumeBySymbol.items()]
result = []
for symbol in symbols:
if self.volumeBySymbol.get(symbol).vol.current.value > 1000000 and self.volumeBySymbol.get(symbol).sma50.current.value > self.volumeBySymbol.get(symbol).sma200.current.value and self.volumeBySymbol.get(symbol).rocp.current.value > 20:
result.append(symbol.Value)
self.Debug("Symbol : {}, rocp : {}".format(symbol.value, self.volumeBySymbol.get(symbol).rocp.current.value))
# self.Debug("Symbol : {}, price : {}".format(symbol.value, self.volumeBySymbol.get(symbol).temp.current.value))
self.Debug(result)
return symbols
class SymbolData:
def __init__(self,symbol,algo):
self.algo = algo
self.symbol = symbol
self.sma50 = SimpleMovingAverage(50)
self.sma200 = SimpleMovingAverage(200)
self.rocp = RateOfChangePercent(21)
self.vol = SimpleMovingAverage(90)
self.temp = 0
history = algo.History(symbol,201,Resolution.Daily)
if not history.empty:
for time,row in history.loc[symbol].iterrows():
self.sma50.Update(time,row['close'])
self.sma200.Update(time,row['close'])
self.rocp.Update(time, row['close'])
self.vol.Update(time, row['volume'])
def Update(self,time,price, vol):
self.sma50.Update(time, price)
self.sma200.Update(time, price)
self.rocp.Update(time, price)
self.vol.Update(time, vol)