| Overall Statistics |
|
Total Trades 253 Average Win 0.85% Average Loss -0.24% Compounding Annual Return 25.313% Drawdown 8.700% Expectancy 0.493 Net Profit 16.903% Sharpe Ratio 2.215 Probabilistic Sharpe Ratio 83.866% Loss Rate 67% Win Rate 33% Profit-Loss Ratio 3.48 Alpha 0.258 Beta 0.017 Annual Standard Deviation 0.118 Annual Variance 0.014 Information Ratio 0.183 Tracking Error 0.406 Treynor Ratio 15.584 Total Fees $1597.57 |
import pandas as pd
import numpy as np
from io import StringIO
class RedditStockSentiment(QCAlgorithm):
def Initialize(self):
self.SetStartDate(2020, 1, 1) # Set Start Date
self.SetCash(100000) # Set Strategy Cash
self.tickers = ["SPCE", "LULU", "CCL", "SDC"]
for stock in self.tickers:
self.AddEquity(stock, Resolution.Hour)
self.AddRiskManagement(TrailingStopRiskManagementModel(0.04))
self.lastday = -1
csv = self.Download("https://www.dropbox.com/s/qydhy62v08tw4em/Reddit_Sentiment_Equity.csv?dl=1")
self.df = pd.read_csv(StringIO(csv))
def OnData(self, data):
algYear = self.Time.year
algMonth = self.Time.month
algDay = self.Time.day
if algDay == self.lastday:
return
self.lastday = algDay
for row in self.df.itertuples():
date = row[-1]
year = date[0:4]
month = date[5:7]
day = date[8:10]
if (int(year) != algYear) or (int(month) != algMonth) or (int(day) != algDay):
continue
stock = str(row[1])
averageSentiment = float(row[3])
numberOfComments = int(row[2])
score = int(row[5])
if(averageSentiment >= 0.1) and not self.Portfolio[stock].IsLong:
self.SetHoldings(stock, 0.25, True)
if(averageSentiment <= -0.1) and not self.Portfolio[stock].IsShort:
self.SetHoldings(stock, -0.07, True)
if (-0.1 < averageSentiment < 0.1):
self.Liquidate(stock)