| Overall Statistics |
|
Total Trades 9 Average Win 0.20% Average Loss -0.35% Compounding Annual Return -19.390% Drawdown 29.500% Expectancy -0.480 Net Profit -19.390% Sharpe Ratio -0.476 Loss Rate 67% Win Rate 33% Profit-Loss Ratio 0.56 Alpha -0.448 Beta 19.41 Annual Standard Deviation 0.282 Annual Variance 0.08 Information Ratio -0.533 Tracking Error 0.282 Treynor Ratio -0.007 Total Fees $0.00 |
import pandas
import numpy as np
### <summary>
### Simple RSI Strategy intended to provide a minimal algorithm example using
### one indicator
### </summary>
class RSIAlgorithm(QCAlgorithm):
def Initialize(self):
'''Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized.'''
# Set our main strategy parameters
self.SetStartDate(2013,1, 1) # Set Start Date
self.SetEndDate(2014,1,1) # Set End Date
self.SetCash(10000) # Set Strategy Cash
RSI_Period = 14 # RSI Look back period
self.RSI_OB = 60 # RSI Overbought level
self.RSI_OS = 40 # RSI Oversold level
self.Allocate = 2 # Percentage of captital to allocate
self.tolerance = 0.00015
self.spread = 20/10000
self.first_stg_up = 0
self.first_stg_down = 0
self.trend = 0
self.trend_n = 0
self.symbol = "EURUSD"
## Rename variables for percentages to make more readable and less confusing
self.tpPercent = 20/10000
self.slPercent = 10/10000
## Reassign these to be variables for Order Tickets
self.tp = None
self.sl = None
self.holdings = 0
self.quant = 10000
# Find more symbols here: http://quantconnect.com/data
self.AddForex("EURUSD", Resolution.Hour)
self.RSI_Ind = self.RSI("EURUSD", RSI_Period)
self.bb_ind = self.BB("EURUSD", 20, 1, MovingAverageType.Simple);
self.slow = self.SMA("EURUSD", 20, Resolution.Hour)
self.fast = self.SMA("EURUSD", 7, Resolution.Hour)
# Ensure that the Indicator has enough data before trading,.
self.SetWarmUp(20)
def OnData(self, data):
## Assign to self.trend, as just 'trend' is not referred to elsewhere
self.trend =1
if not self.Portfolio.Invested and not self.IsWarmingUp:
# If not, we check the RSI Indicator
if self.trend == 1 :
#
## you need to assign to self.order or else variable will remain local
self.order = self.MarketOrder(self.symbol, self.quant)
## you need to define fxClose or else the orders won't be properly placed
fxClose = data[self.symbol].Close
## you need to replace sl with self.sl, as you want these to be global variables
## otherwise, they will not be accessible outside of OnData
self.sl = self.StopMarketOrder(self.symbol, -self.quant, fxClose - self.slPercent)
self.tp = self.LimitOrder(self.symbol, -self.quant, fxClose + self.tpPercent)
#if self.RSI_Ind.Current.Value < self.RSI_OS:
# Buy Apple
# self.SetHoldings("EURUSD", self.Allocate)
else:
if self.trend_n == -1:
# Sell Apple
self.Liquidate("EURUSD")
def OnOrderEvent(self, orderEvent):
## This will check for the boolean value of whether or not the order has been filled
if not (orderEvent.Status == 'Filled'):
return
## python doesn't support null. Instead, check for None
if (self.tp is None) or (self.sl is None):
return
filledOrderid = orderEvent.OrderId
if self.tp == filledOrderId:
self.sl.Cancel()
if self.sl == filledOrderId:
self.tp.Cancel()