Overall Statistics Total Trades 1 Average Win 0% Average Loss 0% Compounding Annual Return 10.037% Drawdown 10.100% Expectancy 0 Net Profit 19.475% Sharpe Ratio 0.842 Loss Rate 0% Win Rate 0% Profit-Loss Ratio 0 Alpha 0.118 Beta -0.774 Annual Standard Deviation 0.122 Annual Variance 0.015 Information Ratio 0.679 Tracking Error 0.122 Treynor Ratio -0.133 Total Fees \$2.26
```import numpy as np
from datetime import datetime, timedelta

### <summary>
### Basic template algorithm simply initializes the date range and cash. This is a skeleton
### framework you can use for designing an algorithm.
### </summary>
class BasicTemplateAlgorithm(QCAlgorithm):
'''Basic template algorithm simply initializes the date range and cash'''

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.'''

self.SetStartDate(2017, 2, 1)  #Set Start Date
self.SetEndDate(2018,12,11)    #Set End Date
self.SetCash(100000)           #Set Strategy Cash
# Find more symbols here: http://quantconnect.com/data
# KG Begin- Line below is the  problem
# KG end
# # define a 10-period RSI indicator with indicator constructor
# self.rsi = RelativeStrengthIndex(10, MovingAverageType.Simple)
# # register the daily data of "SPY" to automatically update the indicator
# self.RegisterIndicator("SPY", self.rsi, Resolution.Daily)

## KG code begin

# define our 30 minute trade bar consolidator. we can
# access the 30 minute bar from the DataConsolidated events

# attach our event handler. The event handler is a function that will
# be called each time we produce a new consolidated piece of data.
thirtyMinuteConsolidator.DataConsolidated += self.ThirtyMinuteBarHandler

# this call adds our 30-minute consolidator to

## KG code end

def ThirtyMinuteBarHandler(self, sender, bar):