Overall Statistics
Total Trades
0
Average Win
0%
Average Loss
0%
Compounding Annual Return
0%
Drawdown
0%
Expectancy
0
Net Profit
0%
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
 
import numpy as np

### <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 KalmanFilterAlgorithm(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(2018, 11, 28)  #Set Start Date
        self.SetEndDate(2018, 11, 30)    #Set End Date  
        self.SetCash(25000)           #Set Strategy Cash
        # Find more symbols here: http://quantconnect.com/data
        self.symbol = "NVDA"
        self.AddEquity(self.symbol, Resolution.Minute) 

        self.heikin_ashi = HeikinAshi()
        
    
    def OnData(self, data): 
        
        if not data.ContainsKey(self.symbol): return
    
        if data[self.symbol] is None:
            self.Log("oh shit " + self.symbol + " data is none at " + str(self.Time)) 
            return
    
        self.heikin_ashi.Update(data[self.symbol]) 
        
        if self.heikin_ashi.IsReady: 
    
            lastPrice = float(str(self.heikin_ashi.Close))