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
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
 
import datetime
import numpy as np
import pandas as pd
import mlfinlab as ml
from scipy import stats

class ModulatedHorizontalAutosequencers(QCAlgorithm):

    def Initialize(self):
        self.SetStartDate(2019, 1, 18)  # Set Start Date
        self.SetEndDate(2019, 1, 19)
        self.SetCash(100000)  # Set Strategy Cash
        self.AddEquity("SPY", Resolution.Tick)
        self.start = datetime.date(2019, 1, 15)
        self.end = datetime.date(2019, 1, 17)
        self.features = ["open", "high", "low", "close", "volume"]
        self.estado = True

    def OnData(self, data):
        if self.estado:
            h1 = self.History(self.Securities.Keys, 
                            self.start, 
                            self.end, 
                            Resolution.Tick)
            
            data = h1[h1.suspicious == False]
            data = data[["lastprice", "quantity"]]
            data = data.loc["SPY R735QTJ8XC9X"]
            
            df = pd.DataFrame()
            df["date_time"] = data.index.values
            df["price"] = data.lastprice.values
            df["volume"] = data.quantity.values
            
            df.to_csv('raw_tick_data.csv', index=False)
            
            volume = ml.data_structures.get_volume_bars('raw_tick_data.csv',
                                            threshold=20000,
                                            batch_size=1000000,
                                            verbose=False)
            
            self.Debug(volume.head())

            self.estado = False