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Hi,

Is there documentation for QuantBook API methods and members?

I am trying to play around with "VIX predicts stock index returns" strategy from the Strategy library in a research notebook. When I try to execute this cell (QuantBook object qb is initialized in a previous cell):

import numpy as np

from QuantConnect.Python import PythonQuandl



oef = qb.AddEquity("OEF", Resolution.Daily)

vix = 'CBOE/VIX'

qb.AddData(QuandlVix, self.vix, Resolution.Daily)

window = qb.RollingWindow[float](252*2)

hist = qb.History([self.vix], 1000, Resolution.Daily)

for close in hist.loc[self.vix]['vix close']:

    self.window.Add(close)

I get a "NameError: name 'QuandlVix' is not defined" when I run this. Any suggestions?

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Accepted Answer

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Pro ,

Also, when I run the backtest for this strategy

class VIXPredictsStockIndexReturns(QCAlgorithm):



    def Initialize(self):



        self.SetStartDate(2006, 1, 1)  

        self.SetEndDate(2018, 8, 1)    

        self.SetCash(100000)          

        self.AddEquity("OEF", Resolution.Daily)

        self.vix = 'CBOE/VIX'

        self.AddData(QuandlVix, self.vix, Resolution.Daily)

        self.window = RollingWindow[float](252*2)

        hist = self.History([self.vix], 1000, Resolution.Daily)

        for close in hist.loc[self.vix]['vix close']:

            self.window.Add(close)





    def OnData(self, data):

        if not data.ContainsKey(self.vix): return

        self.window.Add(self.Securities[self.vix].Price)

        if not self.window.IsReady: return 

        history_close = [i for i in self.window]



        if self.Securities[self.vix].Price > np.percentile(history_close, 90):

            self.SetHoldings("OEF", 1)

        elif self.Securities[self.vix].Price < np.percentile(history_close, 10):

            self.SetHoldings("OEF", -1)

        

    

class QuandlVix(PythonQuandl):

    

    def __init__(self):

        self.ValueColumnName = "VIX Close"

I am a little unsure of how the SetHoldings function works, because the first orders that are executed in this backtest are sell orders. Can I develop short positions in my portfolio even though I might not have "OEF" to begin with? Also, what do the +1 and -1 in the SetHoldings parameters mean? Do they mean 1 unit of security? Because the orders that get executed are orders with quantity greater than 1?

Adam W

3.8k Pro ,

The API for QuantBook behaves almost identically to the typical algorithm API, with the exception of certain methods. For the first error, don't forget to define QuandlVix before you call it.

Take a look here for docs on position sizing. The sign indicates long/short, and the number indicates percentage of unlevered buying power. For instance, SetHoldings('OEF', 1) means to allocate 100% of your portfolio value into OEF. To calculate units of securities instead, use CalculateOrderQuantity().

Yes, you can short a stock without holding it. Conceptually, this means that you are "borrowing" the stock from the broker with the agreement that you will "re-purchase" the stock from market when closing the short position in the future.

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