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How do you import Quandl Spot VIX data in the research environment?

I've attached a copy of the notebook I'm trying to assemble.  The vix futures is returning an empty dataframe and I can't get the Quandl import to work properly.  Can anyone shine some light on the solution?

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The Quandl data source stopped supporting the VIX but you can access it from the CBOE website directly with the self.Download() API.
http://www.cboe.com/publish/scheduledtask/mktdata/datahouse/vixcurrent.csv

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The material on this website is provided for informational purposes only and does not constitute an offer to sell, a solicitation to buy, or a recommendation or endorsement for any security or strategy, nor does it constitute an offer to provide investment advisory services by QuantConnect. In addition, the material offers no opinion with respect to the suitability of any security or specific investment. QuantConnect makes no guarantees as to the accuracy or completeness of the views expressed in the website. The views are subject to change, and may have become unreliable for various reasons, including changes in market conditions or economic circumstances. All investments involve risk, including loss of principal. You should consult with an investment professional before making any investment decisions.


I tried qb.Download() and pd.read_csv() but they're both returning a name error.  I've attached a new notebook showing the error.  I even went to the CBOE website to copy/paste the cvs file link just in case but that didn't do the trick either. I searched for the error online but I admit I don't know enough about websites to understand what they're talking about. Should I wait for the rollout of the upgraded notebook?

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Hi Stephen Hyer 

Sorry about the long wait.

We have recently added CBOE data to our data library.
Please check out the docs, under Alternative Data CBOE, for details.

Below you can find a working notebook code.

%matplotlib inline
from QuantConnect.Data.Custom.CBOE import CBOE
import matplotlib.pyplot as plt
import pandas as pd
import numpy as np

# Create an instance
qb = QuantBook()

# Print the data using Download
# Works with CBOE link
print(qb.Download("http://www.cboe.com/publish/scheduledtask/mktdata/datahouse/vixcurrent.csv"))
# Recommend using QC Cache
print(qb.Download("http://cache.quantconnect.com/alternative/cboe/vix.csv"))

# Select asset data
cboeVix = qb.AddData(CBOE,"VIX").Symbol
h1 = qb.History([cboeVix], 50, Resolution.Daily)
h1.loc[cboeVix].plot()

 

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The material on this website is provided for informational purposes only and does not constitute an offer to sell, a solicitation to buy, or a recommendation or endorsement for any security or strategy, nor does it constitute an offer to provide investment advisory services by QuantConnect. In addition, the material offers no opinion with respect to the suitability of any security or specific investment. QuantConnect makes no guarantees as to the accuracy or completeness of the views expressed in the website. The views are subject to change, and may have become unreliable for various reasons, including changes in market conditions or economic circumstances. All investments involve risk, including loss of principal. You should consult with an investment professional before making any investment decisions.


In playing with that code, RVX appears to be working thankfully.  Is there any chance that other CBOE data might be available in the future like SKEW, VIN/VIF or any other interesting ones?

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Hi DanRock ,

Thank you for the suggestion.
I have notified the Data Team and we look into it ASAP.

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The material on this website is provided for informational purposes only and does not constitute an offer to sell, a solicitation to buy, or a recommendation or endorsement for any security or strategy, nor does it constitute an offer to provide investment advisory services by QuantConnect. In addition, the material offers no opinion with respect to the suitability of any security or specific investment. QuantConnect makes no guarantees as to the accuracy or completeness of the views expressed in the website. The views are subject to change, and may have become unreliable for various reasons, including changes in market conditions or economic circumstances. All investments involve risk, including loss of principal. You should consult with an investment professional before making any investment decisions.


Just to point to some "interesting" ones I mentioned that people might find insight, the following link has the strategy benchmarks.

http://www.cboe.com/products/strategy-benchmark-indexes

Thanks

 

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The material on this website is provided for informational purposes only and does not constitute an offer to sell, a solicitation to buy, or a recommendation or endorsement for any security or strategy, nor does it constitute an offer to provide investment advisory services by QuantConnect. In addition, the material offers no opinion with respect to the suitability of any security or specific investment. QuantConnect makes no guarantees as to the accuracy or completeness of the views expressed in the website. The views are subject to change, and may have become unreliable for various reasons, including changes in market conditions or economic circumstances. All investments involve risk, including loss of principal. You should consult with an investment professional before making any investment decisions.


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