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CBOE Volatility Index (VIX) time-series dataset including daily open, close, high and low.
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README.md [dataflows][m]: integrate dataflows within pipeline specs Oct 16, 2018
datapackage.json
finance_vix_flow.py
pipeline-spec.yaml

README.md

CBOE Volatility Index (VIX) time-series dataset including daily open, close, high and low. The CBOE Volatility Index (VIX) is a key measure of market expectations of near-term volatility conveyed by S&P 500 stock index option prices introduced in 1993.

Data

From the VIX FAQ:

In 1993, the Chicago Board Options Exchange® (CBOE®) introduced the CBOE Volatility Index®, VIX®, and it quickly became the benchmark for stock market volatility. It is widely followed and has been cited in hundreds of news articles in the Wall Street Journal, Barron's and other leading financial publications. Since volatility often signifies financial turmoil, VIX is often referred to as the "investor fear gauge".

VIX measures market expectation of near term volatility conveyed by stock index option prices. The original VIX was constructed using the implied volatilities of eight different OEX option series so that, at any given time, it represented the implied volatility of a hypothetical at-the-money OEX option with exactly 30 days to expiration.

The New VIX still measures the market's expectation of 30-day volatility, but in a way that conforms to the latest thinking and research among industry practitioners. The New VIX is based on S&P 500 index option prices and incorporates information from the volatility "skew" by using a wider range of strike prices rather than just at-the-money series.

Preparation

You will need Python 3.6 or greater and dataflows library to run the script

To update the data run the process script locally:

# Install dataflows
pip install dataflows

# Run the script
python flows/finance-vix.py

TODO

  • Incorporate computed historical data (1990-2003)
  • Consider incorporating VOX data

License

No obvious statement on historical data page. Given size and factual nature of the data and its source from a US company would imagine this was public domain and as such have licensed the Data Package under the Public Domain Dedication and License (PDDL).

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