This chapter is about the analysis of data and investment strategies related to the EURO STOXX 50 and VSTOXX indexes. It uses public data sources (“open data”) and draws heavily on the capabilities of the Python library pandas for data analytics.
The chapter has two major goals. First, it reproduces the stylized fact that stock indexes and volatility indexes in general are negatively correlated. This suggests that (products based on) volatility indexes are a means to hedge market risk resulting from stock indexes. The question, however, is how to best exploit the negative correlation in asset allocation terms. Therefore, the second goal is to illustrate the benefits for equity investors resulting from constant proportion investment strategies involving a volatility index like the VSTOXX. For simplicity, the respective analysis assumes that a direct investment in the VSTOXX is possible. This replicates results as found, for example, in the study by Guobuzaite and Martellini (2012).
4.2 Retrieving Base Data
This section shows how to retrieve and store historical daily closing data for the EURO STOXX 50 index and the VSTOXX volatility index. We mainly work with pandas in the following:
4.2.1 EURO STOXX 50 Data
On the website http://stoxx.com of the index provider STOXX Limited, you find text files containing historical ...