Economics at your fingertips  

Measuring and trading volatility on the US stock market: A regime switching approach

Jose Dapena (), Juan A. Serur and Julián R. Siri

No 659, CEMA Working Papers: Serie Documentos de Trabajo. from Universidad del CEMA

Abstract: The volatility premium is a well-documented phenomenon, which can be approximated by the difference between the previous month level of the VIX Index and the rolling 30-day close-to-close volatility. Along with the literature, we show evidence that VIX is generally above the 30-day rolling volatility giving rise to the volatility premium, so selling volatility can become a profitable trading strategy as long as proper risk management is under place. As a contribution, we introduced the implementation of a Hidden Markov Model (HMM), identifying two states of the nature and showing that the volatility premium undergoes temporal breaks in its behavior. Based on this, we formulate a trading strategy by selling volatility and switching to medium-term U.S. Treasury Bills when appropriated. We test the performance of the strategy using the conventional Carhart four-factor model showing a positive and statistically significant alpha.

Keywords: Realized volatility; expected volatility; volatility premium; regime switching; excess returns; hidden Markov model; VIX. (search for similar items in EconPapers)
JEL-codes: C1 C3 N2 G11 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ore and nep-rmg
Date: 2018-09
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed

Downloads: (external link) (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link:

Access Statistics for this paper

More papers in CEMA Working Papers: Serie Documentos de Trabajo. from Universidad del CEMA Contact information at EDIRC.
Bibliographic data for series maintained by Valeria Dowding ().

Page updated 2019-10-06
Handle: RePEc:cem:doctra:659