ARE VOLATILITY EXPECTATIONS CHARACTERIZED BY REGIME SHIFTS? EVIDENCE FROM IMPLIED VOLATILITY INDICES



evidence from Nishina, Maghrebi and Kim (2006) of higher out-of sample forecasting
power for the S&P 500 and Nikkei 225 implied volatility indices.1

The informational content of implied volatility has been traditionally examined
using conventional regression analysis and GARCH modelling. The present study examines
the nonlinear dynamics of the relationship between implied volatility and realized volatility
using Markov regime-switching models introduced by Hamilton (1989). The economic
motivation for modelling the dynamics of implied volatility with regime-switching
processes lies in the changing likelihood for market volatility to fluctuate between regimes
of higher versus lower volatility and/or slower against faster mean reversion. Much like the
return-generating process, the dynamics of anticipated volatility can be also governed by
different regimes characteristic of periods of bearish or bullish markets and associated with
the troughs and peaks of economic cycles.

In contrast, the literature on implied volatility provides little empirical evidence
based on regime-switching dynamics. This study constitutes, to the best knowledge of the
authors, the first attempt to test for the existence of Markov regime switches in anticipations
of stock market volatility.2 The regime switching approach is rather widely applied to
account for structural breaks in a range of financial variables including interest rates, equity

1 There is evidence from Jorion (1995) for instance that implied volatility provides efficient
estimates of future volatility in currency markets as well.

2 Guo and Wohar (2006) identify regime changes in stock market volatility implied by S&P
100 and S&P 500 options prices using Bai and Perron (1998) method to determine
structural breaks in the mean level of market volatility. Their approach differs however
from Markov regime-switching modelling proposed by Hamilton (1989), which is applied
in the present paper. Furthermore, this model allows for regime-dependent speed of
adjustment and tests for leverage effects and the impact of past realized volatility.



More intriguing information

1. Spatial Aggregation and Weather Risk Management
2. The name is absent
3. Economie de l’entrepreneur faits et théories (The economics of entrepreneur facts and theories)
4. The name is absent
5. Trade Liberalization, Firm Performance and Labour Market Outcomes in the Developing World: What Can We Learn from Micro-LevelData?
6. Transfer from primary school to secondary school
7. Growth and Technological Leadership in US Industries: A Spatial Econometric Analysis at the State Level, 1963-1997
8. PACKAGING: A KEY ELEMENT IN ADDED VALUE
9. The name is absent
10. Pricing American-style Derivatives under the Heston Model Dynamics: A Fast Fourier Transformation in the Geske–Johnson Scheme
11. The name is absent
12. Evidence on the Determinants of Foreign Direct Investment: The Case of Three European Regions
13. Transgression et Contestation Dans Ie conte diderotien. Pierre Hartmann Strasbourg
14. The name is absent
15. The name is absent
16. The name is absent
17. Dual Track Reforms: With and Without Losers
18. Olive Tree Farming in Jaen: Situation With the New Cap and Comparison With the Province Income Per Capita.
19. Industrial Employment Growth in Spanish Regions - the Role Played by Size, Innovation, and Spatial Aspects
20. Do imputed education histories provide satisfactory results in fertility analysis in the Western German context?