Predicting volatility using the Markov-switching multifractal model: Evidence from S&amp;P 100 index and equity options

Chuang, Wen-I; Huang, Teng-Ching; Lin, Bo‐Yen

doi:10.1016/j.najef.2012.06.007

Cited by 25 publications

(8 citation statements)

References 85 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…During this period, the elevated level of volatility across the moneyness spectrum dominates any nuances concerning the skew. This is in contrast to Chuang, Huang, and Lin (2013) who find that implied volatility curves in equity markets are less skewed when volatility levels are lower.…”

Section: Impact Of Economic Factors On Implied Volatilitycontrasting

confidence: 95%

An analysis of implied volatility jump dynamics: Novel functional data representation in crude oil markets

Kearney

Murphy

Cummins

2015

The North American Journal of Economics and Finance

View full text Add to dashboard Cite

Section: Impact Of Economic Factors On Implied Volatilitycontrasting

confidence: 95%

An analysis of implied volatility jump dynamics: Novel functional data representation in crude oil markets

Kearney

Murphy

Cummins

2015

The North American Journal of Economics and Finance

View full text Add to dashboard Cite

“…They claim that regular volatility exhibits long-range dependence whereas extreme volatility has anti-persistent behaviour. Chuang et al (2013) perform a comparative analysis to test the forecasting ability of the Markov switching multifractal (MSM) model against the implied, GARCH and historical volatility models. They used S&P100 index and equity option data for empirical purposes.…”

Section: Studies About the Stock Marketsmentioning

confidence: 99%

Testing for multi-fractality and efficiency in selected sovereign bond markets: a multi-fractal detrended moving average (MF-DMA) analysis

Bayracı¹

2018

IJCEE

View full text Add to dashboard Cite

This study examines the multifractality and relative efficiency in sovereign bond markets, using the multifractal detrended moving average (MF-DMA) approach to quantify the degree of multifractality in the international sovereign bond yields. We use the daily values of the 2-year maturity government bond yields for 12 countries between 2003 and 2014 for empirical analysis. Our results document that all bond markets show multifractal characteristics in various levels. High degree of multifractality is seen in the Spanish, Portuguese and Italian bond markets while low multifractality features belong to the Canadian and the US bond market. The source of multifractality is mainly due to the structure of the bond markets where the recent Eurozone debt crisis has manifested itself as extreme observations.

show abstract

“…The covariance structure illustrates that the increments are positively correlated when (1/2) < H < 1 and exhibit long-memory, while for H = 1/2 the increments are independent and correspond to a standard Brownian motion. To simulate the fractional Brownian motion we use the Davies and Harte (1987) algorithm with Hurst index H = 0.7.…”

Section: Fractional Ornstein-uhlenbeck Processmentioning

confidence: 99%

Forecasting volatility with the realized range in the presence of noise and non-trading

Bannouh

Martens

Dijk

2013

The North American Journal of Economics and Finance

View full text Add to dashboard Cite

a r t i c l e i n f o JEL classification: C58 C53 G17 Keywords: Realized variance Realized range Two time scales High frequency data Market microstructure noise Forecasting a b s t r a c tWe introduce a heuristic bias-adjustment for the transaction pricebased realized range estimator of daily volatility in the presence of bid-ask bounce and non-trading. The adjustment is an extension of the estimator proposed in Christensen et al. (2009). We relax the assumption that all intraday high (low) transaction prices are at the ask (bid) quote. Using data-based simulations we obtain estimates of the probability that a given intraday range is (upward or downward) biased or not, which we use for a more refined bias-adjustment of the realized range estimator. Both Monte Carlo simulations and an empirical application involving a liquid and a relatively illiquid S&P500 constituent demonstrate that ex post measures and ex ante forecasts based on the heuristically adjusted realized range compare favorably to existing bias-adjusted (two time scales) realized range and (two time scales) realized variance estimators.

show abstract

Predicting volatility using the Markov-switching multifractal model: Evidence from S&P 100 index and equity options

Cited by 25 publications

References 85 publications

An analysis of implied volatility jump dynamics: Novel functional data representation in crude oil markets

An analysis of implied volatility jump dynamics: Novel functional data representation in crude oil markets

Testing for multi-fractality and efficiency in selected sovereign bond markets: a multi-fractal detrended moving average (MF-DMA) analysis

Forecasting volatility with the realized range in the presence of noise and non-trading

Contact Info

Product

Resources

About