Determinants of S&amp;P 500 index option returns

Cao, Charles; Huang, Jing-Zhi

doi:10.1007/s11147-007-9015-5

Cited by 23 publications

(9 citation statements)

References 50 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Fengler et al (2003), Mixon (2002), Skiadopoulos et al (1999), and Bondarenko (2007) use PCs to examine the issue for options prices. Cao and Huang (2007) use PCs to examine options returns. There are two major problems with PCs, however.…”

Section: Nonlinear Principal Components Andmentioning

confidence: 99%

On the Number of State Variables in Options Pricing

Zhang

2010

Management Science

View full text Add to dashboard Cite

In this paper, we investigate the methodological issue of determining the number of state variables required for options pricing. After showing the inadequacy of the principal component analysis approach, which is commonly used in the literature, we adopt a nonparametric regression technique with nonlinear principal components extracted from the implied volatilities of various moneyness and maturities as proxies for the transformed state variables. The methodology is applied to the prices of S& P 500 index options from the period 1996-2005. We find that, in addition to the index value itself, two state variables, approximated by the first two nonlinear principal components, are adequate for pricing the index options and fitting the data in both time series and cross sections.options pricing, state variables, nonparametric method, nonlinear principal component analysis

show abstract

Section: Nonlinear Principal Components Andmentioning

confidence: 99%

On the Number of State Variables in Options Pricing

Zhang

2010

Management Science

View full text Add to dashboard Cite

show abstract

“…We interpret this finding to suggest that OTM puts are particularly sensitive to market conditions. Related research on factor models that address index option returns but without resorting to de-levering includes Jones (2006), Cao and Huang (2008), Carverhill, Cheuk, andDyrting (2009), andSerban, Lehoczky, andSeppi (2008). Specifically, by not resorting to de-levering, the econometrics in Serban, Lehoczky, and Seppi (2008) turns out to be more complicated than for our linear factor models.…”

mentioning

confidence: 99%

The Puzzle of Index Option Returns

Constantinides

Jackwerth

Savov

2013

Rev Asset Pric Stud

128

101

View full text Add to dashboard Cite

We construct a panel of S&P 500 Index call and put option portfolios, daily adjusted to maintain targeted maturity, moneyness, and unit market beta, and test multi factor pricing models. The standard linear factor methodology is applicable because the monthly port folio returns have low skewness and are close to normal. We hypothesize that any one of crisis related factors incorporating price jumps, volatility jumps, and liquidity (along with the market) explains the cross sectional variation in returns. Our hypothesis is not rejected, even when the factor premia are constrained to equal the corresponding premia in the cross section of equities. The alphas of short maturity out of the money puts become economically and statistically insignificant. (JEL G11, G13, G14)The returns of index options are highly volatile, skewed, and non-linear in the index return, thereby rendering tests of linear factor pricing models hard to interpret. For example, over the period 1986-2012, a test of a linear factor model with the S&P 500 Index as the sole factor on the cross-section of dailyrebalanced index option portfolio returns consisting of calls and puts of various maturities and moneyness yields an incredible monthly root mean squared (rms) error of 12%. Yet the p-value is 32%-34% and the model is not rejected.An important methodological contribution of this paper is the construction of a panel of leverage-adjusted (that is, with a targeted market beta of one) monthly returns of 54 option portfolios split across type (27 call and 27 put portfolios), each with targeted time to maturity (30, 60, or 90 days), and targeted moneyness (0.90, 0.925, 0.95, 0.975, 1.00, 1.025, 1.05, 1.075, or

show abstract

“…The investors can reduce their risks in the spot market to the maximum possible extent by choosing an optimal position in the options market (Choudhry, 2004), and the magnitude of risk reduction measured in terms of gains from hedging denotes the effectiveness of the market (Cao & Huang, 2007;Hull & White, 2017). Using options at an optimal level for risk dilution transactions upsurge the efficacy of the hedging strategy (Kamara & Siegel, 1987), and the selection of the optimal level purely depends upon the attitude of the investors towards risk (Bond & Thompson, 1985).…”

Section: Optimal Hedging and Hedging Effectivenessmentioning

confidence: 99%

Tackling Investment Risks Using Equity Options During Extreme Economic Upheavals: Indian Evidence

Jose

Varghese

2021

Colombo Bus. J

View full text Add to dashboard Cite

The study is an empirical scrutiny on the Indian equity options market to examine whether it facilitates the reduction of investment risks, focusing on an economic sphere with financial upheavals. The risk mitigation ability is examined with respect to the integration of nearmonth call and put options markets having different levels of exercisability with the equity market in the National Stock Exchange of India. The optimal size of options contracts required for establishing a hedge portfolio that minimises the risk exposure to a maximum possible magnitude and the level of gains resulting from such hedges are identified following the minimum variance approach, using Diagonal BEKK GARCH. The results indicate that ATM, ITM, and DITM call options and ATM, OTM, DOTM, and DITM put options provide effective risk reduction that can be efficiently utilised by the existing as well as prospective investors in the equity market.

show abstract

Determinants of S&P 500 index option returns

Abstract: Option returns, Factor analysis, Option implied volatility, Equally weighted option index, Mean–variance spanning, G10, G12, G13,

Cited by 23 publications

References 50 publications

On the Number of State Variables in Options Pricing

On the Number of State Variables in Options Pricing

The Puzzle of Index Option Returns

Tackling Investment Risks Using Equity Options During Extreme Economic Upheavals: Indian Evidence

Contact Info

Product

Resources

About