Are Index Option Returns Priced In The Stock Market? — New Insights From Factor Decompositions

2020 ◽  
Author(s):  
Tong Wang
Keyword(s):  
Stock Market ◽  
Option Returns ◽  
Index Option

The Puzzle of Index Option Returns

CFA Digest ◽  
2014 ◽  
Vol 44 (6) ◽  
Author(s):  
Brindha Gunasingham
Keyword(s):  
Option Returns ◽  
Index Option

scholarly journals Index option returns and systemic equity risk

2018 ◽  
Vol 4 (4) ◽  
pp. 273-298
Author(s):  
Weiping Li ◽  
Tim Krehbiel
Keyword(s):  
Option Returns ◽  
Equity Risk ◽  
Index Option

scholarly journals Optimal Option Portfolio Strategies: Deepening the Puzzle of Index Option Mispricing

2017 ◽  
Vol 52 (1) ◽  
pp. 277-303 ◽  
Author(s):  
José Afonso Faias ◽  
Pedro Santa-Clara
Keyword(s):  
Asset Allocation ◽  
Risk Premia ◽  
Volatility Risk ◽  
Short Sample ◽  
Option Returns ◽  
Portfolio Strategies ◽  
Portfolio Strategy ◽  
Out Of Sample ◽  
Index Option ◽  
Mean Variance

Traditional methods of asset allocation (such as mean–variance optimization) are not adequate for option portfolios because the distribution of returns is non-normal and the short sample of option returns available makes it difficult to estimate their distribution. We propose a method to optimize a portfolio of European options, held to maturity, with a myopic objective function that overcomes these limitations. In an out-of-sample exercise incorporating realistic transaction costs, the portfolio strategy delivers a Sharpe ratio of 0.82 with positive skewness. This performance is mostly obtained by exploiting mispricing between options and not by loading on jump or volatility risk premia.

The Determinants of the KOSPI200 Index Option Returns

2016 ◽  
Vol 24 (1) ◽  
pp. 65-96
Author(s):  
Byung Jin Kang
Keyword(s):  
Cross Section ◽  
Global Financial Crisis ◽  
Factor Model ◽  
Related Factor ◽  
Related Factors ◽  
Cross Sectional ◽  
Option Returns ◽  
The Cross ◽  
The Global Financial Crisis ◽  
Index Option

This study examines the effects of crisis-related factors on the returns of KOSPI200 index options using a factor model, which was introduced by Constantinides, Jackwerth and Savov (2013). Three factors incorporating price jumps, changes in volatility, and volatility jumps are considered as the crisis-related factors. With the data for the period from 2004 to 2015, we find followings : First, most of the crisis-related factor premia are statistically significant, and their signs are consistent with those expected. Second, these crisis-related factors contribute to improve the understanding of the cross-sectional variation in KOSPI200 index option returns. Third, the crisis-related factor premia became much more significant after the global financial crisis in 2008. Finally, our empirical findings are robust to whether the long options and the in-the-money options are included in the sample or not, and to whether the factor premia are constrained to equal the corresponding premia estimated from the cross-section of equities.

Futures and Option Prices After the Stock Market Close: Evidence from the Korean Markets

2008 ◽  
Vol 16 (2) ◽  
pp. 95-125
Author(s):  
Jae Ha Lee ◽  
Sang Soo Kwon
Keyword(s):  
Stock Market ◽  
Trading Volume ◽  
Return Volatility ◽  
Option Prices ◽  
Option Markets ◽  
Option Returns ◽  
Time Zones ◽  
The Impact

In the KOSPI2oo futures and option markets. additional fifteen minutes (15 : 00∼15 개5) after the underlying stock market close are given tor the adjustments of the futures and option positions. During the first five minutes. 15: 00∼15 : 05. a continuous auction trading is made. while the trading at a single clearing price is made for the remaining ten minutes. 15: 05∼15: 15. Previous studies focused on the synchronous trading in terms of transaction time in the analysis of the lead-lag relationship. truncating the futures and option data during 15 : 00∼15 : 15. In this article. we explore how the KOSPI2oo futures and option returns for the extra fifteen minutes impact the next day's KOSPI200 cash returns, We also examine the lead-lag relationship during the reggular trading hours (9 : 00∼15 : 00) and the impact of the cash returns during 14 : 20∼15 : 00 on futures and option returns during 15 : 00∼15: 15. Our main findings are summarized as follows. First. the KOSPI200 futures and option returns during 15 : 00∼15 : 15 lead the close-to-open KOSPI200 cash return, even though the trading volume and return volatility during 15: 00∼15: 15 are lower relative to the regular stock market session (9 : 00∼15: 00). The impact of the futures and option returns on the cash return lasts hlK) minutes and one minute‘ repectively. after the next day open. Second. the option return during the continuous auction trading session (15 : 00∼ 15 : 05) leads the close-to-open cash return. while the futures return of trading at a single clearing price during 15 : 05∼15 : 10 impacts the close-to-open cash return. Third, we found that the lead-lag relationships among the KOSPI200 futures, option, and cash returns are not constant during the reg비ar stock market session‘ In partieular. the impact of the KOSPI200 cash ret un during 14 : 40∼15 : 00 on the futures and option retuns for the 15 : 00∼15: 15 Interval is much stronger. compared with other time zones. Finally. the KOSPI200 cash return during the last ten minutes of trading at a Single clearing price (14 : 50∼15 : 00). significantly impacts the option return during 15: 00∼15: 05. while there is no impact on the futures return (15 : 00∼15: 15).

Stochastic Skewness and Index Option Returns

2015 ◽  
Author(s):  
Cai Zhu
Keyword(s):  
Option Returns ◽  
Index Option

A Nonlinear Factor Analysis of S&P 500 Index Option Returns

2006 ◽  
Vol 61 (5) ◽  
pp. 2325-2363 ◽  
Author(s):  
CHRISTOPHER S. JONES
Keyword(s):  
Factor Analysis ◽  
Nonlinear Factor Analysis ◽  
Option Returns ◽  
Nonlinear Factor ◽  
Index Option

Cumulative Prospect Theory, Option Returns, and the Variance Premium

2018 ◽  
Vol 32 (9) ◽  
pp. 3667-3723 ◽  
Author(s):  
Lieven Baele ◽  
Joost Driessen ◽  
Sebastian Ebert ◽  
Juan M Londono ◽  
Oliver G Spalt
Keyword(s):  
Prospect Theory ◽  
Cumulative Prospect Theory ◽  
Probability Weighting ◽  
Asset Pricing Model ◽  
Equilibrium Asset Pricing ◽  
Option Returns ◽  
Dynamic Setting ◽  
Editorial Decision ◽  
Equity Index ◽  
Index Option

Abstract We develop a tractable equilibrium asset pricing model with cumulative prospect theory (CPT) preferences. Using GMM on a sample of U.S. equity index option returns, we show that by introducing a single common probability weighting parameter for both tails of the return distribution, the CPT model can simultaneously generate the otherwise puzzlingly low returns on both out-of-the-money put and out-of-the-money call options as well as the high observed variance premium. In a dynamic setting, probability weighting and time-varying equity return volatility combine to match the observed time-series pattern of the variance premium. Received May 30, 2017; editorial decision August 10, 2018 by Editor Andrew Karolyi.

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