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A moneyness-based propensity to sell (MPS) measure, at the aggregate level, determines the propensity of option holders to exercise their winning relative to losing positions. Using data on individual stock and S&P 500 Index options, we find that the MPS measure has significant predictive power over the cross section of delta-hedged option returns. We test the disposition effect in the options market based on a long-short strategy that exploits price distortions induced by the disposition bias. More pronounced evidence of the disposition bias is found for individual at-the-money call options than put options where the significance of abnormal returns remains robust across different subsamples even after we control for the portfolio option greeks and market-based risk factors. The profitability of the long-short strategy is related to limit-to-arbitrage proxies suggesting that behavioral explanations help explain the positive relation between the MPS measure and delta-hedged option returns.

This paper provides option pricing and volume implications for an economy with heterogeneous agents who face model uncertainty and have different beliefs on expected returns. Market incompleteness makes options nonredundant, while heterogeneity creates a link between differences in beliefs and option volumes. We solve for both option prices and volumes and test the joint empirical implications using S&P500 index option data. Specifically, we use survey data to build an Index of Dispersion in Beliefs and find that a model that takes information heterogeneity into account can explain the dynamics of option volume and the smile better than can reduced-form models with stochastic volatility.

This paper investigates informed trading on stock volatility in the option market. We construct non-market maker net demand for volatility from the trading volume of individual equity options and find that this demand is informative about the future realized volatility of underlying stocks. We also find that the impact of volatility demand on option prices is positive. More importantly, the price impact increases by 40% as informational asymmetry about stock volatility intensifies in the days leading up to earnings announcements and diminishes to its normal level soon after the volatility uncertainty is resolved.

We test the Index options market efficiency by means of a statistical arbitrage strategy, i.e. pairs trading. Using data on five Index Option Markets of the Euro Area, we first identify any potential option mispricing based on deviations from the long-run relationship linking their implied volatilities. Then, we evaluate the profitability of a simple pair trading strategy on the mispriced options. Despite the fact that the signals of potential mispricing are frequent, the statistical arbitrage does not produce significant profits, thus providing evidence in support of Index Option market efficiency. The results, which remain unchanged in a variety of robustness checks, also prove that the observed profits are strongly associated to the moneyness of the options traded while they do not correlate to options’ maturity or to financial market turbulence.

This paper investigates the relationship between option trading behavior and option pricing patterns. We argue that greater active trading in the options market due to investor overconfidence leads to higher volatility and larger discrepancies in option pricing, which may be captured by implied volatility spread and implied volatility skewness. Using two different measures of excess option trading, we find that trading activities are correlated in different ways with volatility, volatility spread, and volatility skewness. We also find that these relationships exist both over time and cross-sectionally. We suggest that options investors tend to chase “hot” stocks, as we find evidence of a positive relationship between option trading activities and past underlying equity returns. Heavier trading in the options market also tends to make out-of-the-money call options more (less) expensive than the at-the-money counterparts over time (cross-sectionally). Because trading activities do not predict future equity returns, investor overconfidence, and not informed trading, seems to be a more plausible explanation for our findings.

This study tests whether pairs trade conditional on representative bias in the options and stock markets leads to abnormal returns. While previous literature on representativeness focuses on a single index, S&P 500 and Russell 2000 indexes are used to examine the extent to which representative bias arises due to a pattern of similar information shock in the three analyzed periods. The empirical results of the options market lend little support to the representativeness anomalies because Russell 2000 index, relative to S&P 500 index, does not adjust to a sequence of information shocks in the 2020 economic downturn inflicted by the coronavirus pandemic, despite the asymmetrical responsiveness to information shock over the sample period of 2004 to 2020, and during the 2008 global financial crisis. However, the empirical findings of the stock market verify, to some degree, the existence of representative bias during the sample period of 2004 to 2020. To examine whether asymmetrical representativeness in the options market or representativeness in the stock market yields abnormal returns, pairs trade is designed to exploit riskless profits via buying S&P 500 index and selling Russell 2000 index. Based on the Fama and French three-factor model, the empirical evidence is in support of market efficiency because the pairs trading strategy cannot generate positive abnormal returns in both options and stock markets.

Since the adoption of the SEC’s Rule 10b-21 in 1988, many researchers have been concerned over the effectiveness of short sales constraints in preventing manipulative trading in the derivatives market. We analyze whether options can be used as synthetic short sale instruments to manipulate stock prices before a seasoned equity offer. Due to the existence of strict short sales constraints in the equity market and market makers’ anticipation of manipulative trading, it would be very costly for a manipulator to drive stock prices down artificially either by short selling in the equity market or by using synthetic short sales in the options market. Using a sample of 237 firms that issued SEOs on the NYSE and had options listed on any U.S. options exchange from April 2002 to December 2004, we show that potential manipulators in the options market tend to use put options as a trading vehicle during the SEO’s pre-offer period. The results of our empirical tests support the predictions of our model.

The COVID-19 pandemic has caused turbulence in many areas of the global economy. It also contributed to an increase in volatility on the energy commodities market. This spilled over into the derivatives market, particularly the crude oil futures market. The aim of the article is to compare the costs and effectiveness of using options on WTI oil from before and after the pandemic. The analyzes took into account the value of option premiums and final results obtained by buyers of call options from March 1, 2018 to April 14, 2022. The results showed that buyers of call options during the pandemic, despite paying much higher option premiums, experienced significantly higher payouts and rates of return. They were the highest for options with the longest expiry periods of 21-30 days. Research also showed that during the pandemic, options with strike prices set at a level higher than the price of oil on the contract date had particularly high rates of return, while the highest payout values were achieved by buyers of call options with low strike prices.

Stocks with large increases in call (put) implied volatilities over the previous month tend to have high (low) future returns. Sorting stocks ranked into decile portfolios by past call implied volatilities produces spreads in average returns of approximately 1% per month, and the return differences persist up to six months. The cross section of stock returns also predicts option implied volatilities, with stocks with high past returns tending to have call and put option contracts that exhibit increases in implied volatility over the next month, but with decreasing realized volatility. These predictability patterns are consistent with rational models of informed trading.

This study unravels the transmission of volatility spillovers between NIFTY 50 spot prices and the options market, addressing a significant gap in existing studies. It captures how market connectedness evolved during the pre-COVID, COVID and post-COVID periods, offering fresh insights into price discovery and risk management during systemic shocks. The analysis applies the Dynamic Conditional Correlation-GARCH (DCC-GARCH) model to examine volatility spillovers and assess dynamic connectedness between NIFTY 50 spot prices and options. Furthermore, the Baruník and Krehlík (2018) and Diebold and Yilmaz (2012) models are employed for variance decomposition, providing insights into time-frequency connectedness and offering a detailed view of spillover effects across different time horizons.The findings reveal volatility spillovers between the NIFTY index and option markets across various moneyness levels (ATM, ITM, and OTM) during pre-COVID, COVID and post-COVID periods. The results show persistent long-run spillovers but no significant short-term effects. ATM and ITM options emerge as key volatility transmitters, while the NIFTY index acts as a net absorber, particularly during the COVID-19 crisis. A sharp rise in market connectedness is observed during COVID, which remained elevated in the subsequent period. The results hold important implications for option pricing, hedging and regulation. Persistent long-term spillovers emphasize the importance of models that account for time-varying risk across different moneyness levels. The surge in connectedness during the COVID-19 pandemic highlights the need for dynamic hedging strategies and stronger regulatory oversight, particularly in emerging markets. This study is among the first to analyze volatility spillovers between NIFTY 50 and the options market, with a specific focus on the COVID-19 pandemic.