Option trading after the opening bell and intraday stock return predictability

Prior literature finds that information is reflected in option markets before stock markets, but no study has explored whether option volume soon after market open has predictive power for intraday stock returns. Using novel intraday signed option-to-stock volume data, we find that a composite option trading score (OTS) in the first 30 min of market open predicts stock returns during the rest of the trading day. Such return predictability is greater for smaller stocks, stocks with higher idiosyncratic volatility, and stocks with higher bid–ask spreads relative to their options’ bid–ask spreads. Moreover, OTS is a significantly stronger predictor of intraday stock returns after overnight earnings announcements. The evidence suggests that option trading in the 30 min after the opening bell has predictive power for intraday stock returns.     

U.S. stock market crash risk, 1926–2010

This paper examines how well alternate time-changed Lévy processes capture stochastic volatility and the substantial outliers observed in U.S. stock market returns over the past 85 years. The autocorrelation of daily stock market returns varies substantially over time, necessitating an additional state variable when analyzing historical data. I estimate various one- and two-factor stochastic volatility/Lévy models with time-varying autocorrelation via extensions of the Bates (2006) methodology that provide filtered daily estimates of volatility and autocorrelation. The paper explores option pricing implications, including for the Volatility Index (VIX) during the recent financial crisis.     

INVESTOR EXPECTATIONS OF VOLATILITY INCREASES AROUND LARGE STOCK SPLITS AS IMPLIED IN CALL OPTION PREMIA

Recent studies find abnormal common stock price behavior associated with ex-dates of stock splits. Volatility increases are substantia) and abrupt. This study extends previous analyses to the options market by examining investor perceptions of volatility increases through implied standard deviations of returns. Investors fail to anticipate volatility increases until the ex-date. Furthermore, abnormal option returns are present. The increased volatility and these results suggest option market inefficiency.     

Trading volume and stock returns: A meta-analysis

I examine 468 estimates on the relationship between trading volume and stock returns reported in 44 studies. I study publication bias together with Bayesian and frequentist model averaging to explain the heterogeneity in the estimates. The results yield three key conclusions. First, publication bias distorts the findings of the primary studies. Second, the predictability of stock returns varies with different markets and stock types. Third, different data characteristics, structural variations and methodologies used drive the heterogeneity in the results of the primary articles. In particular, one should be cautious when using monthly data or VAR models.     

Estimation of expected return: CAPM vs. Fama and French

Most practitioners favour a one-factor model (CAPM) when estimating expected return for an individual stock. For estimation of portfolio returns, academics recommend the Fama and French three-factor model. The main objective of this paper is to compare the performance of these two models for individual stocks. First, estimates for individual stock returns based on CAPM are obtained using different time frames, data frequencies, and indexes. It is found that 5 years of monthly data and an equal-weighted index, as opposed to the commonly recommended value-weighted index, provide the best estimate. However, performance of the model is very poor; it explains on average 3% of differences in returns. Then, estimates for individual stock returns are obtained based on the Fama and French model using 5 years of monthly data. This model, however, does not do much better; independent of the index used, it explains on average 5% of differences in returns. These results therefore bring into question the use of either model for estimation of individual expected stock returns.     

Value or volume strategy?

This article reports a study that analyzes financial data for US firms listed during 1996–2005 to examine the asymmetric effects of the informative variables on stock returns between the boom and bust conditions in stock price. The study includes analysis of changing distribution of stock returns across stocks and over time by using a quantile regression (QR hereafter) model and comparison of the results with OLS and LAD estimates. The present empirical results indicate that market investors are more influenced by the fundamental variable, such as P/E ratios, derived from the value strategy when the stock they invest is in experience of a large fall in price. Conversely, when the stock price is hugely rising, market participants increase the loading of the effect of trading volume. Last, although the market returns have a significantly positive impact on the individual stock returns, we further indicate that the systematic effects involved in the market returns are much more notable when this specific stock is experiencing a recession condition in price.     

A unique view of hedge fund derivatives usage: Safeguard or speculation?

We study the common equity and equity option positions of hedge fund investment advisors over the 1999–2006 period. We find that hedge funds' stock positions predict future returns and that option positions predict both volatility and returns on the underlying stock. A quarterly tracking portfolio of stocks based on publicly observable hedge fund option holdings earns abnormal returns of 1.55% through the end of the quarter. Net of fees, hedge funds using options deliver higher benchmark-adjusted portfolio returns and lower risk than nonusers. The results suggest that hedge fund positions reflect significant timing and selectivity skill.     

The information content of implied volatilities and model-free volatility expectations: Evidence from options written on individual stocks

We measure the volatility information content of stock options for individual firms using option prices for 149 US firms and the S&P 100 index. We use ARCH and regression models to compare volatility forecasts defined by historical stock returns, at-the-money implied volatilities and model-free volatility expectations for every firm. For 1-day-ahead estimation, a historical ARCH model outperforms both of the volatility estimates extracted from option prices for 36% of the firms, but the option forecasts are nearly always more informative for those firms that have the more actively traded options. When the prediction horizon extends until the expiry date of the options, the option forecasts are more informative than the historical volatility for 85% of the firms. However, at-the-money implied volatilities generally outperform the model-free volatility expectations.     

The information content of implied skewness and kurtosis changes prior to earnings announcements for stock and option returns

We use option prices to examine whether changes in stock return skewness and kurtosis preceding earnings announcements provide information about subsequent stock and option returns. We demonstrate that changes in jump risk premiums can lead to changes in implied skewness and kurtosis and are also associated with the mean and variability of the stock price response to the earnings announcement. We find that changes in both moments have strong predictive power for future stock returns, even after controlling for implied volatility. Additionally, changes in both moments predict call returns, while put return predictability is primarily linked to changes in skewness.     

A TRANSACTION DATA STUDY OF DAY-OF-THE-WEEK AND INTRADAY PATTERNS IN OPTION RETURNS

In this study common stock, call, and put option returns from 1983 to 1985 are examined by day of the week and time of day. Stock and call return patterns generally are similar, both having relatively low weekend returns and relatively high returns late in the trading day. Put options have high weekend returns, but do not have low returns late in the trading day.     

Stock Return Anomalies and the Tests of the APT

This paper shows that the empirical tests of the Arbitrage Pricing Theory (APT) model are very sensitive to the anomalies observed in January in the stock returns data. There is a strong seasonal pattern in the estimates of the risk premia from the APT model. The most important implication of the findings in this paper is that the APT model can explain the risk-return relation mostly for January. Once the January returns are excluded from the data, there is no significant relation between the expected stock returns and the risk measures predicted by the APT model.     

Underwater Options and the Dynamics of Executive Pay-to-Performance Sensitivities

We empirically analyze the dynamics of executives' pay‐to‐performance sensitivities. Option pay‐to‐performance sensitivities become weaker as options fall underwater, often leading to pressures to reprice options or restore pay‐to‐performance sensitivity in other ways. Building a detailed data set on executives' portfolios of stock and options, we find that the responsiveness of pay‐to‐performance sensitivities (created by all executive holdings of stock and options) to changes in stock price is large. The elasticity of pay‐to‐performance sensitivities with respect to stock price decreases is about 0.7 and is larger for high‐option executives and for executives with high percentages of options already underwater. The dominant mechanism through which companies offset declines in option pay‐to‐performance sensitivities is larger option grants following stock price declines; on average, these larger grants restore approximately 40% of the stock‐price‐induced pay‐to‐performance sensitivity declines. Option repricings are inconsequential in this regard, despite the attention they have attracted. In looking at positive returns, we find the reverse: higher returns both directly increase pay‐to‐performance sensitivities and lead to larger option grants, which raise pay‐to‐performance sensitivities further. Thus, option grants to executives tend to be largest following large stock price increases or large stock price decreases.     

The Price of Correlation Risk: Evidence from Equity Options

We study whether exposure to marketwide correlation shocks affects expected option returns, using data on S&P100 index options, options on all components, and stock returns. We find evidence of priced correlation risk based on prices of index and individual variance risk. A trading strategy exploiting priced correlation risk generates a high alpha and is attractive for CRRA investors without frictions. Correlation risk exposure explains the cross-section of index and individual option returns well. The correlation risk premium cannot be exploited with realistic trading frictions, providing a limits-to-arbitrage interpretation of our finding of a high price of correlation risk.     

Does option trading convey stock price information?

After executing option orders, options market makers turn to the stock market to hedge away the underlying stock exposure. As a result, the stock exposure imbalance in option transactions translates into an imbalance in stock transactions. This paper decomposes the total stock order imbalance into an imbalance induced by option transactions and an imbalance independent of options. The analysis shows that the option-induced imbalance significantly predicts future stock returns in the cross section controlling for the past stock and options returns, but the imbalance independent of options has only a transitory price impact. Further investigation suggests that options order flow contains important information about the underlying stock value.     

Option prices and stock market momentum: evidence from China

Option prices tend to be correlated to past stock market returns due to market imperfections. We unprecedentedly examine this issue on the SSE 50 ETF option in the Chinese derivatives market. To measure the price pressure in the options market, we construct an implied volatility spread based on pairs of the SSE 50 ETF option with identical expiration dates and strike prices. By regressing the implied volatility spread on past stock returns, we find that past stock returns exert a strong influence on the pricing of index options. Specifically, we find that SSE 50 ETF calls are significantly overvalued relative to SSE 50 ETF puts after stock price increases and the reverse is also true after the stock price decreases. Moreover, we validate the momentum effects in the underlying stock market to be responsible for the price pressure. These findings are both economically and statistically significant and have important implications.     

Do Stock Prices and Volatility Jump? Reconciling Evidence from Spot and Option Prices

This paper examines the empirical performance of jump diffusion models of stock price dynamics from joint options and stock markets data. The paper introduces a model with discontinuous correlated jumps in stock prices and stock price volatility, and with state-dependent arrival intensity. We discuss how to perform likelihood-based inference based upon joint options/returns data and present estimates of risk premiums for jump and volatility risks. The paper finds that while complex jump specifications add little explanatory power in fitting options data, these models fare better in fitting options and returns data simultaneously.     

Seasonality in the Option Market

This study examines call and put option returns from 1983 to 1985 for the presence of a January seasonal effect, a monthly effect, and a day-of-the-week effect. Results in dicate the presence of seasonality in call returns, with returns significantly higher in early January and significantly lower on Mondays. Put returns generally exhibit less seasonality, although out-of-the-money put options are significantly lower in January and in-the-money put options are significantly lower in early January. These results are generally consistent with stock return patterns.     

Real and Financial Industry Booms and Busts

We examine how product market competition affects firm cash flows and stock returns in industry booms and busts. Our results show how real and financial factors interact in industry business cycles. In competitive industries, we find that high industry-level stock market valuation, investment, and financing are followed by sharply lower operating cash flows and abnormal stock returns. Analyst estimates are positively biased and returns comove more. In concentrated industries these relations are weak and generally insignificant. Our results are consistent with participants in competitive industries not fully internalizing the negative externality of industry competition on cash flows and stock returns.     

Risk-adjusted option-implied moments

This paper provides a new way of converting risk-neutral moments into the corresponding physical moments, which are required for many applications. The main theoretical result is a new analytical representation of the expected payoffs of put and call options under the physical measure in terms of current option prices and a representative investor’s preferences. This representation is then used to derive analytical expressions for a variety of ex-ante physical return moments, showing explicitly how moment premiums depend on current option prices and preferences. As an empirical application of our theoretical results, we provide option-implied estimates of the representative stock market investor’s disappointment aversion using S&P 500 index option prices. We find that disappointment aversion has a procyclical pattern. It is high in times of high index levels and declines when the index falls. We confirm the view that investors with high risk aversion and disappointment aversion leave the stock market during times of turbulence and reenter it after a period of high returns.     

Changes in the value relevance of goodwill accounting following the adoption of IFRS 3

This study examines the value relevance effects of changes in goodwill accounting in a European setting. International Financial Reporting Standard (IFRS) 3 replaced accounting rules that emphasized goodwill amortization over short useful lives which kept goodwill balances low. Goodwill accounting under IFRS 3 largely relies on manager fair value estimates of acquired business units. Using Swedish data, we show that goodwill amortizations were not value-relevant prior to the adoption of IFRS 3. However, impairments reported in addition to amortization were significantly related to stock returns during that period. In contrast, under the impairment-only regime prescribed by IFRS 3, impairments are no longer statistically related to stock returns.