Trading activity and bid–ask spreads of individual equity options

We empirically examine the impact of trading activities on the liquidity of individual equity options measured by the proportional bid–ask spread. There are three main findings. First, the option return volatility, defined as the option price elasticity times the stock return volatility, has a much higher power in explaining the spread variations than the commonly considered liquidity determinants such as the stock return volatility and option trading volume. Second, after controlling for all the liquidity determinants, we find a maturity-substitution effect due to expiration cycles. When medium-term options (60–90 days maturity) are not available, traders use short-term options as substitutes whose higher volume leads to a smaller bid–ask spread or better liquidity. Third, we also find a moneyness-substitution effect induced by the stock return volatility. When the stock return volatility goes up, trading shifts from in-the-money options to out-of-the-money options, causing the latter’s spread to narrow.     

Does Net Buying Pressure Affect the Shape of Implied Volatility Functions?

This paper examines the relation between net buying pressure and the shape of the implied volatility function (IVF) for index and individual stock options. We find that changes in implied volatility are directly related to net buying pressure from public order flow. We also find that changes in implied volatility of S&P 500 options are most strongly affected by buying pressure for index puts, while changes in implied volatility of stock options are dominated by call option demand. Simulated delta‐neutral option‐writing trading strategies generate abnormal returns that match the deviations of the IVFs above realized historical return volatilities.     

The second moment matters! Cross-sectional dispersion of firm valuations and expected returns

Behavioral theories predict that firm valuation dispersion in the cross-section (“dispersion”) measures aggregate overpricing caused by investor overconfidence and should be negatively related to expected aggregate returns. This paper develops and tests these hypotheses. Consistent with the model predictions, I find that measures of dispersion are positively related to aggregate valuations, trading volume, idiosyncratic volatility, past market returns, and current and future investor sentiment indexes. Dispersion is a strong negative predictor of subsequent short- and long-term market excess returns. Market beta is positively related to stock returns when the beginning-of-period dispersion is low and this relationship reverses when initial dispersion is high. A simple forecast model based on dispersion significantly outperforms a naive model based on historical equity premium in out-of-sample tests and the predictability is stronger in economic downturns.     

Option trading and individual investor performance

This paper examines the impact of option trading on individual investor performance. The results show that most investors incur substantial losses on their option investments, which are much larger than the losses from equity trading. We attribute the detrimental impact of option trading on investor performance to poor market timing that results from overreaction to past stock market returns. High trading costs further contribute to the poor returns on option investments. Gambling and entertainment appear to be the most important motivations for trading options while hedging motives only play a minor role. We also provide strong evidence of performance persistence among option traders.     

Volatility Information Trading in the Option Market

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.     

Options Trading Based on the Forecasting of Volatility Direction with the Incorporation of Investor Sentiment

Using options price data on the Taiwanese stock market, we propose an options trading strategy based on the forecasting of volatility direction. The forecasting models are constructed with the incorporation of absolute returns, heterogeneous autoregressive-realized volatility (HAR-RV), and proxy of investor sentiment. After we take into consideration the margin-based transaction costs, the results of our simulated trading indicate that a straddle trading strategy that considers the forecasting of volatility direction with the incorporation of market turnover achieves the best Sharpe ratios. Our trading algorithm bridges the gap between options trading, market volatility, and the information content of investor overreaction.     

Volatility spreads and earnings announcement returns

Prior research documents that volatility spreads predict stock returns. If the trading activity of informed investors is an important driver of volatility spreads, then the predictability of stock returns should be more pronounced during major information events. This paper investigates whether the predictability of equity returns by volatility spreads is stronger during earnings announcements. Volatility spreads are measured by the implied volatility differences between pairs of strike price and expiration date matched put and call options and capture price pressures in the option market. During a two-day earnings announcement window, the abnormal returns to the quintile that includes stocks with relatively expensive call options is more than 1.5% greater than the abnormal returns to the quintile that includes stocks with relatively expensive put options. This result is robust after measuring volatility spreads in alternative ways and controlling for firm characteristics and lagged equity returns. The degree of announcement return predictability is stronger when volatility spreads are measured using more liquid options, the information environment is more asymmetric, and stock liquidity is low.     

VOLATILITY FORECASTS,TRADING VOLUME,AND THE ARCH VERSUS OPTION‐IMPLIED VOLATILITY TRADE‐OFF

We investigate empirically the role of trading volume (1) in predicting the relative informativeness of volatility forecasts produced by autoregressive conditional heteroskedasticity (ARCH) models versus the volatility forecasts derived from option prices, and (2) in improving volatility forecasts produced by ARCH and option models and combinations of models. Daily and monthly data are explored. We find that if trading volume was low during period t?1 relative to the recent past, ARCH is at least as important as options for forecasting future stock market volatility. Conversely, if volume was high during period t?1 relative to the recent past, option‐implied volatility is much more important than ARCH for forecasting future volatility. Considering relative trading volume as a proxy for changes in the set of information available to investors, our findings reveal an important switching role for trading volume between a volatility forecast that reflects relatively stale information (the historical ARCH estimate) and the option‐implied forward‐looking estimate.     

Real Options,Volatility, and Stock Returns

We provide evidence that the positive relation between firm‐level stock returns and firm‐level return volatility is due to firms’ real options. Consistent with real option theory, we find that the positive volatility‐return relation is much stronger for firms with more real options and that the sensitivity of firm value to changes in volatility declines significantly after firms exercise their real options. We reconcile the evidence at the aggregate and firm levels by showing that the negative relation at the aggregate level may be due to aggregate market conditions that simultaneously affect both market returns and return volatility.     

Volume,volatility and information linkages in the stock and option markets

This paper examines the relationship between option trading activity and stock market volatility. Although the option market is uniquely suited for trading on volatility information, there is little analysis on how trading activity in this market is linked to stock price volatility. The bulk of the discussion tends to focus on whether trading activity in the stock market is informative about stock volatility. To analyze the information in option trading activity for stock market volatility, a sample of 15 stocks with the highest option trading volume is selected. For each stock, it is noted that the trading activities in the put and call option markets have significant explanatory power for stock market volatility. In addition, the results indicate that the call option trading activity has a stronger impact on stock volatility compared with that of the put options. Our results demonstrate that information and sentiment in the option market is useful for the estimation of stock market volatility. Also, the significance of the effects of option trading activity on stock price volatility is observed to be comparable to that of stock market trading activity. Furthermore, the persistence and asymmetric effects in the volatility of some stocks tend to disappear once option trading activity is taken into account.     

Financial overconfidence over time: Foresight,hindsight, and insight of investors

Financial overconfidence leads to increased trading activity, higher risk taking, and less diversification. In a panel survey of online brokerage clients in the UK, we ask for stock market and portfolio expectations and derive several overconfidence measures from the responses. Overconfidence is identified in the sample in various forms. By matching survey data with participants’ transactions and portfolio holdings, we find an influence of overplacement on trading activity, of overprecision and overestimation on diversification, and of overprecision and overplacement on risk taking. We explore the evolution of overconfidence over time and identify a role of past success and hindsight on subsequent investor overconfidence in line with learning to be overconfident.     

Financial reporting for employee stock options: liabilities or equity?

This study seeks to determine whether employee stock options share key characteristics of liabilities or equity. Consistent with warrant pricing theory, we find that common equity risk and expected return are negatively associated with the extent to which a firm has outstanding employee stock options, which is opposite to the association for liabilities. We also find the following. (1) The association is positive for firms that reprice options and less negative for firms that have options with longer remaining terms to maturity, which indicates that some employee stock options have characteristics that make them more similar to liabilities. (2) Leverage measured based on treating options as equity has a stronger positive relation with common equity risk than leverage measured based on treating options as liabilities. (3) The sensitivity of employee stock option value to changes in asset value mirrors that of common equity value and is opposite to that of liability value. Also, we find that, unlike liabilities, employee stock options have substantially higher risk and expected return than common equity. Our findings are not consistent with classifying employee stock options as liabilities for financial reporting if classification were based on the directional association of a claim with common equity risk and expected return. Rather, our findings suggest the options act more like another type of equity.     

Momentum,Reversals, and Fund Manager Overconfidence

This paper examines the role of investor overconfidence and self‐attribution bias in explaining the momentum effect. We develop a novel measure of overconfidence based on characteristics and trading patterns of US equity mutual fund managers. Stocks held by more overconfident managers experience greater momentum profits and stronger return reversals than stocks held by less overconfident managers. The difference in momentum profits is not compensation for risk nor is it attributable to stock characteristics that influence momentum. Our results are consistent with Daniel, Hirshleifer, and Subrahmanyam (1998) who argue that momentum results from delayed overreaction caused by overconfidence and biased self‐attribution.     

ON ESTIMATING STOCK MARKET VOLATILITY: AN EXPLORATORY APPROACH

Traditional methods of estimating market volatility use daily return observations from a stock index to calculate monthly variance. We break with tradition and estimate stock market volatility using the daily, cross-sectional standard deviation of returns for all firms trading on the New York Stock Exchange and the American Stock Exchange. We find a significantly positive relation between risk and return. Market volatility is estimated to be about half the volatility level previously reported. The intraday, cross-sectional market volatility measure provides findings consistent with risk-return theory.     

Investor Psychology and Security Market Under- and Overreactions

We propose a theory of securities market under- and overreactions based on two well-known psychological biases: investor overconfidence about the precision of private information; and biased self-attribution, which causes asymmetric shifts in investors' confidence as a function of their investment outcomes. We show that overconfidence implies negative long-lag autocorrelations, excess volatility, and, when managerial actions are correlated with stock mispricing, public-event-based return predictability. Biased self-attribution adds positive short-lag autocorrelations ("momentum"), short-run earnings "drift," but negative correlation between future returns and long-term past stock market and accounting performance. The theory also offers several untested implications and implications for corporate financial policy.     

Investigation of investors' overconfidence, familiarity and socialization

This study, using a sample of New Zealand investors, investigates three behavioural finance theories: investor overconfidence, socialization and the familiarity effect. We find support for the investor overconfidence theory, using characteristics such as past success, optimism, confidence in one's abilities, investment experience and investment‐related knowledge. Concerning the socialization theory, we observe that the investors actively sought information regarding the stock market, 75 per cent doing this on a weekly basis. Those investors that kept themselves informed daily outperformed other investors by 8 per cent. The familiarity effect was confirmed, showing investors to hold a far too high proportion of local stocks, although the majority of investors believed international equity markets would provide returns that were either better or equal to New Zealand stocks.     

Which past returns affect trading volume?

Anecdotal evidence suggests and recent theoretical models argue that past stock returns affect subsequent stock trading volume. We study 3,000 individual investors over a 51 month period to test this apparent link between past returns and volume using several different panel regression models (linear panel regressions, negative binomial panel regressions, Tobit panel regressions). We find that both past market returns as well as past portfolio returns affect trading activity of individual investors (as measured by stock portfolio turnover, the number of stock transactions, and the propensity to trade stocks in a given month). After high portfolio returns, investors buy high risk stocks and reduce the number of stocks in their portfolio. High past market returns do not lead to higher risk taking or underdiversification. We argue that the only explanations for our findings are overconfidence theories based on biased self-attribution and differences of opinion explanations for high levels of trading activity.     

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.     

Empirical pricing kernels

This paper investigates the empirical characteristics of investor risk aversion over equity return states by estimating a time-varying pricing kernel, which we call the empirical pricing kernel (EPK). We estimate the EPK on a monthly basis from 1991 to 1995, using S&P 500 index option data and a stochastic volatility model for the S&P 500 return process. We find that the EPK exhibits counter cyclical risk aversion over S&P 500 return states. We also find that hedging performance is significantly improved when we use hedge ratios based the EPK rather than a time-invariant pricing kernel.     

Option Prices Leading Equity Prices: Do Option Traders Have an Information Advantage?

Recent evidence shows that option volatility skews and volatility spreads between call and put options predict equity returns. This study investigates whether such predictive ability is driven by option traders’ information advantage. We examine the predictive ability of volatility skews and volatility spreads around significant information events including earnings announcements, other firm‐specific information events, and events that trigger significant market reactions. Consistent with option traders having an information advantage relative to equity traders before information events, we find that the option measures immediately before these events have higher predictive ability for short‐term event returns than they do in a more dated window or before a randomly selected pseudo‐event. We also find that option measures have predictive ability after information events. However, this predictive ability holds only for unscheduled corporate announcements, which suggests that, relative to equity traders, option traders have superior ability to process less anticipated information.