Equity Options

Is there exploitable feedback between stock returns and behaviors of associated options due to concentration of informed traders in one market or the other? In the October 2013 version of their paper entitled “The Joint Cross Section of Stocks and Options”, Byeong-Je An, Andrew Ang, Turan Baliand and Nusret Cakici investigate lead-lag relationships between stock returns and changes in associated option-implied volatilities. In case there is some asymmetry, they examine call option and put option implied volatilities separately. They focus on near-term options with delta of 0.5 and expiration in 30 days. Using daily stock returns and associated call and put option implied volatilities (available from OptionMetrics), firm fundamentals and risk adjustment factors during January 1996 through December 2011, they find that: Keep Reading

The conventional wisdom is that a high (low) ratio of equity put option volume to equity call option volume is bullish (bearish) because it indicates that investors are overly pessimistic (optimistic). Alternative measurements of the U.S. equity market put-call ratio are total options, index options and individual equity options. Index and equity option buyers may have different motives. Alternative sources of put-call ratios are the Chicago Board Options Exchange (CBOE) and the International Securities Exchange (ISE). CBOE counts volumes for all options transactions. ISE relies on “a unique put/call value that only uses opening long customer transactions to calculate bullish/bearish market direction. Opening long transactions are thought to best represent market sentiment because investors often buy call and put options to express their actual market view of a particular stock. Market maker and firm trades, which are excluded, are not considered representative of true market sentiment due to their specialized nature. As such, the…calculation method allows for a more accurate measure of true investor sentiment…” Do the alternative put-call ratios confirm conventional wisdom? Using available historical daily data for CBOE and ISE total, index and equity option put-call ratios and contemporaneous dividend-adjusted levels of S&P Depository Receipts (SPY) through mid-February 2013, we find that: Keep Reading

Does market underestimation of stock price uncertainty around earnings announcements support a short-term straddle strategy (call option and put option with matched strike and expiration, profitable with large stock price moves)? In their January 2013 paper entitled “Anticipating Uncertainty: Straddles Around Earnings Announcements”, Yuhang Xing and Xiaoyan Zhang investigate the performance of short-term, near-the-money straddles during intervals around earnings announcements. Short-term means no more than 60 days to expiration. Near-the-money means moneyness in the range 0.95 to 1.05. They focus on a delta-neutral straddle constructed by appropriately weighting the call and put positions at initiation, but they also consider a simple one call-one put alternative. They examine several straddle holding periods starting at the close five, three or one trading day before scheduled earnings announcement date and ending at the close on or one day after earnings announcement date. They calculate option returns based on the mid-point of the daily closing bid and ask as a fair option price (and require it to be at least $0.125). Using daily stock returns and option prices (with data filtered to exclude implausible data), along with contemporaneous quarterly firm fundamentals, during January 1996 through December 2010, they find that: Keep Reading

Are there strategic asset allocation methodologies that reliably beat equal weight? In the February 2012 version of their paper entitled “Portfolio Optimization Using Forward-Looking Information”, Alexander Kempf, Olaf Korn and Sven Sassning investigate the performance of a minimum variance portfolio based on returns implied by equity options rather than historical returns. They argue that, since option prices reflect the expectations of market participants, the former approach is inherently forward-looking. The methodology involves calculating option-implied volatilities and option-implied correlations. Using daily prices for the Dow Jones Industrial Average (DJIA) stocks and associated option-implied return statistics during 1998 through 2009 for out-of-sample testing, and DJIA stock prices for 1993 through 1997 for historical data tests, they find that: Keep Reading

Do informed options traders know more than other traders? In other words, are there reliable and exploitable predictive relationships between changes in implied volatility and future returns for associated stocks? In the February 2012 version of their paper entitled “The Joint Cross Section of Stocks and Options”, Andrew Ang, Turan Bali and Nusret Cakici investigate the relationship between changes in implied volatility and stock returns for individual stocks. They consider both call-implied and put-implied volatilities based on near-term expirations. Using daily implied volatilities, associated daily stock prices and firm accounting data for a broad sample of U.S. stocks over the period January 1996 through September 2008 (153 months), they conclude that: Keep Reading

Are option traders market leaders, such that information gleaned from options trading anticipates equity returns? In the December 2011 draft of their paper entitled “Exploiting Option Information in the Equity Market”, Guido Baltussen, Bart Van der Grient, Wilma De Groot, Weili Zhou and Erik Hennink examine whether information publicly available from the option market exploitably predicts returns for individual U.S. stocks. Specifically, they investigate the separate and combined information value of four at-the-money (ATM) and out-of-the-money (OTM) equity option trading metrics:

1. OTM Skew: the difference in implied volatilities between OTM puts and ATM calls.
2. RV-IV: the difference between realized volatility over the past 20 trading days (RV) and implied volatility (IV).
3. ATM Skew: the difference in implied volatilities between ATM puts and ATM calls.
4. Change in ATM Skew.

They define an option as ATM (OTM) when the ratio of strike price to stock price is between 0.95 and 1.05 (0.80 and 0.95). They reform equally-weighted quintile sort test portfolios weekly based on Tuesday closes for each metric, with a one-day lag (implementing with Wednesday closing data). Using daily total returns, market capitalizations and options trading data for those of the 1,250 largest stocks in the S&P/Citigroup U.S. Broad Market Index with sufficient options data during January 1996 through October 2009, they find that: Keep Reading

Can investors usefully predict the short-term direction of the stock market by contrasting the outlooks implied by out-of-the-money (OTM) and at-the-money (ATM) market index options. In the October 2011 update of their paper entitled “Implied Volatility Spreads and Expected Market Returns”, Turan Bali, Ozgur Demirtas and Yigit Atilgan investigate the relationship between stock market index implied volatility spread (slope of the volatility smile) and future stock market return. They consider several measures of the implied volatility spread, such as the difference in implied volatilities between the S&P 500 Index OTM put option and the ATM call option that have the highest open interest or trading volume each day. They define moneyness as the ratio of strike price to stock price, with ATM (OTM) having moneyness between 0.95 and 1.05 (from 0.8 to 0.95). They exclude options with time to expiration less than 10 days or more than 60 days, options priced less than $0.125 and options with missing or anomalous data. Using daily closing prices for S&P 500 Index options and S&P 500 Index daily opening and closing levels from January 4, 1996 through September 10, 2008, along with contemporaneous firm and economic data used in robustness tests, they find that: Keep Reading

Are realized (actual historical) and implied volatilities the whole story for equity option valuation? In their December 2011 paper entitled “Fundamental Analysis and Option Returns”, Theodore Goodman, Monica Neamtiu and Frank Zhang investigate the extent to which the equity options market fails to recognize volatility of firm operations (accounting data) and whether any such failure is exploitable. They focus tests on long, one-month-to-expiration, at-the-money straddles (long both a call and a put), which profit from large moves in underlying stock prices. They estimate future volatility in firm fundamentals via regression based on a combination of short-term sales/earnings growth and long-term sales/earnings growth volatility (standard deviation over the last six years). They isolate a “pure” expected fundamental volatility via regression versus implied volatility and the implied-realized volatility gap. Using data as available to estimate the relationship between fundamental volatility and returns on options for individual U.S. stocks during January 1996 through September 2010 (52,251 firm-quarters involving 3,481 distinct firms), they find that: Keep Reading

An upward (downward) trend in implied volatilities with option maturity indicates that investors expect volatility to increase (decrease) over time. Do such expectations reliably predict future stock options prices? In his October 2011 paper entitled “Volatility Term Structure and the Cross-Section of Option Returns”, Aurelio Vasquez investigates whether the implied volatility term structure (measured as slope of implied volatilities across at-the-money options with receding expiration dates) predicts future option returns. Specifically, each month he ranks stocks into deciles by volatility term structure slope and then calculates future returns for extreme deciles from five option trading strategies: (1) naked calls; (2)naked puts; (3) straddles; (4) delta-hedged calls; and, (5) delta-hedged puts. He calculates returns relative to the initial prices of the options traded. Using monthly closing bid and ask prices for at-the-money options (moneyness between 0.95 and 1.05) on a broad sample of U.S. stocks, and associated firm characteristics, during January 1996 through June 2007 (260 stocks per month on average), he finds that: Keep Reading

Does a simple strategy of iteratively selling covered calls (buy-write) on the Russell 2000 Index beat buying and holding the index? In their September 2011 paper entitled “15 Years of the Russell 2000 Buy‐Write”, Nikunj Kapadia and Edward Szado evaluate returns on ten alternative buy‐write strategies for the Russell 2000 Index. Specifically, they consider one-month and two-month maturities and five levels of approximate moneyness: at-the-money (ATM); 2% and 5% in-the-money (ITM); and, 2% and 5% out-of-the-money (OTM). They estimate spread trading friction based on selling at the bid or at the bid-ask midpoint. They hold to expiration and cash settle at approximate expiration intrinsic value. Using monthly Russell 2000 Index total returns and Russell 2000 Index option bid-ask and implied volatility data from January 1996 through March 2011 (182 months), they find that: Keep Reading