Equity Options

Can investors/speculators use equity options to boost return through buying and selling leverage (calls), and/or buying and selling insurance (puts)? If so, which strategies work best? These blog entries relate to trading equity options.

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Stress Test for Equity Index Option Strategies

How well do equity index option strategies work during crises? In his October 2015 paper entitled “The Performance of Equity Index Option Strategy Returns during the Financial Crisis”, Dominik Schulte tests the profitability of long and short equity index option strategies during the financial crisis of 2008, including long (as defined) and short (opposite) versions of:

  • Call: buy a call.
  • Put: buy a put.
  • Straddle: buy a call and sell a put with the same maturity and strike.
  • Strangle: buy a call and a put with the same maturity, but with the call at a higher strike.
  • Butterfly: buy in-the-money and out-of-the-money calls and sell two at-the-money calls, all with the same maturity.
  • Put spread: sell an out-of-the-money put and buy an at-the-money put.
  • Put-call spread: sell an out-of-the-money put and buy an at-the-money call.

He considers maturities of one to three months and moneyness from 90% to 110% as allowed. To assess the import of non-normal return distributions, he considers strategy return skewness, kurtosis and Omega ratio (which incorporates all moments). He estimates trading frictions from bid-ask spreads. Using end-of-month bids and asks for calls and puts on the S&P 500, the EuroStoxx 50 and the DAX indexes during January 2006 through September 2010, he finds that: Keep Reading

When Do Holders of Equity Options Exercise Early?

When does it make sense to exercise equity options early? Does it happen frequently? In the September 2015 version of their paper entitled “Early Option Exercise: Never Say Never”, Mads Jensen and Lasse Pedersen investigate the interaction of investment frictions (shorting, trading and funding costs) and early exercise of equity options. They estimate shorting frictions via daily cost-of-borrow rankings for underlying stocks. They estimate trading frictions via option bid-ask spread rankings. They estimate funding friction as cost of required margins in excess of the risk-free (Federal Funds) rate. Using groomed data for U.S. equity options along with associated stock prices and borrowing cost data spanning 2003 through 2010, they find that: Keep Reading

Simple Stock Index Option Strategies

Do simple stock index option strategies (stock-covered calls, cash-covered puts and collars) outperform the underlying index? To investigate, we examine first the performance of the CBOE S&P 500 BuyWrite Index (BXM), the CBOE S&P 500 PutWrite Index (PUT) and the CBOE S&P 500 95-110 Collar Index (CLL), with the S&P 500 Total Return Index SPTR) as a benchmark. Since these series are modeled indexes rather than tradable assets, we then examine the relatively short records of exchange-traded funds (ETF) and notes (ETN) designed to track BXM, iPath CBOE S&P 500 BuyWrite Index ETN (BWV) and PowerShares S&P 500 BuyWrite (PBP), with SPDR S&P 500 (SPY) as a benchmark. Using end-of-month levels/total returns for SPTR, BXM, PUT and CLL since June 1986, and for SPYBWV and PBP since December 2007 (limited by inception of PBP), all through August 2015, we find that: Keep Reading

Betting Against High Downside Risk?

Do low-volatility strategies work for all stocks? In their April 2015 paper entitled “Low Risk Anomalies?”, Paul Schneider, Christian Wagner and Josef Zechner examine relationships between low-beta/low-volatility stock anomalies and implied stock return skewness. They compute ex-ante (implied) skewness for each stock via a portfolio of associated options that is long (short) out-of-the-money calls (puts). The more investors are willing to pay for downside risk protection (puts), the more negative this measure becomes. Using stock and option price data for 5,509 U.S. stocks for which options are available during January 1996 through August 2014, they find that: Keep Reading

Timing Option Trades to Suppress Trading Frictions

Do equity option traders really bear the relatively large quoted bid-ask spreads as trading frictions? In their March 2015 paper entitled “Option Trading Costs Are Lower Than You Think”, Dmitriy Muravyev and Neil Pearson examine whether the predictability of changes in quoted option prices enables sophisticated investors to suppress option trading frictions. Instead of the bid-ask midpoint, they use a regression-based estimate of the “true value” of an option based on high-frequency publicly available information that reflects trade timing. Because trades tend to occur when true value estimates differ from respective bid-ask midpoints, their adjusted effective spreads (quoted versus true value) differ from the conventionally measured effective spreads. Using tick-level data for 37 individual U.S. stocks and two exchange-traded funds from both the equity and option markets during April 2003 through October 2006 (882 trading days, during which algorithmic trading grows to dominate option markets), they find that: Keep Reading

Options for Retirement?

Is use of long-term stock index call options effective for those approaching retirement with desires of limiting exposure to crashes without sacrificing all benefit of equity exposure? In his January 2015 paper entitled “Individuals Approaching Retirement Have Options (Literally) to Secure a Comfortable Retirement”, Bryan Foltice proposes retirement strategies that employ stock index options during the five years before retirement (when prospective retirees tend to become very risk-averse) to limit equity risk while retaining some reward. These alternatives to conventional (100% stocks, 60%-40% stocks-bonds and 100% minus age in stocks) asset allocation strategies put core funds in Treasury Inflation-Protected Securities (TIPS) to secure retirement income at a real 75% of final working income and funds in excess of the core to buy long-term at-the-money stock index call options. He considers three option-based strategies:

  1. Buy 5-year options at age 60.
  2. Buy a 3-year option at age 60 and a 2-year option at age 63.
  3. Buy 1-year call options each year using the final five annual contributions.

Base modeling assumptions use 1928-2013 historical return statistics, with robustness tests assuming (1) an increased equity risk premium and (2) expectations derived from 2014 data through October. Modeling includes expected costs/fees. Using simulations based on estimates for U.S. stock market capital gains/dividends and for the TIPS real yield, he finds that: Keep Reading

Expected Volatility of Stock Market Volatility as a Predictor

S&P 500 Index options data imply expected S&P 500 Index volatility (VIX) over the next month. In turn, VIX futures options data imply expected volatility of VIX (VVIX) over the next month. Does VVIX predict stock index option and VIX option returns? In their September 2014 paper entitled “Volatility-of-Volatility Risk”, Darien Huang and Ivan Shaliastovich investigate whether VVIX represents a time-varying risk affecting: (1) S&P 500 Index option returns above and beyond the risk represented by VIX; and (2) VIX futures option returns. They measure risk effects via returns on S&P 500 Index options hedged daily by shorting the S&P 500 Index and VIX futures options hedged daily by shorting VIX futures. Using monthly S&P 500 Index returns, VIX futures returns, VIX, VVIX, S&P 500 Index option prices and VIX option prices during February 2006 through June 2013, they find that: Keep Reading

Best Option-based Stock Return Predictors?

Do implications of equity option prices predict returns for underlying stocks? In their December 2013 paper entitled “Option-Implied Volatility Measures and Stock Return Predictability” Xi Fu, Eser Arisoy, Mark Shackleton and Mehmet Umutlu compare the abilities of various option-implied volatility metrics to predict returns for individual stocks at horizons of one to three months. Specifically, they consider:

  • Call-Put Implied Volatility spread (CPIV): difference between at-the-money call and at-the-money put implied volatilities.
  • Implied Volatility Skew (IVSKEW): difference between out-of-the-money put and at-the-money call implied volatilities.
  • Above-Minus-Below (AMB): difference between average of in-the-money put and out-of-the-money call implied volatilities and average of in-the-money call and out-of-the-money put implied volatilities.
  • Call Out-Minus-At (COMA): difference between out-of-the-money call and at-the-money call implied volatilities.
  • Put Out-Minus-At (POMA): difference between out-of-the-money put and at-the-money put implied volatilities.
  • Realized Volatility-Implied Volatility spread RVIV): difference between realized volatility (annualized standard deviation of daily returns over the previous month) and implied volatility.

Each month, they rank stocks into quintiles based on each of these six metrics. They then form respective capitalization-weighted and equal-weighted hedge portfolios that are long (short) the quintiles with the highest (lowest) values of each metric and hold for one month. They also perform regressions to control portfolio returns over one, two and three months for a variety of market, stock and option characteristics. Using firm financial statement data, monthly and daily stock returns and monthly option-implied volatilities (from options with maturities of one to three months) during February 1996 through December 2011 (191 months), they find that: Keep Reading

Trading Around Option Expiration Days

Are there any stock market return/volatility anomalies around the equity option expiration (OE) day (third Friday of each month)? Potential anomalies include: (1) systematic differences in returns and volatilities before, on and after OE; and, (2) systematic differences in OE returns conditional on prior-month returns. To investigate, we examine close-to-close returns from five trading days before through five trading days after OE. Using daily closing prices for the S&P 500 Index for January 1990 through December 2013 (287 OEs, with September 2001 excluded due to trading disruption) and for the iPath S&P 500 VIX Short-Term Futures ETN (VXX) during January 2009 through December 2013 (59 OEs), we find that: Keep Reading

Index Option Strike Price Volume Dispersion as a Return Predictor

Is the level of uncertainty among equity investors, as measured by the dispersion of S&P 500 Index option volume across strike prices, a useful predictor of stock market direction? In their January 2014 paper entitled “Stock Market Ambiguity and the Equity Premium”, Panayiotis Andreou, Anastasios Kagkadis, Paulo Maio and Dennis Philip investigate the ability of this dispersion in investor speculations (designated stock market “ambiguity”) to predict stock market returns. They argue that stock market ambiguity is a direct, forward-looking and readily computed indicator. They compare ambiguity to other commonly cited stock market predictors, with focus on the variance risk premium VRP). Using trading volumes for S&P 500 Index call and put options with maturities of 10 to 360 calendar days on the last trading day of each month, monthly data needed to calculate competing indicators and monthly returns for the broad U.S. stock market during 1996 through 2012, they find that: Keep Reading

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