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An Empirical Study of Option Market Bid-Ask Spreads

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An Empirical Study of Option Market Bid-Ask Spreads Option Market Liquidity - An empirical study of option market bid-ask spreads Master Thesis ETH Zurich¨ Chair of Entrepreneurial Risks Mate Nemes Supervisors: Prof. Didier Sornette Dr. Peter Cauwels Dr. Mika Kastenholz December 2012 Abstract In this thesis we review existing literature on option market liquidity and give an overview of the current state of research. We also examine the impact of macroeconomic shocks and low-liquidity market conditions on bid-ask spreads of stock and ETF options. The core of the paper is a multi-angle analysis of option bid-ask spreads in times of high liquidity and liquidity squeezes, as well as across sectors, maturities, and moneyness. The empirical results show rapidly widening bid-ask spreads as the option sinks deeper into the out-of-the-money space. Large volatility of spreads and differences between sectors, along with correlation num- bers with established fear indices improve general understanding of option market spreads behavior. Impact of macroeconomic shocks and liquidity conditions in the market are clearly recognizable on the time series plots of bid-ask spreads. We also examine options on exchange traded funds to compare and contrast their spreads with simple equity options. In order to provide a practical guide to estimate how bid-ask spreads react to changes of exogenous and endogenous variables, we set up an illustrative regression model. Keywords: Options market, liquidity, bid-ask spread, fear index, market maker, re- gression framework Acknowledgements First and foremost, I would like to express my appreciation to my supervisors for their dedicated help and guidance throughout the preparation of this master thesis. Their in- sights, ideas, and remarkable knowledge of the topics discussed here, were absolutely crucial for this work. I would also like to thank Dr. Ryan Woodard for his kind assis- tance in obtaining option market data. Without his help, it would have been impossible to perform the analytical tests on real-life market data. In this space, I would also like to say thank you to all the professors, lecturers, and academic staff for having the priv- ilege to attend their lectures. Moreover, I must thank all my peers at ETH Zurich¨ with whom I performed project work, group exercises, or simply those who made my days at ETH Zurich¨ unforgettable. Contents 1 Introduction 8 2 An overview of the current state of liquidity research 9 3 Liquidity measures 12 4 Option market bid-ask spreads 16 4.1 Composition . 16 4.1.1 Order processing cost . 17 4.1.2 Inventory holding cost . 17 4.1.3 Model risk . 17 4.1.4 Hedging and rebalancing cost . 19 4.1.5 Other factors . 20 5 Data and methods 23 5.1 Options data . 23 5.2 Underlying . 23 5.3 Examined time periods . 23 5.4 Fear indices and Liquidity proxies . 26 5.4.1 VIX (Bloomberg: VIX Index) . 26 5.4.2 Ted-Spread (Bloomberg: BASTDSP Index) . 27 5.4.3 US 10-year Treasury yields (Bloomberg: USGG10YR Index . 27 5.4.4 German 10-year government bond yields (Bloomberg: GDBR10 Index) . 28 5.4.5 Italian 2-year government bond yields (Bloomberg: GBTP2YR Index) . 29 5.4.6 OTC-X Liquidity Index (Bloomberg: BNKILIQ Index) . 30 5.4.7 Capital Markets Liquidity Index (Bloomberg: CPMKTL Index) 31 5.4.8 Euro-dollar basis swap spread (Bloomberg: EUBSC Index . 32 5.5 Methods . 33 5.5.1 Time series of average bid-ask spreads . 33 5.5.2 Banks . 35 5.5.3 Pinning . 35 3 5.5.4 Regression model . 35 6 Results 36 6.1 Cross-sectoral analysis . 36 6.1.1 Differences across tenors . 36 6.1.2 Cross-sectoral differences . 36 6.2 ETFs . 48 6.3 Deep dive: bank sector . 50 6.3.1 High-capitalization vs. low-capitalization banks . 51 6.3.2 US vs. European banks . 56 6.4 Pin risk . 60 6.5 Regression model of bid-ask spreads . 63 7 Conclusions 70 8 Outlook 72 A Appendix A 78 B Appendix B 81 C Appendix C 87 4 List of Figures 1 VIX index ................................ 26 2 TED spread ............................... 27 3 US 10-year Treasury yields ....................... 28 4 German 10-year government bond yields ................ 29 5 Italian 2-year government bond yields ................. 30 6 OTC-X Liquidity index ......................... 31 7 Capital Markets Liquidity index .................... 32 8 EUR-USD basis swap spread ...................... 33 9 Low-cap cross-sectoral bid-ask spreads in a low-liquidity regime ... 39 10 Low-cap cross-sectoral bid-ask spreads in a high-liquidity regime .. 39 11 High-cap cross-sectoral bid-ask spreads in a low-liquidity regime .. 40 12 High-cap cross-sectoral bid-ask spreads in a high-liquidity regime .. 40 13 Average bid-ask spreads across various moneyness levels in the Bank and Technology sectors in the high liquidity regime .......... 42 14 Average bid-ask spreads across various moneyness levels in the Bank and Technology sectors in the low liquidity regime ........... 42 15 OTM high-cap vs. low-cap bid-ask spreads in the tech sector in a low liquidity regime ............................. 45 16 OTM high-cap bid-ask spreads in the tech sector in a low vs. high liquidity regime (x-axis shows a day count for the sake of comparison) 46 17 Tech sector high-cap vs. low cap average trading volume in a low liquidity regime ............................. 46 18 Tech sector high-cap average trading volume in a high liquidity vs. low liquidity regime (x-axis shows a day count for the sake of comparison) 47 19 Tech sector high-cap average open interest in a high liquidity vs. low liquidity regime (x-axis shows a day count for the sake of comparison) 47 20 Tech sector high-cap vs. low-cap average open interest in a high liq- uidity regime .............................. 48 21 Average bid-ask spreads of options on the most popular ETFs with 1-m maturity in the low liquidity period ................... 50 22 Average bid-ask spreads of high-cap US banks in a high-liquidity period 55 23 Average bid-ask spreads of high-cap US banks in a low-liquidity period 55 5 24 Average bid-ask spreads of US banks in a high-liquidity period .... 59 25 Average bid-ask spreads of European banks in a high-liquidity period 60 26 Apple OTM option ........................... 61 27 Apple ATM option ............................ 62 28 Apple ITM option ............................ 62 29 Apple OTM vs. ATM vs. ITM in July .................. 63 30 The comparison of the actual and the predicted values for the simple linear model in the low liquidity period ................ 66 31 The comparison of the actual and the predicted values for the simple linear model in the high liquidity period ................ 66 32 The comparison of the transformed spread and the predicted values for the final model in the low liquidity period ............... 70 33 The comparison of the transformed spread and the predicted values for the final model in the high liquidity period ............... 70 34 The output of the Breusch-Pagan test for the simple linear model ... 87 List of Tables 1 Average relative bid-ask spreads of OTM options (at 90% of the strike price) across maturities and sectors .................. 36 2 25th, 50th and 75th percentiles of daily sector spreads distribution in the high liquidity regime at 90% moneyness .............. 38 3 25th, 50th and 75th percentiles of daily sector spreads distribution in the low liquidity regime at 90% moneyness ............... 38 4 Correlation of high-cap vs. low-cap banks with the VIX index across various moneyness levels and with 1-month maturity ......... 53 5 Correlation of high-cap vs. low-cap banks with the VIX index across different maturities at 90% moneyness ................. 53 6 Correlation of high-cap vs. low-cap banks with the various fear and liquidity indices at 90% moneyness and with 1-month maturity .... 54 7 Average bid-ask spreads of high-cap vs. low-cap US banks with 1- month maturity ............................. 54 8 Correlation of US vs. European banks with the VIX index across vari- ous moneyness levels with 1-month maturity .............. 58 6 9 Correlation of US vs. European banks with the VIX index across dif- ferent maturities at 90% moneyness .................. 58 10 Correlation of US vs. European banks with various fear indices at 90% moneyness and with 1-month maturity ................. 58 11 Average bid-ask spreads of US vs. European banks with 1-m maturity 59 12 The coefficients of the simple linear model ............... 65 13 The ANOVA table of the simple linear model .............. 65 14 The normality test of the simple linear model ............. 67 15 The model summary of the final model ................. 68 16 The coefficients of the final model ................... 69 17 The normality test of the final model .................. 69 18 Average annualized volatility of OTM (at 90% of the strike price) bid- ask spreads across sectors ....................... 81 19 Cross-moneyness correlation with the VIX index ............ 82 20 Cross-index correlation of OTM (at 90% of the strike price) bid-ask spreads ................................. 82 21 Cross-maturity correlation with the VIX index at 90% moneyness ... 82 22 Average bid-ask spread, trading volume and open interest across sectors 83 23 Statistical significance of correlation coefficients of the bank sector (p- values) .................................. 85 24 Average bid-ask spread of options on the most popular ETFs with 1-m maturity ................................. 86 25 Model summary of the simple linear model ............... 87 26 The residual statistics of the simple linear model ............ 88 7 1 Introduction Since 15 September 2008, liquidity has been on the forefront of financial markets’ at- tention. On that day Lehman Brothers, one of the longest standing and most renowned investment banks, collapsed and its demise triggered a rapid dry-up of liquidity in al- most all major markets.
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