We analyze the behavior of both the bid-ask spread and the depth of ETF options during the May 6t... more We analyze the behavior of both the bid-ask spread and the depth of ETF options during the May 6th, 2010 Flash Crash. During the Flash Crash stub quotes (maximum quote size allowed) consistently occurred for more than 90% of the ETF option series examined in this study. Correspondingly, the best bid-ask depth for these options completely disappeared for several minutes during the Flash Crash, showing that all liquidity had totally disappeared from the market. Even after the stock market recovered from the Flash Crash the option spreads were significantly larger and the depth smaller compared to before the crash. Such a sudden decline in prices, expansion of bid-ask quotes, and removal of depth with no apparent associated news event is called a “liquidity black hole” and occurs more often than publicly reported.
We develop a new autoregressive conditional seasonal variance (ARCSV) process that captures both ... more We develop a new autoregressive conditional seasonal variance (ARCSV) process that captures both the changes in and the persistency of the intraday seasonal (U-shape) pattern of volatility. Unlike other procedures for seasonality, this approach allows for the intraday volatility pattern to change over time, resulting in an increase in the filtering performance over the extant deterministic filtering models. We quantify the gains in the filtering performance by comparing our model with the flexible Fourier form (FFF) model of Andersen and Bollerslev [J. Empir. Finance, 1997a, 4, 115–158]. Moreover, the ARCSV model does not create any statistical distortion in the filtered series, as occurs with other de-seasoning processes. We prove that the ARCSV model satisfies the spectral criteria required to be judged as a good filtering process. Monte Carlo simulation results show that the performance of the ARCSV model is superior to the FFF model. In particular, the seasonal adjustment performance of the ARCSV model is robust under the condition that the innovation of the underlying seasonal variance process is large and the daily non-seasonal variance process is misspecified.
For anyone who wants to minimize financial risk through future and related cash markets, this boo... more For anyone who wants to minimize financial risk through future and related cash markets, this book contains pedagogy and "quick reference" features, making it useful for students and practitioners alike. Organized by topic rather than type of contract, the text first covers the concepts, empirical evidence and essential equations needed to appreciate the techniques and applications of hedging, pricing and arbitrage. It then discusses the various futures contracts, explaining, in detail, how to use these products to meet specific risk management goals. A blend of academic insights and business "know-how", this book works equally well as a main text for courses on financial futures, as a supplement to any textbook on options and futures or as a practical, on-the-job guide to futures markets.
This book thoroughly explains the options markets. Moreover, the work contains several unique fea... more This book thoroughly explains the options markets. Moreover, the work contains several unique features, including computer codes to calculate changes in options properties, and a historic evaluation of options strategies and pricing theories. As a result, traders learn what works and what doesn't work. Specific features include: exotic options; the factors influencing option pricing; advanced trading strategies such as spreads and straddles; the importance of delta, gamma and theta; and risk management with options.
The transition from manual to electronic markets in options paved the way for pricing efficiencie... more The transition from manual to electronic markets in options paved the way for pricing efficiencies and improved liquidity from options high-frequency market making (HFMM). We find that HFMM reduces option bid–ask spreads, although with differences across both option and firm characteristics. Depth increases with the number of market maker quote revisions, conflicting with extant high-frequency research in other markets. The largest absolute change for spreads (depth) is for mid-size (large) companies. However, the change to penny quotes for options caused HFMM to have less of an effect on both spreads and depth, showing that penny quoting exacerbates the pricing efficiency generated by more frequent quote revisions.
We analyze the behavior of both the bid-ask spread and the depth of ETF options during the May 6t... more We analyze the behavior of both the bid-ask spread and the depth of ETF options during the May 6th, 2010 Flash Crash. During the Flash Crash stub quotes (maximum quote size allowed) consistently occurred for more than 90% of the ETF option series examined in this study. Correspondingly, the best bid-ask depth for these options completely disappeared for several minutes during the Flash Crash, showing that all liquidity had totally disappeared from the market. Even after the stock market recovered from the Flash Crash the option spreads were significantly larger and the depth smaller compared to before the crash. Such a sudden decline in prices, expansion of bid-ask quotes, and removal of depth with no apparent associated news event is called a “liquidity black hole” and occurs more often than publicly reported.
We develop a new autoregressive conditional seasonal variance (ARCSV) process that captures both ... more We develop a new autoregressive conditional seasonal variance (ARCSV) process that captures both the changes in and the persistency of the intraday seasonal (U-shape) pattern of volatility. Unlike other procedures for seasonality, this approach allows for the intraday volatility pattern to change over time, resulting in an increase in the filtering performance over the extant deterministic filtering models. We quantify the gains in the filtering performance by comparing our model with the flexible Fourier form (FFF) model of Andersen and Bollerslev [J. Empir. Finance, 1997a, 4, 115–158]. Moreover, the ARCSV model does not create any statistical distortion in the filtered series, as occurs with other de-seasoning processes. We prove that the ARCSV model satisfies the spectral criteria required to be judged as a good filtering process. Monte Carlo simulation results show that the performance of the ARCSV model is superior to the FFF model. In particular, the seasonal adjustment performance of the ARCSV model is robust under the condition that the innovation of the underlying seasonal variance process is large and the daily non-seasonal variance process is misspecified.
For anyone who wants to minimize financial risk through future and related cash markets, this boo... more For anyone who wants to minimize financial risk through future and related cash markets, this book contains pedagogy and "quick reference" features, making it useful for students and practitioners alike. Organized by topic rather than type of contract, the text first covers the concepts, empirical evidence and essential equations needed to appreciate the techniques and applications of hedging, pricing and arbitrage. It then discusses the various futures contracts, explaining, in detail, how to use these products to meet specific risk management goals. A blend of academic insights and business "know-how", this book works equally well as a main text for courses on financial futures, as a supplement to any textbook on options and futures or as a practical, on-the-job guide to futures markets.
This book thoroughly explains the options markets. Moreover, the work contains several unique fea... more This book thoroughly explains the options markets. Moreover, the work contains several unique features, including computer codes to calculate changes in options properties, and a historic evaluation of options strategies and pricing theories. As a result, traders learn what works and what doesn't work. Specific features include: exotic options; the factors influencing option pricing; advanced trading strategies such as spreads and straddles; the importance of delta, gamma and theta; and risk management with options.
The transition from manual to electronic markets in options paved the way for pricing efficiencie... more The transition from manual to electronic markets in options paved the way for pricing efficiencies and improved liquidity from options high-frequency market making (HFMM). We find that HFMM reduces option bid–ask spreads, although with differences across both option and firm characteristics. Depth increases with the number of market maker quote revisions, conflicting with extant high-frequency research in other markets. The largest absolute change for spreads (depth) is for mid-size (large) companies. However, the change to penny quotes for options caused HFMM to have less of an effect on both spreads and depth, showing that penny quoting exacerbates the pricing efficiency generated by more frequent quote revisions.
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