Post-'87 crash fears in the S&P 500 futures option market

By David S. Bates. 2000

1,390 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/4f3fbf62af48a8b8fb1e14eb89a58b6f1d21c876

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Citations in the corpus

Calibration and hedging under jump diffusion (2007, background): “they require implausible levels of correlation between volatility and returns and excessively high “volatility of volatility” to match observed prices of index options (Bakshi et al., 1997; Bates, 2000).”
Implied volatility surfaces: uncovering regularities for options on financial futures (2001, background): “Recently, Bates (1999) examined implicit distributions associated with options on the S&P 500 futures for a period post the 1987 crash and found that options prices did not adjust as extreme (negative) moves failed to occur.”
APPROXIMATING GARCH‐JUMP MODELS, JUMP‐DIFFUSION PROCESSES, AND OPTION PRICING (2006, background): “Without switching off jumps, the volatility dynamic in equation (3.14) is more general than that in Bakshi et al. (1997), Bates (2000), or Pan (2002), for it allows for volatility jumps as well.5 Finally, we consider the dynamics under the risk-neutral measure.”
Pricing Vulnerable Options with Jump Clustering (2017, background): “Second, these models are considered to be inconsistent with empirical observations in ﬁnancial markets, where jumps are clearly visible (Bakshi, Cao, & Chen, 1997; Bates, 1996, 2000; Eraker, 2004; Eraker, Johannes, & Polson, 2003; Pan, 2002).”
Opaque financial reports, R2, and crash risk (2009, background): “So-called smirk curves have characterized the implied volatility of individual stock options as well as index options since the crash of October 1987, and they are widely held to reflect risk of future crashes (see Dumas, Fleming, and Whaley, 1998 or Bates, 2000).”
Investor Sentiment and Option Prices (2008, positive): “Bates (2000) finds that including a jump can improve the model’s ability to generate option smile, but in order to do so parameters must be set to unreasonable values that are inconsistent with the time-series properties of underlying asset prices and option prices.”
Extracting Model-Free Volatility from Option Prices (2007, background): “, Black and Scholes [1972], Galai [1977], MacBeth and Merville [1979], Rubinstein [1985], Chance [1986], Shastri and Tandon [1986], Lauterbach and Schultz [1990], and Bakshi, Cao, and Chen [1997]). 3For a survey of the broader literature on volatility forecasting and informational efficiency, see Fi”
High-Frequency Trading and Extreme Price Movements (2018, background): “For instance, EPMs may impair risk management (Duffie and Pan, 2001), derivative pricing (Bates, 2000; Eraker, Johannes, and Polson, 2003) and portfolio allocation (Jarrow and Rosenfield, 1984; Liu, Longstaff, and Pan, 2003).”
Separating Microstructure Noise from Volatility (2006, methodology): “1See Bates (2000), Duffie et al. (2000), Eraker et al. (2003), Pan (2002), among others, and the references therein.”
The information content of high-frequency data for estimating equity return models and forecasting risk (2010, methodology): “Studies of stochastic volatility models with similar findings under risk-neutral measure include Bakshi, Cao, and Chen (1997), Bates (2000), among others. A unified approach using both returns and options data, pursued by Chernov and Ghysels (2000), Eraker (2004) and Jones (2003), has also stressed ”
Optimal portfolios and Heston's stochastic volatility model: an explicit solution for power utility (2005, methodology): “Such a specification was first proposed by Merton (1980) and is used in a couple of papers such as Bakshi/Chao/Chen (1997) and Bates (2000).”
Delta-Hedged Gains and the Negative Market Volatility Risk Premium (2003, methodology): “In his model, the volatility risk premium is linear in volatility (see also the set of assumptions in Bates (2000), Eraker, Johannes and Polson (2000) and Pan (2000)).”
Short-Term Market Risks Implied by Weekly Options (2017, methodology): “Second, we test the quality of the approximation methods for the two-factor stochastic volatility model of Bates (2000).”
No-Arbitrage Semi-Martingale Restrictions for Continuous-Time Volatility Models subject to Leverage Effects, Jumps and i.i.d. Noise: Theory and Testable Distributional Implications (2007, background): “among others, Ait-Sahalia (2002), Andersen, Benzoni and Lund (2002), Bates (2000) , Chan and”
Delta-hedging vega risk? (2004, background): “It has received numerous explanations in the economico-financial literature, such as the leverage effect or crash fears (see Jackwerth–Rubinstein [43] or Bates [8]).”