The dynamics of the volatility skew: A Kalman filter approach

Generalized parameter functions for option pricing

“…CSbased enhanced models with five or more hidden neurons exhibit quite similar out-of-sample RMSE, which are close to the optimal ones, shown in Table 5. 27 According to Bedendo and Hodges (2009), new trades incorporate new information; thus, robustness of the option pricing method to such trades is very important.…”

“…According to Bedendo and Hodges (2009), much attention has been devoted to understanding and modeling the dynamics of the implied volatility functions, which is a crucial task for both trading, pricing and risk-management of option positions 4 . For our analysis, we estimate the following three regression-based DVF specifications, as proposed 5 in Dumas et al (1998):…”

Information Content of Options Trading Volume for Future Volatility: Evidence from the Taiwan Options Market

“…For example, using datasets containing comprehensive transaction records, Pan and Poteshman (2006) and Chang et al (2009) show that the transactions of different categories of option traders reveal varying degrees of directional information, whilst Ni et al (2008) find that the trading volume of non-market makers contains volatility information. 2 To the best of our knowledge, no study has yet utilized the complete transaction records of an options market to investigate which category of option traders (domestic institutional traders, foreign institutional traders or individuals) possess volatility 1 See Canina and Figlewski (1993), Jorion (1995), Fleming (1998), Blair et al (2001), Poon and Granger (2003), Pong et al (2004), Jiang and Tian (2005), Doran et al (2007), Konstantinidi et al (2008) and Bedendo and Hodges (2009). 2 See also Chan et al (2002), Chakravarty et al (2004), Cao et al (2005) and Chern et al (2008) . information.…”

An efficient estimate and forecast of the implied volatility surface: A nonlinear Kalman filter approach

“…The problem is, error in the first step may cause remarkable inaccuracy in the second step. So Bedendo and Hodges (2009) adopts one-step Kalman filter approach to provide a more accurate and robust estimation for the model parameters, and it is the first application of Kalman filter to the updating of volatility skew.…”

“…Compared to Bedendo and Hodges (2009), we don't restrict the measurement equation-which is used to capture single implied volatility surface at each time-to be linear, since many non-linear parameterizations have much better fitting accuracy and theoretical backgrounds. Coefficients of the measurement equation are factors driving the evolution of the whole surface, whose dynamics can be described by a set of stochastic differential equations.…”