Timeline for Option Pricing Model Calibration In Practice
Current License: CC BY-SA 3.0
11 events
| when toggle format | what | by | license | comment | |
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| Jun 26, 2015 at 15:00 | comment | added | user16651 | S&P , option price Microsoft Corporation , ... | |
| Jun 26, 2015 at 13:50 | comment | added | bcf | @BehrouzMaleki Thanks for the detailed response. I am familiar with calibration and model evaluation methods - my question is, which data to use? | |
| Jun 25, 2015 at 21:03 | comment | added | user16651 | This allows us to bypass the bisection algorithm entirely. Another remedy is to use the loss function described in Christoffersen et al. (2009), which serves as an approximation to the IVMSE. | |
| Jun 25, 2015 at 20:57 | history | edited | user16651 | CC BY-SA 3.0 |
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| Jun 25, 2015 at 20:43 | comment | added | user16651 | By Bisection Method , Christoffersen (2009). | |
| Jun 25, 2015 at 20:33 | comment | added | emcor | How do you determine the model price $P$!? | |
| Jun 25, 2015 at 20:19 | comment | added | user16651 | Carr and Madan (1999) present a derivation of the call price based on the Fourier transform. It offers advantages in terms of reduced computation time and an integrand that decays faster than the integrand of the original Heston (1993) formulation. | |
| Jun 25, 2015 at 20:18 | comment | added | Gordon | For calibration, a quick valuation, in particular, analytical approach, is preferred. What valuation method will you use for the Heston variance model calibration? | |
| Jun 25, 2015 at 20:15 | comment | added | user16651 | The application of Fourier transforms to option pricing is not limited to obtaining probabilities, as is done in Heston’s (1993) original derivation. As explained by Wu (2008), the literature approaches Fourier transforms in option pricing in two broad ways. The first approach considers option prices to be analogous to cumulative distribution functions. This is the approach adopted by Heston (1993), Carr and Madan (1999), Bakshi and Madan (2000), and others. The second approach considers option prices to be analogous to probability density functions. | |
| Jun 25, 2015 at 20:06 | comment | added | Gordon | Under the Heston variance model, the option pricing is either based on Monte Carlo or Fourier transformation; however, either is time consuming. How do you compute the option price in your calibration? | |
| Jun 25, 2015 at 19:57 | history | answered | user16651 | CC BY-SA 3.0 |