## Abstract We combine the best features of two highly successful quadrature option pricing streams, improving the linked issues of numerical precision and abscissa positioning. Coupling the recombining abscissa (node) approach used in Andricopoulos, A., Widdicks, M., Duck, P., and Newton, D.P. (20
An efficient approximation method for American exotic options
β Scribed by Geunhyuk Chang; Jangkoo Kang; Hwa-Sung Kim; In Joon Kim
- Publisher
- John Wiley and Sons
- Year
- 2006
- Tongue
- English
- Weight
- 239 KB
- Volume
- 27
- Category
- Article
- ISSN
- 0270-7314
No coin nor oath required. For personal study only.
β¦ Synopsis
Abstract
The authors suggest a modified quadratic approximation scheme, and apply this scheme to American barrier (knockβout) and floatingβstrike lookback options. This modified scheme introduces an additional parameter into the quadratic approximation method, originally suggested by G. BaroneβAdesi and R. Whaley (1987), to reduce pricing errors. When the barrier is close to the underlying asset's current price, the approximation formula is more accurate than lattice methods because the optimal exercise boundary is independent of the underlying asset's current price. That is, the proposed method overcomes the βnearβbarrierβ problem that occurs in lattice methods. In addition, the pricing error decreases when the underlying asset's volatility is high. This approximation scheme is more efficient than B. Gao, J. Huang, and M. Subrahmanyam's (2000) method. As a second application of the modified approximation scheme, the authors provide an approximation formula for American floatingβstrike lookback options which is the first approximation formula ever suggested in the literature. Compared to S. Babbs' (2000) binomial approach, our approximation method is more efficient after controlling for pricing errors, and is more accurate after controlling for computing time. Β© 2007 Wiley Periodicals, Inc. Jrl Fut Mark 27:29β59, 2007
π SIMILAR VOLUMES
This study proposes a forward Monte Carlo method for the pricing of American options. The main advantage of this method is that it does not use backward induction as required by other methods. Instead, the proposed approach relies on a wise determination about whether a simulated stock price has ent
We revisit the stochastic mesh method for pricing American options, from a conditioning viewpoint, rather than the importance sampling viewpoint of Broadie and Glasserman (1997). Starting from this new viewpoint, we derive the weights proposed by Broadie and Glasserman (1997) and show that their wei