“…First, we have to introduce a further approximation to make the coefficients totally computable, since the joint distributions necessary to compute u 0 , u 1 , φ 1 and ψ 1 are usually unknown. This approximation is of the same type as the one appearing in Antonelli and Scarlatti (2009), which also contains an estimation of the relative error. …”
Section: The Methods In Practicementioning
confidence: 99%
“…is ensured within an appropriate radius of convergence (see Antonelli and Scarlatti (2009) for the details).…”
Section: The Correlation Expansion Approachmentioning
confidence: 99%
“…(12) and we want to identify the four coefficients of the polynomial. To do so, we are going to apply the method developed in Antonelli and Scarlatti (2009) …”
Section: The Correlation Expansion Approachmentioning
confidence: 99%
“…In Antonelli and Scarlatti (2009) the setting was one dimensional, but the ease of the method made us try an application to a multidimensional situation, such as the present one. The method is based on an iterative procedure.…”
mentioning
confidence: 99%
“…In this paper we tackle the pricing of an exchange or Fisher-Margrabe option (Margrabe 1978;Fisher 1978), under stochastic volatility using an analytical approximation recently introduced in a work by Antonelli and Scarlatti (2009) to evaluate plain vanilla European call options, by writing a power series expansion of the no arbitrage price with respect to the correlation parameter between asset and volatility. It resulted fairly general, working for a variety of models, including the Stein and Stein (1991), the Heston (1993) and the Hull and White (1987) ones.…”
Efficient valuation of exchange options with random volatilities while challenging at analytical level, has strong practical implications: in this paper we present a new approach to the problem which allows for extensions of previous known results. We undertake a route based on a multi-asset generalization of a methodology developed in Antonelli and Scarlatti (Finan Stoch 13:269-303, 2009) to handle simple European one-asset derivatives with volatility paths described by Ito's diffusive equations. Our method seems to adapt rather smoothly to the evaluation of Exchange options involving correlations among all the financial quantities that specify the model and it is based on expanding and approximating the theoretical evaluation formula with respect to correlation parameters. It applies to a whole range of models and does not require any particular distributional property. In order to test the quality of our approximation numerical simulations are provided in the last part of the paper.
“…First, we have to introduce a further approximation to make the coefficients totally computable, since the joint distributions necessary to compute u 0 , u 1 , φ 1 and ψ 1 are usually unknown. This approximation is of the same type as the one appearing in Antonelli and Scarlatti (2009), which also contains an estimation of the relative error. …”
Section: The Methods In Practicementioning
confidence: 99%
“…is ensured within an appropriate radius of convergence (see Antonelli and Scarlatti (2009) for the details).…”
Section: The Correlation Expansion Approachmentioning
confidence: 99%
“…(12) and we want to identify the four coefficients of the polynomial. To do so, we are going to apply the method developed in Antonelli and Scarlatti (2009) …”
Section: The Correlation Expansion Approachmentioning
confidence: 99%
“…In Antonelli and Scarlatti (2009) the setting was one dimensional, but the ease of the method made us try an application to a multidimensional situation, such as the present one. The method is based on an iterative procedure.…”
mentioning
confidence: 99%
“…In this paper we tackle the pricing of an exchange or Fisher-Margrabe option (Margrabe 1978;Fisher 1978), under stochastic volatility using an analytical approximation recently introduced in a work by Antonelli and Scarlatti (2009) to evaluate plain vanilla European call options, by writing a power series expansion of the no arbitrage price with respect to the correlation parameter between asset and volatility. It resulted fairly general, working for a variety of models, including the Stein and Stein (1991), the Heston (1993) and the Hull and White (1987) ones.…”
Efficient valuation of exchange options with random volatilities while challenging at analytical level, has strong practical implications: in this paper we present a new approach to the problem which allows for extensions of previous known results. We undertake a route based on a multi-asset generalization of a methodology developed in Antonelli and Scarlatti (Finan Stoch 13:269-303, 2009) to handle simple European one-asset derivatives with volatility paths described by Ito's diffusive equations. Our method seems to adapt rather smoothly to the evaluation of Exchange options involving correlations among all the financial quantities that specify the model and it is based on expanding and approximating the theoretical evaluation formula with respect to correlation parameters. It applies to a whole range of models and does not require any particular distributional property. In order to test the quality of our approximation numerical simulations are provided in the last part of the paper.
By means of classical Itô's calculus we decompose option prices as the sum of the classical Black-Scholes formula with volatility parameter equal to the root-mean-square future average volatility plus a term due by correlation and a term due to the volatility of the volatility. This decomposition allows us to develop …rst and second-order approximation formulas for option prices and implied volatilities in the Heston volatility framework, as well as to study their accuracy. Numerical examples are given.
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