L. Clewlow and C. Strickland. Implementing derivatives models. John Wiley & Sons Ltd., Chichester, 1999.  Home/Search   Document Not in Database   Summary   Related Articles   Check

.... depending on the development of interest rates For simple cases analytical formulas are available, but for a range of products, whose cash flows depend on a value of a financial variable in the past so called path dependent products Monte Carlo simulation techniques have to be applied [6] [10]. By utilizing massively parallel architectures very efficient implementations can be achieved [29] 46] For a detailed description of the technique implemented see [37] HPF PROCESSORS : PR(NUMBER OF PROCESSORS( HPF DISTRIBUTE (BLOCK) ONTO PR : VALUE . TYPE(BOND) B the ....

L. Clelow and C. Strickland. Implementing derivative Models. John Wiley & Sons, 1998.

....74S05, 74S20, 91B02, 34K28. 1 Introduction This paper addresses the general problem of developing and evaluating ecient techniques and environments for the solution of the American Option Valuation Problem. Considerable research e ort has been dedicated recently in this direction see e.g. [1, 2, 3, 4, 7, 5, 9]. The problem admits several mathematical formulations. We focus on the moving boundary formulation and, to x the ideas, on the put case. We introduce a general approach for front tracking that works with any practical method used for xed boundaries and presents several advantages. It allows for ....

L. Clewlow and C. Strickland, Implementing Derivatives Models, Willey, (1998).

....(2000) 623639 The particular contribution of the work in this paper centers on the novel coupling of performance models with individual application codes which may be used for dynamic performance optimizations. Given a particular nancial option calculation (from a plethora of coding possibilities [4]) it is possible to construct performance models which may be used at run time to dynamically steer the codes execution. Choices such as the number of nodes to be used and even the choice of system (when several are available) can be determined by the performance model. This leads to an ....

.... trajectories were simulated using the ran1( generator from [8] The accuracy of the resulting price is primarily a function of the number of Monte Carlo trials performed (although elegant methods of increasing this accuracy level are available, such as control variates and antithetic variables [4]) The trajectory calculations are autonomous, hence this method can exploit parallel computation very eectively, and close to linear speedup can be achieved even with relatively low bandwidth high latency inter processor communication channels. We will investigate the pricing of two nancial ....

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L. Clewlow, C. Strickland, Implementing Derivative Models, Wiley, New York, 1998.

....parameters of the volatility process confirm the significance of a non trivial correlation structure in the model dynamics. 17 One possible direction to enrich the volatility and correlation structure further is to assume a four factor model with two correlated stochastic volatility processes [7]. The calibration issue also remains to be resolved in detail, where the focus of concern will be an e#cient procedure for backing out a implied correlation surface from observed option prices. ....

Clewlow, L. and C. Strickland (1998). Implementing Derivatives Models. John Wiley & Sons Ltd.

....of interest rates For simple cases analytical formulas are available, but in general numerical techniques have to be applied. Products, whose cash flows depend on a value of a financial variable in the past (path dependent products) are priced with Monte Carlo simulation techniques (see [5] [7]) Instruments without path The work described in this paper was partially supported by the Special Research Program SFB F011 AURORA of the Austrian Science Fund and by NEC Europe Ltd. within the co operation project ADVANCE of the C C Research Laboratories, St. Augustin, Germany, with the ....

L. Clelow, C. Strickland. Implementing Derivative Models. John Wiley & Sons, 1998.

.... security, e.g. stock prices or interest rates For simple cases analytical formulas are available, but for a range of products, whose cash flows depend on a value of a financial variable in the past so called path dependent products Monte Carlo simulation techniques have to be applied [38, 35]. By utilizing massively parallel architectures very efficient implementations can be achieved [31, 47] 15 0 100 200 300 400 500 600 N 0 10 20 30 40 50 secs measured predicted Figure 6. Measured versus predicted computation times of the Cholesky factorization for various problem ....

C. S. L. Clelow. Implementing derivative Models. John Wiley & Sons, 1998.

.... security, e.g. stock prices or interest rates For simple cases analytical formulas are available, but for a range of products, whose cash flows depend on a value of a financial variable in the past so called path dependent products Monte Carlo simulation techniques have to be applied [60, 54]. By utilizing massively parallel architectures very efficient implementations can be achieved [50, 86] The parallel pricing system has been encoded as an HPF program (see Figure 4.11) and executed on the NEC Cenju 4 [57] distributed memory multiprocessor system. HPF PROCESSORS : ....

C. Strickland L. Clelow. Implementing derivative Models. John Wiley & Sons, 1998.

....sampled. It is known that the application of these closed form solutions leads to substantial pricing errors for discretely sampled options [1, 2, 3] This feature has necessitated the development of practical and efficient computational methods for the evaluation of path dependent options [4]. Most research has focussed on either partial differential equation, Monte Carlo or tree based methods. In contrast to these approaches, in this paper I will develop an alternative based on the path integral formulation of the pricing problem. For many years, theoretical physicists have been ....

....will greatly reduce the dimension of the random paths to be simulated. In effect, it allows random simulations to be replaced with deterministic calculations. Standard methods to increase the efficiency of the Monte Carlo evaluation can still be used. These include variance reduction techniques [4], the simulation of sample paths using the Brownian bridge process [42] or the use of quasi Monte Carlo sampling [4, 43] Interestingly, quasi Monte Carlo sampling is known to be more advantageous for low dimensional numerical integrals. The partial averaging method can therefore increase the ....

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L. Clewlow and C. Strickland, Implementing Derivative Models, (John Wiley and Sons) London 1998.

.... underlying, e.g. stock prices or interest rates For simple cases analytical formulas are available, but for a range of products, whose cash flows depend on a value of a financial variable in the past so called path dependent products Monte Carlo simulation techniques have to be applied [33] [28]. By utilizing massively parallel architectures very efficient implementations can be achieved [25] 41] For a detailed description of the technique implemented see [11] and [18] The Monte Carlo simulation is based on a discrete representation of a stochastic process that describes the dynamics ....

C. S. L. Clelow. Implementing derivative Models. John Wiley & Sons, 1998.

....and efficient procedure involving the use of trinomial trees for modelling the spot process (2.2) so that it is consistent with initial market data. The procedure is similar to constructing trinomial trees for the short rate, as outlined by Hull and White [1994a, 1994b] and described in detail in Clewlow and Strickland [1998]. Valuing Energy Options in a One Factor Model Clewlow and Strickland energy single factor 10 These trees can then be used for pricing American style and path dependent options. American option valuation requires evaluation of the following expression Y = exp( ....

....) 2 1 2 2 2 2 2 2 , j k j k x t x j k x t x t p j i i j i d a a s (4.6) j i d j i u i m p p p , 1 = The procedure described so far applies to the process x with q( t = 0 and x = 0 . 4 The methodology generalises in a straightforward way to non constant time and space steps (see Clewlow and Strickland [1998], Chapter 5. 5 See Hull and White [1993] Valuing Energy Options in a One Factor Model Clewlow and Strickland energy single factor 12 The second stage in the tree building procedure consists of displacing the nodes in the simplified tree in order to add the proper drift and to be consistent ....

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Clewlow L, and C Strickland, 1998, Implementing Derivatives Models, John Wiley and Sons, London.

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L. Clewlow and C. Strickland. Implementing derivatives models. John Wiley & Sons Ltd., Chichester, 1999.

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C. Strickland L. Clelow. Implementing derivative Models. John Wiley & Sons, 1998.

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C. S. L. Clelow. Implementing derivative Models. John Wiley & Sons, 1998.

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L. Clewlow and C. Strickland. Implementing derivative models. John Wiley & Sons, 1998.

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Clewlow, L. and C. Strickland (1998) Implementing Derivatives Models, John Wiley & Sons.

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L. Clelow, C. Strickland. Implementing derivative Models. John Wiley & Sons, 1998.

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