Pricing Barrier Options Research Articles

Parallel option pricing on GPU: barrier options and realized variance options

This paper shows two examples of how the analysis of option pricing problems can lead to computational methods efficiently implemented in parallel. These computational methods outperform “general purpose” methods (i.e., for example, Monte Carlo, finite differences methods). The GPU implementation of two numerical algorithms to price two specific derivatives (continuous barrier options and realized variance options) is presented. These algorithms are implemented in CUDA subroutines ready to run on Graphics Processing Units (GPUs) and their performance is studied. The realization of these subroutines is motivated by the extensive use of the derivatives considered in the financial markets to hedge or to take risk and by the interest of financial institutions in the use of state of the art hardware and software to speed up the decision process. The performance of these algorithms is measured using the (CPU/GPU) speed up factor, that is using the ratio between the (wall clock) times required to execute the code on a CPU and on a GPU. The choice of the reference CPU and GPU used to evaluate the speed up factors presented is stated. The outstanding performance of the algorithms developed is due to the mathematical properties of the pricing formulae used and to the ad hoc software implementation. In the case of realized variance options when the computation is done in single precision the comparisons between CPU and GPU execution times gives speed up factors of the order of a few hundreds. For barrier options, the corresponding speed up factors are of about fifteen, twenty. The CUDA subroutines to price barrier options and realized variance options can be downloaded from the website http://www.econ.univpm.it/recchioni/finance/w13. A more general reference to the work in mathematical finance of some of the authors and of their coauthors is the website http://www.econ.univpm.it/recchioni/finance/.

Ergodic approximation of the distribution of a stationary diffusion: Rate of convergence

We extend to Lipschitz continuous functionals either of the true paths or of the Euler scheme with decreasing step of a wide class of Brownian ergodic diffusions, the Central Limit Theorems formally established for their marginal empirical measure of these processes (which is classical for the diffusions and more recent as concerns their discretization schemes). We illustrate our results by simulations in connection with barrier option pricing.

A new radial basis functions method for pricing American options under Merton's jump-diffusion model

A new radial basis functions (RBFs) algorithm for pricing financial options under Merton's jump-diffusion model is described. The method is based on a differential quadrature approach, that allows the implementation of the boundary conditions in an efficient way. The semi-discrete equations obtained after approximation of the spatial derivatives, using RBFs based on differential quadrature are solved, using an exponential time integration scheme and we provide several numerical tests which show the superiority of this method over the popular Crank–Nicolson method. Various numerical results for the pricing of European, American and barrier options are given to illustrate the efficiency and accuracy of this new algorithm. We also show that the option Greeks such as the Delta and Gamma sensitivity measures are efficiently computed to high accuracy.

An efficient algorithm for Bermudan barrier option pricing

An efficient option pricing method based on Fourier-cosine expansions was presented by Fang and Oosterlee for European options in 2008, and later, this method was also used by them to price early-exercise options and barrier options respectively, in 2009. In this paper, this method is applied to price discretely American barrier options in which the monitored dates are many times more than the exercise dates. The corresponding algorithm is presented to practical option pricing. Numerical experiments show that this algorithm works very well and efficiently for different exponential Levy asset models.

A Stochastic Approach to the Valuation of Barrier Options in Heston’s Stochastic Volatility Model

In the valuation of continuous barrier options the distribution of the first hitting time plays a substantial role. In general, the derivation of a hitting time distribution poses a mathematically challenging problem for continuous but otherwise arbitrary boundary curves. When considering barrier options in the Heston model the non-linearity of the variance process leads to the problem of a non-linear hitting boundary. Here, we choose a stochastic approach to solve this problem in the reduced Heston framework, when the correlation is zero and foreign and domestic interest rates are equal. In this context one of our main findings involves the proof of the reflection principle for a driftless Ito process with a time-dependent variance. Combining the two results, we derive a closed-form formula for the value of continuous barrier options. Compared to an existing pricing formula, our solution provides further insight into how the barrier option value in the Heston model is constructed. Extending the results to the general Heston framework with arbitrary correlation and drift, we obtain approximations for the joint random variables of the Ito process and its maximum in a weak sense. As a consequence, an approximate formula for pricing barrier options is established. A numerical case study is also performed which illustrates the agreement in results of our developed formulas with standard finite difference methods.

Double Barrier Options in Regime-Switching Hyper-Exponential Jump-Diffusion Models

We present a fast and accurate algorithm for calculating prices of finite lived double barrier options with arbitrary terminal payoff functions under regime-switching hyper-exponential jump-diffusion models, which generalize Kou's model. Extensive numerical tests demonstrate excellent agreement of our results with those obtained using other methods. The first step of our approach is Carr's randomization, which we prove for barrier options under strong Markov processes of a wide class. The resulting sequence of perpetual option pricing problems is solved using an efficient iteration algorithm and the Wiener-Hopf factorization.

Pricing Bounds on Barrier Options

This paper proposes the optimal pricing bounds on barrier options in an environment where plain-vanilla options and no-touch options can be used as hedging instruments.Without specifying underlying processes, we derive super-/sub-hedging portfolios which are static ones consisting of not only plain-vanilla options but also cash-paying no-touch options and/or asset paying no-touch options that pay one cash or one underlying asset respectively if the barrier has not been hit. Our pricing bounds are the value of the super-/sub-hedging portfolio. Moreover, they are the optimal pricing bounds through finding risk-neutral measures under which the barrier option price is equal to the hedging portfolio's value. Our model-independent pricing bounds are useful because a price of a barrier option is significantly dependent on a model. It is demonstrated through numerical examples that prices outside our pricing bounds can be produced by models which are calibrated to market prices of plain-vanilla options, but not to that of a no-touch option.

An Accurate FFT-Based Algorithm for Bermudan Barrier Option Pricing

An efficient and accurate numerical method, which is called the CONV method, was proposed by Lord et al in [1] to price Bermudan options. In this paper, this method is applied to price Bermudan barrier options in which the monitored dates may be many times more than the exercise dates. The corresponding algorithm is presented to practical option pricing. Numerical experiments show that this algorithm works very well for different exponential Lévy asset models.

Pricing barrier and average options in a stochastic volatility environment.

This paper proposes a new approximation method of pricing barrier and average options under stochastic volatility environment by applying an asymptotic expansion approach. In particular, a high-order expansion scheme for general multi-dimensional diffusion processes is effectively applied. Moreover, the paper combines a static hedging method with the asymptotic expansion method for pricing barrier options. Finally, numerical examples show that the fourth or fifth-order asymptotic expansion scheme provides sufficiently accurate approximations under the λ-SABR and SABR models.

DOUBLE BARRIER OPTIONS IN REGIME-SWITCHING HYPER-EXPONENTIAL JUMP-DIFFUSION MODELS

We present a very fast and accurate algorithm for calculating prices of finite lived double barrier options with arbitrary terminal payoff functions under regime-switching hyper-exponential jump-diffusion (HEJD) models, which generalize the double-exponential jump-diffusion model pioneered by Kou and Lipton. Numerical tests demonstrate an excellent agreement of our results with those obtained using other methods, as well as a significant increase in computation speed (sometimes by a factor of 5). The first step of our approach is Carr's randomization, whose convergence we prove for barrier and double barrier options under strong Markov processes of a wide class. The resulting sequence of perpetual option pricing problems is solved using an efficient iteration algorithm and the Wiener-Hopf factorization.

PRICES OF BARRIER AND FIRST-TOUCH DIGITAL OPTIONS IN LÉVY-DRIVEN MODELS, NEAR BARRIER

We calculate the leading term of asymptotics of the prices of barrier options and first-touch digitals near the barrier for wide classes of Lévy processes with exponential jump densities, including the Variance Gamma model, the KoBoL (a.k.a. CGMY) model and Normal Inverse Gaussian processes. In the case of processes of infinite activity and finite variation, with the drift pointing from the barrier, we prove that the price is discontinuous at the boundary. This observation can serve as the basis for a simple robust test of the type of processes observed in real financial markets. In many cases, we calculate the second term of asymptotics as well. By comparing the exact asymptotic results for prices with those of Carr's randomization approximation, we conclude that the latter is very accurate near the barrier. We illustrate this by including numerical results for several types of Lévy processes commonly used in option pricing.

Barrier option pricing for exchange rates under the Levy–HJM processes

In this paper, we present closed-forms for the valuation of the barrier option whose underlying is exchange rate under the multi-dimensional Levy process, including stochastic interest rates and stochastic assets. Instantaneous forward interest rates are assumed under the Heath et al. [1992. Econometrica 60, 77–105] framework, and the analytic formulas of the exchange rate barrier option are obtained when the Levy process is restricted in a double exponential process.

Pricing Discrete Barrier Options Under Stochastic Volatility

This paper proposes a new approximation method for pricing barrier options with discrete monitoring under stochastic volatility environment. In particular, the integration-by-parts formula and the duality formula in Malliavin calculus are effectively applied in pricing barrier options with discrete monitoring. To the best of our knowledge, this paper is the first one that shows an analytical approximation for pricing discrete barrier options with stochastic volatility models. Furthermore, it provides numerical examples for pricing double barrier call options with discrete monitoring under Heston and λ-SABR models.

High-order accurate implicit methods for barrier option pricing

This paper deals with a high-order accurate implicit finite-difference approach to the pricing of barrier options. In this way various types of barrier options are priced, including barrier options paying rebates, and options on dividend-paying-stocks. Moreover, the barriers may be monitored either continuously or discretely. In addition to the high-order accuracy of the scheme, and the stretching effect of the coordinate transformation, the main feature of this approach lies on a probability-based optimal determination of boundary conditions. This leads to much faster and accurate results when compared with similar pricing approaches. The strength of the present scheme is particularly demonstrated in the valuation of discretely monitored barrier options where it yields values closest to those obtained from the only semi-analytical valuation methods available. The scheme is also applied to the analysis of Greeks data such as Delta and Gamma.

Pricing barrier options by a regime switching model

This paper introduces a new way of estimating parameters in a Brownian motion regime switching asset model to incorporate volatility clustering. The regime switching model is then applied to pricing of up-and-in barrier call options. We take the probability of crossing the barrier between simulation points into account, and we increase accuracy in simulations by importance sampling. The regime switching model is compared to the Normal Inverse Gaussian model and the traditional Black–Scholes model, and option prices from the regime switching model are compared to the closed form expression of up-and-in barrier calls in a Black–Scholes market.

Pricing barrier and American options under the SABR model on the graphics processing unit

SUMMARYIn this paper, we presented our study on using the graphics processing unit (GPU) to accelerate the computation in pricing financial options. We first introduced the GPU programming and the SABR stochastic volatility model. We then discussed pricing options with quasi Monte Carlo techniques under the SABR model. In particular, we focused on pricing barrier options by quasi Monte Carlo and conditional probability correction methods and on pricing American options by the least squares Monte Carlo method. We then presented our GPU‐based implementation for pricing barrier options and hybrid CPU–GPU implementation for pricing American options. In addition, we described techniques for efficient use of GPU memory. We provided details of implementing these GPU numerical schemes for pricing options and compared performances of the GPU programs with their CPU counterparts. We found that GPU‐based computing schemes can achieve 134 times speedup for pricing barrier options, while maintaining satisfactory pricing accuracy. For pricing American options, we also reported that when the least squares Monte Carlo method is used, special techniques can be devised to use less GPU memory, resulting in 22 times speedup, instead of the original 10 times speedup. Copyright © 2011 John Wiley & Sons, Ltd.

CONTINUOUSLY MONITORED BARRIER OPTIONS UNDER MARKOV PROCESSES

In this paper, we present an algorithm for pricing barrier options in one‐dimensional Markov models. The approach rests on the construction of an approximating continuous‐time Markov chain that closely follows the dynamics of the given Markov model. We illustrate the method by implementing it for a range of models, including a local Lévy process and a local volatility jump‐diffusion. We also provide a convergence proof and error estimates for this algorithm.

Accurate Pricing of Continuous Barrier Options with Local Volatility

In this paper we develop accurate technics to price continuous barrier options using a one dimensional finite difference scheme, allowing for time dependent drift as well as time and state dependent volatilities. We provide numerical examples which demonstrate the smoothness and accuracy of such methods in the Black-Scholes context as well as in the Dupire Local Volatility model.

Solution of the Black-Scholes Equation for Pricing of Barrier Option

In this paper two different methods are presented to approximate the solution of the Black-Scholes equation for valuation of barrier option. These techniques can be applied directly for all types of differential equations, homogeneous or inhomogeneous. The use of these methods provides the solution of the problem in a closed form while the mesh point techniques provide the approximation at mesh points only. Also, the two schemes need less computational work in comparison with the traditional methods. These techniques can be employed for problems with initial condition. In this paper we use the variational iteration and homotopy perturbation methods for solving the Black-Scholes equation with terminal condition. Numerical results are compared with theoretical solutions in order to confirm the validity of the presented procedures.

Barrier Option Pricing with Model Averaging Methods under Local Volatility Models

In this paper, we propose a method to provide the distribution of option price under local volatility model when market-provided implied volatility data are given. The local volatility model is one of the most widely used smile-consistent models. In local volatility model, the volatility is a deterministic function of the random stock price. Before estimating local volatility surface (LVS), we need to estimate implied volatility surfaces (IVS) from market data. To do this we use local polynomial smoothing method. Then we apply the Dupire formula to estimate the resulting LVS. However, the result is dependent on the bandwidth of kernel function employed in local polynomial smoothing method and to solve this problem, the proposed method in this paper makes use of model averaging approach by means of bandwidth priors, and then produces a robust local volatility surface estimation with a confidence interval. After constructing LVS, we price barrier option with the LVS estimation through Monte Carlo simulation. To show the merits of our proposed method, we have conducted experiments on simulated and market data which are relevant to KOSPI200 call equity linked warrants (ELWs.) We could show by these experiments that the results of the proposed method are quite reasonable and acceptable when compared to the previous works.