A Survey of Parallel Tree- based Methods on Option Pricing PRESENTER: LI,XINYING

Outline  Introduction  Black-Scholes Model  Binomial Options Pricing Model  Trinomial Options Pricing Model  Improved Binomial Option Pricing  CPU-GPU Hybrid Parallel Binomial  Summary

Introduction Stock Bond Currency Underlying Asset!

Introduction Option’s price is based on the corresponding underlying asset’s price. + A suitable price of option

Introduction According to the Options’ right: Call Option & Put Option Option Styles: European Option American Option Bermudan Option Asian Option Barrier Option Binary Option Exotic Option Vanilla Option Classification of options

Introduction CPU: efficient in serial computin g Central Processing Unit (CPU) Graphics Processing Unit (GPU) GPU: efficient in parallel computing CPU: efficient in serial computing

Introduction Option pricing:  High demand on calculating speed  Heavy computation volume  The calculation procedure could be parallelized Input: price of the underlying asset GPU: parallel computing Output: option price Efficient Algorithm

Introduction Storage Accuracy Efficiency Properties for evaluating the option pricing method Therefore, a series of tree-based algorithms have been proposed to optimize the previous ones from different aspects.

Outline  Introduction  Black-Scholes Model  Binomial Options Pricing Model  Trinomial Options Pricing Model  Improved Binomial Option Pricing  CPU-GPU Hybrid Parallel Binomial  Summary

Black-Scholes Model

Outline  Introduction  Black-Scholes Model  Binomial Options Pricing Model  Trinomial Options Pricing Model  Improved Binomial Option Pricing  CPU-GPU Hybrid Parallel Binomial  Summary

Binomial Options Pricing Model (BOPM) The Binomial Model was first proposed by Cox, Ross and Rubinstein in Essentially, the model uses a “discrete-time” model of the varying price over time of the underlying financial instrument. Option valuation using this method is, as described, a three-step process: 1.Price tree generation, 2.Calculation of option value at each final node, 3.Sequential calculation of the option value at each preceding node.

Binomial Options Pricing Model (BOPM)

Use of the Model Handling a variety of conditions & Over a period of time rather than a single point Slower than the Black- Scholes formula but more accurate, especially for long-dated options Less practical for options with several sources of uncertainty and complicated features

Outline  Introduction  Black-Scholes Model  Binomial Options Pricing Model  Trinomial Options Pricing Model  Improved Binomial Option Pricing  CPU-GPU Hybrid Parallel Binomial  Summary

Trinomial Options Pricing Model The Trinomial Tree was developed by Phelim Boyle in It is an extension of the Binomial options pricing model, and is conceptually similar. Under the Trinomial method, at each node, the price has three possible paths: an up, down and stable or middle path.

Trinomial Options Pricing Model

More accurate than the BOPM when fewer time steps are modelled. For vanilla options, the binomial model is preferred due to its simple implementation. For exotic options, the trinomial model is more stable and accurate, regardless of step-size. Use of the Model

Outline  Introduction  Black-Scholes Model  Binomial Options Pricing Model  Trinomial Options Pricing Model  Improved Binomial Option Pricing  CPU-GPU Hybrid Parallel Binomial  Summary

Improved Binomial Option Pricing It is proposed by Mohammad Zubair and Ravi Mukkamala in This algorithm exploits the underlying memory hierarchy using cache blocking techniques. Assume cache of the processor running Vanilla algorithm can hold up to m elements of the array. Considering the nested loop which includes the outer and inner loop, we partition the computation into a certain number of blocks. And therefore, we can fetch m elements of the array into cache.

Improved Binomial Option Pricing

Outline  Introduction  Black-Scholes Model  Binomial Options Pricing Model  Trinomial Options Pricing Model  Improved Binomial Option Pricing  CPU-GPU Hybrid Parallel Binomial  Summary

CPU-GPU Hybrid Parallel Binomial It is proposed by Nan Zhang et al. in The hardware devices includes two CPU cores and a GPU. CPU 1: communication & synchronization CPU 2 GPU Both share equal workload with each other. To see the performance of the hybrid algorithm we did two groups of tests where L, the maximum number of levels in a block, was set to 20 and 50, respectively. Principle of Hybrid

CPU-GPU Hybrid Parallel Binomial Speedup plots of the CPU parallel implementation and the hybrid implementation

Outline  Introduction  Black-Scholes Model  Binomial Options Pricing Model  Trinomial Options Pricing Model  Improved Binomial Option Pricing  CPU-GPU Hybrid Parallel Binomial  Summary

Summary In order to improve the calculation efficiency, GPU computation became a promising tool for option pricing. We mainly focus on the parallel tree-based algorithms on option pricing. The Black-Scholes Model is the theory basis of all the other algorithms. All the other tree-based algorithms including the trinomial lattice are based on the method of binomial lattice. In the future, we will further improve the parallel algorithm on GPU to achieve better accuracy and efficiency on option pricing.

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