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GPGPU를 활용한 하이브리드 파생결합증권의 가치평가

A Pricing of Hybrid DLS with GPGPU

초록/요약

The objective of this study is to develop an efficient numerical method for pricing the DLS (Derivative Linked Securities). It is a kind of the ELS (Equity Linked Securities) in Korean Over-the-Counter market. The distinct feature of this hybrid DLS is that it has two equities and an interest rate as its underlying assets. Unlike most ELS with two underlying assets, we need to perform additional Monte Carlo simulation to calculate the solution either PDE methods or Monte Carlo method. The payoff structure of hybrid DLS consist with a standard 2-Star step-down type ELS and the range accrual product which depends on the number of days in the coupon period that the index stay within the pre-determined range. We assume that the 2-Dimensional GBM (Geometric Brownian Motion) as the model of two equities and a no-arbitrage interest model (One-Factor Hull and White interest rate model) as a model for the interest rate. In this study, we employ the Monte Carlo simulation method with CUDA (Compute Unified Device Architecture) parallel computing as the GPGPU (General Purpose computing on Graphic Processing Unit) technology for fast and efficient numerical valuation of DLS. Comparing the Monte Carlo method with single CPU computation or MPI implementation, the result of Monte Carlo simulation with CUDA parallel computing produces higher performance.

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목차

Abstract i
Contents iii
1. Introduction
2. Hybrid Derivative Linked Securities
2.1 Explanation of Hybrid DLS
2.2 Mathematical Models
2.2.1 The 2-Dimensional Geometric Brownian Motion
2.2.2 The One-factor Hull and White Interest-rate Model
3. GPGPU Computing with CUDA
3.1 Basic CUDA
3.2 Random Number Generation Using cuRAND Library
4. Numerical Results
4.1 Two-in-One (2in1) ELS
4.2 CD-Equity Hybrid DLS
5. Conclusion
Reference

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