• Journal of Service Research and Studies
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• v.8 no.1
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• pp.103-122
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• 2018

The purpose of this study is to present the direction of ELS investment by analyzing the actual investment return of the ELS commodities and analyzing the investment effect of ELS that investors have felt unsatisfactory at financial marketing service. The research method is based on the step-down type ELS. We calculated the probability of achieving early redemption condition and maturity repayment condition, early redemption estimated yield, and maturity repayment estimated yield. As the study result, the probability of achieving 100% of the early redemption condition was 74.5%, and the probability of the early redemption condition 95% was 83.0%, 90% was 89.5%, 85% was 92.5%, and 80% was 96.5% respectively. In the case of the lowest 75%, the probability of holding to maturity is analyzed to be 2.5%, and the probability of early redemption is high. The probability of the stock price growth within 65% of the maturity repayment condition was 98.5% and the probability of the stock price growth within 60%~45% of the maturity repayment condition was 100%. 65% of maturity repayment condition was analyzed as 1.5% risk of principal loss, and the probability of achieving the committed yield of maturity was high. As a key measure of ELS investment, it is advantageous to select a commodity with a low rate of maturity repayment and a high rate of early redemption.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.20 no.4
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• pp.277-293
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• 2016

We develop an efficient numerical method for pricing the Derivative Linked Securities (DLS). The payoff structure of the hybrid DLS consists 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 Geometric Brownian Motion (GBM) 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 the Compute Unified Device Architecture (CUDA) parallel computing as the General Purpose computing on Graphic Processing Unit (GPGPU) 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.