Fast Monte Carlo Simulation for Pricing Equity-Linked Securities

Hanbyeol Jang, Sangkwon Kim, Junhee Han, Seongjin Lee, Jungyup Ban, Hyunsoo Han, Chaeyoung Lee, Darae Jeong, Junseok Kim

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)


In this paper, we present a fast Monte Carlo simulation (MCS) algorithm for pricing equity-linked securities (ELS). The ELS is one of the most popular and complex financial derivatives in South Korea. We consider a step-down ELS with a knock-in barrier. This derivative has several intermediate and final automatic redemptions when the underlying asset satisfies certain conditions. If these conditions are not satisfied until the expiry date, then it will be checked whether the stock path hits the knock-in barrier. The payoff is given depending on whether the path hits the knock-in barrier. In the proposed algorithm, we first generate a stock path for redemption dates only. If the generated stock path does not satisfy the early redemption conditions and is not below the knock-in barrier at the redemption dates, then we regenerate a daily path using Brownian bridge. We present numerical algorithms for one-, two-, and three-asset step-down ELS. The computational results demonstrate the efficiency and accuracy of the proposed fast MCS algorithm. The proposed fast MCS approach is more than 20 times faster than the conventional standard MCS.

Original languageEnglish
Pages (from-to)865-882
Number of pages18
JournalComputational Economics
Issue number4
Publication statusPublished - 2020 Dec


  • Brownian bridge
  • Equity-linked securities
  • Monte Carlo simulation
  • Option pricing

ASJC Scopus subject areas

  • Economics, Econometrics and Finance (miscellaneous)
  • Computer Science Applications


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