Journal of Korea Society of Industrial Information Systems (한국산업정보학회논문지)

Korea Society of Industrial Information Systems (한국산업정보학회)
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An exercise algorithm for mezzanine products using artificial neural networks

인공신경망을 이용한 메자닌 상품의 행사 알고리즘

  • 유재필 (상명대학교 경영공학과)
  • Received : 2023.01.13
  • Accepted : 2023.02.25
  • Published : 2023.02.28
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Abstract

Mezzanine products are financial investment products with both bond and stock characteristics, which are mainly issued by low-grade companies in the financial market to secure liquidity. Therefore, bondholders investing in mezzanine products must make decisions about when they want to convert to stocks, along with whether they invest in mezzanine products issued by the company. Therefore, in this paper, a total of 2,000 learning data and 200 predictive experimental data with stock conversion events completed by major industries are divided, and mezzanine event algorithms are designed and performance analyzed through artificial neural network models. This topic is meaningful in that it proposed a methodology to scientifically solve the difficulties of exercising mezzanine products, which are of high interest in the financial field, by applying artificial neural network technology.

메자닌 상품은 채권과 주식의 성격을 모두 가진 금융 투자 상품인데 주로 등급이 낮은 회사가 유동성을 확보하기 위해 금융시장에서 발행한다. 따라서 메자닌 상품에 투자하는 사채권자들은 해당 회사가 발행하는 메자닌 상품에 투자하면 주식으로 전환하는 여부와 함께 주식으로 전환하고자 하는 시점에 대해서 의사결정을 해야 한다. 예컨대 메자닌 상품의 투자자와 발행회사는 투자자의 전환권 행사 여부와 시점에 대한 의사결정 문제가 가장 중요한데 이를 위한 투자 판단 지표가 매우 부족하므로 직관적이거나 정성적인 판단에 의존할 수밖에 없다. 따라서 본 논문에서는 주요 업종별 주식 전환 행사가 완료된 총 2,000개의 학습 데이터와 200개의 예측 실험 데이터로 구분하고 인공신경망 모델을 통해서 메자닌 행사 알고리즘을 설계하고 성능을 분석한다. 본 주제는 금융 분야에서 관심이 높은 메자닌 상품 행사의 난제를 인공신경망 기술을 적용하여 과학적으로 해결하는 방법론을 제안했다는 점에서 그 의의를 갖는다.

Keywords

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