Research on Pricing Factors of Structured Financial Products: Taking USD 100% Capped ProNote with Participation as an Example
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Research on Pricing Factors of Structured Financial Products: Taking USD 100% Capped ProNote with Participation as an Example

Yanxin Tang 1*
1 City University of Hong Kong
*Corresponding author: yanxitang2-c@my.cityu.edu.hk
Published on 28 October 2025
Journal Cover
AEMPS Vol.233
ISSN (Print): 2754-1177
ISSN (Online): 2754-1169
ISBN (Print): 978-1-80590-485-4
ISBN (Online): 978-1-80590-486-1
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Abstract

This article aims to address the issues of the guaranteed return realization path, derivative income quantification, and comprehensive risk assessment for the 100% guaranteed return structured notes in US dollars, as well as to fill the current research gap in the academic field regarding the pricing logic and risk-return characteristics of this specific type of product, and to improve the pricing theory system for structured products. The study uses the discounted cash flow (DCF) model to calculate the value of the fixed income hedging layer. It quantifies the return elasticity of the S&P 500-linked options through Monte Carlo simulation and completes the pricing calibration by combining sensitivity tests and comparisons with similar products in the market. The data used are the actual values of the three-year US Treasury bond yield in July 2025 at 3.824%, the annualized volatility of the S&P 500 over the past three years at 15.91%, and the dividend rate at 1.23%. The results show that for a principal of $1 million, $874,200 of low-risk assets are required to ensure the principal is protected. The value of the derivative layer options is $118,600. After deducting a 1% cost, the annualized expected return is 7.81% (in the best scenario, 23.86%), which is in line with the similar products of DBS Bank during the same period, thus verifying the fairness. This research can provide support for the decision-making of cross-border investors, the optimization of issuers' products, and the improvement of the market pricing system.

Keywords:

Structured notes, Structural product pricing, Monte Carlo simulation.

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Tang,Y. (2025). Research on Pricing Factors of Structured Financial Products: Taking USD 100% Capped ProNote with Participation as an Example. Advances in Economics, Management and Political Sciences,233,9-17.

References

[1]. Lee, T. S. and Lin, H.Y. (2009). The pricing of structured notes with credit risk. Investment Management and Financial Innovations, 6 (4), 221-232

[2]. Mccrickerd, R. and Pakkanen, M. S. (2018). Turbocharging Monte Carlo pricing for the rough Bergomi model. Quantitative Finance, 18(11), 1877-1886

[3]. Droms, W. G. and Strauss, S. N. (2012). Structured Notes in a Balanced Portfolio: Enhancing Returns with Tail Risk Protection. Journal of Financial Planning, 25 (11), 68-75

[4]. Sabrina, T. W. (2024). Structured Notes: A nontraditional, customizable tool that’s useful for retiring clients. Source Media dba Arizent.

[5]. Sharma, A., Chen, F., Noh, J., Dejesus, J. and Schlener, M. (2024). Hedging and Pricing Structured Products Featuring Multiple Underlying Assets. Conference acronym’ICAIF, 14 (17), 1-7.

[6]. Li, H. (2023). Case Analysis of HSBC's "Profit to Flexibility" Structured Deposit Product. Journal of Financial Research, 5 (518), 187-202.

[7]. Kim, C. and Jeong, Y. (2023). A Practical Monte Carlo Method for Pricing Equity-Linked Securities with Time-Dependent Volatility and Interest Rate. Journal of Computational Finance.10.1007/s10614-023-10394-3.

[8]. Fang, Y., Zhang, Y. X., Liu, J. Z. and Zhang J. (2018). A study of Pricing for Structured Financial Products Linked with Multi-Asset. Journal of Fudan University (Natural Science), 57(5): 554-564, 579.

[9]. Gao, Y., Wang, J. H. and Yang, A. J. (2011). Estimation on Portfolio Risk via Time-varying T-copula and Monte-carlo Method. Chinese Journal of Management Science, 19(2): 10-15.

[10]. Smith, J. and Johnson, M. (2023). Structured Products in Retirement Portfolios: A Mean- Variance Analysis. Journal of Retirement Planning, 10 (2), 45-68.

[11]. John, C. H. (2023). Options, Futures, and Other Derivatives. Pearson Education, 108-112.

References

[1]. Lee, T. S. and Lin, H.Y. (2009). The pricing of structured notes with credit risk. Investment Management and Financial Innovations, 6 (4), 221-232

[2]. Mccrickerd, R. and Pakkanen, M. S. (2018). Turbocharging Monte Carlo pricing for the rough Bergomi model. Quantitative Finance, 18(11), 1877-1886

[3]. Droms, W. G. and Strauss, S. N. (2012). Structured Notes in a Balanced Portfolio: Enhancing Returns with Tail Risk Protection. Journal of Financial Planning, 25 (11), 68-75

[4]. Sabrina, T. W. (2024). Structured Notes: A nontraditional, customizable tool that’s useful for retiring clients. Source Media dba Arizent.

[5]. Sharma, A., Chen, F., Noh, J., Dejesus, J. and Schlener, M. (2024). Hedging and Pricing Structured Products Featuring Multiple Underlying Assets. Conference acronym’ICAIF, 14 (17), 1-7.

[6]. Li, H. (2023). Case Analysis of HSBC's "Profit to Flexibility" Structured Deposit Product. Journal of Financial Research, 5 (518), 187-202.

[7]. Kim, C. and Jeong, Y. (2023). A Practical Monte Carlo Method for Pricing Equity-Linked Securities with Time-Dependent Volatility and Interest Rate. Journal of Computational Finance.10.1007/s10614-023-10394-3.

[8]. Fang, Y., Zhang, Y. X., Liu, J. Z. and Zhang J. (2018). A study of Pricing for Structured Financial Products Linked with Multi-Asset. Journal of Fudan University (Natural Science), 57(5): 554-564, 579.

[9]. Gao, Y., Wang, J. H. and Yang, A. J. (2011). Estimation on Portfolio Risk via Time-varying T-copula and Monte-carlo Method. Chinese Journal of Management Science, 19(2): 10-15.

[10]. Smith, J. and Johnson, M. (2023). Structured Products in Retirement Portfolios: A Mean- Variance Analysis. Journal of Retirement Planning, 10 (2), 45-68.

[11]. John, C. H. (2023). Options, Futures, and Other Derivatives. Pearson Education, 108-112.

Cite this article

Tang,Y. (2025). Research on Pricing Factors of Structured Financial Products: Taking USD 100% Capped ProNote with Participation as an Example. Advances in Economics, Management and Political Sciences,233,9-17.

Data availability

The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

About volume

Volume title: Proceedings of ICFTBA 2025 Symposium: Data-Driven Decision Making in Business and Economics

ISBN: 978-1-80590-485-4(Print) / 978-1-80590-486-1(Online)
Editor: Lukášak Varti
Conference website: https://2025.icftba.org/Bratislava.html
Conference date: 12 December 2025
Series: Advances in Economics, Management and Political Sciences
Volume number: Vol.233
ISSN: 2754-1169(Print) / 2754-1177(Online)

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