This paper provides a methodology for fast and accurate pricing of the long-dated contracts that arise as the building blocks of insurance and pension fund agreements. It applies the recursive marginal quantization (RMQ) and joint recursive marginal quantization (JRMQ) algorithms outside the framework of traditional risk-neutral methods by pricing options under the real-world probability measure, using the benchmark approach. The benchmark approach is reviewed, and the real-world pricing theorem is presented and applied to various long-dated claims to obtain less expensive prices than suggested by traditional risk-neutral valuation. The growth-optimal portfolio (GOP), the central object of the benchmark approach, is modelled using the time-dependent constant elasticity of variance model (TCEV). Analytic European option prices are derived and the RMQ algorithm is used to efficiently and accurately price Bermudan options on the GOP. The TCEV model is then combined with a $3/2$ stochastic short-rate model and RMQ is used to price zero-coupon bonds and zero-coupon bond options, highlighting the departure from risk-neutral pricing.
Deep Least Squares Monte Carlo methods for the valuation of variable annuities with guarantees
Guangdong Provincial/Zhuhai Key Laboratory of Interdisciplinary Research and Application for Data Science, Beijing Normal-Hong Kong Baptist University(北京师范大学-香港浸会大学联合国际学院数据科学交叉研究与应用广东省/珠海重点实验室);Actuarial Studies and Business Analytics, Macquarie University(麦考瑞大学精算研究与商业分析系);Department of Mathematics, Hong Kong University of Science and Technology(香港科技大学数学系)
A deep learning approach for pricing convertible bonds with path-dependent reset and call provisions
Shanghai Lixin University of Accounting and Finance(上海立信会计金融大学);Shanghai Science and Technology Industry Research Center(上海市科技产业研究中心);Beijing Normal-Hong Kong Baptist University(北京师范大学-香港浸会大学联合国际学院)
Dipartimento di Scienze Economiche e Statistiche, Università degli Studi di Udine(乌迪内大学经济与统计科学系);Faculty of Economics and Business, University of Amsterdam(阿姆斯特丹大学经济商学院)