Abstract

With the development of financial analysis techniques, computer technology, and artificial intelligence, the valuation methods for convertible bonds in the financial markets are constantly evolving and developing. This article discusses various approaches to valuing convertible bonds, including the Black-Scholes model, the Binomial model, the Monte Carlo model, and artificial intelligence techniques like machine learning. The article provides a detailed overview of each valuation method and analyzes the strengths and weaknesses of each approach.

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