The establishment of option prices is one of the crucial aspects in derivative trade. Black-Scholes model (BSM) is one of the most popular models of option price establishment. The option exchanges such as CBOE, HKEX, and NSE use this model to determine the price options. Black-Scholes Model is modelled with stock price movement as a stochastic process. Another popular model is binomial model (BSM), originated from stock exchange movement model which divides interval time [0, T] into n equal length step. It holds several models to determine the value of up-move, down-move, and probability. Binomial model is categorised as Cox-Ross-Rubinstein, Jarrow-Rudd, and Leisen-Reimer. There are numerous literatures which discuss the relation between BM and BSM, including the convergence of binomial model and BSM. The former’s model which is often put side-by-side with BSM is Cox-Ross-Rubinstein. Even though this model is quite simple, it requires a lot, even thousands of steps to render Cox-Ross-Rubinstein to converge with BSM. It certainly takes a lot of time to calculate. Therefore, in this study, with limited steps, Jarrow-Rudd and Leisen-Reimer models are compared to BSM with the Cox-Ross-Rubinstein model. It aims to check on which binomial model is more convergent to BSM with limited steps in the same period. The data collected were secondary data from finance.yahoo.com. Judgemental sampling was used for technique sampling and several shares, with large market capitalization in Hongkong, India, and Indonesia are chosen. By calculating the MAFE error value from option price of BSM and BM, it is discovered that Leisen-Reimer with 101 steps is more convergent to BSM.
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