Understanding How Dividends Affect Option Prices

In this paper, we propose a pricing model for stock option valuation. The model is derived from the classical Black-Scholes option pricing equation via the application of the constant elasticity of variance (CEV) model with dividend yield. This modifies the Black- Scholes equation by incorporating a non-constant volatility power function of the underlying stock price, and a dividend yield parameter

A Note on Black-Scholes Pricing Model for Theoretical Values of Stock Options

In this paper, we consider some conditions that transform the classical Black-Scholes Model for stock options valuation from its partial differential equation (PDE) form to an equivalent ordinary differential equation (ODE) form. In addition, we propose a relatively new semi-analytical method for the solution of the transformed Black-Scholes model. The obtained solutions via this method can be used to find the theoretical values of the stock options in relation to their fair prices. In considering the reliability and efficiency of the models, we test some cases and the results are in good agreement with the exact solution

The Modified Black-Scholes Model via Constant Elasticity of Variance for Stock Options Valuation

In this paper, the classical Black-Scholes option pricing model is visited. We present a modified version of the Black-Scholes model via the application of the constant elasticity of variance model (CEVM); in this case, the volatility of the stock price is shown to be a non-constant function unlike the assumption of the classical Black-Scholes model

An empirical assessment of symmetric and asymmetric jump-diffusion models for the Nigerian stock market indices

We examine empirically, the suitability of three stock price models viz: geometric Brownian motion, symmetric and asymmetric jump-diffusion models, on the empirical log-returns of the Nigerian All-Share Index. 5334 daily observed data from January 2, 1998, to February 21, 2020, were utilized. Using a non-parametric jump-test method, our results show that jumps are present in the empirical log-returns of the stock market price. The results obtained for the optimal parameters in the models indicate high jump intensity, more upward jumps, and a positively skewed jump process. However, the parameters in the asymmetric jump-diffusion model were found to be more sensitive to the varied threshold of jumps in the log-returns than the symmetric jump-diffusion model. The suitability analysis results show that the symmetric jump-diffusion model fits the market indices better. Therefore, it can be used for future predictions of the market price