The Covid-19 pandemic, an epidemic since early 2020, has had a significant impact on global financial problems, including in Indonesia. It has brought about in increasingly erratic stock price movements. In general terms, stock prices have some features that describe price movements. Some of these features include Jump and Leptokurtic. These features are obtained by modelling the stock price with the best model that can capture some features. This paper investigates the Merton Jump Diffusion (MJD) model and implemented stock prices in Indonesia to see if the model could capture some share price features during the Covid-19 pandemic. The Merton Jump Diffusion model is built based on the Black Scholes model by adding a Poisson Jump Process arrangement. There are additional parameters, namely jump intensity, mean, standard deviation, and the other two are the immediate expected return and instantaneous volatility. It is assumed that the MJD model is an exponential Levy model with a Brownian drift motion and Poisson Process arrangement to form the log-return of the MJD model. Based on the MJD log-return model's density function, the parameter values estimated by using the Maximum Likelihood Estimation algorithm and computed using MATLAB. The probability density moment of Merton Jump Diffusion is calculated to determine the skewness and kurtosis values and build a Leptokurtic plot based on the log-return value and the density of the MJD Model. The Indonesian share price being modelled is 10 Blue Chips shares during the Covid-19 pandemic period 23/12/2019 –23/12/2020. The empirical result shows that the selected Blue Chips Stocks in Indonesia exhibit several jumps, as evidenced by jump intensities' values. Log return density of MJD reveals the presence of leptokurtic feature as evidenced by excessive kurtosis values. It is found that the MJD model is suitable for modelling Indonesia's stock prices during the Covid-19 pandemic.

Keywords: Merton Jump Diffusion, Indonesia Stock Price, Jump, Leptokurtic, Maximum Likelihood Estimation