Abstract
In the modern financial market, investors have to make quick and efficient investment decisions. The problem arises when the investor does not know the right tools to use in investment decision making. Different tools can be implemented in trading strategies to predict future stock prices. Therefore, the primary objective of this paper is to analyse the performance of the Geometric Brownian Motion (GBM) model in forecasting Nestle stock price by assessing the performance evaluation indicators. To analyse the stocks, two software were used, namely Microsoft Excel and Python. The model is trained for 16 weeks (4 months) of data from May to August 2019 and 2020. The simulated sample is for four weeks (1 month) which is for September 2019 and 2020. The findings show that during the Pandemic Covid-19, short-term prediction using GBM is more efficient than long-term prediction as the lowest Mean Square Error (MSE) value is at one week period. In addition, the Mean Absolute Percentage Error (MAPE) for all GBM simulations is highly accurate as it shows that MAPE values are less than 10%, indicating that the GBM method can be used to predict Nestle stock price during an economic downturn.
Highlights
The year 2020 was the year that most, if not all, will remember throughout their lifetime
For the Geometric Brownian Motion model, the stock return is calculated, drift value and volatility value are generated, and the forecasted stock price is computed as the output for the model
The main objective of this paper is to analyse the efficiency of the geometric Brownian Motion (GBM) model in predicting the stock price of Nestle before and during Pandemic Covid 19
Summary
The year 2020 was the year that most, if not all, will remember throughout their lifetime. That was the year starting from March, where the Covid-19 pandemic spread like wildfire. The earth stood still when the governments around the world imposed lockdowns to limit movements to contain the spread of the virus. The stock market crashed as a result of panic selling among retail investors. As sectors such as tourism and services are halted, employers in these sectors needed to take drastic measures such as cutting wages and imposing furlough on their employees. Given that most of the stocks have had their price drop significantly during the initial few weeks of the lockdown due to uncertainties, retail investors sees this as an opportunity to make investments, albeit short term or long term ones
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