Stock Price Prediction of the Largest Automotive Competitors Based on the Monte Carlo Method

Čečević Bojana Novićević (), Antić Ljilja () and Jevtić Adrijana ()
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Čečević Bojana Novićević: University of Niš, Faculty of Economics, Republic of Serbia
Antić Ljilja: University of Niš, Faculty of Economics, Republic of Serbia
Jevtić Adrijana: University of Belgrade, Technical faculty in Bor, Republic of Serbia, Department for Engineering Management

Economic Themes, 2023, vol. 61, issue 3, 419-441

Abstract: The transition to electric vehicles would be a great improvement for the population. On the other hand, this transition will make a great pressure for companies in the automotive industry, since they would have to develop such vehicles and make them better than traditional ones. Moreover, the transition period can last a long time. In the meantime, fossil fuel car sale rates are still dominant in the world. In this paper, the stock price prediction is made for two of the world’s largest competitors in automotive industry - Toyota and General Motors. The prediction covers one year, based on historical data of stock price trends using Monte Carlo simulation in two possible cases: the first, with 1,000 outcomes, and the second, with 10,000 outcomes. After price simulation, a comparative analysis of the results obtained for these two companies follows. The results show that the greater the number of outcomes specified in the prediction, the greater the variability of the results compared to the variability of historical data. In other words, the transition of General Motors to the leading position is not impossible.

Keywords: stock prices; Monte Carlo method; automotive industry (search for similar items in EconPapers)
JEL-codes: C15 G14 G17 G18 (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:vrs:ecothe:v:61:y:2023:i:3:p:419-441:n:1

DOI: 10.2478/ethemes-2023-0022

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