Monte Carlo Simulation Forecasting the Prices of Selected Stocks in the Automotive Sector
Abstract
Investors are exposed to risk and uncertainty because of changes in financial markets’ prices. Investors perceive the risks associated with changes in the market prices as higher due to inaccuracy in predicting future returns because of fluctuations in prices. For this reason, they adopt different risk management methods that reduce or eliminate these risks. This research relies on Monte Carlo Simulation technique in predicting forthcoming yield rates from three companies operating under Turkish automotive segment namely, Dogus Automotive (DOAS), Tofas (TOASO) and Ford Otosan (FROTO). The simulation, which runs from January 1, 2023, to December 31, 2023, gives investors research-based insights that help them make strategic investment choices in times of high volatility in the market. According to the results, by modeling prospective future scenarios, MCS can be employed as a viable means of predicting stock prices in financial markets which subsequently helps people make rational investments thereby securing profitable ventures. Furthermore, this study offers practical suggestions in the form of MCS-generated volatility ranges. Investors can determine when it is advisable to buy or sell stocks in order to reduce potential losses and increase profits by setting realistic price objectives and allocating the portfolio differently in accordance with these calls.
Keywords
Risk Management, Financial Markets, Automotive Industry, Stock Forecasting, Monte Carlo Simulation
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