Stock price prediction based on the Monte Carlo method

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dc.citation.epage368
dc.citation.issue1
dc.citation.rankM33
dc.citation.spage358
dc.citation.volumeXIX
dc.contributor.authorJevtić, Adrijana
dc.contributor.authorRiznić, Dejan
dc.contributor.authorTomić, Miša
dc.contributor.authorTomić, Nevena
dc.date.accessioned2023-12-26T08:49:38Z
dc.date.available2023-12-26T08:49:38Z
dc.date.issued2023
dc.description.abstractThe automotive industry market has always been very specific. Today, this market is even more demanding, because the principle of the products offered there is changing fundamentally. The electric cars that are on the market today are still in the early stages, but they have great potential. In this paper, a prediction was made on the stock prices of Tesla, Inc., one of the pioneers in the industry of electric cars. The forecast of stock prices of this company was made for one year, i.e. for 252 trading days settled on the Monte Carlo method. MATLAB software was used for the forecast based on three years of historical data on stock prices. The results of the simulation performed show that the longer the forecast period, the greater the deviations from the historical data. From the predicted values, it can be concluded that the stock price volatility varies greatly in the case of 10,000 possible outcomes and for different prediction periods. In addition to the extreme values of the predicted stock price for the observed period, the most frequently predicted stock price value is close to the average historical price.
dc.identifier.isbn978-86-6305-136-2
dc.identifier.issn2620-0597
dc.identifier.urihttps://mksm.tfbor.bg.ac.rs/downloads/2023/IMCSM_2023_Book_of_proceedings_Issue_1.pdf
dc.identifier.urihttps://repozitorijum.tfbor.bg.ac.rs/handle/123456789/2474
dc.language.isoen
dc.publisherUniversity of Belgrade, Technical Faculty in Bor
dc.rights.licenseCC-BY-NC-ND
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.sourceIMCSM23 proceedings - XIX International May Conference on Strategic Management, May 25, 2023, Bor, 2023, 358-368
dc.subjectAutomotive industry
dc.subjectStock price movement
dc.subjectMonte Carlo method
dc.subjectPrice prediction
dc.subjectMATLAB
dc.subjectTesla Inc.
dc.titleStock price prediction based on the Monte Carlo method
dc.typeconferenceObject
dc.type.versionpublishedVersion

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