dc.contributor.author | Dzikevičius, Audrius | |
dc.contributor.author | Šaranda, Svetlana | |
dc.date.accessioned | 2023-09-18T16:48:50Z | |
dc.date.available | 2023-09-18T16:48:50Z | |
dc.date.issued | 2016 | |
dc.identifier.issn | 2029-7491 | |
dc.identifier.other | (BIS)VGT02-000033172 | |
dc.identifier.uri | https://etalpykla.vilniustech.lt/handle/123456789/117163 | |
dc.description.abstract | Technical and fundamental analyses are widely used to forecast stock prices due to lack of knowledge of other modern models and methods such as Residual Income Model, ANN-APGARCH, Support Vector Machine, Probabilistic Neural Network and Genetic Fuzzy Systems. Although stock price forecast models integrating both technical and fundamental analyses are currently used widely, their integration is not justified comprehensively enough. This paper discusses theoretical one-factor and multi-factor stock price forecast models already applied by investors at a global level and determines possibility to create and apply practically a stock price forecast model which integrates fundamental and technical analysis with the reference to the Lithuanian stock market. The research is aimed to determine the relationship between stock prices of the 14 Lithuanian companies listed in the Main List by the Nasdaq OMX Baltic and various fundamental variables. Based on correlation and regression analysis results and application of c-Squared Test, ANOVA method, a general stock price forecast model is generated. This paper discusses practical implications how the developed model can be used to forecast stock prices by individual investors and suggests additional check measures. | eng |
dc.format | PDF | |
dc.format.extent | p. 292-307 | |
dc.format.medium | tekstas / txt | |
dc.language.iso | eng | |
dc.relation.isreferencedby | Academic Search Complete | |
dc.relation.isreferencedby | C.E.E.O.L | |
dc.relation.isreferencedby | Index Copernicus | |
dc.relation.isreferencedby | DOAJ | |
dc.source.uri | https://doi.org/10.3846/bme.2016.337 | |
dc.subject | VE05 - Socioekonominių sistemų universalaus tvarumo tyrimai / Universal sustainability research | |
dc.title | Formation of an integrated stock price forecast model in Lithuania | |
dc.type | Straipsnis kitoje DB / Article in other DB | |
dcterms.references | 49 | |
dc.type.pubtype | S3 - Straipsnis kitoje DB / Article in other DB | |
dc.contributor.institution | Vilniaus Gedimino technikos universitetas | |
dc.contributor.faculty | Verslo vadybos fakultetas / Faculty of Business Management | |
dc.subject.researchfield | S 004 - Ekonomika / Economics | |
dc.subject.ltspecializations | L103 - Įtrauki ir kūrybinga visuomenė / Inclusive and creative society | |
dc.subject.en | Stock price | |
dc.subject.en | Forecast | |
dc.subject.en | Correlation analysis | |
dc.subject.en | Regression analysis | |
dc.subject.en | Fundamental analysis | |
dc.subject.en | Technical analysis | |
dc.subject.en | Model | |
dc.subject.en | Investment | |
dcterms.sourcetitle | Business, management and education = Verslas, vadyba ir studijos | |
dc.description.issue | Nr. 2 | |
dc.description.volume | T. 14 | |
dc.publisher.name | Technika | |
dc.publisher.city | Vilnius | |
dc.identifier.doi | 10.3846/bme.2016.337 | |
dc.identifier.elaba | 20220020 | |