20.500.12556/RUL-174951 Application of Machine Learning to Fundamental Analysis of Securities Uporaba strojnega učenja pri analizi vrednostnih papirjev This inquiry tests whether a classic, fundamentals-based valuation philosophy can be systematically validated in today's data-rich environment. My approach centers on estimating a security's intrinsic worth using linear and non-liner models and maintaining a buffer for error, a contrast to methods that prioritize price momentum. I constructed and historically simulated statistical models on two decades of corporate data from 2003 to 2023 to derive these rational value estimates. The process incorporated a novel signal processing technique and was rigorously designed to avoid the analytical illusion of survivorship bias. The findings from the simulation were unambiguous: portfolios of the most favorably priced assets consistently generated returns superior to a broad market proxy. Crucially, simpler, interpretable models performed on par with their complex counterparts. The work thus validates these enduring principles for a modern context, while noting the growing challenge of finding a unique edge in automated markets. V tej raziskavi s pomočjo sodobnih tehnik strojnega učenja preverjam, ali je mogoče načela vrednostnega investiranja Benjamina Grahama uspešno uporabiti na današnjih trgih. V nasprotju s pogostimi pristopi, ki se osredotočajo na cenovne trende, sem razvil regresijske modele za izračun ocenjene poštene vrednosti (OPV) delnic. Modeli temeljijo na Grahamovih načelih, kot sta notranja vrednost in marža varnosti. Modele sem testiral na podatkih ameriških delnic med letoma 2003 in 2023, pri čemer sem uporabil inovativno tehniko glajenja fundamentalnih podatkov in dosledno upošteval pristranskost preživelih. Benjamin Graham value investing machine learning fundamental analysis fair value survivorship bias financial accounting time series smoothing Benjamin Graham vrednostno investiranje strojno učenje fundamentalna analiza poštena vrednost pristranskost preživelih finančno računovodstvo glajenje časovnih vrst true false false Angleški jezik Slovenski jezik Magistrsko delo/naloga 2025-10-10 12:55:00 2025-10-10 12:55:07 2025-12-02 04:06:23 0000-00-00 00:00:00 2025 0 0 0000-00-00 NiDoloceno NiDoloceno NiDoloceno 0000-00-00 0000-00-00 0000-00-00 62686 253453315 Panteleev_Aleksandr_-_Uporaba_strojnega_ucenja_pri_analizi_vrednostnih_papirjev.pdf Panteleev_Aleksandr_-_Uporaba_strojnega_ucenja_pri_analizi_vrednostnih_papirjev.pdf 1 79C4A8A1D8FDA84FF75EFF3382267806 16d827763ab8837b648b2a6037314741b034cdc8e56bd79f81945c02fd6a7ab6 59c783b1-a5c7-11f0-9328-0050569b8976 https://repozitorij.uni-lj.si/Dokument.php?lang=slv&id=219860 Fakulteta za elektrotehniko 0 0 0