English Predvidjanje cene zlata uzimajuci u obzir broj zarazenih virusom Covid 19

  • Jovana Stokanovic Sevic Singidunum University
  • Ana Jovancai Stakic Singidunum University
Ključne reči: cena zlata, covid 19, model drvo odlucivanja, model linearne regresije, K-nearest neighbours model, Support vector machine model

Sažetak


Početak zdravstvene i ekonomske krize izazvane pojavom novog virusa Covid-19 pokazao nam je da je u percepciji investitora zlato i dalje visoko cenjeno kao čuvar vrednosti.
Ovaj rad ima za cilj da testira nekoliko modela i odabere najbolji za predviđanje cene zlata na svetskom tržištu za naredni dan, za pet i deset dana, uzimajući u obzir broj obolelih i umrlih od virusa Covid-19.
Verujemo da predviđanja sa parametrima Covid-19 daju tačnije rezultate od predviđanja koja kao informaciju uzimaju samo istorijske cene zlata.
Ova predviđanja mogu pomoći donosiocima odluka da li je, u kom trenutku i u kom iznosu, najbolje investirati u zlato i finansijske instrumente vezane za zlato, u odnosu na projektovanu cenu zlata iz modela.
U radu se testiraju modeli pod nazivom Decision tree, K-nearst neighbours, model linearne regresije i Support vector machine na osnovu informacija o cenama zlata i broju slučajeva i smrti od virusa Covid-19.
U radu će se videti da čak i modeli sa samo podacima o ceni zlata daju prilično pouzdana predviđanja, ali u ovakvim nestabilnim vremenima, modeli koji uzimaju u obzir faktor nestabilnosti daju tačnija predviđanja.
Istraživanje ima za cilj da odredi optimalnu količinu informacija na kojoj će modeli „naučiti“ da daju što tačniji mogući rezultat.
Obrada podataka i modeli ovog rada su urađeni u programskom jeziku Python.

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2022/10/21
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