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master's thesis
Predviđanje volatilnosti pomoću neuronskih mreža
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2018. urn:nbn:hr:168:137633
Vinković, Damjan
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

Cite this document

Vinković, D. (2018). Predviđanje volatilnosti pomoću neuronskih mreža (Master's thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:137633

Vinković, Damjan. "Predviđanje volatilnosti pomoću neuronskih mreža." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2018. https://urn.nsk.hr/urn:nbn:hr:168:137633

Vinković, Damjan. "Predviđanje volatilnosti pomoću neuronskih mreža." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2018. https://urn.nsk.hr/urn:nbn:hr:168:137633

Vinković, D. (2018). 'Predviđanje volatilnosti pomoću neuronskih mreža', Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 11 July 2024, https://urn.nsk.hr/urn:nbn:hr:168:137633

Vinković D. Predviđanje volatilnosti pomoću neuronskih mreža [Master's thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2018 [cited 2024 July 11] Available at: https://urn.nsk.hr/urn:nbn:hr:168:137633

D. Vinković, "Predviđanje volatilnosti pomoću neuronskih mreža", Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2018. Available at: https://urn.nsk.hr/urn:nbn:hr:168:137633

Metadata
TitlePredviđanje volatilnosti pomoću neuronskih mreža
Title (english)Volatility Forecasting Using Neural Networks
AuthorDamjan Vinković
MentorZvonko Kostanjčar (mentor)
Committee memberZvonko Kostanjčar (predsjednik povjerenstva)
Committee memberTomislav Petković (član povjerenstva)
Committee memberMate Puljiz (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2018-07-13, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
Istraživači već godinama ulažu velike napore kako bi iskoristili stalna poboljšanja u tehnologiji da optimiziraju načine donošenja odluka pri obradi velikih količina podataka pomoću kojih bi predvidjeli aspekte financijskih tržišta i povećali povrate. Neuronske Mreže omogućavaju fleksibilan način u istraživanju dinamika na ekonomskim i financijskim tržištima. Glavni problem s kojim se istraživači susreću pri korištenju takvih naprednijih modela je manjak fundamentalnog ekonomskog znanja pri biranju ulaza u model. Ovaj rad predstavlja novi model ulančanih neuronskih mreža kako bi se predvidjela volatilnost S\&P 500 indeksa. Specifičnost je korištenje fundamentalno objašnjenih vremenskih serija kao ulaza u model, te valuacija predikcije volatilnosti s obzirom na referentne GARCH i VIX pokazatelje.
Abstract (english)
For many years researchers have made extensive efforts to take advantage of technological advances to optimize the decision making process by evaluating extensive amounts of information in order to forecast aspects of financial markets hoping to increase investment return. Artificial Neural Network (ANN) provides a flexible way of examining the dynamics of various economic and financial problems. The main issue researches had when building advanced models is a lack of fundamental economical knowledge when choosing model inputs. This paper proposes a new model of arrayed Neural Networks in order to predict the S\&P 500 Index volatility by using fundamentally explained time series as inputs and then test the prediction against GARCH and VIX serving as benchmarks.
Keywords
Keywords (english)
Languageenglish
URN:NBNurn:nbn:hr:168:137633
Study programmeTitle: Information and Communication Technology
Study programme type: university
Study level: graduate
Academic / professional title: magistar/magistra inženjer/inženjerka informacijske i komunikacijske tehnologije (magistar/magistra inženjer/inženjerka informacijske i komunikacijske tehnologije)
Type of resourceText
File originBorn digital
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Created on2019-03-19 13:45:30