Web aplikacija za procjenu rizičnosti ulaganja u kriptovalute u stvarnom vremenu

master's thesis

• Title (english): Web Application for Real-Time Cryptocurrency Investment Risk Assessment
• Author: Petar Mioč
• Mentor: Zvonko Kostanjčar (mentor)
• Committee member: Zvonko Kostanjčar (predsjednik povjerenstva)
• Committee member: Tomislav Petković (član povjerenstva)
• Committee member: Stjepan Begušić (član povjerenstva)
• Granter: University of Zagreb; Faculty of Electrical Engineering and Computing; Zagreb
• Defense date and country: 2025-02-27, Croatia

Abstract

Ovaj rad bavi se tehničkom analizom tržišta kriptovaluta i razvojem web aplikacije za procjenu
rizika ulaganja u stvarnom vremenu. Analizirani su ključni tehnički indikatori, uključujući RSI,
Stochastic Oscillator, Williams %R, MACD, Bitcoin indeks volatilnosti i Indeks straha i
pohlepe, koji omogućuju investitorima objektivnu procjenu tržišnih trendova.
Razvijena web aplikacija koristi React.js za frontend i Node.js za backend, omogućujući
korisnicima jednostavan pristup tržišnim podacima. Fokus istraživanja bio je na Bitcoinu zbog
njegove stabilnosti i dostupnosti pouzdanih API-ja, dok su druge kriptovalute ocijenjene kao
manje pouzdane za analizu.
Rezultati rada potvrđuju važnost tehničkih indikatora u donošenju informiranih investicijskih
odluka te predlažu daljnja poboljšanja aplikacije, uključujući integraciju dodatnih izvora
podataka, personalizaciju korisničkog iskustva i implementaciju strojnog učenja.

Abstract (english)

This thesis explores the role of technical analysis in cryptocurrency market investment
decisions and presents the development of a real-time risk assessment web application. Key
technical indicators such as RSI, Stochastic Oscillator, Williams %R, MACD, Bitcoin
Volatility Index, and the Fear & Greed Index were analyzed to provide investors with an
objective assessment of market trends.
The developed web application, built using React.js for the frontend and Node.js for the
backend, allows users to easily access market data. The research primarily focused on Bitcoin
due to its stability and reliable API support, while other cryptocurrencies were deemed less
suitable for analysis.
Findings confirm the significance of technical indicators in investment decision-making and
propose further improvements to the application, including the integration of multiple data
sources, user customization options, and the implementation of machine learning models for
trend prediction.

• Keywords: Tehnički indikatori; Analiza rizika; kriptovalute
• Keywords (english): Tehnical indicators; Risk Analysis; crypto-currency
• Language: croatian
• URN:NBN: urn:nbn:hr:168:170976
• Study programme: Title: Computing; Study programme type: university; Study level: graduate; Academic / professional title: magistar/magistra inženjer/inženjerka računarstva (magistar/magistra inženjer/inženjerka računarstva)
• Type of resource: Text
• File origin: Born digital
• Access conditions: Open access
• Created on: 2025-03-12 11:14:08