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Uporaba spletnih virov pri napovedovanju nihanj na trgu digitalnih valut
MAJERČIČ, ROK (Author), Lavbič, Dejan (Mentor) More about this mentor... This link opens in a new window

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Abstract
Napovedovanje nihanja vrednosti klasičnih finančnih inštrumentov je znan in široko obravnavan problem. Raziskovalci so v preteklosti ta problem reševali s tehnično in temeljno analizo. Prva se pri napovedovanju opira na zgodovinske podatke o valuti oziroma delnici (tržna vrednost delnice oziroma valute ter obseg trgovanja), druga pa analizira zunanje informacije, ki lahko vplivajo na nihanje vrednosti delnice/valute (npr.: predstavitev novega izdelka v podjetju lahko zviša vrednost delnice tega podjetja, medtem ko nižja bonitetna ocena neke države lahko zmanjša vrednost njene valute). V tej magistrski nalogi se bomo osredotočili predvsem na slednjo – temeljno analizo. Uspešnost le-te pa bomo prikazali na dokaj novem, še ne povsem uveljavljenem trgu digitalnih valut. Glavna prednost, ki jo predstavlja trg digitalnih valut v primerjavi s klasičnimi finančnimi trgi, je predvsem njena P2P narava delovanja. To pomeni, da ima vsak uporabnik vpogled v celotni potek trgovanja (naročila, povpraševanja, ponudbe, transakcije). Poleg tega pa so javno dostopne tudi informacije o delovanju omrežja (porabljena računska moč, količina valute v obtoku, število rudarjev …). V prvem, uvodnem delu bo narejen pregled obstoječih metod za napovedovanje nihanja valut, ki jih bomo prevzeli predvsem s področja trgovanja vrednostnih papirjev. V tem delu bomo tudi okvirno predstavili naše izboljšave ter prednosti, ki jih nudi trg digitalnih valut. V nadaljevanju bo podrobno opisano delovanje trga digitalnih valut; opisan bo potek posamezne transakcije, kakšna je vloga rudarjev v omrežju Bitcoin, kako poteka verifikacija uporabnikov in transakcij ter tudi kako je mogoče trgovati z digitalnimi valutami. V naslednjem poglavju bo opisano uporabljeno razvojno okolje (zgradba aplikacije, uporabljena orodja ter knjižnice). V osrednjem delu bo predstavljen razvoj naše predlagane metode, s katero želimo napovedati nihanje valute Bitcoin. Ta del bo razdeljen na tri osrednje sklope: podatkovno rudarjenje, analiza zajetih podatkov ter izvedba simulacije. V prvem sklopu bodo opredeljeni spletni viri ter metode, s katerimi se bo izvajal zajem. V drugem sklopu bo izvedena analiza zajetih podatkov, iz katerih bodo izbrani tisti, ki bi lahko vplivali na vrednost valute. V zadnji fazi bodo izbrani podatki uporabljeni v simulaciji napovedovanja nihanja valute, kjer bomo uporabili dva pristopa, večkratno linearno regresijo ter umetno nevronsko mrežo.

Language:Slovenian
Keywords:tehnična analiza, temeljna analiza, digitalna valuta, Bitcoin, P2P, napovedovanje, podatkovno rudarjenje, strojno učenje
Work type:Master's thesis/paper (mb22)
Organization:FRI - Faculty of computer and information science
Year:2015
Views:1434
Downloads:534
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Secondary language

Language:English
Title:Using internet-based data sources for Crypto-Currency market prediction
Abstract:
Forecasting volatility of traditional financial instruments is a well known and widely addressed problem. In the past, researches addressed it by using technical and fundamental analysis. The former looks at the past price movement of a currency or a stock (their market value and trading volumes), while the latter analyses outside information which can cause fluctuations in the currency or stock value (e.g.: introducing a new product in the company can increase the value of company’s stocks, while lower rating of a country can reduce the value of its currency). The present master’s thesis focuses on the latter, i.e. fundamental analysis. Its effectiveness will be demonstrated on a fairly new and not yet well established digital currency market. The main advantage introduced by the digital currency market — in comparison with traditional financial markets — is its P2P nature. This means that every user has an insight into the entire trading process (market orders, demands, offers, transactions). Moreover, the user has access to all the information regarding the functioning of the network (computer power consumption, amount of currency in circulation, numbers of miners...). The first, introductory part of the thesis offers an overview of existing methods for predicting currency fluctuations that were adopted which mostly come from the field of trading with securities. Moreover, a rough presentation of our improvements and the advantages of the digital currency market are presented. Follows a detailed description on how the digital currency market functions: the process of transactions is described, the role of miners in the Bitcoin Network and the process of verification of users and transactions are explained, and the possibilities of trading with digital currencies are shown. In the next chapter the adopted development environment is described (how the application is built, tools that were used and libraries). The central part of the thesis demonstrates the development of our proposed method, the goal of which is to predict price movements of Bitcoin. This part is divided into three main parts: data mining, analysis of the considered data and the simulation. In the first part the web resources and methods of data collecting are defined. In the second part, an analysis of the data collected is conducted, on the basis of which only the data that could influence the value of currency is selected. Lastly, the selected data is implemented in a tool simulation which predicts currency fluctuations in which two models were applied: multiple linear regression and artificial neural network.

Keywords:technical analysis, fundamental analysis, digital, Bitcoin currency, P2P, prediction, data mining, machine learning

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