How well do investor sentiment and ensemble learning predict Bitcoin prices?

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216275%3A25410%2F23%3A39920845" target="_blank" >RIV/00216275:25410/23:39920845 - isvavai.cz</a>

Výsledek na webu

<a href="https://www.sciencedirect.com/science/article/abs/pii/S0275531922002227" target="_blank" >https://www.sciencedirect.com/science/article/abs/pii/S0275531922002227</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.ribaf.2022.101836" target="_blank" >10.1016/j.ribaf.2022.101836</a>

Jazyk výsledku

angličtina

Název v původním jazyce

How well do investor sentiment and ensemble learning predict Bitcoin prices?

Popis výsledku v původním jazyce

Investor sentiment is widely recognized as the major determinant of cryptocurrency prices. Although earlier research has revealed the influence of investor sentiment on cryptocurrency prices, it has not yet generated cohesive empirical findings on an important question: How effective is investor sentiment in predicting cryptocurrency prices? To address this gap, we propose a novel prediction model based on the Bitcoin Misery Index, using trading data for cryptocurrency rather than judgments from individuals who are not Bitcoin investors, as well as bagged support vector regression (BSVR), to forecast Bitcoin prices. The empirical analysis is performed for the period between March 2018 and May 2022. The results of this study suggest that the addition of the sentiment index enhances the predictive performance of BSVR signifi-cantly. Moreover, the proposed prediction system, enhanced with an automatic feature selection component, outperforms state-of-the-art methods for predicting cryptocurrency for the next 30 days.

Název v anglickém jazyce

How well do investor sentiment and ensemble learning predict Bitcoin prices?

Popis výsledku anglicky

Investor sentiment is widely recognized as the major determinant of cryptocurrency prices. Although earlier research has revealed the influence of investor sentiment on cryptocurrency prices, it has not yet generated cohesive empirical findings on an important question: How effective is investor sentiment in predicting cryptocurrency prices? To address this gap, we propose a novel prediction model based on the Bitcoin Misery Index, using trading data for cryptocurrency rather than judgments from individuals who are not Bitcoin investors, as well as bagged support vector regression (BSVR), to forecast Bitcoin prices. The empirical analysis is performed for the period between March 2018 and May 2022. The results of this study suggest that the addition of the sentiment index enhances the predictive performance of BSVR signifi-cantly. Moreover, the proposed prediction system, enhanced with an automatic feature selection component, outperforms state-of-the-art methods for predicting cryptocurrency for the next 30 days.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

50206 - Finance

Projekt

<a href="/cs/project/GA22-22586S" target="_blank" >GA22-22586S: Aspektově orientovaná analýza sentimentu finančních textů pro predikci finanční výkonnosti podniku</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2023

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Research in International Business and Finance

ISSN

0275-5319

e-ISSN

1878-3384

Svazek periodika

64

Číslo periodika v rámci svazku

January

Stát vydavatele periodika

NL - Nizozemsko

Počet stran výsledku

16

Strana od-do

101836

Kód UT WoS článku

000919065300001

EID výsledku v databázi Scopus

2-s2.0-85145720521