Emoji driven crypto assets market reactions

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F24%3A10489891" target="_blank" >RIV/00216208:11320/24:10489891 - isvavai.cz</a>

Výsledek na webu

<a href="https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=0RaFeUrV8V" target="_blank" >https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=0RaFeUrV8V</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.2478/mmcks-2024-0008" target="_blank" >10.2478/mmcks-2024-0008</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Emoji driven crypto assets market reactions

Popis výsledku v původním jazyce

In the burgeoning realm of cryptocurrency, social media platforms like Twitter have become pivotal in influencing market trends and investor sentiments. In our study, we leverage GPT-4 and a fine-tuned transformer-based BERT model for a multimodal sentiment analysis, focusing on the impact of emoji sentiment on cryptocurrency markets. By translating emojis into quantifiable sentiment data, we correlate these insights with key market indicators such as BTC Price and the VCRIX index. Our architecture&apos;s analysis of emoji sentiment demonstrated a distinct advantage over FinBERT&apos;s pure text sentiment analysis in such predicting power. This approach may be fed into the development of trading strategies aimed at utilizing social media elements to identify and forecast market trends. Crucially, our findings suggest that strategies based on emoji sentiment can facilitate the avoidance of significant market downturns and contribute to the stabilization of returns. This research underscores the practical benefits of integrating advanced AI-driven analyzes into financial strategies, offering a nuanced perspective on the interaction between digital communication and market dynamics in an academic context.

Název v anglickém jazyce

Emoji driven crypto assets market reactions

Popis výsledku anglicky

In the burgeoning realm of cryptocurrency, social media platforms like Twitter have become pivotal in influencing market trends and investor sentiments. In our study, we leverage GPT-4 and a fine-tuned transformer-based BERT model for a multimodal sentiment analysis, focusing on the impact of emoji sentiment on cryptocurrency markets. By translating emojis into quantifiable sentiment data, we correlate these insights with key market indicators such as BTC Price and the VCRIX index. Our architecture&apos;s analysis of emoji sentiment demonstrated a distinct advantage over FinBERT&apos;s pure text sentiment analysis in such predicting power. This approach may be fed into the development of trading strategies aimed at utilizing social media elements to identify and forecast market trends. Crucially, our findings suggest that strategies based on emoji sentiment can facilitate the avoidance of significant market downturns and contribute to the stabilization of returns. This research underscores the practical benefits of integrating advanced AI-driven analyzes into financial strategies, offering a nuanced perspective on the interaction between digital communication and market dynamics in an academic context.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

50201 - Economic Theory

Projekt

<a href="/cs/project/GX19-28231X" target="_blank" >GX19-28231X: Dynamické modely pro digitální finance</a><br>

Návaznosti

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

Rok uplatnění

2024

Kód důvěrnosti údajů

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

Název periodika

Management &amp; Marketing

ISSN

1842-0206

e-ISSN

2069-8887

Svazek periodika

19

Číslo periodika v rámci svazku

2

Stát vydavatele periodika

RO - Rumunsko

Počet stran výsledku

21

Strana od-do

158-178

Kód UT WoS článku

001270048700002

EID výsledku v databázi Scopus

2-s2.0-85198981994