Pump It: Twitter Sentiment Analysis for Cryptocurrency Price Prediction

This study demonstrates the significant impact of market sentiment, derived from social media, on the daily price prediction of cryptocurrencies in both bull and bear markets. Through the analysis of approximately 567 thousand tweets related to twelve specific cryptocurrencies, we incorporate the se...

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Main Authors: Vladyslav Koltun, Ivan P. Yamshchikov
Format: Article
Language:English
Published: MDPI AG 2023-09-01
Series:Risks
Subjects:
Online Access:https://www.mdpi.com/2227-9091/11/9/159
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author Vladyslav Koltun
Ivan P. Yamshchikov
author_facet Vladyslav Koltun
Ivan P. Yamshchikov
author_sort Vladyslav Koltun
collection DOAJ
description This study demonstrates the significant impact of market sentiment, derived from social media, on the daily price prediction of cryptocurrencies in both bull and bear markets. Through the analysis of approximately 567 thousand tweets related to twelve specific cryptocurrencies, we incorporate the sentiment extracted from these tweets along with daily price data into our prediction models. We test various algorithms, including ordinary least squares regression, long short-term memory network and neural hierarchical interpolation for time series forecasting (NHITS). All models show better performance once the sentiment is incorporated into the training data. Beyond merely assessing prediction error, we scrutinise the model performances in a practical setting by applying them to a basic trading algorithm managing three distinct portfolios: established tokens, emerging tokens, and meme tokens. While NHITS emerged as the top-performing model in terms of prediction error, its ability to generate returns is not as compelling.
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spelling doaj.art-4d9d0241b1d9483d9bc57d451380493e2023-11-19T12:51:17ZengMDPI AGRisks2227-90912023-09-0111915910.3390/risks11090159Pump It: Twitter Sentiment Analysis for Cryptocurrency Price PredictionVladyslav Koltun0Ivan P. Yamshchikov1Instituto Superior de Economia e Gestao, University of Lisbon, 1200-781 Lisbon, PortugalTHWS, CAIRO, 97082 Würzburg, GermanyThis study demonstrates the significant impact of market sentiment, derived from social media, on the daily price prediction of cryptocurrencies in both bull and bear markets. Through the analysis of approximately 567 thousand tweets related to twelve specific cryptocurrencies, we incorporate the sentiment extracted from these tweets along with daily price data into our prediction models. We test various algorithms, including ordinary least squares regression, long short-term memory network and neural hierarchical interpolation for time series forecasting (NHITS). All models show better performance once the sentiment is incorporated into the training data. Beyond merely assessing prediction error, we scrutinise the model performances in a practical setting by applying them to a basic trading algorithm managing three distinct portfolios: established tokens, emerging tokens, and meme tokens. While NHITS emerged as the top-performing model in terms of prediction error, its ability to generate returns is not as compelling.https://www.mdpi.com/2227-9091/11/9/159cryptocurrencysentiment analysistwitter
spellingShingle Vladyslav Koltun
Ivan P. Yamshchikov
Pump It: Twitter Sentiment Analysis for Cryptocurrency Price Prediction
Risks
cryptocurrency
sentiment analysis
twitter
title Pump It: Twitter Sentiment Analysis for Cryptocurrency Price Prediction
title_full Pump It: Twitter Sentiment Analysis for Cryptocurrency Price Prediction
title_fullStr Pump It: Twitter Sentiment Analysis for Cryptocurrency Price Prediction
title_full_unstemmed Pump It: Twitter Sentiment Analysis for Cryptocurrency Price Prediction
title_short Pump It: Twitter Sentiment Analysis for Cryptocurrency Price Prediction
title_sort pump it twitter sentiment analysis for cryptocurrency price prediction
topic cryptocurrency
sentiment analysis
twitter
url https://www.mdpi.com/2227-9091/11/9/159
work_keys_str_mv AT vladyslavkoltun pumpittwittersentimentanalysisforcryptocurrencypriceprediction
AT ivanpyamshchikov pumpittwittersentimentanalysisforcryptocurrencypriceprediction