Application of Sentiment Analysis and Machine Learning Techniques to Predict Daily Cryptocurrency Price Returns - CORE Reader thumbnail
Application of Sentiment Analysis and Machine Learning Techniques to Predict Daily Cryptocurrency Price Returns - CORE Reader
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TwitterdatawascompiledthroughspecialaccesstotheTwitterAPIAcademicResearchtrackwiththehelpofProfessorMikeIzbicki.Initially,collectedandutilizedbyIzbicki,Papalexakis,andTsotras(2019) However,theresultsofthispaperfindthatsocialmediasentimentrelatingtoBitcoindoesnotaddsignificantpredictivevaluetoforecas
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Summary

This paper explores the application of sentiment analysis and machine learning techniques to predict daily cryptocurrency price returns. The study finds that social media sentiment related to Bitcoin does not significantly predict price returns for cryptocurrencies. Machine learning models that assume linearity between price returns and sentiment scores were less accurate than models that do not assume linearity. The VADER sentiment analysis tool was used to compute sentiment scores of tweets, and LSTM neural networks were used to predict cryptocurrency prices. The study also highlights the impact of public sentiment on stock and cryptocurrency prices.

Top Highlights

  • TwitterdatawascompiledthroughspecialaccesstotheTwitterAPIAcademicResearchtrackwiththehelpofProfessorMikeIzbicki.Initially,collectedandutilizedbyIzbicki,Papalexakis,andTsotras(2019)
  • However,theresultsofthispaperfindthatsocialmediasentimentrelatingtoBitcoindoesnotaddsignificantpredictivevaluetoforecastingdailypricereturnsforeachofthesixcryptocurrenciesusedforanalysisandthatmachinelearningmodelsthatdonotassumelinearitybetweenthecurrentdaypricereturnandpreviousdailypricereturnscombinedwithpreviousdailysentimentscoresweremoreaccur...
  • Throughtheseexamples,wecanobservethatpublicsentimentandinvestoremotionsmaypotentiallyhavealargeimpactonstockandcryptocurrencyprices.
  • VADER(ValenceAwareDictionaryforSentimentReasoning),alexicon-basedmethod,isoptimizedforsocialmediadataandhasbeenusedbymanyresearcherswhoanalyzethesentimentofTwitterandotherfinancialsocialmediadata
  • Asaresult,moreandmoreinvestorsarediversifyingtheirinvestmentportfoliostoincludepopularcryptocurrenciessuchasBitcoin, Ethereum, Tether, and Solana

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machine learning

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