Sentiment analysis is the process by which users’ opinions are tracked on so- cial networks. In my empirical application I scrape the comments of 18 cryptocurrencies by order of capitalization posted on StockTwits, Reddit, and Twitter during the reference period 2021-02-21T 23:00:00Z - 2021-09-15T 23:00:00Z. Through Granger causality I statistically determine a causality between variables expressed in a VAR model, first from an aggregate point of view using PCA; then individually, to test how well each series performs. Finally, leveraging the β of each coin adjusted for sentiment, I apply a strategy of pairs trading among highly correlated cryptocurrencies.
La sentiment analysis è il processo attraverso il quale vengono tracciate le opin- ioni degli utenti sui social network. Nella mia applicazione empirica raschio i commenti di 18 criptovalute per ordine di capitalizzazione pubblicati su StockTwits, Reddit e Twitter nel periodo di riferimento 2021-02-21T 23:00:00Z - 2021-09-15T 23:00:00Z. Attraverso la causalità di Granger determino statisticamente una causalità tra le variabili espresse in un modello VAR, prima da un punto di vista aggregato utilizzando la PCA; poi individualmente, per testare il rendimento di ogni serie. Infine, sfruttando il β di ogni moneta aggiustata per il sentimento, applico una strategia di pairs trading tra criptovalute altamente correlate.
GIVING CONTENT TO INVESTOR SENTIMENT: THE ROLE OF SOCIAL MEDIA IN THE CRYPTOCURRENCY PRICE PREDICTION
ROSSINI, EDOARDO
2020/2021
Abstract
Sentiment analysis is the process by which users’ opinions are tracked on so- cial networks. In my empirical application I scrape the comments of 18 cryptocurrencies by order of capitalization posted on StockTwits, Reddit, and Twitter during the reference period 2021-02-21T 23:00:00Z - 2021-09-15T 23:00:00Z. Through Granger causality I statistically determine a causality between variables expressed in a VAR model, first from an aggregate point of view using PCA; then individually, to test how well each series performs. Finally, leveraging the β of each coin adjusted for sentiment, I apply a strategy of pairs trading among highly correlated cryptocurrencies.È consentito all'utente scaricare e condividere i documenti disponibili a testo pieno in UNITESI UNIPV nel rispetto della licenza Creative Commons del tipo CC BY NC ND.
Per maggiori informazioni e per verifiche sull'eventuale disponibilità del file scrivere a: unitesi@unipv.it.
https://hdl.handle.net/20.500.14239/1426