Home

Forecasting Cryptocurrencies Log-Returns: a LASSO-VAR and Sentiment Approach

Abstract Views
2
Author
Federico DAmario Milos Ciganovic
Category
Financial
Date Posted
2022/09/22
Date Retrieved
2022/09/22
Date Revised
Date Written
2022/09/22
Description
Cryptocurrencies have become a trendy topic recently primarily due to their disruptive potential and reports of unprecedented returns. In addition academics increasingly acknowledge the predictive power of Social Media in many fields and more specifically for financial markets and economics. In this paper we leverage the predictive power of Twitter and Reddit sentiment together with Google Trends indexes and volume to forecast the log returns of ten cryptocurrencies. Specifically we consider Bitcoin Ethereum Tether BinanceCoin Litecoin EnjinCoin Horizen Namecoin Peercoin and Feathercoin. We evaluate the performance of LASSO-VAR using daily data from January 2018 to January 2022. In a 30 days recursive forecast we can retrieve the correct direction of the actual series more than 50% of the time. We compare this result with the main benchmarks and we see a 10% improvement in Mean Directional Accuracy (MDA). The use of sentiment and attention variables as predictors increase significantly
Downloads
1
Exports
0
JEL Classifications
C32 C53 C55 G17
Keywords
Cryptocurrencies Time series analysis Sentiment analysis Natural Language Processing
News Mentions
0
Pages
26
Random
960
Readers
0
Shares and Likes
0
Tweets
0
URL
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4227022
TOP