From Gold to Blockchain: How Macro Forces Shape Crypto Returns

Abstract

This thesis explores the dynamic interplay between traditional economic indicators, specifically inflation rates, gold prices and market sentiment in predicting the future returns of the 20 largest cryptocurrencies, excluding stablecoins and initial coin offers (ICOs). The daily returns of cryptocurrencies are analyzed over a three-year period. Utilizing multiple regression analysis techniques on data, this study aims to quantify and model the influences of these traditional and contemporary economic measures on cryptocurrency performance. The research seeks to bridge the gap between conventional financial theories and the rapidly evolving digital currency landscape by investigating the extent to which these economic indicators can forecast cryptocurrency market movements. In a financial ecosystem increasingly intertwined with digital innovations, this thesis posits that the Consumer Price Index (CPI) and gold, often viewed as a traditional safe haven, could be significantly correlated with cryptocurrency valuations. Moreover, the study delves into the role of market sentiment, derived from economic news and social media, in shaping cryptocurrency trends, suggesting that sentiment analysis, particularly using advanced tools like the Fear and Greed index for real-time social media text analysis, provides predictive insights into market fluctuations. Through comprehensive data analysis, this research not only aims to enhance the understanding of digital asset pricing dynamics but also contributes to strategic investment and policy decisions in the digital age. By integrating established economic measures with cutting-edge sentiment analysis, the thesis offers a novel perspective on the potential drivers of cryptocurrency markets, providing valuable insights for investors and the broader financial community.