Dissertations, Theses, and Capstone Projects

Date of Degree

6-2024

Document Type

Dissertation

Degree Name

Ph.D.

Program

Economics

Advisor

Seungho Baek

Advisor

Merih Uctum

Committee Members

Wim Vijverberg

Subject Categories

Behavioral Economics | Econometrics | Finance

Keywords

Cryptocurrency, Sentiment, Cryptocurrency Anomalies, Law of One Price, Purchasing Power Parity.

Abstract

Chapter 1 - Herd Instinct in the Digital Currency Markets: In this chapter, We establish that the actions of influential opinion leaders in the digital currency markets and potential investors following their lead drive abnormal cryptocurrency returns. We develop a psychological and behavioral factor, named the herd behavior index, that detects the herd instinct of the investors in cryptocurrency markets and captures anomalies in cryptocurrency returns. Our finding shows that the herd behavior index can explain the variation in cryptocurrency returns. Moreover, there exists a time-series relationship between abnormal returns and the investors’ herd instinct, and the herd behavior index consistently forecasts future digital currency returns. Finally, we find notable gains even after considering transaction costs by implementing a long/short trading strategy based on the herd behavior index.

Chapter 2 - Bitcoin’s Law of One Price: Exchange Rate Insights: In this chapter, I investigate the persistent price differences in Bitcoin across countries, challenging the Law of One Price (LOP). We show that cointegration between nominal exchange rates and cryptocurrency premiums, revealing significant regional differences, particularly in Korea, known for the ”Kimchi premium.” Our analysis indicates that Bitcoin prices, rather than nominal exchange rates, primarily drive the mean-reverting process, deviating from traditional Purchasing Power Parity (PPP) concepts. The study also highlights the predictive power of Bitcoin prices for nominal exchange rates, advocating the inclusion of Bitcoin premiums in exchange rate forecasting models. This research not only deepens the understanding of Bitcoin market dynamics but also emphasizes the utility of Bitcoin premiums in forecasting nominal exchange rate.

Chapter 3 - Lexical Choice, Investment Sentiment, and Bitcoin Anomalies: In this chapter, I investigate how the choice of lexical information significantly influences the connection between Bitcoin investors’ behavioral sentiment and their investment decisions. To assess the effectiveness of sentiment features in the Bitcoin market, I employ both the bag-of-words approach and the context-driven approach in text mining. My findings suggest that the detection of textual tones related to Bitcoin investment on a Reddit web forum varies across linguistic resources. Additionally, I observe that content-driven sentiment is predictive of variations in Bitcoin returns and changes in Bitcoin trading volume. Furthermore, we document that the long-short strategy developed based on content-driven sentiment for the Bitcoin asset demonstrates robust outperformance, even after considering fees.

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