Bitcoin cross-market price dynamics: Three essays looking into consensus, fear and memory

Abstract

This thesis investigates dynamics in Bitcoin cross-market price disparity from three inherently connected aspects. In chapter 2, an examination of Bitcoin cross-market convergence is of considered. Investigating into cross-market heterogeneity can serve as a novel first step towards Bitcoin’s unobserved price process and valuation. Our strategy quantifies collective dynamics among international bitcoin markets via cross-market risk-return distances. We link price dynamics among major Bitcoin-fiat pairs as distance dependent measures of risk-adjusted return. Empirical evidence supports a solid convergence pattern from both individual markets and aggregated market perspectives; we thus draw inference on cross-market consensus. We further discuss the impacts of positive and negative macroeconomic shocks on convergence, followed by an analysis of impacts brought by converging trends in information sharing efficiency among selected Bitcoin markets. Our distance measures additionally serve as a model-free instrument to resolve pricing mysteries for emerging and zero-fundamental speculative assets. In chapter 3, we examine whether fear can be a sentimental driver for Bitcoin cross-market price convergence. Valuation of Bitcoin is rather subjective and is sensitive to investors’ psychological conditions. Literature drawing on sentimental factors for Bitcoin is yet under-developed. This paper examines if fear sentiment can be considered as a driving factor in Bitcoin price dynamics. In our empirical framework, we characterise dynamics in Bitcoin cross-market risk-return distance via Convergence Speed and examine therole of investors’ fear in this process. Empirical results suggest that our composite FEAR proxy as a risk expectation in major conventional financial markets can significantly accelerate the convergence among Bitcoin markets, after controlling for five sets of determinants of Bitcoin price returns. The explanatory power and predictability of FEAR imply that participants’ decision-making in Bitcoin markets is adaptive to sentimental conditions extracted from a traditional economy, rather than purely isolated and detached as initially designed. Our study suggests hints for understanding the mechanism of the Bitcoin price evolving process under an Adaptive Market Hypothes is as well as adding new evidence for Bitcoin as a hedge for traditional financial assets. In chapter 4, by revisiting informational efficiency, this chapter exhibits episodes of long memory and cross-market information transmission in Bitcoin price dynamics. We argue price behaviour of Bitcoin is in line with adaptive market theory by(Lo2004;2005;2017)and hypothesise the adaptive learning patterns can be governed by along memory process. To set up the model for examination, we characterise Bitcoin cross-market disparity Patterns via the framework of fractional co-integrated vector auto-regression(FCVAR). Bitcoin prices in five developed markets are of considered and the examination of long Memory phenomena covers two aspects, i.e., the individual markets and the cross-market interdependence(co-integration). In addition, we exhibit fear sentiment can be a driver for relationships among information across five developed markets. Findings in this research are robust to structural breaks, to sample selections and to rolling window settings

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ORCID for Ming-Chien Sung: orcid.org/0000-0002-2278-6185

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