A dynamical systems approach to cryptocurrency stability

Carey Caginalp ^{1,2
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1.
Department of Mathematics, University of Pittsburgh, USA
2.
Economic Science Institute, Chapman University, USA

Received: 17 April 2019 Accepted: 09 July 2019 Published: 08 August 2019
MSC : 65L07

Abstract
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Recently, the notion of cryptocurrencies has come to the fore of public interest. These assets that exist only in electronic form, with no underlying value, offer the owners some protection from tracking or seizure by government or creditors. We model these assets from the perspective of asset flow equations developed by Caginalp and Balenovich, and investigate their stability under various parameters, as classical finance methodology is inapplicable. By utilizing the concept of liquidity price and analyzing stability of the resulting system of ordinary differential equations, we obtain conditions under which the system is linearly stable. We find that trend-based motivations and additional liquidity arising from an uptrend are destabilizing forces, while anchoring through value assumed to be fairly recent price history tends to be stabilizing.
- ordinary differential equations,
- mathematical finance,
- asset bubbles,
- quantitative finance
Citation: Carey Caginalp. A dynamical systems approach to cryptocurrency stability[J]. AIMS Mathematics, 2019, 4(4): 1065-1077. doi: 10.3934/math.2019.4.1065

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Abstract

Recently, the notion of cryptocurrencies has come to the fore of public interest. These assets that exist only in electronic form, with no underlying value, offer the owners some protection from tracking or seizure by government or creditors. We model these assets from the perspective of asset flow equations developed by Caginalp and Balenovich, and investigate their stability under various parameters, as classical finance methodology is inapplicable. By utilizing the concept of liquidity price and analyzing stability of the resulting system of ordinary differential equations, we obtain conditions under which the system is linearly stable. We find that trend-based motivations and additional liquidity arising from an uptrend are destabilizing forces, while anchoring through value assumed to be fairly recent price history tends to be stabilizing.

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