The Financial Turbulence of Bitcoin: An Analysis of Transaction Costs and Their Implications for Investor

Abstract

This thesis investigates the transaction costs of trading volatile cryptocurrency Bitcoin in attempt to provide valuable insight for the investors interested in such assets. A model created in Python is utilizing historical data to forecast transaction costs for different risk profiles and portfolio sizes. The findings suggest that transaction costs vary significantly depending on the size of the portfolio and risk profiles of the investors. Costs are negligible for smaller portfolios but become excessively high for larger portfolios. To address market volatility, another dataset was used, representing the most stable periods of Bitcoin, attempting to enhance robustness of the model. This research deliberately avoids technological assessment and critique, rather focusing on the financial behaviours offering insight that could potentially devalue the asset. The primary goal is to equip the investors with financial insights and tools in order to avoid the costs and potential risks when using investing in Bitcoin.