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Shen, Jiadi (2018) Backtesting in VaR Models of Bitcoins. [Dissertation (University of Nottingham only)]

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Abstract

Bitcoins is the most famous cryptocurrency in the world and is getting more and more important as an investment product. But from bitcoins’ historical performance, it can be read that this cryptocurrency has large volatilities which brought many risks to investors. The purpose of this dissertation is trying to use Value at Risk(VaR) as the risk management tool for bitcoins. And Basic Historical Simulation, Hull White and Parametric methods are used in this dissertation to evaluate VaR of bitcoins.

Due to the disadvantages of VaR models, backtesting is used to each model to check the accuracy of those models. Not only unconditional back tests such as Kupiec tests but also conditional backtesting is applied in this paper.

In the end, most of VaR models perform well to bitcoins since they pass several backtesting and it can be concluded that VaR is a reliable tool for bitcoins risk management. Also, volatility adjustment can increase the accuracy of VaR models that applied to products with large volatilities.

Key words: Bitcoins, Value at Risk, Volatility Adjustment, Backtesting, Risk Management

Item Type:	Dissertation (University of Nottingham only)
Depositing User:	SHEN, JIADI
Date Deposited:	01 Aug 2022 15:43
Last Modified:	01 Aug 2022 15:43
URI:	https://eprints.nottingham.ac.uk/id/eprint/54384

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