Backtesting in VaR Models of Bitcoins

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 i...

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Main Author: Shen, Jiadi
Format: Dissertation (University of Nottingham only)
Language:English
Published: 2018
Online Access:https://eprints.nottingham.ac.uk/54384/
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author Shen, Jiadi
author_facet Shen, Jiadi
author_sort Shen, Jiadi
building Nottingham Research Data Repository
collection Online Access
description 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
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spelling nottingham-543842022-08-01T15:43:40Z https://eprints.nottingham.ac.uk/54384/ Backtesting in VaR Models of Bitcoins Shen, Jiadi 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 2018-12-01 Dissertation (University of Nottingham only) NonPeerReviewed application/pdf en https://eprints.nottingham.ac.uk/54384/1/dissertation3.0.pdf Shen, Jiadi (2018) Backtesting in VaR Models of Bitcoins. [Dissertation (University of Nottingham only)]
spellingShingle Shen, Jiadi
Backtesting in VaR Models of Bitcoins
title Backtesting in VaR Models of Bitcoins
title_full Backtesting in VaR Models of Bitcoins
title_fullStr Backtesting in VaR Models of Bitcoins
title_full_unstemmed Backtesting in VaR Models of Bitcoins
title_short Backtesting in VaR Models of Bitcoins
title_sort backtesting in var models of bitcoins
url https://eprints.nottingham.ac.uk/54384/