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DC Field | Value | Language |
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dc.contributor.author | Suda, David | - |
dc.contributor.author | Spiteri, Luke | - |
dc.date.accessioned | 2022-06-30T07:07:04Z | - |
dc.date.available | 2022-06-30T07:07:04Z | - |
dc.date.issued | 2019 | - |
dc.identifier.citation | Suda, D., & Spiteri, L. (2019). Analysis and comparison of bitcoin and s and p 500 market features using hmms and hsmms. Information, 10(10), 322. | en_GB |
dc.identifier.uri | https://www.um.edu.mt/library/oar/handle/123456789/98539 | - |
dc.description.abstract | We implement hidden Markov models (HMMs) and hidden semi-Markov models (HSMMs) on Bitcoin/US dollar (BTC/USD) with the aim of market phase detection. We make analogous comparisons to Standard and Poor’s 500 (S and P 500), a benchmark traditional stock index and a protagonist of several studies in finance. Popular labels given to market phases are “bull”, “bear”, “correction”, and “rally”. In the first part, we fit HMMs and HSMMs and look at the evolution of hidden state parameters and state persistence parameters over time to ensure that states are correctly classified in terms of market phase labels. We conclude that our modelling approaches yield positive results in both BTC/USD and the S and P 500, and both are best modelled via four-state HSMMs. However, the two assets show different regime volatility and persistence patterns—BTC/USD has volatile bull and bear states and generally weak state persistence, while the S and P 500 shows lower volatility on the bull states and stronger state persistence. In the second part, we put our models to the test of detecting different market phases by devising investment strategies that aim to be more profitable on unseen data in comparison to a buy-and-hold approach. In both cases, for select investment strategies, four-state HSMMs are also the most profitable and significantly outperform the buy-and-hold strategy. | en_GB |
dc.language.iso | en | en_GB |
dc.publisher | MDPI | en_GB |
dc.rights | info:eu-repo/semantics/openAccess | en_GB |
dc.subject | Markov processes | en_GB |
dc.subject | Hidden Markov models | en_GB |
dc.subject | Cryptocurrencies -- Law and legislation | en_GB |
dc.subject | Cryptocurrencies | en_GB |
dc.title | Analysis and comparison of Bitcoin and S and P 500 market features using HMMs and HSMMs | en_GB |
dc.type | article | en_GB |
dc.rights.holder | The copyright of this work belongs to the author(s)/publisher. The rights of this work are as defined by the appropriate Copyright Legislation or as modified by any successive legislation. Users may access this work and can make use of the information contained in accordance with the Copyright Legislation provided that the author must be properly acknowledged. Further distribution or reproduction in any format is prohibited without the prior permission of the copyright holder. | en_GB |
dc.description.reviewed | peer-reviewed | en_GB |
dc.identifier.doi | 10.3390/info10100322 | - |
dc.publication.title | Information | en_GB |
Appears in Collections: | Scholarly Works - FacSciSOR |
Files in This Item:
File | Description | Size | Format | |
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Analysis and comparison of Bitcoin and S and P 500 market features using HMMs and HSMMs.pdf | 1.82 MB | Adobe PDF | View/Open |
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