On the speculative nature of cryptocurrencies: A study on Garman and Klass volatility measure
We propose to measure volatilities of 102 active cryptocurrencies using Garman and Klass (GK) volatility measures and model the measures using asymmetric bilinear Conditional Autoregressive Range (ABL-CARR) model. Results reveal volatility persistence and leverage effects which can improve the predi...
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my.um.eprints.248232020-06-15T03:01:57Z http://eprints.um.edu.my/24823/ On the speculative nature of cryptocurrencies: A study on Garman and Klass volatility measure Tan, Shay Kee Chan, Jennifer So Kuen Ng, Kok Haur Q Science (General) QA Mathematics We propose to measure volatilities of 102 active cryptocurrencies using Garman and Klass (GK) volatility measures and model the measures using asymmetric bilinear Conditional Autoregressive Range (ABL-CARR) model. Results reveal volatility persistence and leverage effects which can improve the predictability of volatility, reduce risk and hence lessen the level of speculation in cryptocurrency market. We further relate volatility features for the top five cryptocurrencies to their time of development and transaction speed and recommend investors to distinguish between long-term or short-term speculation in their investment profile. © 2018 Elsevier Inc. Elsevier 2020 Article PeerReviewed Tan, Shay Kee and Chan, Jennifer So Kuen and Ng, Kok Haur (2020) On the speculative nature of cryptocurrencies: A study on Garman and Klass volatility measure. Finance Research Letters, 32. p. 101075. ISSN 1544-6123 https://doi.org/10.1016/j.frl.2018.12.023 doi:10.1016/j.frl.2018.12.023 |
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Q Science (General) QA Mathematics Tan, Shay Kee Chan, Jennifer So Kuen Ng, Kok Haur On the speculative nature of cryptocurrencies: A study on Garman and Klass volatility measure |
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We propose to measure volatilities of 102 active cryptocurrencies using Garman and Klass (GK) volatility measures and model the measures using asymmetric bilinear Conditional Autoregressive Range (ABL-CARR) model. Results reveal volatility persistence and leverage effects which can improve the predictability of volatility, reduce risk and hence lessen the level of speculation in cryptocurrency market. We further relate volatility features for the top five cryptocurrencies to their time of development and transaction speed and recommend investors to distinguish between long-term or short-term speculation in their investment profile. © 2018 Elsevier Inc. |
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Article |
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Tan, Shay Kee Chan, Jennifer So Kuen Ng, Kok Haur |
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Tan, Shay Kee Chan, Jennifer So Kuen Ng, Kok Haur |
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Tan, Shay Kee |
title |
On the speculative nature of cryptocurrencies: A study on Garman and Klass volatility measure |
title_short |
On the speculative nature of cryptocurrencies: A study on Garman and Klass volatility measure |
title_full |
On the speculative nature of cryptocurrencies: A study on Garman and Klass volatility measure |
title_fullStr |
On the speculative nature of cryptocurrencies: A study on Garman and Klass volatility measure |
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On the speculative nature of cryptocurrencies: A study on Garman and Klass volatility measure |
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on the speculative nature of cryptocurrencies: a study on garman and klass volatility measure |
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Elsevier |
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2020 |
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http://eprints.um.edu.my/24823/ https://doi.org/10.1016/j.frl.2018.12.023 |
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