Noncausal autoregressive model in application to bitcoin/USD exchange rates

Andrew Hencic; Christian Gouriéroux

doi:10.1007/978-3-319-13449-9_2

Noncausal autoregressive model in application to bitcoin/USD exchange rates

Andrew Hencic, Christian Gouriéroux

Research output: Contribution to journal › Article › peer-review

Abstract

This paper introduces a noncausal autoregressive process with Cauchy errors in application to the exchange rates of the Bitcoin electronic currency against the US Dollar. The dynamics of the daily Bitcoin/USD exchange rate series displays episodes of local trends, which can be modelled and interpreted as speculative bubbles. The bubbles may result from the speculative component in the on-line trading. The Bitcoin/USD exchange rates are modelled and predicted.

Original language	English
Pages (from-to)	17-40
Number of pages	24
Journal	Studies in Computational Intelligence
Volume	583
DOIs	https://doi.org/10.1007/978-3-319-13449-9_2
Publication status	Published - 1 Jan 2015
Externally published	Yes

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title = "Noncausal autoregressive model in application to bitcoin/USD exchange rates",

abstract = "This paper introduces a noncausal autoregressive process with Cauchy errors in application to the exchange rates of the Bitcoin electronic currency against the US Dollar. The dynamics of the daily Bitcoin/USD exchange rate series displays episodes of local trends, which can be modelled and interpreted as speculative bubbles. The bubbles may result from the speculative component in the on-line trading. The Bitcoin/USD exchange rates are modelled and predicted.",

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AB - This paper introduces a noncausal autoregressive process with Cauchy errors in application to the exchange rates of the Bitcoin electronic currency against the US Dollar. The dynamics of the daily Bitcoin/USD exchange rate series displays episodes of local trends, which can be modelled and interpreted as speculative bubbles. The bubbles may result from the speculative component in the on-line trading. The Bitcoin/USD exchange rates are modelled and predicted.

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Noncausal autoregressive model in application to bitcoin/USD exchange rates

Abstract

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