Noncausal Autoregressive Model in Application to Bitcoin ...

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Bitcoin/USD exchange rates are modelled and predicted. The mixed causal-noncausal autoregressive model is shown to better t the data than the traditional purely causal model. A forecasting exercise using the noncausal model is then presented. Chapter three examines the performance of nonlinear forecasts of noncausal processes Some of the latest research comes from , modelling and predicting the Bitcoin/USD exchange rate through the application of a non-causal autoregressive model. Using data from daily closing rates of Bitcoin/USD from February 2013-June 2013, results from the analysis show that the Bitcoin/USD rate “displays episodes of local trends, which can be modelled and interpreted as speculative bubbles ... exchange rate through the application of a non-causal autoregressive model. Using data from daily closing rates of Bitcoin/USD from February 2013-Jun e 2013, results from the analysis Since its launch in 2008, Bitcoin becomes one of the most successful and fast-growing alternative currencies. As of 2017, the market capitalization is around $46 billions and arguably expected to continue growing. The Bitcoin to the US dollar exchange rate has been very volatile and fluctuating significantly. Although Bitcoin was designed as a medium of exchange, it is now more as an ... Chapter two 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 display episodes of local trends, which are modelled and interpreted as speculative bubbles. The structure of the Bitcoin market is described to give context for the ...

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