Statistical Analysis of the Exchange Rate of Bitcoin

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Hencic and Gourieroux (2014) model and predict the exchange rate of Bitcoin versus the U.S. Dollar, using a noncausal autoregressive process with Cauchy errors. Their results show that the daily Crypto-currency bubbles: An application of the Phillips–Shi–Yu (2013) methodology on Mt. Gox bitcoin prices. Applied Economics, 47 (23), 2348–2358. CrossRef Google Scholar 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 Here is a brief description from a 2015 article in the Econometrics of Risk called Noncausal Autoregressive Model in Application to Bitcoin/USD Exchange Rates I’ve always been a little behind the curve on lag operators, but basically Ψ (L -1 ) is a function of the standard lagged operators, while Φ (L) is a second function of offsets to A Hencic's 3 research works with 51 citations and 450 reads, including: Forecast Performance and Bubble Analysis in Noncausal MAR(1,1) Processes

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Login system using PHP with MYSQL database

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