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Autoregressive integrated moving average
Autoregressive integrated moving average
We analyze the time series data of all the currencies during the last 6 months using an autoregressive integrated moving average (ARIMA) model.
Xt = Exchange rate
t = Measured in days
p = Number of times lags
d = Degree of differencing
q = Order of the moving-average model
ARIMA(p', q) would be equal to
or equivalently by . . .
L = Lag operator
α = Parameters of the autoregressive part
θ = Parameters of the moving average part
ε = Error terms
We rank the currencies based on the minimum Root Square Deviation. This is a highly reliable metric even in turbulent times.
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