A feature of a series that makes it behave like a random walk, so shocks never fade. It is tested for before series are used in regressions.
Where you will meet it
Unit root comes up in 4 learning outcome notes across the FRM syllabus.
A few of them:
Stationary Time Series FRM Part I · Quantitative analysis
“A root of exactly one is a unit root, and the series is not stationary.”
Non-Stationary Time Series FRM Part I · Quantitative analysis
“A unit root means the characteristic equation of the autoregression has a root equal to 1.”
Non-Stationary Time Series FRM Part I · Quantitative analysis
“If two independent series each contain a unit root, regressing one on the other typically gives a high R², a large t-statistic and a very low Durbin-Watson statistic, even though there is no relationship.”
Non-Stationary Time Series FRM Part I · Quantitative analysis
“A unit root is tested with the Dickey-Fuller test, which writes the AR(1) model in differences: Change = γ × yt−1 + εt.”
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