T1. Time Series Data Flashcards

1
Q

What are time series data?

A

A sequence of data points recorded in chronological order.

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2
Q

When are observations made?

A

At equally-spaced intervals in time (e.g. annually, monthly, weekly)

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3
Q

Key difference between time series data and cross-sectional data

A

Cross section data are (can be?) independent, time series are not.

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4
Q

5 phenomena of time series data

A

Trends, breaks, seasonality, cycles, noise

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5
Q

What is meant by trends in time series data?

A

The gerenal direction in which time series data develops

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6
Q

How can linearise trends in data?

A

Applying approriate transformation (e.g. taking logs).

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7
Q

What is meant by breaks in time series data?

A

Variations that occur due to sudden causes and are usually ex ante unpredictable (but usually rationalisable with hindsight).

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8
Q

What is meant by seasonality in time series data?

A

A predictable periodic pattern that recurs or repeats over regular intervals.

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9
Q

What is meant by cycles in time series data?

A

Cycles occur when a series follows an up and down pattern that is not seasonal.

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10
Q

4 phases of cycles

A

Peak, recession, trough, expansion

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11
Q

How are cycles different from seasonality?

A

The periodicity of cycles is variable and the durations of each phases in the cycle also varies.

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12
Q

What is meant by noise in time series data?

A

Some time series are highly unpredictable. Pure as-if-random noise for example is often an irreducible component of time series.

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13
Q

Time series data notation

A

Xt denotes a variable observed at time t.

where t = 1, 2, 3, … is the sequence

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14
Q

Notation for 1st, 2nd, and h’s lag

A

The first lag of the variable is the value in the periods before: Xt-1

The second lag of the variable is the value two periods before: Xt-2

h’s lag: Xt-h

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15
Q

Notation for h’s lead

A

h’s lead is Xt+h

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16
Q

What is meant by autocorrelation?

A

A correlation between the time series and its own past self.

17
Q

Equation for autocorrelation

A
18
Q

How do lagged variables impact observations?

A

We lose one observation.

When calculating the same autocorrelation of any given series with fixed size T, we cannot put too much confidence in the values for large gaps.

19
Q

What do we call the plot of an autocorrelation?

A

A correlogram.

20
Q

Correlogram for strong autocorrelation with past values

A
21
Q

Correlogram for strong seasonal correlation

A
22
Q

Correlogram for no correlation with past values

A