Table 5

Out-of-sample forecast evaluation [h = 120]

Clark and West test
Full samplePre-COVIDCOVID#
Model 1 vs Model 2Model 1 vs Model 3Model 1 vs Model 2Model 1 vs Model 3Model 1 vs Model 2Model 1 vs Model 3
Consumer goods0.0892a [4.23]0.2764a [5.04]0.1007a [4.50]0.3975a [5.16]2.4765a [4.04]5.7999a [4.95]
Consumer Services0.0341a [6.67]0.5057a [19.87]0.0444a [8.32]0.5015a [16.79]2.5197a [6.69]9.3796a [9.78]
Financials0.0376a [7.13]0.3604a [21.56]0.0427a [6.73]0.3505a [16.97]3.8129a [6.49]10.6388a [11.82]
HealthCare0.0546a [2.66]0.1028c [1.63]0.0593a [2.46]0.1537a [2.08]1.4538a [2.73]3.8291a [5.48]
Industrials0.0305a [5.27]0.3098a [9.45]0.0393a [5.99]0.3625a [9.73]7.3485a [2.03]12.7912a [2.40]
Materials0.0551a [5.89]0.0966a [2.17]0.0707a [6.27]0.0860c [1.57]7.8840a [6.17]15.2597a [7.12]
Technology0.1042a [3.22]0.1720a [3.32]0.1405a [3.57]0.2089a [2.73]1.8555b [1.80]4.2805a [2.12]
Telecoms0.0537a [3.64]0.4602a [3.32]0.0397a [3.14]0.3429b [1.97]3.9582a [3.73]9.2347a [4.84]

Note(s): Model 1 is the Historical Average model; Model 2 is the model without control; Model 3 is the model with control. The Clark and West test measures the significance of the difference the forecast errors of two competing models. The null hypothesis of a zero coefficient is rejected if this statistic is greater than +1.282 (for a one sided 0.10 test), +1.645 (for a one sided 0.05 test) and +2.00 for 0.01 test (for a one sided 0.01 test) (see Clark and West, 2007). Values in square brackets – [] are for t-statistics. a, b and c indicate statistical significance at 1%, 5 and 10% levels respectively. #Due to the data scope for COVID, we use 10 and 20 days for out-of-sample forecast evaluation

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