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192<br />

the <strong>in</strong>vertibility condition holds. The proposed modified test procedure works as<br />

follows:<br />

i) Construct u u i as the probability that Yi is less than the actually observed price<br />

change yi:<br />

u u i<br />

bPr½YiyijF i 1; ZiŠ<br />

¼ Xyi<br />

bPr½Yi¼jjF i 1; ZiŠ<br />

(4.1)<br />

j¼ 1<br />

for each i: 1→n, and construct u i l as the probability that Yi is less than the<br />

actually observed price change m<strong>in</strong>us one:<br />

u l i<br />

bPr½Yiyi1jF i 1; ZiŠ<br />

¼ Xyi 1<br />

bPr½Yi¼jjF i 1; ZiŠ:<br />

(4.2)<br />

j¼ 1<br />

ii) Then use this sequence <strong>of</strong> probabilities to generate a sequence <strong>of</strong> artificial<br />

random numbers from the conditional uniform distributions on the <strong>in</strong>tervals<br />

[ui l , u i u ], i.e.,<br />

ui U u l i ; uu i ; i : 1 ! n: (4.3)<br />

If the model is correctly specified, the u i’s drawn under the true parameter<br />

values (to calculate u i l and ui u ) are i.i.d. follow<strong>in</strong>g a uniform distribution on the<br />

<strong>in</strong>terval [0,1] (see the Appendix). Moreover, one can map the u i’s <strong>in</strong>to a standard<br />

normal distribution us<strong>in</strong>g u i* ≡ Φ −1 (u i). Under the correct model, the normalized<br />

u i*’s are i.i.d. standard normal distributed.<br />

JBX HAL<br />

R. Liesenfeld et al.<br />

Fig. 10 Autocorrelation function <strong>of</strong> the density forecast variable ui* for Jack <strong>in</strong> the Box Inc. (JBX)<br />

and HalliburtonpCompany ffiffi (HAL). The dashed l<strong>in</strong>es mark <strong>of</strong>f the approximate 99% confidence<br />

<strong>in</strong>terval 2:58 n

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