*3.2.2 The effect on the cumulative days (*�*1,0)*

We also examine the effect of the changes in VIX on the CARs over days �1 and 0. **Table 7** presents the results. Panel A is for the NYSE and Panel B is for the NASDAQ. Cumulative ΔVIX represents the contemporaneous cumulative changes in VIX over days �1 and 0. Our results for the NYSE are consistent with those of Kliger and Kudryavtsev [16].<sup>12</sup> For upgrades, the statistically significant *negative* difference indicates that the CARs are stronger when the cumulative change in VIX is *negative* (i.e., Cumulative ΔVIX<0) than that when the cumulative change in VIX is *positive* (i.e., Cumulative ΔVIX>0). However, for downgrades, the statistically significant *negative* difference suggests that the CARs are stronger when the cumulative change in VIX is *positive* (i.e., Cumulative ΔVIX> 0) than that when the cumulative change in VIX is *negative* (i.e., Cumulative ΔVIX<0).

<sup>12</sup> Kliger and Kudryavtsev [16] do not test stocks listed on the NASDAQ.


#### **Table 7.**

*The effect of changes in VIX on the cumulative abnormal returns (CARs) for the NYSE (Panel A) and the NASDAQ (Panel B).*

In comparison with the NYSE, we show that the corresponding magnitudes of the CARs are larger for the NASDAQ. It is in line with the argument that the telecoms industry is more sensitive to changes in investor sentiment. In short, these findings provide further evidence supporting the hypothesis stating that abnormal returns around recommendation revisions are correlated with contemporaneous changes in VIX [16].

Overall, our results of SKEW and VIX show that SKEW and VIX can act as different measures for investor sentiment in the financial markets. That is, SKEW measures investors' greed while VIX is an investors' fear gauge.
