My analysis assumes that rating changes across the investment-grade boundary relate to changes in the co-movement of fundamental characteristics of investment-grade and high-yield issuers. If this is not the case, it is unsurprising that we do not observe changes in co-movement following index exclusions that result from rating changes. We then require an alternative explanation as to why, irrespective of rating changes, we observe increases in betas following CDX.HY inclusions. It is possible thin-trading may play a role. The CDX indices represent issuers who have an eligible credit rating and the most liquid CDS spreads. If, upon inclusion, an issuer’s CDS spread is more frequently traded and incorporates market-wide news more rapidly, this may suggest some downward bias in our pre- inclusion betas. To test this alternative explanation, I adopt a test similar to the one suggested by Vijh (1994) and Barberis et al. (2005). I first calculate daily percentage bid- ask spreads during the same 120-day pre- and post-event windows for all issuers included in the CDX.IG or CDX.HY. I then split the samples by issuers who became more or less liquid following their inclusion according to decreases or increases in six month average daily percentage bid-ask spread. If my results are driven by thin-trading, we should expect to see issuers whose bid-ask
spreads decreased upon inclusion to exhibit increases in beta and issuers whose bid-ask spread increases to exhibit decreases in beta. The results are presented in Table 3.9.
Table 3.9: Univariate regressions of issuers’ daily CDS returns on CDX.IG and CDX.HY returns condi- tioned on liquidity changes. ∆BAis the cross-sectional mean change in average daily percentage bid-ask
spreads between the pre- and post-event windows.BA1is the cross-sectional mean of average daily percent-
age bid-ask spreads in the pre-event window. ∆BAi<0 (%) is the percentage of average bid-ask spread
changes in the cross-section that are negative. ∆β is the cross-sectional mean change in loading on the
relevant index factor between the pre- and post-event windows. β1 is the cross-sectional mean beta in the
pre-event window. ∆βi>0 (%)is the percentage of beta changes in the cross-section that are positive.
t-stat gives the results of the cross-sectional t-test and p-value is ascribed by the Wilcoxon signed-rank test. Significance at 1% is denoted by (∗ ∗ ∗), 5% (∗∗) and 10% (∗). n is the sample size.
CDX.IG Inclusions CDX.HY Inclusions Full Sample Full Sample
∆BA -0.02 0.00
BA1 0.09 0.05
∆BAi<0 (%) 77.3 58.5
n 66 53
More Liquid Less Liquid More Liquid Less Liquid
∆β 0.15 0.08 0.03 0.34
β1 0.47 0.55 0.48 0.44
t-stat 2.82∗∗∗ 1.32 0.55 4.60∗∗∗ p-value 0.01∗∗∗ 0.21 0.62 0.00∗∗∗
n 51 15 31 22
We observe that the CDS spread of the average issuer included in the CDX.IG becomes more liquid; 77% of issuers experience decreases in their six month average daily percentage bid-ask spreads. The observed decrease is on average approximately 2%, from 8% to 6%. Pre-inclusion betas are lower for issuers that became more liquid but mean beta changes are positive in both sub-samples. However, the beta changes are only statistically significant for the issuers which became more liquid and both tests assign significance at the 1% level for this sub-sample. Thin- trading does appear to play a role in beta increases following CDX.IG inclusions. By contrast, the average issuer included in the CDX.HY does not experience a change in liquidity. 58% experienced decreases in their bid-ask spreads but the average bid-ask spread is unchanged at 5.5% before and after inclusion. Whilst beta changes are positive in both sub-samples, they are only statistically
significant for issuers which became less liquid. Both tests assign significance at the 1% level for this sub-sample. Hence thin-trading does not explain beta increases following CDX.HY inclusions. In sum, CDX.HY inclusions result in increases in co-movement that cannot be explained be either rating or liquidity changes. Under the fundamentals hypothesis, if indexed high-yield issuers exhibit some unobserved fundamental characteristic, unrelated to credit ratings, this could poten- tially explain the inclusion results. However, given the findings of this chapter as well Chapter 2, this source of commonality would have to outweigh commonality in fundamental characteristics already captured by industry affiliation and/or rating classification. This seems highly implausi- ble. Index exclusions do not result in decreases in co-movement, even though they are governed by observable characteristic changes, credit rating and corporate actions, which should relate to a change in the issuer’s fundamental characteristics. Yet Markit’s CDX indices allow style in- vestors to trade excluded issuers, which remain indexed with the majority of issuers included in the on-the-run index series, via previous off-the-run series. In this way, I interpret both results as being consistent with the excess co-movement hypothesis; issuers included in or excluded from the CDX.HY co-move by more than implied by changes in co-movement in their fundamentals. Due to data limitations, I are unable to draw strong conclusions with respect to the CDX.IG index. However, my results are generally supportive of excess co-movement amongst these issuers, just not to the same extent as that of CDX.HY issuers. It is of course possible and to some extent plausible that industry itself, as a classification, generates excess co-movement in spreads. This however, is beyond the scope of this thesis and is left as an interesting avenue for future research.
VII. Conclusion
In this chapter I have examined the effects of indexation on co-movement dynamics in the CDS market. The CDX.IG and CDX.HY indices, administered by Markit, were introduced in 2003 and represent the CDS spreads of the most liquid North American corporate issuers. They allow market participants to take aggregate exposure to diversified portfolios of credit risk and index membership is governed mainly by an issuer’s rating classification as either investment-grade or
high-yield. By exploiting the CDX eligibility rules, I have provided empirical evidence of excess co-movement in the CDS spreads of CDX indexed issuers. I have shown that issuers excluded from either the investment-grade or high-yield index do not change in co-movement with the index even though index exclusions result from observable characteristic changes that relate to changes in the issuer’s fundamental characteristics. Issuers included in these indices experience increases in co-movement. In the case of CDX.HY inclusions, I am able to identify increases in co-movement irrespective of the observable characteristic changes that govern them. Thus, increases in co- movement around index inclusions cannot simply be explained by changes in rating and therefore changes in fundamentals correlated with ratings.
Through Chapters 2 and 3 of this thesis I have documented several key empirical results that should be considered in conjunction with one another. Firstly, there exists strong common factors in high-yield rated issuers spreads’. These factors form a central feature of the correlation struc- ture of the CDS market. Building on this, I have shown that the CDX indexation process seems to, at least partially, explain why the high-yield factor arises. That is, an important driving force of the correlation dynamics of high-yield rated issuers, in particular, is their index assignment and the trading behaviour of market participants at the index level. In fact, these factors plays a more important role in the spreads of high-yield indexed issuers than industry common factors, where fundamentals-based explanations are more readily available; industry affiliates share common fun- damental characteristics. The sensitivity of issuers to factors pertaining to the high-yield index increase upon indexation regardless of the rating changes that govern the assignment. I conclude there is excess co-movement in CDS spreads, whereby they diverge from their fundamental value. They diverge to the extent that indexed high-yield issuers, from unrelated economic sectors, form a prevalent correlation cluster in the CDS market. Such evidence raises concerns about the overall efficiency of the CDS market. My body of evidence is the first to question this assertion.