Pilar Abad

Credit Rating Announcements, Trading Activity and Yield Spreads: The Spanish Evidence

We test whether different rating announcements contain pricing-relevant information and modify trading activity patterns in the Spanish corporate debt markets. We observe a significant widening of yield spreads in short- and long-term corporate debt after reviews of downgrades and negative outlook reports. Additionally, certain rating announcements encourage trading activity even when the information is not pricing-relevant. The release of information arouses investor interest for the involved securities. Thus, trading frequency increases, although larger-sized transactions, which should denote possible portfolio rebalancing, are not observed. In the short-term market, trading volumes are found to fade after reviews for downgrade.

ACCURATE OF VAR CALCULATED USING EMPIRICAL MODELS OF THE TERM STRUCTURE

This work compares the accuracy of different measures of Value at Risk (VaR) of fixed income portfolios calculated on the basis of different multi-factor empirical models of the term structure of interest rates (TSIR). There are three models included in the comparison: (1) regression models, (2) principal component models, and (3) parametric models. In addition, the cartography system used by Riskmetrics is included. Since calculation of a VaR estimate with any of these models requires the use of a volatility measurement, this work uses three types of measurements: exponential moving averages, equal weight moving averages, and GARCH models. Consequently, the comparison of the accuracy of VaR estimates has two dimensions: the multi-factor model and the volatility measurement. With respect to multi-factor models, the presented evidence indicates that the Riskmetrics model or cartography system is the most accurate model when VaR estimates are calculated at a 5% confidence level. On the contrary, at a 1% confidence level, the parametric model (Nelson and Siegel model) is the one that yields more accurate VaR estimates. With respect to the volatility measurements, the results indicate that, as a general rule, no measurement works systematically better than the rest. All the results obtained are independent of the time horizon for which VaR is calculated, i.e. either one or ten days.

Institutional Versus Retail Investors’ Behavior Around Credit Rating News

This paper investigates the impact of credit rating downgrades on the liquidity and trading behavior of both segments of trading in the U.S. corporate bond market: the institutional- and the retail-sized ones. Using the TRACE dataset, we test if both market segments behave different and what hypotheses explain this potential divergence. We test the regulatory constraints hypothesis (regulatory mandates may force institutional bondholders to sale downgraded bonds), the informed-uninformed traders’ hypothesis (information could be responsible for different trading activity patterns before credit rating changes depending the segment of trading), and the usual information hypothesis. We obtain evidence of increased trading activity and price adjustments around downgrades for both segments. Rating-contingent regulation induces larger intensity responses in the institutional segment. Finally, we observe trading anticipation before downgrades that is consistent with the existence of informed institutional investors.

The Effect of Rating Contingent Guidelines and Regulation Around Credit Rating News

This paper investigates the effect of rating-based portfolio restrictions that many institutional investors face on the trading of their bond portfolios. Particularly, we explore how credit rating downgrades affect to bondholders that are subject to such rating-based constrains in the US corporate bond market. We go beyond the well-documented investment grade (IG) threshold by analyzing downgrades crossing boundaries usually used in investment policy guidelines. We state that the informativeness of rating downgrades will be different according to whether they imply crossing investment-policy thresholds or not. We analyze corporate bond data from the TRACE dataset to test our main hypothesis and find a clear response around the announcement date consistent with portfolio adjustments made by institutions in their fulfillment of investment requirements for riskier assets.

The Effects of Credit Rating Announcements on Bond Liquidity: An Event Study

This paper investigates liquidity shocks on the US corporate bond market around credit rating change announcements. These shocks may be induced by the information content of the announcement itself, and abnormal trading activity can be triggered by the release of information after any upgrade or downgrade. Our findings show that: (1) the market anticipates rating changes, since trends liquidity proxies prelude the event, and additionally, large volume transactions are detected the day before the downgrade; (2) the concrete materialization of the announcement is not fully anticipated, since we only observe price overreaction immediately after downgrades; (3) a clear asymmetric reaction to positive and negative rating events is observed; (4) different agency-specific and rating-specific features are able to explain liquidity behavior around rating events; (5) financial distress periods exacerbate liquidity responses derived from downgrades and upgrades.