Antonio Díaz

Estimating Corporate Yield Curves

Tests of arbitrage-free pricing models show that we can expect less reliable corporate yield curve estimates than Treasury yield curve estimates. An examination of the structure of errors produced by common statistical yield curve models indicates that even with careful data selection, significant liquidity and tax-induced errors remain. It is a welcome result that the extent of the errors due to liquidity and tax effects is modest. Moreover, pooling bonds by broad rating category produces no significant deterioration in yield curve estimates.

An Empirical Study of Credit Default Swaps

This is an examination of the pricing of credit default swaps that traded around the dates of the Asian currency crisis using two different credit risk models. The cost of default insurance is generally found to be lower than the expected value of payments in the event of default. According to both models, the cost of default insurance is greater than the expected value of payments for credit default swaps written on entities domiciled in countries subject to the Asian currency crisis, a finding attributable to moral hazard.

Term structure of volatilities and yield curve estimation methodology

In this paper, we estimate the term structure of interest rate volatilities. It is well known that volatility is the main input for option and other fixed income derivatives valuation models. However, we find that volatility estimates depend significantly on the model used to estimate the zero coupon yield curve (Nelson and Siegel; Vasicek and Fong) and the assumption concerning the heteroskedasticity structure of errors (OLS or GLS weighted by duration). We conclude in our empirical analysis that there are significant differences between these volatility estimates in the short term (less than one year) and in the long term (more than 10 years).

Continuous Assessment in Large Groups: A Proposal

Meeting new demands for implementing a continuous assessment system in the classroom is not an easy task, especially when using only the existing resources and working with the same large student groups and the same staff. In our course, students themselves carry out the grading and recording process. Course evaluation results indicate that the continuous assessment system has a significant positive effect on exam scores. However, this correlation is not significant in male student samples. The larger the group, the weaker the learning effectiveness of the continuous assessment in terms of scores on the final exam. The results of a voluntary and anonymous survey conducted among our students at the end of two consecutive courses revealed that the continuous assessment method was well accepted.

Estimating the volatility term structure

In this paper, we proceed to estimate term structure of interest rate volatilities, finding that these estimates depend significantly on the model used to estimate the term structure (Nelson and Siegel or Vasicek and Fong) and the heteroscedasticity structure of errors (OLS or GLS weighted by duration). We conclude in our empirical analysis that there are significant differences between these volatilities in the short (less than one year) and long term (more than ten years). Finally, we can detect that three principal components explain 90% of the changes in volatility term structure. These components are related to level, slope and curvature.

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.

What If Two Different Interest Rates Datasets Allow for Describing the Same Financial Product

The chance to choose among more than one dataset for representing and describing the movements in the financial market of the same financial entity has noteworthy effects on the practical quantifications. The case we consider in the paper concerns two datasets, different and deemed to be equivalent between them, referred to risk free interest rates. In light of the volatility term structure discrepancies between the two databases and of some closed formulas for stochastically describing the behavior of the financial valuation discrepancies by means of the Vasicek interest rate process, we show two relevant practical evidences. The application concerns the pricing of two derivative cases. The aim is to quantify how much the use of one dataset rather than the other impacts on the final result.

The Influence of Dynamic Risk Aversion in the Optimal Portfolio Context

Despite the influence of risk aversion in the optimal portfolio context, there are not many studies which have explicitly estimated the risk aversion parameter. Instead of that, researchers almost always choose random fixed values to reflect the common levels of risk aversion. However, the above could generate optimal portfolios, which do not reflect the actual investor’s attitude towards risk. Otherwise, as it is well known, an individual is more or less risk averse according to the economic and political circumstances. Given the above, we model the risk aversion attitude so that it changes over time, in order to take into account the variability in agents’ expectations. Therefore, the aim of this paper is to shed light on the choice of the risk aversion parameter that correctly represents the investors’ behaviour. For that purpose, we build optimal portfolios for different types of investment profiles in order to compare whether it is better to use a constant risk aversion parameter or a dynamic one. In particular, our proposal is based on estimating the time-varying risk aversion parameter as a derivation of the market risk premium. For that purpose, we implement several statistical univariate and multivariate models. Specifically, we use conditional variance and correlation models, such as GARCH (1, 1), GARCH-M (1, 1) and DCC-GARCH.

Socially Responsible Investment, Should You Bother?

Companies included on a sustainability index meet several criteria based on an assessment of their economic, environmental and social practices. Each of these companies satisfies a different number of criteria and these standards can be quite different in quality and rigor. In this sense, RobecoSAM provides a Corporate Sustainability Assessment of the companies included in the Dow Jones Sustainable Index. The three proposed classes (Gold, Silver and Bronze) can be considered as social responsible (SR) ratings. Therefore, we examine the financial performance of portfolios composed of stocks according to these ratings. We assume that highly conscious SR investors could base their portfolio decision-making process on these SR ratings. From an extensive dataset, our results show that SR investments not only have no cost for investors but also outperform the market. Additionally, there are no significant differences among SR portfolios depending on the SR rating.