Abstract
The Italian Minibond market was born in 2013 and was expected to ease debt financing of SMEs as a complementary channel to bank credit. In this chapter, we investigate what were the determinants of the issuing prices of Minibonds in the ExtraMotPro market from 2013 to 2016, with a special focus on small listings by non-financial issuers and on default risk. We find evidence that the rating of Minibond issuers by credit rating agencies did not help investors reduce information asymmetries about their creditworthiness.
Minibonds had credit-risk premia similar to speculative grades’ and higher than those of non-rated issues. We evaluate the credit standing of issuers through a statistical and a financial approach. In both cases, we find that issuers rated as investment grade by agencies are generally riskier than those rated speculative grade. Furthermore, the premia related to our credit-risk assessment are higher for riskier firms than for safer firms. However, we also find evidence that safer borrowers might have signaled their quality to investors through underpricing. Our evidence calls for interventions aimed at improving the information efficiency of the Italian Minibond market.
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- 1.
Laws 34-2012 and 212-2012, later augmented and amended by Laws 9-2014, 116-2014 and 232-2016.
- 2.
Beyond these, starting from 2017, retail investors in personal long-term savings plans (‘Piani di Individuali di Risparmio’) have some fiscal incentives if they hold at least 70 percent of the plan’s asset value in securities issued by companies with stable operating activities in Italy.
- 3.
Minibond issuers were 86 in 2014, 54 in 2015 and 88 in 2016.
- 4.
We owe this information to KF Economics Srl (http://kfeconomics.com/wordpress/). From 2013 to 2016, the failure rate of Italian SMEs was 1.7 percent and 1.1 percent for larger companies.
- 5.
We gratefully acknowledge KF Economics Srl for granting us access to this database.
- 6.
This is a good working approximation in half of the cases, which had maturities below 12 months, but we admit it can be loose for the rest, which will reach maturity after March 2019, as long as investors might have expected money market rates to rise from that date onward. However, these potentially problematic cases are just two out of 127.
- 7.
Key maturities range from 6 months to 10 years and are equally spaced at 6-month intervals. We collected the quarterly time series of 19 par yields from 1st January 2013 to 1st January 2017.
- 8.
Take heed of the fact that, over the 2013 to 2016 period, the par-yield curve of Italian Govies was basically and constantly upward sloping.
- 9.
Italian government bonds (bills) were not really free of default risk over the 2013 to 2016 period, but were definitely less so than small Italian Minibonds issues such as those in our sample.
- 10.
In one case, a Minibond was proposed to investors as bullet, but then was issued as amortizing, a fact that is controlled for explicitly.
- 11.
Before proceeding to 2SLS estimation, we run OLS on the reduced form equations associated with our system. As there are nine exogenous variables in each equation that are significant at least at the 5 percent size of t-tests, the system meets the rank condition for identification. We also checked the endogeneity of ‘Yield’ and ‘log(face value of issue)’ with the Durbin-Wu-Hausman test (Davidson and MacKinnon 1993), and did not reject it at the 10 percent level for both variables.
- 12.
The reader can argue that, in our estimated system, the importance of the rating variables is somewhat reduced exactly because of the presence of these indices. We claim that this is not the case for two reasons: first, there is no relevant difference in the distributions of both indices by rating grade in our sample; second, when we removed both indices from the demand equation, the coefficients on the rating variable did not change much and did not become statistically significant. Details about this are available from the authors upon request.
- 13.
Companies were randomly drawn from a comprehensive database of about 1.2 million cases of Italian companies, solvent and insolvent, observed from 2013 to 2016. We gratefully acknowledge KF Economics Srl for granting us access to these data (see Footnote 3).
- 14.
De Socio and Michelangeli (2015) suggest that a score above 50 signals financial vulnerability. This makes the Vulnerability Score somewhat comparable to our Insolvency Score, since the latter can be interpreted as the probability of insolvency of company drawn from a pool where the average insolvency rate is 50 percent.
- 15.
In plain words, the distributions that we examine are those of the residuals of Minibonds’ yield spreads regressed against all variables that describe the bonds’ contractual features.
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Grasso, A.G., Pattarin, F. (2019). Risk and Pricing on the Italian Minibond Market. In: Gualandri, E., Venturelli, V., Sclip, A. (eds) Frontier Topics in Banking. Palgrave Macmillan Studies in Banking and Financial Institutions. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-030-16295-5_2
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