Understanding Mortgage-backed Securities
by Michiel Bertsch
A research project on the mathematical modeling of fixed income
markets has recently begun at the CNR institute for applied mathematics
in Rome (Istituto per le Applicazioni del Calcolo – IAC-CNR).
The aim is to combine ‘real world problems’ with high quality
research in mathematical finance, in order to obtain a better
and more efficient understanding of the correct pricing of complicated
fixed income products such as mortgage-backed securities. The
project is intrinsically interdisciplinary, and uses techniques
varying from the statistical analysis of financial data to the
development of basic models and their numerical simulation.
IAC has started a project on financial mathematics in collaboration
with INA SIM S.P.A. (INA is a major insurance company in Italy).
The aim of the project is both to study existing mathematical
and statistical models for the correct pricing of fixed income
financial products, and to develop new ones. In the early stage
we focus on one hand on the analysis of the relevant statistical
data and, on the other, on the study of existing advanced models
in the academic literature. In a second stage, these two activities
are intended to ‘meet’ in order to develop accurate models for
the pricing of complicated financial products and their numerical
implementation.
A particular example of such products are the so-called mortgage-backed
securities (MBS’s). Roughly speaking, the US fixed income market
is divided in three areas: treasury bills, corporate bonds and
MBS’s, but nowadays the latter area is the bigger one. MBS’s are
liquid and they are securitized for default risk. Their only disadvantage
is the prepayment risk, and it is exactly this point which makes
MBS’s difficult to price and creates a challenge to financial
modelers. Someone with a mortgage usually does not optimize the
moment at which he exercises the prepayment option of the mortgage,
and even pooling several mortgages together does not average out
this effect. In the academic literature only very few advanced
pricing models have been proposed; however, after more than 30
years of experience, the US market is a source of considerable
data. This means that the necessary ingredients are present to
improve the methods of quantitative analysis of MBS’s. In this
context, we observe that quantitative analysis becomes a particularly
powerful tool in the case of new emerging markets, in which even
aggressive traders may lack the necessary experience to be as
efficient as usual. In the future, in the new European context,
MBS’s could very well form such an emerging market.
A closing remark regards the dramatic problem of the almost complete
absence of good research in applied mathematics in Italian industry.
The project on MBS’s is attracting first rate students and postdocs.
Some of them will become academic researchers, but I am convinced
that others will find a job in Italian financial institutes. Having
researchers with a PhD degree in mathematics in strategic positions
in private companies would be an important step towards further
high-quality collaboration with Italian industry.
Please contact:
Michiel Bertsch - University of Rome ‘Tor Vergata’ and CNR-IAC
Tel: +39 06 440 2627
E-mail: bertsch@iac.rm.cnr.it
