@techreport{eprints2781,
          author = {Michele Bonollo and Irene Crimaldi and Andrea Flori and Laura Gianfagna and Fabio Pammolli},
            year = {2015},
           title = {Assessing financial distress dependencies in OTC markets:
a new approach by Trade Repositories data},
            note = {This paper is a preliminary version of the article published in Financial Markets and Portfolio Management, 2016(4)},
     institution = {IMT Institute for Advanced Studies Lucca},
            type = {EIC working paper series},
           month = {October},
       publisher = {IMT Institute for Advanced Studies Lucca},
             url = {http://eprints.imtlucca.it/2781/},
        keywords = {Keywords: Financial distress interdependence, Joint probability of distress, Interest rate
swap, Systemic risk, Trade repositories. 
Jel codes: G01, G18, G19},
        abstract = {After the recent financial crisis, it is undoubtedly recognized the importance of assessing
not only the risk of distress for a single {$\backslash$}financial entity", but also the distress dependencies
between the different {$\backslash$}entities", where by {$\backslash$}entities" we mean in a broad sense any relevant
cluster of products, risk factors, counterparties. In this paper, we focus on the Interest Rate
Swap (IRS) segment as a significant fraction of the OTC market. We define a distress indicator
by combining some distress drivers, such as averaged volumes, liquidity, volatility and
bid-ask proxies. Hence, we analyse the distress dependencies among sub-markets identified
by the segmentation of the IRS market according to contractual and financial features. We
try to combine in an innovative way some new ingredients, namely the more granular data
on OTC derivatives available from the trade repositories along with the classical JPoD approach
introduced in the recent years by the IMF for studying the distress interdependence
structure among financial institutions. The proposed technique seems to be quite promising.
Indeed, the results are quite close to the practical intuition. At the best of our knowledge,
this work is the first empirical study based on trade repositories' data for assessing systemic
risk.}
}