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9

Fitch should be available right here: Sovereign Ratings History With Moody's it's not so easy, I don't know if there's a complete source available free of charge. But Sovereign Default and Recovery Rates, 1983-2007 has some data in the appendix III, though not so up to date and in a not that convenient format. Same goes about S&P, Sovereign Ratings ...


5

S&P credit rating change information until 2012 (European Union only): http://www.standardandpoors.com/ratings/articles/en/us/?articleType=HTML&assetID=1245327302187


5

You cannot do it. It is an under-determined problem. That is to say, a whole multitude (subspace of $\mathbb{R}^{N\times N}$) of migration matrices will agree with any given table of default probabilities. Say you want to find a transition matrix for 2 states (IG, HY) plus default $$\left(\begin{matrix} p_{11} & p_{12} & p_{1D} \\ p_{21} ...


4

Actually, there is a practical way to do it. You can use you PoD estimates to assign a credit rating to your securities and then use a published transition matrix for your purposes. Or you can estimate transition probabilities by linear interpolation based on the PoD values that you have. Here is a publication containing transition matrices from ...


4

(P) prefix : As a service to the market and typically at the request of an issuer, Moody's will assign a provisional rating when it is highly likely that the rating will become final after all documents are received, or an obligation is issued into the market. A provisional rating is denoted by placing a (P) in front of the rating. Such ratings may also be ...


3

Yes, you can have two different ratings. The issuer has one credit rating, but the individual issues, even if they are both senior unsecured/secured with the same maturity, coupon, etc. can have different ratings. The key factor is going to be the structure/provisions of the issue itself. For example, an issue with a sinking fund is going to be viewed as ...


3

This is an interesting question. I'll make a guess on what may be the driving factors for "ratings inflation" based on these assumptions: Rating agencies compete among themselves to conduct bond rating business with issuers, since they are paid for their services by the issuer. Bond issuers choose the agency that promises the highest rating, since the ...


3

If the transition matrix has distinct eigenvalues, you can diagonalize it and then take the cube root of the diagonal. E.g., you can compute the SVD, verify that the eigenvalues are distinct, take the cube root of the diagonal matrix, then re-multiply it together.


3

You are right, the rules to time-scale a T-years transition matrix $M_T$ are: $M_{k·T} = M_T^k$ $M_{T/k} = \sqrt[k]{M_T}$ The root of a matrix M can be obtained using the spectral decomposition: $M = P·D·P^{-1} \Longrightarrow M^k = P·D^k·P^{-1}$ where $P$ and $D$ are the eigenvectors and eigenvalue matrices of $M_T$. Note: The Perron-Frobenius tells ...


2

Depending upon how much data you have, you might find Violi (2004) useful. Nickell et al. (2000), while principally considering time-dependent stability tests, refers a bit to significance testing between the matrices of different agencies and might also provide some insight.


1

I would think it is because it can be bound between 2 points it can assume wide range shapes It fits the data empirically (as you said) On a related note Sometime back I read a paper which might give you more formal reason. It is for estimating and simulating recovery rates . I havnt used it to model credit migration probabilities . But I think one ...


1

I believe that your problem can be formulated as: Find PD matrix that is as close as possible to a given PD matrix (result of some previous calibration, or the matrix computed using average hazard rate, or any other "target", or the penalty on non-smoothness) subject to the following constraints: The values that are given must be matched exactly ...


1

The typical approach is to try to fit a ratings migration matrix to available rating transition data. If default rates are all you have then that's going to be difficult. Instead, I might try to fit a separate reduced form credit model on survival probability $P_\ell$ for each rating $\ell$ by fitting the function $$ P_\ell(T) = \exp\left( -\int_0^T h(t) ...


1

Bloomberg terminal page: CSDR (="Sovereign Debt Ratings")


1

SD is selective default http://www.reuters.com/article/2013/06/28/us-cyprus-downgrade-standardandpoors-idUSBRE95R0YQ20130628 +u is unsolicited rating http://lexicon.ft.com/Term?term=unsolicited-rating



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