Structured

Former Lehman researchers team up on arb-free cash CLO model

Friday, May 7, 2010

Two quants who worked together at Lehman Brothers immediately prior to its collapse have published what they believe is the first top-down, risk-neutral model for pricing cashflow CLOs. Yadong Li and Ziyu Zheng’s paper – see A Top-Down Model for Cash CLOs – is based in large part on work they carried out at Lehman Brothers, which was the biggest arranger of loan-backed CSOs such as the Exum Ridge deal, and which was keen to find ways to compare prices of these synthetic tranches with tranches of traditional cashflow deals.

The model makes no attempt to derive a CLO tranche valuation from the price of individual loans since, as the authors point out, there is no strong arbitrage relationship between the price of the underlying assets and those of the CLO tranches.

Instead, it takes an approach somewhat similar to CSO pricing models. However, instead of using a credit derivative index such as CDX as an input, the analysts suggest deriving prices from a hypothetical, liquid “index CLO”. They suggest that dealers work together to come up with a set of several standard market scenarios, and use them to price a handful of index CLOs. These prices can then be used as the basis for pricing all other CLOs.

Li remains in a similar role at Barclays Capital in New York, while Zheng is head of model risk research at Morgan Stanley.


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Comment by: Nalin Aeron. Posted 1 year ago

I liked the paper too... its good for triangulating the market .. however i think CLOs with good SF bucket will have a higher valuation for BB and Equity tranches using this model.. one way to counter this to to find a solution using a similar deal as IDX. One thing which is not clear to me that I have to create separate CLO IDX for different vintages. Also MM deal will also look better with this deal. So need to adjust model accordingly. But overall good approach.

Comment by: Anonymous. Posted 1 year ago

Having just read this Li-Zheng paper, I commend the authors. The approach is creative and well presented and provides a good discussion of how the market now prices CLO tranches. Interestingly, there's no need for the user to specify a correlation assumption (or "guess") since such information is embedded in the prices of the index CLO. For me, it remains a strong disadvantage that the model does not "know" the underlying loans. A risk manager does want to see the impact of specific underlying loans and what their default means for the position. Consider, for example, that an investor may own many tranches of separate deals and needs to understand its aggregation of risk to distinct loans (such as First Data) within the deals.

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