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As we show in Chapter 6, a treasury desk faces no hedging needs: if it is a desk within a financial institution the risk remains within the firm; if it is the treasury of a development institution or a corporation, the risk is outsourced. In any case it does not remain with the treasury itself. Because of this it has specific risk and valuation issues which it is our intent to prepare the reader for.

Not surprisingly for a book centered around debt, credit will be the paramount issue and we shall strive to show how as an issue it appears almost everywhere. Its first appearance is in the realm of curve construction, the fundamental process by which we generate forward floating rates and calculate their present values. The pricing of financial instruments, swaps in particular, have been subject to profound changes due to the interpretation and perception of the credit risk involved: from the different risk incurred by financial institutions borrowing in different currencies, to the different credit risk inherent in rates of different maturities, to finally the different credit risk linked to the posting or not posting of collateral. The classical theory of swap pricing (see Duffie and Singleton [32]) considered the credit risk of a swap

to be the same as the interbank credit when in practice, due to collateral posting, it was the same as the overnight rate. These details appear small in a normal environment but assume great proportions in a turbulent market. Moreover, with the increasing disappearance of complex exotic structures and the focusing on vanilla ones, the small details will become even more important. Curve construction and in particular discounting plays an exact role in our discussion because, as we introduced previously, a treasury operation does not carry out hedging. A correct discounting of an instrument is essential to arrive at what constitutes the raison d'etre of a treasury operation, the funding level.

In a debt-raising operation the funding level is the measure of everything. After showing how this level is essentially an asset swap spread, we will position it at the center of our discussion. Our goal will be to place in the reader's hands an imaginary rope representing the funding level of some imaginary entity of which the reader is the treasurer. Once in possession of the rope, the reader will learn what makes this rope move, what in the financial world pulls at its extremities or shifts it. Bond pricing will be seen almost entirely in terms of discounting and, with the risk of confusing thereader, the issue will be stressed to the point of introducing a quantity representing the credit correction to the money market discount factor. This will be to show that this appendix to the risk-free discount factor is what moves, through the prism of the asset swap, the funding level on the other side. To remain with the image of the rope, we shall try to show how, while always representing credit risk, there are many, often parallel, curves that take different meanings. CDS spreads, yields, benchmarks, and the asset swap spread itself can be related to each other or differ by little, but they can also mean and imply different types of credit risks.

The understanding of the difference between the various representations of credit risk can only come from an understanding of credit as a modeling of default; because our focus is always the valuation of hnancial instruments in the context of trading, our modeling will be risk neutral and centered around the concept of credit default swaps. Although it might seem like a detour, an introduction to the basics of credit modeling is fundamental to understanding the relationship between the market data, the CDS spread, and the concept of survival probability. We have tried to present it in a way that makes the latter appear as a risky discount factor, the appendix to the riskless discount factor we mentioned previously.

Our goal is therefore to make the reader comfortable with the concept of credit risk and the idea of its representation as a spread. Once we do so, we can show what else can be seen to affect this spread from liquidity issues to leverage (Schwarz [75], Adrian and Shin [2], and Acharya and Pedersen [1]). It is partly with this intent that we touch upon emerging markets, markets that in their simplicity allow us to identify with ease individual factors. A simple example would be the bid-offer spreads: large or small spreads appear in every market; however, in developed markets many factors can drive their size. In emerging markets one can, most of the time, see a simple correlation between maturity, credit standing of the country and/or region, and bid- offer spread size–the mark of liquidity. We can simply offer an introduction without straying too much from our path: hopefully with it the reader can continue in the discovery of this fascinating topic.

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