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Quantitative Analysis
Parallel Processing
Numerical Analysis
C++ Multithreading
Python for Excel
Python Utilities
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I. Basic math.
II. Pricing and Hedging.
1. Basics of derivative pricing I.
2. Change of numeraire.
3. Basics of derivative pricing II.
4. Market model.
5. Currency Exchange.
6. Credit risk.
A. Delta hedging in situation of predictable jump I.
B. Delta hedging in situation of predictable jump II.
C. Backward Kolmogorov's equation for jump diffusion.
D. Risk neutral valuation in predictable jump size situation.
E. Examples of credit derivative pricing.
a. Credit Default Swap.
b. At-the-money CDS coupon.
c. Option on CDS.
d. Basket Credit derivative.
F. Credit correlation.
G. Valuation of CDO tranches.
7. Incomplete markets.
III. Explicit techniques.
IV. Data Analysis.
V. Implementation tools.
VI. Basic Math II.
VII. Implementation tools II.
VIII. Bibliography
Notation. Index. Contents.

At-the-money CDS coupon.

et MATH be a fixed CDS coupon schedule. It makes sense to introduce a coupon $c_{t}$ that sets market value of a CDS to zero given market conditions at time moment $t$ . The $c_{t}$ is a stochastic process.

Based on the relationship MATH we obtain MATH The expression in the numerator is a price of combination of risky annuities. We can use it as a numeraire as long as there is no default. Hence, there exists a probability measure such that the $c_{t}$ is a martingale.

We represent the price of the CDS using the quantity $c_{t}$ : MATH Hence, we replace a non-observable quantity $R_{k}$ with the directly quoted quantity $c_{t}$ .

We introduce the notation

MATH (Risky annuity)
and write the last result as MATH

Notation. Index. Contents.

Copyright 2007