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An Introduction to Derivative Securities, Financial Markets, and Risk ManagementAdvanced Financial Risk Management, 2nd ed.

 Blog Entries

Kamakura Corporation Named to World Finance 100

August 26, 2014
Transfer Pricing and Valuation Yield Curves without Swap Data: A KeyBank and KeyCorp Example

August 18, 2014
More Evidence on the Funding “Subsidy” of the Too Big to Fail Banks

August 14, 2014
Mortgage Servicing Rights Values Close Mixed for the Week as Current and Forward Mortgage Rates Drop 0.03%

August 13, 2014
Liquidity At Risk – A stochastic look at cashflows

August 12, 2014
Five of Seven Regional Banks Trade at Credit Spreads Better than the Too Big to Fail Banks

August 12, 2014
Kinder Morgan Energy Partners Leads the 20 Best Value Bond Trades with Maturities of 10 Years or More

August 11, 2014
Measuring the Funding Costs of the Too Big to Fail Banks:
The U.S. Dollar Cost of Funds Index™


August 8, 2014
Forward 1 Month T-Bill Rates Plunge 0.26% in 2 Years but Forward 10 Year U.S. Treasury Yield Drops Only 0.04% from Last Week

August 6, 2014
Credit Spreads and Default Probabilities: A Simple Model Validation Example

August 5, 2014
Vodafone Group PLC: Default Risk is Down Sharply But Value Ranks in the Bottom 10% of Bonds

July 30, 2014
American International Group Inc. Bonds:
A Reward to Risk Ratio Twice as High as the Median Bond Issue


July 29,2014
AT&T Inc. Bonds: Ten Times the Risk of IBM and Below Average Value

July 15, 2014
Brazil, Italy, Spain, Credit Default Swaps and the
European Commission Short Sale Ban, 2010-2014


July 14, 2014
Bank of America and MBIA Lead U.S. Bank Credit Default Swap Trading Volume, 2010-2014

March 19, 2014
Stress Testing and Interest Rate Risk Models: A Multi-Factor Stress Testing Example

March 13, 2014
Stress Testing: A Credit Spread Ranking of 12 U.S. and 12 International Banks

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This quote has been added to our May 22, 2009 "Great Quotations" blog entry, but it hits so close to home we repeat it here.

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In part 10 of this series on yield curve smoothing, we included the maximum smoothness forward rate approach in our comparison of 23 different smoothing techniques, both in terms of smoothness and “tension” or length of the resulting forward and yield curves.  In each of our worked examples, we showed how to derive unique forward rate curves and yield curves based on the same set of sample data.  This sample data assumed that we had observable zero coupon yields or zero coupon bond prices to use as inputs.  At most maturities, this will not be the case and the only observable inputs will be coupon-bearing bond prices.  In this post, we show how to use coupon-bearing bond prices to derive maximum smoothness forward rates and yields.  The same approach can be applied to the 22 other smoothing techniques summarized in Part 10 of this series.

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Over the three day Martin Luther King holiday in the USA, another event took place in Santiago that brought a smile to my face.  This blog is an appreciation of one of my favorite people, Sebastián Piñera, newly elected President of Chile.

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In the first 10 installments of this series on yield curve smoothing, we committed the most common sin there is in the yield curve smoothing literature.  We used one set of “made up” data instead of hundreds or thousands of real data points to judge the performance of yield curve smoothing techniques.  In this blog, we explain why the test proposed by David Shimko is essential to judging the accuracy and realism of yield curve smoothing techniques.  We dust off some old yield data from the attic to illustrate how the test works.

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After riding up Mauna Kea volcano yesterday, Lance Armstrong is getting ready to travel from the Big Island of Hawaii to Adelaide for the Tour Down Under and the start of the 2010 cycling season.  Thanks to a blog that I stumbled on over the holidays, it seems like a good time to appreciate the risk management lessons from Lance over the years.  That’s the subject of today’s post.

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