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

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“You’re not going to believe this,” my friend’s note said.  “Check out this annual report and look how one of the largest banks in the world is reporting its interest rate risk.”  He was right. I took a look at this large and prestigious bank’s interest rate risk reporting and I was immediately transported back to the disco era, 1977.  This post turns the clock back 30 years and explains how using net income simulation, with no market valuation-based risk analysis, destroyed the savings and loan industry and cost the U.S. taxpayers $1 trillion the first time.  We also explain how a bank, which we call Bank X, traveled so far back in time.

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For many years, “operational risk” was an area of risk management of great interest but lacking in a theoretical and conceptual framework that would place operational risk in the context of an integrated approach to enterprise wide risk management.  Indeed, to many, “operational risk” was a table of losses for specific events and not much else.  This is the operational risk equivalent of credit risk modeling with loss given default statistics but no default probabilities.

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One of the few virtues of being an aged (or more politely, “experienced”) risk manager is that one has made a lot of analytical mistakes that are easy to remember. Another virtue is that you have seen others make mistakes that proved fatal or near fatal, so we can remember the consequences of those errors too. In risk management, it would be nice if we never repeated the mistakes of the past, but, alas, we take two steps forward and one step backward. In this series, we discuss risk management errors by some of the world’s largest financial institutions and point out their consequences to help all of us avoid errors of the past and obvious errors going forward. In this post, we point out the consequences of basing risk assessment on a pseudo monte carlo approach instead of the real thing.

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Traditional asset and liability management (ALM) has ignored mortgage defaults and focused on interest rate-driven and mortgage age-driven prepayment. The events of the last two years have made it more obvious that prepayment and default are intimately linked and that home prices are a critical driver of both probabilities. This post explains how mortgage prepayment and default are modeled on an integrated basis using multinomial logit.

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One of the most frequently asked questions posed by clients is this: How did Kamakura choose Honolulu for its head office location? This post explains.

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