Editor’s Letter

The “January Effect” is still in effect (S&P 500 +5.29% on the month), but where did all the volatility go? During the last three months of 2011, the standard deviation of the daily return on the S&P 500 Index was 1.68%. During January 2012, it was 0.49%. What happened? Did we somehow solve all of our economic problems at the turn of the year? How could I have missed that?

December in the U.S. ended with the Senate quickly leaving town for the rest of the year after tossing a small bomb to the House of Representatives, in the form of a vote to keep taxes on 160 million workers from going up on January 1 that a number of Republican Congressmen opposed but didn’t want to vote against. With Congress gone, a couple of weeks went by with no self-inflicted crises emanating from Washington. And even after they returned, Obama’s State of the Union address and the drama of the Republican Presidential primaries keptWashington distracted for the rest of the month, apparently to the relief of the financial markets.

Meanwhile, discussion continued in Europe, with much confidence expressed about the prospects for achieving an accepted and workable plan to resolve the euro crisis. With only a few dissenters (e.g., Britain) and with a few successful bond sales by the weaker countries (despite credit rating downgrades of nine Eurozone countries by Standard and Poor’s) and, notably, with no hard deadlines to be met during the month, the anxiety levels on both sides of the Atlantic have ticked down. What could possibly go wrong now?

Leaving that poignant question hanging, let us turn to this issue of The Journal of Derivatives. The recent financial crisis revealed serious problems in pricing collateralized debt instruments, such as subprime CMO tranches. But credit researchers have long known that market tranche prices are not consistent with theoretical values from the standard models, as shown by the existence and persistence of the “correlation skew.” In our lead article, Hamerle, Igl, and Plank explore the fact that the main focus in modeling default risk for a credit portfolio has been on the correlations, not so much on the market risk premia for the individual credits’ downside risk. They extract information on left tail risk from options on an obligor’s stock and show that treating the risk premium more carefully can substantially reduce the mispricing implied by the typical skew in tranche correlations. The next article looks at the market for single-stock futures at the Eurex. These futures contracts have only been allowed to trade in Europe and the U.S. in the last few years. Bialkowski and Jakubowski explore what factors are most important in explaining the relative success or lack of success for futures on a particular stock. Active trading and high volatility in the underlying increase futures activity, while greater institutional ownership reduces it. A larger sized contract hurts futures trading, but a larger tick size appears to help it. And the stock’s beta seems not to matter at all.

Mortgages have figured prominently in our recent market disruption, which has brought increased focus on one of the hardest major classes of securities to value. Prepayment risk has always been a problem with mortgages, since it depends not just on the level of the interest rate, but on its whole time path, which led to models that have to be solved by Monte Carlo simulation. Adding default risk too, for the increasing number of non-guaranteed mortgages, makes things much worse. Tsai and Chiang offer a different modeling approach that treats mortgage prepayment and default as Poisson jumps, the same way reducedform models for risky corporate bonds do. This allows closed-form valuation equations and a major increase in computational efficiency.

The next article looks at “charm.”No, it isn’t a piece about quarks in particle physic or a report on New York’s “Fashion Week.” Here charm refers to the partial derivative of an option’s delta with respect to the time to expiration. As Mastinsek shows, charm should not be ignored in delta hedging an option when it gets close to expiration. At a given stock price, delta changes rapidly in the last few days before expiration, and it pays to adjust the hedge ratio to account for the option’s charm.

Finally, in the last article, Chang, Chen, and Wu show how to substantially improve computational efficiency for the spread and basket option pricing model originally proposed by Borovkova, Permana, and Weide in the Summer 2007 issue of JOD.

As this is being written, I find myself in a period of watchful waiting between two major events in the U.S. that are fraught with uncertainty. On February 2, Punxsutawney Phil, the official U.S. Groundhog, revealed his meteorological forecast that we would have six more weeks of winter. (Non-U.S. readers should search the Internet for “groundhog day” to read about our quaint customs.) The other event of great consequence is the Super Bowl. With no inside information at this time, beyond the fact that the New York Giants obviously ought to win, because … well …we’re so deserving, I leave you with the fervent hope: “Go Giants!”

Stephen Figlewski

Editor

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