How VaR Modeling Gone Wrong Cut Pay of Wall Street’s Most Powerful CEO, JPMorgan Chase’s Jamie Dimon, by Half
President Barack Obama’s favorite Wall Street CEO, JPMorgan Chase’s Jamie Dimon is facing more than having his pay cut in half to $11.5 million for 2012, compared with $23 million a year earlier. He is facing the prospect of seeing his reputation, cemented until now by his smart handling of the bank during the financial crisis, becoming tarnished as he has been deemed ultimate responsible for the banks’ loss of more than $6.2 billion in the first nine months of 2012 on bets by U.K. trader Bruno Iksil, nicknamed the London Whale, who operated under Chief Investment Officer Ina Drew.
The Chief Investment Office (CIO) was supposed to manage excess cash while minimizing risk using credit derivatives as part of a hedging strategy; instead, their trades became so large that the bank couldn’t easily unwind them. At the bottom of this miscalculation were blunders in the development, testing and approval of a new VaR model to measure the risk of their Synthetic Credit Portfolio.
VaR (Value at Risk) is a metric that attempts to estimate the risk of loss on a portfolio of assets. A portfolio’s VaR represents an estimate of the maximum expected mark-to-market loss over a specified time period, generally one day, at a stated confidence level, assuming historical market conditions. Through January 2012, according to the 129-page report from a task force led by Michael Cavanagh, co-head of the firm’s corporate and investment bank, the VaR for the Synthetic Credit Portfolio was calculated using a “linear sensitivity model,” also known within the Firm as the “Basel I model,” because it was used for purposes of Basel I capital calculations and for external reporting purposes. The Basel I model captured the major risk facing the Synthetic Credit Portfolio at the time, which was the potential for loss attributable to movements in credit spreads.
However, the model was limited in the manner in which it estimated correlation risk: that is, the risk that defaults of the components within the index would correlate. As the value of the tranche positions in the Synthetic Credit Portfolio increased, this limitation became more significant, as the value of these positions was driven in large part by the extent to which the positions in the index were correlated to each other. The main risk with the tranche positions was that regardless of credit risk in general, defaults might be more or less correlated.
This limitation meant that the Basel I model likely would not comply with the requirements of Basel II.5, which originally had been expected to be formally adopted in the United States at the end of 2011. One of the traders responsible for the Synthetic Credit Portfolio therefore instructed an expert in quantitative finance within the Quantitative Research team for CIO to develop a new VaR model for the Synthetic Credit Portfolio that would comply with the requirements of Basel II.5. They believed that the Basel I model was too conservative, that it was producing a higher VaR than was appropriate.
Early in the development process, CIO considered and rejected a proposal to adopt the VaR model used by the Investment Bank’s credit hybrids business for the Synthetic Credit Portfolio. Because the Investment Bank traded many customized and illiquid CDSs, its VaR model mapped individual instruments to a combination of indices and single name proxies, which CIO Market Risk viewed as less accurate for CIO’s purposes than mapping to the index as a whole. He believed that, because the Synthetic Credit Portfolio, unlike the Investment Bank, traded indices and index tranches, the Investment Bank’s approach was not appropriate for CIO. The Model Review Group agreed and, in an early draft of its approval of the model, described CIO’s model as “superior” to that used by the Investment Bank.
The Model Review Group, charged with the formal approval of the model, performed only limited back-testing, comparing the VaR under the new model computed using historical data to the daily profit-and-loss over a subset of trading days during a two-month period, not even close to a typically required period of 264 previous trading days, a year. In addition, they were pressured by the CIO to accelerate its review, overlooking operational flaws apparent during the approval process; for instance, it was found later that the model operated through a series of Excel spreadsheets, which had to be completed manually, by a process of copying and pasting data from one spreadsheet to another. The Model Review Group discovered that, for purposes of a pricing step used in the VaR calculation, CIO was using something called the “West End” analytic suite rather than Numerix, an approved vendor model. CIO assured the Model Review Group that both valuations were in “good agreement.”
On January 30, the Model Review Group finally authorized CIO Market Risk to use the new VaR model which would utilize the Gaussian Copula model, a commonly accepted model used to map the approximate correlation between two variables, to calculate hazard rates and correlations. A hazard rate is the probability of failure per unit of time of items in operation, sometimes estimated as a ratio of the number of failures to the accumulated operating time for the items. For purposes of the model, the hazard rate estimated the probability of default for a unit of time for each of the underlying names in the portfolio.
Once in operation, a spreadsheet error caused the VaR for April 10 to fail to reflect the day’s $400 million loss in the Synthetic Credit Portfolio. This error was noticed, first by personnel in the Investment Bank, and by the modeler and CIO Market Risk, and was corrected promptly. Because it was viewed as a one-off error, it did not trigger further inquiry. Later in May, in response to further losses in the Synthetic Credit Portfolio, a review of the West End calculated discovered that it was using the Uniform Rate model rather than Gaussian Copula model, contrary to the Model Review Group approval.
Although this error did not have a significant effect on the VaR, an operational error was found in the calculation of the relative changes in hazard rates and correlation estimates. Specifically, after subtracting the old rate from the new rate, the spreadsheet divided the result by their sum instead of their average, as the modeler had intended. This error likely had the effect of muting volatility by a factor of two and of lowering the VaR, minimizing the estimate of the potential loss in the Synthetic Credit Portfolio, which ultimately grew to more than $6.2 billion. Despite this humongous loss, JPMorgan Chase disclosed full-year 2012 record net income of $21.3 billion on revenue of $99.9 billion, guaranteeing Dimon’s survival at the helm for the moment.Read Full Post | Make a Comment ( None so far )