Second-quarter results included the following significant items:
$4.4 billion pretax loss ($0.69 per share after-tax reduction in earnings) from CIO trading losses and $1.0 billion pretax benefit ($0.16 per share after-tax increase in earnings) from securities gains in CIO's investment securities portfolio in Corporate. "JP Morgan Second Quarter 2012 Earning Release July 13, 2012"It turns out that JPMorgan lost $4B with the ubiquitous 'garbage in: garbage out' and a lack of controls. One might reasonably expect more when so many experts and dollars are involved! We can all learn from JPMorgan's mistakes: learn to be skeptical of statistical models; learn how the desired result is accepted without question; learn how easily contradictory evidence is discarded; learn how bright individuals with short term incentives need close supervision.
JP Morgan recently published a report regarding how such a well managed and closely audited organization could lose so much money so quickly. Thanks to Zerohedge who brought the report to my attention! Zerohedge focused on the report's finding of an EXCEL formula error. There are more gems in the report that inspire comment and show exactly how much you can trust JP Morgan to know the right thing and to do the right thing, even with its own money.
Read Zerohedge's comments here: http://www.zerohedge.com/news/2013-02-12/how-rookie-excel-error-led-jpmorgan-misreport-its-var-years
The CIO is JPMorgan's Chief Investment Office which manages the banks money. Here's how the task force report describes the CIO:
JPMorgan’s businesses take in more in deposits than they make in loans and, as a result, the Firm has excess cash that must be invested to meet future liquidity needs and provide a reasonable return. The primary responsibility of CIO, working with JPMorgan’s Treasury, is to manage this excess cash. CIO is part of the Corporate sector at JPMorgan and, as of December 31, 2011, it had 428 employees, consisting of 140 traders and 288 middle and back office 22 employees. page 21
Managing JPMorgan's money is a big job. They don't just park it in T-Bills or index funds. They seek higher returns which leads them to riskier investments. A concept called VaR (Value at Risk) is a statistical metric to measure and manage investment risk. Banks employ 'modelers' to create these metrics and apply them to specific investments such as Synthetic Credit Obligations (CDOs).
For traders, the lower the VaR on their investments the better, because then the trader can put more money at risk. If VaR gets too high senior management may not allow a trader to continue adding to their position for fear of putting too much money at risk.
From the task force's report:
From February to April, the new VaR model was in operation. A CIO employee who reported to the modeler was responsible for daily data entry and operation of the new model. In April, an employee from the IT Department (who had previous experience as a senior quantitative developer) also began to provide assistance with these tasks. Notwithstanding this additional assistance, 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, 126 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. page 127Why was it viewed as a one-off error? What gave them the confidence that the 'error' would not occur again? And, even if it was a one-off it should have triggered further inquiry and investigation. Clearly, they simply did not want to believe that the new VaR model could be wrong, because it gave the traders a better answer. And note that the CIO employee using the model reported to the creator of the model. What would happen if/when that employee found a mistake in the model?
. . . . further errors were discovered in the Basel II.5 model, including, most significantly, an operational error 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 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, although it is unclear by exactly what amount, particularly given that it is unclear whether this error was present in the VaR calculation for every instrument, and that it would have been offset to some extent by correlation changes. It also remains unclear when this error was introduced in the calculation. page 128Shit happens. Mistakes are made. Why wasn't this mistake caught before going in to production? This kind of 'honest' mistake can be made in any software or back of an envelope. Year ago I completed a financial valuation of an acquisition target for my company. My wise boss then had me analyze and present all of my assumptions and results (e.g. EBITDA, IRR, NPV, EPS) compared to those provided by our investment bankers. And then he insisted on understanding exactly why the bankers' result were different or similar to those of my own analysis.
Mr. Weiland and another member of CIO Market Risk contacted the Model Review Group regularly in the last two weeks of January to inquire into the progress of the model approval and, in a January 23, 2012 e-mail to the modeler, the trader to whom the modeler reported wrote that he should “keep the pressure on our friends in Model Validation and [Quantitative Research].” There is some evidence the Model Review Group accelerated its review as a result of this pressure, and in so doing it may have been more willing to overlook the operational flaws apparent during the approval process. page 125The modeler who is responsible for creating the metric by which the trader should be controlled reports to the trader. And JPMorgan is Sar-Box compliant!
In addition, many of the tranches were less liquid, and therefore, the same price was given for those tranches on multiple consecutive days, leading the model to convey a lack of volatility. While there was some effort to map less liquid instruments to more liquid ones (i.e., calculate price changes in the less liquid instruments derived from price changes in more liquid ones), this effort was not organized or consistent page 124
The VaR metric is based on volatility. The inputs to the VaR model were less volatile than in reality. So the VaR model yielded a lower VaR. These are smart people working at JPMorgan. They knew exactly how much confidence to put in this VaR model.
Report of JPMorgan Chase & Co. Management Task Force
Regarding 2012 CIO Losses January 16, 2013 http://files.shareholder.com/downloads/ONE/2272984969x0x628656/4cb574a0-0bf5-4728-9582-625e4519b5ab/Task_Force_Report.pdf