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The following is a script for a presentation that was given by J.P. Morgan Chase & Co. and will be recorded for playback on an unaffiliated third party’s website who has licensed the Core C-IGAR Sigma Long-Short Index from J.P. Morgan Chase & Co. This presentation relates to the Core C—IGAR Sigma Long-Short Index, part of the Commodity IGAR family of indices. The slides relating to such presentation can be found at http://www.sec.gov/Archives/edgar/data/19617/000089109209004083/e36903_fwp.pdf.
Webinar Script
Intro
Thank you for dialling in. My name is Eynour Boutia and I lead the Commodity Investments Group at J.P. Morgan. The presentation we have prepared for you is about the latest addition to the Commodity IGAR family of indices, Core C-IGAR Sigma Long-Short. For reasons of brevity it will be referred to as C-IGAR Sigma for the rest of this presentation.
Slide 1
C-IGAR Sigma retains the main concept of the C-IGAR family, which is to invest based on consistent momentum. Momentum is the tendency of outperforming assets to outperform again in the future. If there is momentum, assets that were “winners” in the past have a high probability to outperform past “losers”. Momentum has historically worked in Commodities due to three main reasons:
| 1. | Inelasticity of demand and supply. For example, mining operations need time to ramp up production; a gold producer cannot reopen a closed mine overnight to respond to price movements. Similarly, consumers will need to fill up their gas tanks for a while even if oil prices spike. |
| 2. | Correlation of the Commodities market with business cycles. |
| 3. | Behavioural biases caused by investors being unable to process all the information that is publicly available instantaneously, or because investors may follow existing price trends thereby creating momentum |
Momentum can also work well when applied to individual commodities due to the differences in the cycles of the different sectors, and furthermore in the cycles of individual commodities within those sectors. It is this kind of momentum that is the focus of C-IGAR Sigma, which goes long up to 7 of the best performing commodities and short up to an additional 7 of the worst performing commodities each month.
By exploiting momentum in commodities the C-IGAR Sigma has delivered an IRR of 14.8% from Jan 1991 to Sep 2009 with volatility over the same period of 15.9%, outperforming S&P GSCI™ Index by about 11.5% on an annualized basis since 1991.
I should mention that the C-IGAR family was launched in September 2006. C-IGAR Sigma was launched in June 2009, leveraging on the insight that we gained from 3 years of out-of-sample performance.
Slide 2
In the next three slides I will explain how the index is constructed. Slide 2 shows the investment universe. C-IGAR Sigma invests in 14 out of the 24 sub-indices in the S&P GSCI™ Index. It focuses on the more liquid of the commodities in the S&P GSCI™ Index while still maintaining a good representation of the energy, agriculture, industrial metals and precious metals sectors. Depending on the price signals, C-IGAR Sigma may be invested in commodities as diverse as Crude Oil, Gold, Corn and Copper.
Slide 3
On slide 3, we explain more precisely how C-IGAR Sigma selects its long and short positions, or long and short “legs”. For the long leg, the process is as follows: At the end of each month, the commodity sub-indices that have displayed positive returns in the past 12 month period are selected. Following that, the Consistency Test and the Reversal test are applied to filter out the sub-indices that haven’t displayed a clear trend, or that have shown a rapid reversal of past momentum over the previous month. Finally, if more than 7 sub-indices are left, the 7 with the highest 12-month performance are included in with a weight of 1/7. Otherwise, as many sub-indices as fulfil all the above criteria are included, however the weights still remain 1/7 per sub-index. The short leg is created using a symmetrical methodology, by selecting poorly performing sub-indices and applying the two tests for negative instead of positive momentum.
Slide 4
Let me explain the Consistency Test and Reversal Test a bit more. The Consistency test is common to all C-IGAR indices and attempts to select sub-indices that have delivered a positive or negative performance in a smooth way. We test for this by checking to see if the returns of a particular commodity have been positive or negative in each of the past 12 months. When evaluating a commodity for inclusion in the long leg, we are interested in the months where performance was positive, and symmetrically for the short leg we are interested in months where performance was negative. In order to assign more relevance to more recent months, we have assigned exponentially decaying weights to the months, with the more recent months receiving higher weights.
For example, a commodity that displays a fairly clear trend, such as the first time series in the illustration, will pass the test. However, a commodity that moved abruptly in a single month but hasn’t exhibited a clear trend (in the middle), or a commodity whose trend has undergone a change of direction in the past few months (in the bottom) will fail.
Slides 5
The Reversal test was designed exclusively for C-IGAR Sigma. It attempts to avoid investment in commodities that have shown a recent, rapid reversal. In effect, it removes from the long leg selection any commodity that has dropped by more than 10% in the previous month. Similarly it removes from the short leg those commodities that have gained more than 10% in the previous month.
Slide 6
Once the long and short legs have been determined for a given month, the overall exposure of C-IGAR Sigma is scaled down, aiming to achieve a realised volatility at or below the Target Volatility Level (20%). The scaling factor is determined by observing the 21-day and 63-day volatilities of what C-IGAR Sigma would look like without this Volatility Control mechanism and using the more conservative of the two to determine the change in exposure. The new composition is rolled into over the course of 5 business days starting on the 12th business day of each month.
Slide 7
Using momentum, along with the additional mechanisms we implemented, C-IGAR Sigma tracks bull and bear markets quite well on the historical back-test. In 1997 to 1999, where commodities were arguably in a bear market as indicated by the downward movement in the S&P GSCI™ Index, C-IGAR Sigma would have gradually reduced its long exposure and increased its short exposure to the point of being 100% short. It would then have moved its net exposure longer as the market recovered. Similarly in the latest bull market (starting around 2003), C-IGAR Sigma drastically reduced the number of short positions it took. It then rapidly switched back to being net short of the market in the recent downturn and is now switching back to being net long as the potential for recovery becomes more evident. It is interesting to note that on average C-IGAR Sigma would have had roughly equal exposure on the long and the short side, which shows that opportunities to profit by being short commodities are just as frequent as for long investments.
Please note that all data on this presentation has been hypothetical until the launch of CIGAR Sigma on June 15 2009, however the main concepts driving the index have been around in the form of the extended C-IGAR Family since September 2006.
Slide 8
C-IGAR Sigma is published daily on a T+1 basis under Bloomberg ticker CMDSLSTR Index<go>. Thank you for listening, I will now turn it over to [ ].