EXHIBIT 4.22CAM’s Composite Performance Disclosures CAM Asset Management Small Capitalization Equity Composite Year-EndYear-End CompositeFirm% of GrossNetIndexNumber ofCompositeAssetsAssetsFirm YearReturnReturnReturnPorfoliosDispersion(US$Mil)(US$Mil)Assets 6/30/200316.89%15.89%12.97%402%$375.6$467.180% 2002–8.60%–9.60%–14.47%374%$311.1$377.382% 200111.74%10.74%13.10%354%$338.1$383.288% 200015.78%14.78%20.86%275%$275.9$299.592% 199925.08%24.08%3.03%163%$124.2$124.2100% 19981.85%0.85%–5.06%10%$ 18.0$ 18.0100% Standard deviation22.65%21.83% Notes:CAM is an SEC-registered investment adviser that specializes in small-capitalization equity management. The results presented herein have been prepared and presented in compliance with the AIMR PPS and GIPS for the entire period shown. Monthly composite results have been linked geometrically and are asset weighted by beginning-of-month asset values of included portfolios. Monthly results of included portfolios are time weighted. The composite is managed using a value-oriented, bottom-up investment strategy. The benchmark used in this report is the S&P 600 SmallCap Index. The index returns include dividends. The composite is composed of all small cap accounts managed against the aformentioned in- dex whose investment guidelines do not differ materially from the guidelines established by CAM for its small cap accounts. Net product perfor- mance reflects the payment of management fees and trading costs. CAM charges a flat 1.00% management fee for accounts with assets less than $25 million and 0.80% for accounts with assets over $25 million. The fee schedule is described in full in CAM’s Form ADV, which is available on re- quest. The composite was created on January 31, 1998, and all numbers and figures were calculated using and reported in U.S. dollars. The compos- ite contains only fee-paying accounts. Leverage was not used in the management of any of the accounts included in this composite. There is no minimum size criterion for composite membership.
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from high to low. This number is meaningful because we calculate most, if not all, performance-related statistics from the reported composite av- erage. As a result, our expectations are then based on the average weighted return in the composite. It is important to know that it is possi- ble to invest in a specific product and receive a return that is higher or lower than the reported average.
However, dispersion is not necessarily a bad thing. Investment man- agers that invest accounts from a model portfolio and rebalance all ac- counts when the model changes tend to have tighter dispersion numbers. In contrast, a manager that lets a portfolio “age” can experience wider swings in account dispersion—especially during volatile periods of time.
While the high-low dispersion figure is useful, it can lead us to some questionable conclusions. A composite with a great number of accounts may have a few outlier portfolios that stretch the dispersion figure, leading the analyst to infer that dispersion is generally high. To resolve this issue, the analyst can request the underlying portfolio returns for each account and can calculate the percentage of accounts with returns within one stan- dard deviation of the mean and, if necessary, within two standard devia- tions of the mean.
Step 1: Calculate the average return for the period (yearly in this case)
where AAR1= Annual account return for year 1 for each account in the composite.
Note: This formula includes only accounts that were fully invested for the entire year. Accounts that were invested for a portion of a given year are not included in that year, but would be included in the following year (assuming they stayed in the composite for the full year). Accounts with large cash inflows and/or large cash outflows during a given year might ex- perience additional dispersion compared to accounts that did not experi- ence large inflows/outflows because the timing of the asset inflow/outflow might impact returns. In this case, the analyst might elect to exclude these accounts from the calculation.
Step 2: Calculate the standard deviation of accounts for the pe- riod. The formula for this statistic will be covered in detail in the next chapter.
Step 3: Determine how many of the composite accounts have returns within +/– one standard deviation of the average account return and take that number as a percentage of the total number of accounts. This gives
Average Account Return AAR Accounts
=
∑
1K#
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you the percentage based on number of accounts. It is also helpful to calcu- late this statistic in relation to assets as opposed to number of accounts. To do this, add the assets from each of the accounts that fall within one stan- dard deviation of the average account and take that sum as a percentage of the total assets in the composite.
Year-End Composite/Firm Assets
The “composite assets” column goes hand in hand with the number of ac- counts column. When reviewed together, they give the analyst a very clear indication of the product’s development over time. By focusing on either column in isolation, you run the risk of not seeing the big picture. For ex- ample, it is possible to lose accounts but see a substantial increase in assets under management. This could be due to market appreciation on the re- maining accounts or to the addition of a single large account or a combina- tion of both.
To remedy this, I typically request the following additional information:
■Number of accounts gained each year.
■Number of accounts lost each year.
■Amount of assets redeemed each year.
■Amount of assets gained each year.
Armed with this additional information, the analyst can quickly de- termine what influenced the composite’s asset growth—inflow of new accounts, inclusion of new accounts with large asset base, or market appreciation. The math also works when assets decline rather than increase.
The total firm assets column tells us how big the total firm is and gives us a good indication as to a given product’s importance to the firm. The last column in the performance disclosures (“% of firm assets”) is simply the ratio of the product’s assets taken as a percentage of the total firm as- sets. The higher the percentage, the more important the product is likely to be to the firm’s revenue base. However, percentage of assets as an indicator of contribution to overall firm revenues can be misleading when the firm in question also manages products with incentive (performance) fees, such as hedge funds, private equity funds, and other “alternative” asset classes. It is not uncommon for incentive fees to represent between 20% and 30% of the absolute profit generated by the product. As a result, it is possible for a firm to generate more revenue from alternative asset classes despite a lower asset base.
Comparing the composite and firm assets stated in CAM’s composite disclosures, we can also see that the amounts differ from the figures we got
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from the third-party database after running the screen (Exhibit 2.4). This could be a simple error or something more. In any case, it gives us some- thing to follow up with when we speak to the manager.
Fine Print
What would disclosures be without the fine print? The performance disclo- sures shown in Exhibit 4.22 appear at the bottom of the report. While no one enjoys reading the fine print, it is an essential part of the analysis. A great deal of information can be obtained simply by reading through the notes section of the performance disclosures.
The notes in CAM’s performance disclosures tell us that the perfor- mance figures were “prepared and presented in compliance with the AIMR PPS and GIPS for the entire period shown.” As a result, we now know that CAM claims to have adhered to all of the regulations covered in the previ- ous section. The notes do not, however, state that the results have been ver- ified through an official “AIMR audit.” This audit is not performed by AIMR; rather it is typically performed by an accounting firm with exper- tise in AIMR procedures and regulations. It would be a good idea to follow up with CAM to see if they have or plan on having an audit to verify AIMR compliance. If they have had an audit done, request a copy of the letter prepared by the audit firm. If not, it might be a good idea to find out why and to possibly do a spot check of the composite to test how complete CAM was when they put the composite figures together.
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CHAPTER 5
Risk Analysis
I
s last year’s best-performing manager the best choice to hire today? Not necessarily. To make that assessment, we need to understand what risks that manager took to achieve those stellar results.Just as there are two sides to a coin, there are two sides to returns- based analysis. Performance is usually the most prevalent, but in many ways risk is just as important (if not more important). Investment manager analysts who make the decision to hire or fire an investment manager based solely on that manager’s historical performance are effectively flipping a coin to make their investment decisions. It is this “heads you win, tails you lose” mentality that is responsible for more investment losses and heartache than anything else I have seen in this industry.