Valuation Model Service

C olumbine C apital S e r v I c e s, I n c. Valuation Model Service Annotated Presentation 2006 Price Value

Copyright 2006 by Columbine Capital Services, Inc. All rights reserved. Columbine Capital Services, Inc. Two North Cascade Avenue Suite 450 Colorado Springs, CO 80903 Telephone: 719.635.5174 Fax: 719.634.5867 URL: www.columbinecap.com E-Mail: info@columbinecap.com

Notes on Model Results Columbine s models are intended to aid investment professionals familiar with industry practices and statistical tools at the CFA level in screening for stocks demonstrating historically successful measures of value and momentum. The results presented in this document are intended to illustrate the statistical characteristics of those models. These results were achieved by the retroactive application of models that were designed with the benefit of hindsight. When evaluating the performance of such models it is important to consider the following: The results reported here are hypothetical. Unless otherwise noted, they were compiled after the end of the period specified and do not represent decisions made by Columbine Capital Services during that time. As such, these results do not reflect the impact that any material market or economic factors might have had on Columbine's application of these models if they actually had been used to manage client assets during the periods presented here. These results do not represent actual trading using client assets. They should not be considered indicative of the investment skill of Columbine Capital Services, Inc. Columbine has never managed client funds according to the strategies depicted in this document, nor does it offer investment management services based on these strategies to investors. Clients for Columbine's research services actually had investment results that were materially different from the results portrayed here. The performance of past rankings does not assure the profitability or utility of future rankings. Used in isolation, these models could generate frequent relative and absolute losses; annual portfolio turnover could exceed 300%. Concentrations in the stocks of particular economic sectors or industry groups would be common. Unless otherwise noted, all returns are calculated on a time-weighted basis, using monthly valuation, based on equal-weighted deciles and universes. Returns include reinvested dividends (total return) and are presented gross of brokerage commissions, market impact, or other expenses of trading. Subscription fees for Columbine s services are not included in the performance calculations; a client s actual return would be reduced by the incorporation of those fees. The effect of fees and expenses on performance will vary with the relative size of the fee and account performance. For example, assume assets under management of $500 million, and an annual rate of return of 10.0%. The compound effect of an annual subscription fee of $25,000 per year over a ten-year period would reduce that annual rate of return by 0.34 basis points to 9.997%. We base our computations on data from commercial sources that we believe to be reliable, but we cannot guarantee the accuracy of that data. Decile-by-decile results for all Columbine models during the periods reported on here (or for any period) are available on request. A complete history of every ranking made by Columbine Capital Services, Inc. is available for inspection in our offices. Notes on Results ver.03-1.doc 02/13/03

Agenda Introducing Columbine Capital Services What we do Why clients choose Columbine Service overview Model characteristics Coverage & delivery Performance How we can add value in your process Applications for investment decision-support This presentation is broken up into three main sections: Introducing Columbine Who we are and what we do. Why some of the industry s top institutional investors have chosen to work with Columbine. A overview of the service How are the Columbine rankings computed, what can you expect from the stocks ranked buy and sell, and how successful have the Columbine forecasts been? How we can add value in your process Practical applications for the Columbine rankings in support of your investment decision process. Valuation Model Service 1

What Columbine Does Search for new sources of alpha Original quantitative research Build alpha-forecasting models Unique, innovative methodology Apply models to rank stocks worldwide Weekly rankings for 25,000+ companies Deliver rankings to subscribers Internet & hard copy reports Work with clients Integrate our rankings into your process All of Columbine s services spring from our extensive R&D. We have been conducting original research into the sources of alpha (active return) for more than two decades. What we learn about alpha sources finds expression in mathematical models, each designed to forecast active return based on different return characteristics, investment styles, and country markets. Every week we gather the latest financial and market data for more than twenty thousand companies worldwide and feed that information into our models. The models output clear, unambiguous rankings (usually 1-10) that summarize each model s forecast of each company s future active return. We deliver the updated rankings from our models to our client firms in the US, the UK, and Canada. Subscribers receive updated rankings electronically and in hard copy reports. Columbine s work doesn t end with data delivery. We work closely with clients to help them integrate our rankings into their own processes. Some of the world s most successful professional money managers support their decision-making process with quantitative equity rankings from Columbine. Our clients include money managers, banks, mutual funds, insurance companies, hedge funds, and plan sponsors. Valuation Model Service 2

Rankings Forecast Alpha Model rank 1 2 3 4 5 6 7 8 9 10 Negative alpha Market Positive alpha The rankings that come out of the various Columbine models are, in effect, forecasts of future alpha (active return over a benchmark). The chart above illustrates the relative alphas associated with each rank of a typical Columbine model. In our system a rank of 1 is best (high positive active return), and 10 is worst (negative active return). Generally, the average alphas (active returns) generated by each ranking of our models present a stair-step, or monotonic progression. Some of the Columbine models exhibit non-linear return characteristics, generating the majority of their predictive power at the extremes of the rankings with little information in the middle ranks. Although there is an average active return value associated with every model ranking, it is more practical to view the Columbine model rankings as relative probability statements. From this perspective higher ranked issues are more likely to produce positive alphas than lower ranked issues. That is, a 2 is more likely to produce alpha than is a 3, a three is more likely than a 4, and so on. By consistently constructing portfolios with issues exhibiting a higher probability of generating positive alpha you increase the likelihood that the portfolio as a whole will succeed in doing so. Valuation Model Service 3

Why Choose Columbine Independence Employee-owned equity research firm Experience Serving institutional investors since 1976 Credibility Backtest doesn t have to be a dirty word Service Maximize subscribers benefit from service Columbine Capital Services, Inc. is an independent research firm with offices in Colorado Springs, Colorado. As an entirely employee-owned company we offer you objective analysis, free of extraneous influences. Founded in 1976 by the firm's president, John S. Brush, Ph.D., Columbine has been serving the needs of institutional investors longer than the majority of funds have been in existence. Each of Columbine s three principals has more than fifteen years of experience in institutional quantitative research. We understand your business and we appreciate your problems. One byproduct of Columbine s depth of experience is our awareness of the many ways to fool yourself with statistics. We recognize the importance of holdout samples, simulations free of survivorship and look-ahead biases, and meaningful measures of statistical significance. As a Columbine subscriber you can have confidence in the integrity of the methodology used to create the models you are incorporating into your process. Ultimately, Columbine s success flows from the success of our clients. To insure that you receive the maximum benefit from your Columbine service we are happy to consult with you on how to make the best use of our rankings. This includes sharing our own new research findings and keeping you apprised of contemporary performance for our factors and models. Valuation Model Service 4

Valuation Model Service Pure valuation measure Synthesis of 5 valuation factors Complement to other types of analysis Published since 1998 Price Value The Columbine Valuation Model forecasts future alpha from an objective measure of each stock s intrinsic value. The model s rankings are a synthesis of five individual value-oriented factors drawing on reported and estimated earnings, book value, cash flow, and dividends. This is a building block model; it is not intended to stand alone. The Valuation Model complements, but does not duplicate the characteristics of other forms of analysis; it is intended to be used as one element of a complete stock selection system. Our design goal for this model is to maximize its ability to discriminate between attractive and un-attractive issues. This is measured as the difference in alphas generated by a model s top (1 st ) and bottom (10 th ) deciles over the long-term time horizons of interest to institutional investors. Valuation Model alpha forecasts are predictive out as far as three years in the future. We developed the Valuation Model in 1997 and began publishing Valuation Model rankings from live data in 1998. Valuation Model Service 5

Valuation Model Results Top decile active return (annualized) through December 31, 2005 1 Year 4.6% 3 Years 8.1% 5 Years 14.3% 10 Years* 5.9% Since Inception 6.0% Published rankings (*includes backtest) in Columbine 1500 Universe Monthly rebalancing, no transactions costs Although developed in a historical database, the Valuation Model has produced out-of-sample results consistent with its development testing. Here are the returns generated by the Valuation Model s top decile stocks (equal-weighted) in the Columbine 1500 Universe across several different time horizons. These are annualized active returns vs. the universe at each time period. We began publishing the Valuation Model rankings at the beginning of 1998, so the ten-year return figures include backtest rankings. At the beginning of every month we measure each stock s attractiveness with the Valuation Model and rank-order all the issues into deciles (equal 10% groupings). Stocks in the top 10% (ranked 1) are most likely to outperform the market, and those in the bottom 10% (ranked 10) are most likely to underperform. At each month-end we compute the average return (equal-weighted) for the stocks in each decile and the return of the equal-weighted universe from which the deciles were selected to determine the active return (excess over the benchmark universe return). We then link these monthly returns for the entire period and calculate each decile s annualized rate of return. No transactions costs are included. Please see the Notes on Model Results. Valuation Model Service 6

What Makes Our Model Different Gradient maximization methodology Portfolio-oriented process aligns models with investment strategy Proprietary technique produces unique models Designed for institutional use Typically, 6-12 month holding period Withstand realistic transactions costs Evolve to maintain its fitness Re-optimized annually At Columbine, our principal tool for designing alpha-forecasting models is an optimization methodology from the world of operations research called gradient maximization (grad max) 1. This is an intelligent search technique that simulates the management of a portfolio over time in order to learn the optimal alpha forecasting model for a specific investment strategy. Columbine s innovative application of this technique to institutional equity research is unique, as are the models that it produces. Columbine s models are designed for use by professional investment managers, not retail investors. We incorporate realistic transactions costs into the modelbuilding process, and we optimize our models for holding periods that reflect typical institutional practice. We recognize that markets evolve over time; gradually changing their pattern of rewarding some company characteristics and punishing others. The Columbine models also evolve to fit their environment. Every year we re-optimize our models over the previous ten years of data. This allows our models to respond to major trends in investor behavior without being seduced into chasing fads. 1 For more detailed information on the gradient maximization methodology, we recommend: Brush, J.S., and V.K. Schock. 1995. "Gradient Maximization: An Integrated Return/Risk Portfolio Construction Procedure." Journal of Portfolio Management, vol. 21, no. 4 (Summer):89-98. Valuation Model Service 7

How the Model Works Stock s input factor rankings (1-10) Trailing EPS to Price Book Value to Price Forward EPS to Price Cash Flow to Price Dividend Yield Columbine Valuation Model (Optimal weighting of input factor rankings) Stock s Valuation ranking: 1= best 10 = worst Model version: 2005 Stock rankings from the Valuation Model are a synthesis of the inputs from five individual value-oriented factors: Trailing EPS to Price trailing 12-month EPS, divided by current price Cash Flow to Price trailing 12-month EPS, net of dividends, plus depreciation, divided by current price Book Value to Price latest reported book value, divided by current price Forward EPS to Price consensus EPS estimates (forward 4 quarters), divided by current price Dividend Yield trailing 12-month dividends, divided by current price The Valuation Model combines each stock s rankings from these factors in a linear equation of five terms: Valuation raw score = B 1 f 1 + B 2 f 2 + + B 5 f 5 Where B is the sensitivity of a stock s future active return to the value of its corresponding factor f. (Our proprietary Gradient Maximization optimization process determines the model s factor weightings). We then sort the stocks on their raw scores from best to worst and assign rankings from 1 (top 10%) to 10 (bottom 10%). Valuation Model Service 8

Updates & Delivery Model rankings updated weekly Data as of Friday close Updated rankings available Saturday AM Delivery options Electronic data files Download from Columbine Web Site www.columbinecap.com Automatic delivery via E-mail or FTP FactSet screening & downloading Hard copy Columbine Research Book We compute the Valuation Model rankings every weekend based on Friday closing prices and fundamentals. Updated ranking data typically is available on Saturday morning. (If you re ever in doubt about the currency of our information, check the Update Status display on the Columbine web site which reports the date of the last ranking update.) Valuation Model rankings are available electronically through the Internet as data files that can be loaded into Excel, Access, or other applications on your system. We can automatically deliver your data files each weekend via E-mail or FTP, or you can download files yourself from a password-protected client page on Columbine's web site. The web site delivery option is particularly useful for clients who often work from home or while traveling. Columbine subscribers who are FactSet users can access Valuation Model rankings through the Universal Screening and Data Downloading menus. If you prefer paper to electronic information we can send you hard copy Research Book reports of the Valuation Model rankings via overnight express for delivery on Tuesday. These Research Book reports also are available as PDF files for electronic delivery over the weekend. Valuation Model Service 9

1 2 3 4 5 6 7 8 9 10 Easy to Interpret Average active return by Valuation Model rank Buys -4.4% -1.4% Sells 5.6% 4.0% -6% -4% -2% 0% 2% 4% 6% 8% Test universe: Columbine 1500 Universe, test period: 1992-2001 1-month holding periods, annualized, no costs It s easy to interpret and use the Valuation Model rankings. Generally, we consider stocks in the model s top 20% (ranked 1 or 2) to be buys, and those in the bottom 20% (ranked 9 or 10) to be sells. The chart above sets out the average active return (annualized) associated with each rank of the current Valuation Model in the Columbine 1500 Universe over a ten year test period. The chart s results are based on one-month holding periods and are reported gross of transactions costs. The Valuation Model exhibits a fair degree of non-linearity most of its predictive power is in the extreme rankings. The middle rankings (3 to 8) are useable, but display a lot more noise than the top and bottom 20%. For the ten years of this test the Valuation Model s 10 th decile stocks appear to produce less negative active return than the 9 th decile. This is a function of the tremendous outperformance of the dot.com and other Technology stocks in 1998 and 1999, many of which were (quite properly) ranked as 10 th decile on Valuation. Excluding those two years the 10 th decile return would return to the typical pattern greater negative active return than the 9 th decile. Valuation Model Service 10

100% Stable Rankings Stocks Ranked Buy or Sell by Valuation Model 87% Same signal 79% Signal reverses 71% 63% 0% 0% 0% 0% 1% 0 3 6 9 12 Months following initial ranking Test Universe: Columbine 1500 Universe, test period: 1992-2001 How much do the Valuation Model s rankings change over time? We can compute ranking autocorrelations and decile turnovers, but those measures don t provide most users with the practical insight they need into what to expect from the model s rankings on a day-to-day basis. The graph above is an attempt to provide that insight. For the Valuation Model, we consider issues ranked 1 or 2 (top-ranked 20%) as buys and those ranked 9 or 10 (bottom-ranked 20%) as sells. The critical questions for using the model s rankings revolve around changes to those signals. The graph illustrates what happens to the rankings of typical buy- or sell-ranked stocks over time. This data is based on monthly rankings from the Valuation Model in the Columbine 1500 Universe over a ten year test period. The top (green) line sets out what percentage of stocks still exhibited the same signal (buy or sell) 1, 3, 6, and 12 months later. The bottom (red) line shows the percentage of stocks that reversed their signal (buy becoming a sell, or vice versa) over the same time periods. Valuation Model rankings are very stable a year after the initial ranking you can expect more than 60% of the issues to display the same signal and only 1% to have reversed their signal. Valuation Model Service 11

Long-Term Utility Valuation Model Average active return by holding period 7% 6% 5% 4% 3% Top decile 2% 1% 0% 0 6 12 18 24 30 36 Holding period (months) Test universe: Columbine 1500 Universe Test period: 1992-2001, no transactions costs Long-term predictive ability is vital if model rankings are to be useful in institutional portfolio strategies. Stocks identified as attractive by the Valuation Model tend to generate significant alphas for as long as three years. It is this ability to identify stocks that keep generating alpha month-after-month, year-after-year, that gives the model its utility in institutional portfolio management. The graph above illustrates the average active return (unannualized) associated with the Valuation Model s 1-ranked stocks at holding periods of 1, 3, 6, 12, 24, and 36 months. These are unrebalanced, buy-and-hold results, gross of transactions costs, over a ten-year test period in the stocks of the Columbine 1500 Universe. The Valuation Model continues producing useful alpha out as far as three years in the future. The slight hitch in the growth of the model s active return at the 24- month holding period is largely an artifact of the Tech stock bubble years of 1998 and 1999. Valuation Model Service 12

Sector Variation Valuation Model Average top- minus bottom-decile spread Transportation Basic Industries Capital Goods Technology Energy Financials Utilities Consumer Cyclicals Consumer Staples Healthcare 0% 5% 10% 15% 20% Test universe: Columbine 1500 Universe, test period: 1992-2001 One-month holding periods, annualized results, no costs The Valuation Model is generally predictive in all segments of the market, but, as you might expect, it is more effective in some sectors than in others. The chart above illustrates the model s discriminatory ability in each of ten different economic sectors within the Columbine 1500 Universe stocks over a tenyear test period. This study treated each sector as a separate universe of stocks and ranked all issues within each sector into deciles by the Valuation Model. The bars represent the average top- minus bottom-decile spread observed in each sector. All results are based on a one-month holding period returns (annualized) and do not include transactions costs. Not surprisingly, the model generates its biggest spreads in value-oriented sectors like Transportation, Basic Industries, and Capital Goods. It s less predictive in more growth-oriented sectors such as Consumer Cyclicals, Consumer Staples, and Healthcare. Valuation Model Service 13

Annual Active Return Valuation Model top decile Through December 31, 2005 37.8% 13.6% 11.8% 6.4% 7.1% 7.9% 4.6% 9.3% 12.0% 9.2% 10.5% 4.6% Backtest -10.7% -19.1% Published '92 '93 '94 '95 '96 '97 '98 '99 '00 '01 '02 '03 '04 '05 Test universe: Columbine 1500 Universe Monthly rebalancing, no transactions costs Here is the history of the Valuation Model s top decile annual active returns. These results are based on rankings made every month. All returns are gross of transactions costs. The universe is the institutionally-oriented Columbine 1500. Like any other quantitative measure that focuses on a single aspect of return, the Valuation Model s performance varies over time, but the results do show good year-to-year stability. The results prior to 1998 are based on backtest results, but since the Valuation Model is an integration of factors that have been published and proved previously in other testing, we can have a higher level of confidence in the future prospects for this model. Not surprisingly, the Valuation Model performed extremely poorly during the Tech run-up at the end of the 90s, but recovered nicely as investors turned toward value in 01. Please see the Notes on Model Results. Valuation Model Service 14

Applications Source of value-oriented buy ideas Stocks ranked 1 or 2 are buys Sell discipline Stocks ranked 9 or 10 are sells Use as a screen or overlay Double-Buy strategy Add as a valuation-driven input factor into your own multifactor model Blend with Momentum Earlier we referred to Columbine as a provider of decision-support for investment managers. What does that mean in practice? Here are some of the ways our clients apply the Valuation Model s rankings. Many managers use the rankings simply as a source of value-oriented new buy ideas. Issues ranked 1 or 2 are current buys by the model. Starting your own analysis with a short list of high-potential issues saves time and can improve your portfolio s return. Setting up an effective sell discipline can be just as valuable as finding strong stocks to buy. The future prospects for stocks ranked 9 or 10 on the Valuation Model are very poor consider them current sells. One of the most popular (and effective) applications for the Valuation Model is to use the model s rankings as a screen or overlay in combination with other measures. Identifying issues that are attractive both on the Valuation Model and on other fundamental or technical tools can narrow your search to a small number of very attractive issues. We will examine one such strategy the Double Buy. Other managers utilize the model s rankings as the value component in a multifactor system of their own design. This building block approach saves resources over creating your own valuation input. Valuation Model Service 15

Double-Buy Signal Concept: High momentum stocks that also are cheap are likely to outperform their peers Criteria: Strong positive momentum (top quintile of Columbine Momentum Model as proxy) Ranked 1 or 2 by Valuation Model Indicated action: Immediate buy a few high potential names The concept of the Double-Buy signal is simple stocks that exhibit strong positive momentum (good growth stocks) that also are cheap are likely to outperform their peers that are fairly priced to overvalued. The criteria for applying this concept are equally simple. First use some fundamental process to identify high momentum stocks. Then screen that group of growth stocks by the Valuation Model to find issues ranked 1 or 2 the undervalued issues. Only a small number of stocks will meet this two-way test, but those issues tend to have extraordinary potential and should be considered immediate buy candidates. Valuation Model Service 16

Double-Buy Results Average active return (annualized) 16.0% Momentum buys Double-Buy stocks (±11% of buys) 8.8% 10.0% 7.4% 6.8% 8.8% 7.0% 3.9% 1 3 6 12 Holding period (months) Test universe: Columbine 1500 Universe Test period: 1971-2001, no transactions costs Using the Valuation Model to screen growth stocks can produce significant levels of added return. Here are the results we observed from the Double-Buy signal over the years 1971-2001. The test was run in the stocks of the Columbine 1500 Universe. Results are equal-weighted and are reported gross of transactions costs. We used our own Momentum Model to provide a proxy for the growth style. The Momentum Model an optimized multifactor model that synthesizes five growthoriented inputs is the natural complement to the Valuation model. For the purpose of this test we considered stocks in the Momentum Model s top-ranked quintile to be momentum buys. The graph reports the annualized average active return generated at holding periods of 1, 3, 6, and 12 months. For each holding period the left-hand bar illustrates the active return of all the momentum buys. The right-hand bar represents the average active return generated by the momentum buy stocks that concurrently were ranked 1 or 2 by the Valuation Model. On average, the momentum buy stocks that exhibited the Double-Buy signal (about 11% of the quintile) substantially outperformed their peers at every holding period. Valuation Model Service 17

Blended with Momentum Models by Valuation weight (%) Total return 20% 50% 70% 18% 40% 60% 80% 16% 30% 14% 12% 0% 20% 10% Pure momentum 90% 100% Pure Valuation Universe 12% 14% 16% 18% 20% Standard deviation of return Test universe: Columbine 1500 Universe, test period: 1992-2001 Monthly rebalancing, variable round-trip costs The Valuation Model can improve results in a more sophisticated multifactor approach too. Adding a a portion of valuation to momentum-oriented models enhances return and reduces volatility. To demonstrate this we used the same Momentum Model as in the previous example. The graph above plots the annualized return and standard deviation of return generated by each of eleven model portfolio simulations. We tested portfolios based on the rankings from each of the two models used alone, plus nine blended models that combined the Valuation and Momentum model rankings into a composite score. For these blended-strategy models we varied the weightings on the two primary models in 10% increments. All the simulations were done in our Columbine 1500 Universe over the period of January 1992 through December 2001. We ran equal-weighted portfolios of 150 stocks, rebalancing monthly, in strategies with equivalent turnover (approximately 100% annually). Round-trip transactions costs were assessed against all simulated portfolio actions using our variable costs algorithm. Adding the Valuation Model to momentum strategies lowered portfolio volatility and raised return. All of the combined strategies were more efficient (higher Sharpe ratios) than pure momentum. The 50/50 blend of valuation and momentum was the maximum efficiency strategy, generating the highest Sharpe ratio, and the highest overall portfolio return. Valuation Model Service 18

A Manager s s Resource Save time Spend your own analysis more profitably Save resources Creating your own systems = $$$$ Improve return Proven forecasting ability Here are some of the ways Columbine s Momentum Model can help you: Save time Use the model to screen a large universe of stocks down to a smaller list of strong buy candidates. This lets you spend your time and analytical talents on choosing among those issues that have already been determined to be attractive. Save resources Many of our clients could create a momentum-driven forecasting model of their own; some already had one when they hired us. But building a model that can approach the long-term predictive power and stability of the Momentum Model requires an expenditure of resources greatly in excess of the model s annual subscription cost. The make vs. buy decision is clear. Improve return In the highly competitive business of investment management small differences in return can have big payoffs. With the Momentum Model you have a state-of-the art, active return forecasting tool that is continuously updated and improved to keep it adding maximum value in your portfolios. Valuation Model Service 19

Columbine Factors Columbine utilizes thirteen individual return and risk factors in creating the Columbine Component Models and our Stock Selection Models. Each multifactor model has a different recipe of these thirteen factors, and not every factor is used in every model. Columbine s criteria for selecting these particular factors are two-fold: First, each factor has to make economic sense; simply exhibiting a correlation with future return is not sufficient without a sensible rationale. Second, each factor has to demonstrate significant predictive power on its own. In the case of the three risk factors that predictive power is more related to the volatility of future return. Ranking convention: Deciles (1-10). For return factors a ranking of 1 (top 10%) indicates most likely to outperform and 10 (bottom 10%) indicates most likely to underperform. For risk factors a 1 ranking indicates the lowest risk, while 10 is the highest risk. Return Factors BOOK VALUE The book value-to-price ratio. Defined as: current book value divided by current stock price. CASH FLOW The cash flow-to-price ratio. Defined as: trailing four-quarter EPS, minus trailing twelve-month dividends, plus depreciation, divided by the current stock price. COLUMBINE ALPHA Columbine's objective measure of each stock's price momentum. Based on a unique, volatility- and risk-adjusted model, the Columbine Alpha Factor forecasts each issue's probable performance over the next six to twelve months. Defined as: the alpha estimate resulting from a generalized least squares regression of weekly (Fridayto-Friday) stock price changes for the past twelve months against weekly changes in the S & P 500 Composite Index for the same period. We apply a proprietary weighting structure to the stock price change and market change data before the regression is run. DIVIDEND YIELD The ratio of a stock's dividends paid during the past year to its current price. Defined as: trailing twelve-month dividends, divided by the current stock price. EARNINGS CHANGE Short-term change in EPS. Defined as: current trailing twelve-month EPS, minus trailing twelve-month EPS one quarter ago, divided by current stock price. EARNINGS GROWTH Long-term change in EPS. Defined as: current trailing twelve-month EPS, minus trailing twelve-month EPS two years ago, divided by current stock price. Columbine Factors.doc 24-Feb-05

EARNINGS SURPRISE A comparison of a company s reported earnings to the latest consensus estimate. Defined as: actual reported EPS for the fiscal quarter just completed, minus the latest median EPS estimate for the same fiscal quarter, divided by one plus the latest median EPS estimate for the quarter. Stocks ranked 1 have had the largest positive earnings surprises; those ranked 10 have had the largest negative surprises (disappointments). If the reported and estimate figures are the same, the stock is ranked a neutral 5. If the company s last earnings announcement is more than 30 days old the stock is ranked a neutral 6. ESTIMATED EARNINGS YIELD An earnings yield based on the consensus EPS estimate. Defined as: median estimated EPS for the next four quarters, divided by the current stock price. ESTIMATE REVISION A multifaceted measure of revisions during the past 60 days to sell-side analysts estimates of each company s FY1 earnings. Double weight is given to changes in the last 30 days. If a company is more than six months into its fiscal year a blend of FY1 and FY2 data is used. The factor ranking is a synthesis of three individual components: Analyst Agreement Are the estimates changing in concert? Defined as: number of positive revisions minus the number of negative revisions, divided by the total number of estimates. Revision Confidence Are the extreme estimates changing? Defined as: change in the highest estimate plus change in the lowest estimate, divided by the current stock price. Revision Magnitude How big is the typical revision? Defined as: change in the median estimate divided by the current mean estimate. REPORTED EARNINGS YIELD The classic "value" measure based on reported EPS figures. Defined as: current trailing four-quarters EPS divided by the current stock price. Risk Factors BETA The standard measure of a stock's market risk. Defined as: the beta estimate from regressing five years of weekly stock price changes against the weekly changes in the S & P 500 Composite Index for the same five years. MARKET LIQUIDITY A measure of how difficult it may be to trade a given stock. Defined as: current stock price times the average daily trading volume over the previous full month. EARNINGS VOLATILITY A measure of how variable a company's quarterly earnings are. Defined as: the standard deviation of the reported EPS over the past twelve quarters, divided by the current price. For More Information Please contact David Ament at 719.635.5174, or via E-mail: d.ament@columbinecap.com Columbine Factors.doc 24-Feb-05

Valuation Model Service Results through: July, 2006 Columbine Capital Services, Inc. Columbine 1500 Universe Model description: Multifactor component model that forecasts stock alphas based on an optimal combination of five valuation measures, including both estimated and reported EPS yield. Total return (dividends re-invested), monthly rebalanced, gross of transactions costs Absolute returns Annualized historical statistical characteristics: 1971-date Month of July, 2006 Decile alpha beta sigma Sharpe R 2 Track Error Top decile -0.9% Top 8.40 0.98 19.59 0.99 0.82 8.22 Bottom decile -7.4% Bottom -7.25 1.23 26.65-0.26 0.70 15.17 Columbine 1500-3.2% Cumulative Monthly Active Return vs. Columbine 1500 Universe 1.5 1.0 Top decile: +5.76% annually Bottom decile: -4.86% annually Return (ln) 0.5 0.0-0.5-1.0 '97 '98 '99 '00 '01 '02 '03 '04 '05 '06 Annual Active Return vs Columbine 1500 Universe (eql-wtd) Decile '97 '98 '99 '00 '01 '02 '03 '04 '05 '06 Top 4.8% -9.6% -15.9% 7.5% 34.8% 14.8% 9.2% 10.5% 4.6% 2.1% Bottom -10.4% 24.3% 114.1% -33.0% -37.7% -29.7% 3.9% -6.3% -2.6% -6.5% Annual Top-Bottom Decile Spread Return (eql-wtd) Spread 16.4% -29.7% -66.9% 0.4% 95.8% 54.6% 4.3% 16.7% 6.7% 8.7% N.B., Spread figures are computed by linking monthly top-bottom spread returns Compounded Decile Active Return vs Columbine 1500 Universe through July, 2006 Decile Month 3-mon YTD 1 yr 3 yrs* 5 yrs* 10 yrs* Incep* Top 2.3% 3.1% 2.1% -1.9% 7.3% 9.2% 5.8% 5.9% Bottom -4.3% -5.6% -6.5% -0.9% -5.9% -10.6% -4.9% -4.2% Compounded Top-Bottom Decile Spread Return through July, 2006 Spread 6.5% 8.9% 8.7% -1.7% 13.0% 19.9% 2.0% 0.0% * Annualized RoR; Incep date: 12/31/97 The results reported here are hypothetical. These results do not represent actual trading using client assets. The performance of past rankings does not assure the profitability of future rankings. Copyright, 2006 Columbine Capital Services, Inc. See the Notes on Model Results. Not for general distribution. Model Analysis 24 01-Aug-2006

Valuation Model Service Columbine 1500 Universe Results through: July, 2006 Top- and Bottom-Decile Active Return and Spread Return Results in the Columbine 1500 universe, monthly rebalanced, gross of transactions costs Shading: 95th to 5th percentile range; Error bars = 1 standard deviation Current Mean Latest Month Year-to-Date Trailing-12 Months 12% 10% 8% 6% 4% 2% 0% -2% -4% -6% -8% Top Bottom Spread 60% 50% 40% 30% 20% 10% 0% -10% -20% -30% -40% Top Bottom Spread 60% 50% 40% 30% 20% 10% 0% -10% -20% -30% -40% Top Bottom Spread Top Bottom Spread Top Bottom Spread Top Bottom Spread Current 2.30% -4.25% 6.55% Current 2.13% -6.49% 8.71% Current -1.93% -0.87% -1.74% Pctile 79 92 88 Pctile 17 54 49 Pctile 12 39 25 Sigmas +0.7-0.9 +0.9 Sigmas -0.7-0.2-0.2 Sigmas -1.0 +0.1-0.5 Current: Current period return value Pctile: Percentile rank of current value in historical series (100 = best) Sigmas: Difference of current value from historical mean in standard deviations Historical Return Series: January, 1971 through July, 2006 Monthly series Calendar year series Trailing-12 month series Top Bottom Spread Top Bottom Spread Top Bottom Spread Best 12.0% -23.0% 27.1% Best 34.8% -37.7% 95.8% Best 55.7% -61.4% 223.4% 95th 4.3% -5.7% 10.6% 95th 21.0% -30.5% 53.2% 95th 22.1% -27.8% 53.9% Mean 0.7% -0.3% 1.0% Mean 8.4% -2.7% 13.9% Mean 8.7% -2.9% 15.5% 5th -2.7% 4.8% -6.5% 5th -4.3% 19.4% -18.1% 5th -7.7% 28.3% -35.1% Worst -13.3% 33.8% -47.0% Worst -15.9% 114.1% -66.9% Worst -28.1% 163.2% -80.7% Std Dev 2.4% 4.4% 6.3% Std Dev 9.5% 24.6% 28.3% Std Dev 10.9% 22.4% 35.0% Hit Rate 64.9% 55.7% 58.3% Hit Rate 88.9% 61.1% 72.2% Hit Rate 84.1% 64.2% 73.1% t -stat 5.92-1.58 3.32 t -stat 5.31-0.66 2.95 t -stat 4.72-0.75 2.61 Best: Best value observed in historical series 95th: 95th percentile value in historical series Mean: Mean value of historical series 5th: 5th percentile value in historical series Worst: Worst value observed in historical series Std Dev: Standard deviation of historical series Hit Rate: Percentage of periods with correct results t-stat: t-statistic of historical mean Copyright, 2006 Columbine Capital Services, Inc. See the Notes on Model Results. Not for general distribution. Model Analysis 25 01-Aug-2006

Valuation Model Service Results Multi-Month Periods Ending July 31, 2006 The Valuation Model Service combines multiple measures of equity valuation into one, optimized, easy to use ranking. The model distills the raw data of company earnings, cash flow, book value, and dividends into an objective forecast of the impact those values are likely to have on a stock s performance as far as three years in the future. Absolute total return in % points, based on monthly rebalancing, gross of transaction costs Equal-weighted results unless otherwise noted 3rd Annualized compound return Since May Jun Jul Quarter 2006 1 year 3 years 5 years 10 years* 12/31/97 S & P 500 Stocks Top decile Universe Bottom decile -3.01-2.88-7.49 0.29-0.08-0.08 1.62 2.22 24.68 14.02 18.53 14.94-0.21-1.45-1.45 2.48 4.88 15.49 8.50 12.31 9.31-2.82-5.47-5.47-9.70-3.32 4.64-2.26 3.18-0.36 Columbine 1500 Universe Stocks Top decile Universe Bottom decile -4.15-4.27-7.06 0.38-0.89-0.89 4.58 2.67 24.41 19.34 18.41 15.21-0.31 1.06-3.19-7.44-3.19-7.44 2.33-4.59 4.81 3.61 16.08 8.79 9.18-3.37 11.68 4.34 8.55 1.95 Columbine Total US Universe Top decile Universe Bottom decile -3.34-4.64-8.85 1.30-0.03-0.03 10.29 7.84 28.72 26.99 NA 20.42-0.80-2.53-2.53 4.56 6.94 19.11 15.91 13.42 12.08-2.84-6.13-6.13-5.46-1.85 4.51-2.78 NA -2.07 S & P 500 Index (cap-wtd) -2.88 0.14 0.62 0.62 3.34 3.58 10.15 2.46 8.69 4.64 * Includes backtest results (1971-1997). We began publishing the Valuation Model in January of 1998. The results reported here are hypothetical. These results do not represent actual trading using client assets. The performance of past rankings does not assure the profitablility of future rankings. Valuation Model Service Results Update Tuesday, August 01, 2006

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