Q:  How would you describe your investment philosophy? A: All AIM growth portfolios share the philosophy of investing in companies which generate sustainable growth in earnings and cash flows that are not anticipated by the market. We seek those companies through fundamental analysis and proprietary quantitative research. A key part of our philosophy is to remain objective. We use a balanced approach that does not focus on just one factor, but balances earnings, quality, and valuation. We’re not interested in opinions. We’re interested in the facts driving the fundamentals. We're trying to achieve better risk-adjusted returns relative to our peers and we believe that the key to outperformance in our space is a better understanding of how to avoid risks. In many cases it is defense that wins. We do everything we can to avoid owning high-risk stocks, or stocks that have the potential for earnings disappointments, unsustainable growth, or are just too expensive. We have screening tools that identify high-risk stocks with great accuracy, mostly tools which have been developed in-house and proprietary screenings. For example, we look at balance sheet metrics that show if inventory and accounts receivables become problematic, or if there is a divergence of growth in cash flow versus net income. More than 60% of the time companies that fall in these high-risk models underperform by levels of over 1,000 basis points on average. Q: Would you define your universe? How many stocks belong to it? A: Our universe is comprised of stocks with capitalization of more than $5 billion and growth rates of more than 10%. This comprises approximately 400 stocks. We’re a style-pure large-cap growth fund, so the vast majority of our assets are in companies with market caps over $14 billion. Q:  Since a key part of your philosophy is avoiding stocks with risks not identified by the market, could you explain what you do to understand the risks ahead? For example, how does the news that Intel’s revenue will be below the forecast fit? A: Our risk models are proactive and combine different factors. It’s not just cash flow or net income, but the combination of factors that makes the model powerful. We identify expensive companies that cannot sustain growth. These stocks are likely to underperform, and it's a predictive model. We had no exposure to Intel because of our fundamental analysis. According to our internal earnings projections, estimates were too high. It also didn’t rank well on our screens. The thrust of our fundamental research is challenging Wall Street’s assumptions to figure out what these companies can really earn. We own companies that rank well on our quantitative models and fundamentally, based on objective facts, have achievable or low earnings estimates. We maintain a disciplined approach with a focus on finding earnings discrepancies versus consensus expectations. Q:  In terms of your strategy and process, can you explain what parameters you monitor and why? A: We have a balanced, objective, and non-emotional approach. As we’ve discussed, we commence with risk models, eliminating high-risk stocks as potential portfolio candidates. In addition, we employ our quantitative screens, including examining earnings because we believe that earnings growth drives stock prices over the long term. We look at quality, which we measure in many different ways. We look at profitability measurements such as gross margins and balance sheet metrics. We look at capital use because managements decisions about how to deploy capital are very important. Is management shareholder friendly? Do they buy back stock? Do they raise or initiate dividends? Or, are they planning acquisitions that we know are deleterious to shareholders? We objectively look for both strong and sustainable growth. Finally, we measure valuation. In our space, we've found that the most effective way to value companies is based upon cash flow measurements and, in particular, cash flow yield. It’s a very balanced approach with multiple factors. We believe you need different factors to achieve consistent returns, because there are times when certain factors are ineffective. The purpose of these screens is to remain fact-based, focusing on companies that will outperform. We’ve back-tested these factors, most of them for at least 20 years, and our model should outperform the market. We couple our buy and risk models together in order to narrow our universe. Then we do focused, fundamental research. Fundamentally, we want to identify and understand the drivers of companies that can exceed expectations, not only because that's a positive catalyst to the stock price, but also because it’s a great defense against getting surprised on the downside. We break down Wall Street’s models and assumptions about revenues, earnings, selling, general and administrative expenses, etc., and we challenge those assumptions and try to discover where they’re wrong. If we can say that a company's revenues are too low, based on a new product cycle, or margins are too conservative because of cost-cutting programs, that greatly reduces the chance of owning a company like Intel when it misses earnings estimates. Q:  You said that it’s part of your DNA to avoid high-risk stocks. How do you define expensive stocks? Do you use historical or forward-looking earnings? A: We mostly value our universe using free cash flow measurements, (based upon forward-looking numbers) historical free cash flow, and a company’s relative ranking to our universe. We also look at forward-looking Price/Earnings metrics, but to a lesser extent. Valuation is a component we consider in identifying certain high-risk stocks. Q:  How is your research team organized? A: We have a team of analysts divided into sectors, who do fundamental research on the companies that we own, or that rank well. In addition, AIM has sector funds with their own teams. Our team is able to tap into these different teams, and that's a rich resource of information. Our analysts look at industry factors, such as addressable markets, the competitive environment, pricing, product cycle, etc. Then, they look at company specific factors. We’re trying to find all the different fundamental factors and drivers of a company’s performance, where it differs, and most importantly, where we can get ahead of Wall Street. Our analysis is based on factual data, not on opinions or top-down calls. It is all about what's happening at the company, using objective data to determine why, and to what extent, estimates are low. Our analysts input internal earnings expectations into a spreadsheet that contains data about what we think the company can earn and where it differs from the Street. Q:  In terms of portfolio construction, can you describe the types of holdings, the turnover, the sector ratings? Do you follow any benchmarks? A: We own 50 to 80 stocks in our portfolio. Typically, the largest holding is around 5%, but there are few large holdings. It’s a diversified portfolio across different sectors and industries, but is built with a bottom-up process. We also make sure that the portfolio doesn’t become too concentrated in the most expensive stocks in our universe. We're compared to the Russell 1000 Growth Index, but we're not an indexcentric manager. We won’t own a company unless it meets our strict criteria. Over time, we won’t look like the index. Q:  Could you give us some examples of stocks that your research process successfully identified and an example of when it didn't work so well? A: Nordstrom’s (the department store) would be a good example. A couple of years ago it ranked well in our models and our analyst found same-store-sales expectations to be conservative. Additionally, Nordstrom had implemented a new inventory management system, becoming more efficient. Their margins were low. Based on the fact that same-store sales and margin assumptions looked conservative, our analyst projected that numbers should move higher over the next year. We bought the stock and both same-store sales and margins exceeded expectations. Of course, there are stocks where our process fails. An example was Dell last year. It ranked well in our models. Through our fundamental work, we identified a couple of factors that would provide a cushion to earnings. First, we thought that their market share would accelerate, as IBM was selling its PC business to Lenovo, because every time we had seen disruption in the PC channel with these types of deals it led to share gains for Dell. In addition, Dell was generating excess free cash flow, which we expected to be used to buy back stock. We thought this aggressive share buyback was not properly factored into estimates. We were right about those two factors, but we missed one point. Average selling prices came down faster than we expected. Dell mispriced its products, which caused estimates to come down and Dell's stock underperformed. Q:  Since you invest in large companies with multiple product segments, geographic markets and currencies, doesn’t it get difficult to track 400 companies? A: Yes, there are a lot of moving parts with these large companies, and we know that sometimes we are wrong, but that's why we have a diversified portfolio. We believe that it’s all about a disciplined, objective approach. Even with large companies, there are usually a couple of important drivers that you can point to in the income statement, while most other factors cancel themselves out over time. The important part is identifying the main drivers. A recent example would be Hewlett-Packard. The new management team focused on reaccelerating the top line through new products and on expanding margins through cost cutting. In that perspective, the top-line assumptions were not aggressive. We thought that they could at least hit those numbers with new products and identified cost savings. Q:  What are the milestones of your risk control process? A: Our whole process is focused on doing a better job than our competitors in managing risk, and we believe that's one of our advantages. By identifying highrisk stocks and carving them out of our universe, we believe we have a clear relative advantage with regard to risk management. Furthermore, we limit exposure to the most expensive stocks in our universe. We also use software tools that allow us to identify fundamental and macroeconomic risks in our portfolio. For example, what happens to our portfolio if interest rates jump unexpectedly, or if oil prices skyrocket? Overall, we use a diversified set of tools for risk management.