Q: What is the history and structure of the fund?

While the fund has a more than seven-year track record, the investment strategy we employ in managing the stocks within the portfolio has a nearly 20-year track record. 

We were hired seven years ago as a sub-advisor for a predecessor fund. That fund was renamed the Wells Fargo Advantage Large Cap Core Fund and still maintains the same overall investment strategy and process—it has the same process, the same portfolio manager, and the same philosophy. 

The fund contains 50 stocks at any given time, all weighted about equally, each with about a 2% position. Two ways in which we likely differ in comparison to other large-cap equity funds are that we are a little on the low side as far as the number of names we own, and that most others do not maintain equal weights as we do.

Our main performance benchmark is the S&P 500 Index, which consists of domestic medium- and large-cap companies. Although this is a large-cap fund, we own what are considered large and mid caps, because they are what dominate the U.S. economy. 

The positions we manage in this fund are, without exception, domestic. We even avoid ADRs [American Depository Receipts] in order to remain wholly domestic in our investments.

Q: How would you describe your investment philosophy?

I want each of the fund’s 50 stocks to have a high likelihood of the company reporting a positive earnings surprise. And of the ones we predict to possess a high probability to exceed expectations, I select from among the most undervalued. 

The quantitative work we do may tell me that profit margins are improving, but we like to look under the hood to see what is driving these numbers to gauge whether or not the improvement is sustainable. 

Our qualitative analysis focuses on looking inside each company to get a read on those metrics that look good, to distinguish between the ones that look good right now versus the ones that are likely to remain looking good and possibly continue to improve. 

Q: What is your investment strategy and process?

Investing is both a science and an art, and we apply both in our analytical approach, combining quantitative or scientific and qualitative or more artful analyses. Our intent is to narrow the broad investment universe to a handful of names that we feel represent our best new opportunities, the best candidates for our 50-stock model portfolio.

We have a proprietary quantitative model that incorporates multiple factors designed to give us objectivity, uniformity, and consistency in the way we evaluate the overall broad universe of medium- and large-cap companies. I don’t fall in love with companies; what I love is seeing moneymaking opportunities. That objectivity is important to us.

There are 50 stocks in my portfolio and 500 in the S&P 500. And, typically, there are about 1,000 to 1,200 companies in the overall broad universe of medium- to large-cap companies. Our quantitative model ranks these in order, from number 1 to 1,200, based upon the investment merits of the multiple factors that make up our proprietary quantitative model. We consider three types of measures: valuation, earnings, and momentum.

Quantitative factors include metrics such as multiples of earnings and cash flow and growth in those two metrics. On the earnings side, we look at a company’s history, its consistency in reporting positive earnings surprises coupled with past estimate revisions from Wall Street analysts, and its forward-looking earnings estimates and subsequent revisions that may follow a company’s forward-looking sales estimates, as well as some momentum measures. 

Momentum includes relative strength of the stock and its trading volume. We review the recent trading history to determine whether, when the stock hit its high, volume surged or was weak. We ask ourselves: when the stock hit its low over the last month, did volume surge or did volume dry up? That reveals investor interest. 

The valuations, earnings, and momentum factors that make up our proprietary quantitative model are simply the first pass in evaluating the stocks. Over the entire universe of 1,200 companies, we will consider only the top quintile, the top 20%, as new purchase candidates for the portfolio.

At that point, we begin our fundamental qualitative analysis. We look at each company with an eye toward investment merit and risk. We look at new products, new management, the organization of the company, and past history of their success level on acquisitions and divestitures, for example. 

Q: Would you share some examples of your research process and how you look for opportunities?

One thing I like about our investment process is how objective it is. There are no biases involved. If a stock has merit, the quantitative model will push it up to the top of our list for consideration.

For example, we have owned Hanesbrands Inc. for a couple of years. When the portfolio was a bit underweight in consumer staples, I was looking for fresh ideas. I was not thinking in terms of consumer discretionary, of apparel, or that Hanesbrands was the way to go. But when we performed our straightforward quantitative analysis, it bubbled up to the top. 

Hanesbrands ranked among the top of each of the three sub-composites within the overall composite, and it ranked in the top 10% overall, on valuation, on earnings, and on momentum. Quantitatively, it looked good. Even though Hanesbrands is considered consumer discretionary versus consumer staples, the company primarily makes items that are fairly necessary to everyday life: underwear, t-shirts, and some sports apparel items. 

So, here was a consumer discretionary name meeting all our criteria. As a result, I am a little overweight in consumer discretionary, but this is a consumer discretionary name that gives me features like one would find in consumer staples.

Skyworks Solutions, Inc. is another example of how we conduct our research process. It’s a technology company that’s involved mainly with semiconductors. In my portfolio I had a couple of sell candidates within technology, specifically semiconductors, because even though the quantitative model was showing a lot of semiconductor names as ranking highly, those that were primarily dependent upon personal computers were starting to show weakness both in terms of their price and some of our quantitative rankings.

One such sell candidate was Marvel Technology Group Ltd, another semiconductor name, but one that was more heavily tied to personal computers. More compact, portable products like tablets and notebooks were taking a serious toll on the personal computer marketplace. In contrast, Skyworks is much more tied to mobile devices and IoT, the Internet of things.

The qualitative analysis of Skyworks validated the quantitative work. A higher content of its technology was being installed inside devices dominating the marketplace, devices it was designed for, such as Android and Apple phones. Both of those customers are expanding and growing. 

When you are taking share and your end clients are growing, that is unquestionably a good thing. This was an opportunity for me to upgrade the portfolio, selling Marvel and replacing it with Skyworks.

Wal-Mart Stores, Inc. is another good example of a name th?at was in the portfolio at one time. It was still highly ranked in the total composite model, but was unbalanced with low valuation and somewhat unfavorable earnings potential. Just because your shares are cheaply priced does not automatically make you right for this portfolio. I am not just looking for undervalued companies or turnaround situations where it might take a while to play out. Wal-Mart failed to impress us on the qualitative end, specifically the earnings side.

When I viewed the results of the qualitative analysis, it felt like a value trap. On the earnings side, estimate revisions were heading downward, so while this was a low-priced stock, one that a lot of investors might favor in terms of its history, we refuse to fall in love with companies. 

We look for diversification of opportunity, not just one opportunity in a particular investment. The qualitative work we did indicated that Wal-Mart was a value trap, a sell candidate. And so I sold our stake in Wal-Mart last fall. 

Right after I sold it, energy prices declined steeply, and Wal-Mart began performing quite well for a while—it was a cheap stock and had investors thinking that everyone would take the dollars they saved at the gas pump and go shopping at lower-end retail establishments. Interestingly, there was no sign of this anticipated follow-through by the consumer, and so earnings proved a disappointment for Wal-Mart.

Q: What is your portfolio construction process?

We start by looking at the broad investment universe and narrow it down to just a handful of companies representing the best new candidates for the portfolio. Revisiting this regularly and objectively is what keeps our portfolio fresh. Our main objective is always to seek companies likely to report at or above earnings expectations while composing a portfolio that is more undervalued than the market, one that is selling at a lower P/E ratio.

The construction process has alpha, but it also includes risk controls. There are 1,200 companies in our investment universe and so our first step is always to apply our quantitative model to determine which stocks rank in the top 20%. That is only the alpha measure. Of those 200 companies, we must still rank them best to worst qualitatively, analyzing which companies rank at the top in terms of valuation and earnings and have momentum. This boils our list down to the top 80 or so companies on an alpha-excess return.

One of my goals is to have my sector weightings resemble the S&P 500 Index, which has ten sectors. We like to be at a plus or minus 5% weighting relative to the S&P 500. Sector and industry weightings reflect a form of risk assessment in the portfolio. Market cap is another assessment. We do not want the size of our portfolio to be measurably large cap or measurably small cap versus the benchmark.

We use the Barra risk model. Some of the common factor risks within this model are in momentum, beta, volatility, growth tilt, and value tilt. In this portfolio we gauge the risk factors and prefer to tilt it toward momentum and value. The current portfolio has positive exposure to both the value risk factor and the growth risk factor; we like that diversification of investment opportunity.

One thing that may set us apart is that we want a high conviction level on every one of our 50 names. When we buy a stock, it is to replace a stock that we are selling. So, we bring in the new stock on a full weighting, meaning it has gone through a rigorous evaluation before we start to buy. Every new company, every new position, comes in with a full 2% portfolio weighting. That is what goes to the trading desk, which works the order in a way that has minimal impact in the marketplace. 

Again, our buy discipline is such that each stock has to rank in the top quintile for it to even be considered. At that point, it goes through further scrutiny on the qualitative side to determine investment merit, and on the risk control side, via the widely accepted risk model that we use. 

In the same way, our sell discipline is such that any stock in the portfolio whose quantitative model rank falls below medium of the entire universe automatically becomes a sell candidate. We do the same quantitative analysis before we sell as when we buy, and then we look inside the company. If we think its fall is just a slight or temporary blip within the company, as far as why some of the metrics have declined, we might wait for the next ranking to see, but if there is significant shortfall in some of the metrics, it becomes a strong sell candidate. There’s no hesitation.

The reason we take such an objective approach is that the substantial history in our model shows that the top quintile stocks, according to the parameters of our quantitative model, outperform other stocks. Stocks ranked below medium, on the other hand, tend to underperform the overall market. 

Our sell discipline means that we have an objective indicator to highlight any potential sell candidate, one that alerts us to begin looking for a replacement. That measure of objectivity on both the buy and sell discipline has been rewarded in the portfolio. Why? Because the overall market goes through changes. The market goes up; the market goes down. Sometimes it orients toward growth, and other times it’s more value oriented.

By using a combination of both quantitative, bottom-up metrics and the qualitative to gauge what is going on in the market and what is going on in the company, and what risk controls I need to favor or move against, it enables us to construct a portfolio that has outperformed in all different market environments.

We start each position with a full (approximate 2%) weighting as all the others and let the market take it from there. Then, for risk control purposes, once a stock reaches 3% to 3.5% weighting, we trim it back to avoid the specific risk issue. When we sell a stock, we sell all of it. It becomes a zero weighting in our model portfolio. We give that trade order to the traders and let them work it in a way that yields minimal market impact.

The high conviction level that we insist upon for both buys and sells is what hedges us against the danger of falling in love with a particular stock and letting that cloud our investment thinking. We either want it in the portfolio or we don’t. It’s black and white, all or nothing. We bring it in at a full position and we sell it completely when it triggers our sell discipline.

Q: How do you define and manage risk?

Risk is an important factor, and there are, of course, various types of risk. Whether you are a client who has been with us for a long time or one who has only been with us for a short time, we do not want you to be surprised when you see the performance and the portfolio results.

For example, in both 2009 and 2010, we underperformed the S&P 500 Index by a small measure, but our clients who know us and understand us were not surprised. The market during that time period was dominated by top-down macro events, such as the fiscal stimulus program. That unprecedented stimulus, for example, resulted in a boost in the bottom line of poor quality companies, those most desperately in need of a lifeline. 

The increase this injection of liquidity into the economy represented to their bottom line served to inflate their stock price, unfairly in our eyes. That bottom line boost came not from developing new products and taking market share, but from monetary policy and an ostensibly one-time infusion of government-sourced capital. 

Our buy discipline, with its strict parameters and focus on sustainable earnings, prevents us from being tempted to buy such stocks. You need to be disciplined and consistent in your process and style adherent for that kind of risk control to take place. Our clients see our performance and are not surprised at how we perform in up or down markets.

Another measure of risk, again from the client’s standpoint, is how we protect them in a down market. In the 19 calendar years that we have managed this product, there have been four years when the S&P 500 was down. We outperformed the index in all four of those years. Our downside capture ratio is around 80%.

The third measure of risk concerns the portfolio manager. I ask myself: what are the risks within the portfolio and the positioning of the portfolio? My decisions on diversification, sector weights, industry weights, and common factor risks are predicated upon this. We use our industry-accepted risk management tool to determine whether we have high or low beta; a more momentum-oriented portfolio or a defensive one; a more growth-oriented portfolio or a more value-oriented one. 

We apply tilting and sector differentials in our portfolio management. If there exist, for example, more healthcare names in our list of the top 20%, especially within the top 100 names, I will tilt the portfolio in that direction. If we see more of a value tilt in our top-ranked companies, we’ll tilt in that direction instead. This does not represent a major risk for us because of our commitment to equal weighting among our positions—we don’t make large bets. 

We prefer a broad exposure to our best ideas and what that tells us.