Steven Cress' 6 picks: 3 dividend income, 3 AI growth stocks

0:10Steve Cress, our head of quant at Seeking Alpha. Always fantastic to talk to you on Investing Experts. Welcome back to the show. Rina, thank you so much for having me and organizing this today. It's a pleasure to be back. People that may have missed your last episode on every metric that we measure. It surpassed by far every previous episode that we've had. So really want to encourage those listeners that haven't heard it, you shared with us three stocks to buy from the PQP, the ProQuant Portfolio, and AlphaPix. It was extremely salient, I think, for investors to understand how those portfolios, what the strategy is behind it, the timelines, how frequently you're in and out of names.

0:59Share with us maybe if you could just catch listeners up that didn't catch that episode and that just need a refresher in general, how you're approaching stocks with the quant system. A very brief, I think, refresher would be instructive. Yeah, absolutely. And a little bit about myself. I've been in the investment world for about 35 years. The bulk of my career was spent at Morgan Stanley, where I worked for 13 years running a prop trading desk in quantitative strategies. Later, I would work at Northern Trust heading up international investments. I also founded a hedge fund that was focused on quantitative strategies.

1:41And simultaneously, when I was running the hedge fund, I also started a FinTech company, which was an early version of AI and a systematic stock picking model. That Seeking Alpha likes so much, they bought the company. And that is what has brought me here today, as we have integrated the quant into the Seeking Alpha platform. So, a little bit about what I would like to cover today. As Rita just indicated, I'm going to give her a little refresher on why quant. The last presentation, as she mentioned, we went over a couple of our top ideas from the PQP portfolio and from the AlphaPix portfolio. But considering markets have been so volatile and whipsawing over the last month, I wanted to present a different strategy today.

2:26And I refer to this often as a barbell approach, since there's a lot of uncertainty with the environment, the economy, the market, the Fed and interest rates, tariffs. A good approach right now in periods of uncertainty is to use, again, what I refer to as a barbell approach where we'll focus on top income stocks, but we'll also focus on top AI stocks that we expect to do well. So, that's sort of combining growth with income. And we're going to get into that in a little bit. First, to answer Rina's question and give a little refresher, how do we achieve our results with the quant system? Well, the quant system is really very similar to what a fundamental analyst does.

3:07If you were an analyst at Merrill Lynch or Morgan Stanley or Goldman Sachs, you would apply fundamental analysis techniques where you look at conventional metrics for value, profitability, growth. The only issue is when you are an analyst of that sort, you're only capable of maybe covering 15 to 20 stocks. And typically, they do it in one sector. And often, in their coverage of 15 to 20 stocks, because there's limited time in writing up these companies and how they're being impacted by the environment or earnings, they typically can only get a handful of reports out every month. And this is where the power of quant comes in.

3:46We still apply the same fundamentals. Quant fundamentals and metrics can be different. What we use is what I refer to as a GARP approach. At Seeky Alpha, GARP would be growth at a reasonable price. And we also add a little extra to that. We focus on momentum. And we also focus on positive analyst revisions as well. So, it's really a dynamic model. We're focusing on a couple different styles. We like the diversification because we believe that diversification minimizes risk and maximizes returns over the long term. So, then we add the power of computer processing, which really helps put the quant word into it.

4:25We look at it sometimes as quantamental, where we combine quant and fundamental. But the power of that computer processing gives us the ability to cover about 4 ,500 stocks versus a human analyst that could maybe only cover 15 to 20 stocks. And we, through our power of computer processing, can issue fresh directional recommendations on a stock every single day. So, literally every day, we go through every company's cash flow, income statements, balance sheets, hundreds of financial metrics. We update it every morning between 4 a.m. and 6 a.m. And based on the fresh data that comes out, every single day, we issue, in essence, a new directional recommendation.

5:06Now, often that directional recommendation gets, say, the same. It could be a strong buy or hold or sell. Sometimes it changes. It's all based on how the data comes in. And when we look at a company and we make that decision for buying or selling, what we do is we measure the strength or weakness of that company and its metrics and its balance sheet and income statement against other companies in the same sector. So, it's really a relative analysis. And that's how we have the ability to really rank 1 through 4 ,500. And then within sectors, the strong from the weak. So that's a little bit of a refresher there.

5:42And the system works. Our simulated trades, this is not really an investable product because on any given day, there's about 350 to 400 strong buys. But what we are showing is a Dell rebalance of our strong buys versus a Dell rebalance of Wall Street strong buys and the S &P 500. And you can see over the last five years, the Seiki Alpha quant strong buys are up 219 % versus Wall Street analysts for the same period. Their strong buys are up only 33%. And they actually underperform the S &P 500, which is up 64%. But the quant absolutely crushing both using our methodology. So, I thought, you know, what we would do is talk about something a little bit different, as I mentioned.

6:26Considering there's been a lot of volatility in the markets, I sort of like a barbell approach. during periods of uncertainty. The S &P 500 is really unchanged from where it was four weeks ago, but it's had some big swings up and down in that period. So, we're really uncertain as to what could transpire over the next few weeks. So, volatility could remain with the market. Largely, that volatility has come from the government shutdown, which is now over, but it was just about the longest government shutdown we ever had. It went from October 1st to November 12th. Previous to the government shutdown, the markets were optimistic because the Fed was on a trend of cutting interest rates.

7:06And they were cutting interest rates because there was concern over labor. They felt that at the time, that was outweighing the sticky inflation that the economy is still experiencing. Unfortunately, that sticky inflation is still around. There are a number of elements that contribute to it. Tariffs are really starting to have a fuller effect now compared to when they were announced many months ago. So, the Fed is uncertain with the data that they're seeing. And in fact, most interest rate traders are sort of split between feeling if there will be a rate cut or there will not be a rate cut and the size of that rate cut.

7:43And with market volatility, actually, just over the last five days, the best performing sector has been energy, utilities, and consumer staples. These are real and healthcare. Even though they're down, they have outperformed technology, consumer discretionary, and financial services down by about 4%. So, what this indicates us is that there's a rotation to safe haven sectors and stocks. And clearly, we have seen that in stocks. Many of the consumer discretionary companies, technology companies, small cap, mid cap, really selling off quite sharply over the last month. even though the broader index is unchanged.

8:19Some of the sectors that are more risk-on have really come off, and stocks within those sectors have come off. So, the market's been getting very defensive, and headlines that you see are probably very typical of what we saw. Meta opening up down 1.4%. AI bubble fears are in the spotlight. So, for equities, valuations have been stretched. For many AI stocks, they have been extremely stretched, and we no longer have the confidence that the Fed will continue to cut rates. So, that has introduced a lot of uncertainty and volatility. FedSpeak Index is near the most hawkish that it has been, really going from the negative domain to a positive domain, with the Fed sort of increasing that hawkish sentiment.

9:03When we had the government shutdown, there was delayed key economic data. That creates uncertainty because we don't know what economic data will be coming out. Is it good? Is it bad? So, in coming weeks, we will see more economic data. But there's definitely been a lag in it. Fed officials have definitely, as I mentioned, turned more hawkish, suggesting a third cut may be unnecessary during the month of December. In addition, outside of FedPowell and his hawkish sentiment, the Kansas City and Boston Fed chiefs, Jeffrey Schmidt and Susan Collins, both mentioned further cuts could stall the 2 % inflation target.

9:41So, investors await the release of backlog data, especially the September job reports. Interest rate traders on November 6th, 70 % of interest rate traders expected a rate cut in December. 30 % did not. Today, 53 % of traders expect a rate cut, and 47 % do not. So, it's really evened out. Nobody's really sure what's going to happen. So, in addition to that, looking at general sentiment for the market, I often look at an index called the CNN Fear and Greed Index. It's just about as good as any to give you an indication where market sentiment was. And a couple of weeks ago, I'd say four to six weeks ago, we were in the greed territory.

10:21Then it went into neutral. Last week, it was in the fear territory. And now, it's in the extreme fear territory. So, a softer labor market could really anchor expectations for those rate cuts. and we'll have to see what happens on the back of that. We could see a pullback, as we have seen with some of the broader market, not necessarily the Magnificent 7. They have come down, but not nearly as much as the broader market. So, we could see a retraction, and we have seen a retraction in the valuations of many AI stocks and many tech stocks and consumer discretionary and small and mid-cap. Having said that, Buffett seems to have confidence.

11:03He took a new position in Alphabet, and it was a huge position of$4.3 billion, which signals confidence in AI from one of the market's most traditional and cautious investors. So, I think that's a fairly good sign. AI stocks with strong fundamentals and durable demand do remain well-positioned for a long-term recovery. So some of them have come down, and mostly the ones that have to do with powering up data centers and the infrastructure, which were really rocketing earlier in the year, have come down considerably. But the earnings outlook and really recent earnings for many of these companies, both top and bottom line, were very good.

11:45So it's really a market that's being driven by sentiment more so than fundamentals. Can I ask to that point, something that Brian Stewart and I have been talking about on the Wall Street Roundup podcast on Fridays has been this notion of the fact that it's so difficult to ascertain valuation, specifically with AI related names. and the fact that if you look at the quant ratings for almost every AI name, the valuation grade is a D or an F. And Brian was saying that in this time, he's kind of taking valuation out of the picture because there are other elements that play beyond fundamentals. What would you say to that in terms of grounding quant's place in this market and also the nature of or the notion evaluation?

12:31Yeah. So, you know, with a quant, I believe it's a very flexible model. We can have a stock that's rated a strong buy or buy with a valuation grade of a D. So, it's basically D through A plus can allow a stock to have a strong buy. When it does move into the D minus or F territory, that's sort of a circuit breaker. And if you do see it, and often those stocks can be a a hold, or sometimes a sell, it does mean the valuation is extreme. And our preference would be to look for stocks that have a better valuation framework. And it doesn't have to be much better. So, the company could still have substantial growth.

13:14And you could still have a valuation grade of a D or a D-plus and buy the stock. So, that has kept us out of some stocks like NVIDIA, which has done really well. And at one point, like Tesla, when it did really well, the valuation grades were F. and the system didn't allow us to buy it. But I will say, the system also recommended other stocks that actually outperformed those stocks. And we have a very good track record. As I showed you with that long-term track record, we've beaten the S &P 500 every year since 2010 using our methodology. So, I would say you could be flexible with evaluation, but only up to a certain point with our quant model.

14:00So, you know, once you see that D minus or F for the valuation grade, it could be a winner and we could let that winner run as a hold, but we're not adding to the position. Appreciate that. I hope that gives a little bit of an explanation. So, you know, conversely, I would say if I took the other side, you know, this quant model we're running in like 1999, 98, the year 2000, it absolutely would have avoided a lot of the stocks that blew up. And in fact, having run the model back at that point in time, I could tell you what it did do. Is that actually in 2001, 2002, 2003, it started focusing heavily on industrial and material stocks.

14:42And it was actually an incredible period for our quant. The quant product that I was running at the time was actually for Morgan Stanley on the prop trading desk. So, during that period, the quant model absolutely did quite well. It avoided a lot of the blew-ups that occurred during the TMT era. If you were in 1997 through 2000, people could have argued, oh, there were many stocks that had no earnings and no revenue, but the stocks were appreciating by 1 ,000%. They were 10 baggers up until they did. So, it gives you a little bit of history, a longer history on the model, which brings us to the focus.

15:20There are AI stocks that we do believe are attractive at this level. But since there is uncertainty and volatility in the environment, I also want to make the case for a couple defensive stocks which have quality yields. As I mentioned, we have strong labor data that will reduce the likelihood of a near-term rate cut, and that will add to the uncertainty of the equity markets. In volatile environments, investors can often rotate towards dividend stocks that have reliable earnings, steady cash flow, and attractive yields. And, of course, quality high-dividend-yield stocks can provide stability during periods of uncertainty.

15:55So, without further ado, I want to go into three income stocks that I like. We have Merck, which is a healthcare company, pharmaceutical. It's a tremendous company. It's got a market cap of$230 billion. It has a quant strong buy rating. And our quant system within the healthcare sector ranks 8 out of 976 stocks. And within the pharmaceutical industry, it ranks 3 out of 177 stocks. Mostly, people know that this company operates through pharmaceutical and health animal segments. The company has a tremendous ROE. It's a 40 % return on equity. The Ford EBITDA growth is 47%. It is dirt cheap. The multiple in this company, the Ford PE, is 10.4 times.

16:40And the interest coverage ratio for the dividend is 21.3 times. So, actually, what I'd like to do is take us into the platform. I'm actually on the premium platform where you could see Merck stock is up a little bit today. Year-to-date, the stock is down 4.5%, but we do have a quant strong buy on it. Over the last month, you could see the stock is up 10.63%. So, when the S &P has been flat, this is actually appreciated. And if you look to the right side, you'll see the rating summary. That rating summary actually shows you three independent sources. It is CK Alpha contributors, and the consensus there is buy.

17:22Wall Street consensus is a buy. And the quant system has a strong buy. So certainly over the last month, the quant system has definitely been right on that. What makes up that quant strong buy are the factor grades underneath. As I mentioned, we look at five core factors, which would be valuation, growth, profitability, momentum, and EPS revisions. And if we clicked on valuation, you could see that the underlying metrics look really good. And what we attempt to do by showing these academic letter grades, we want to give you an instant characterization of how the company compares to its sector.

18:00So, when you look at the PE and it has a B +, the absolute multiple is 11 times, the sector is 17 times. So, it's at a 36 % discount to the sector. hence the B-plus grade. And the forward P is actually even more attractive at 10.7 times versus the sector at 18 times, hence the A-minus grade. So, that academic letter grade instantly tells you, okay, this stock has a better valuation framework compared to this sector. If we were to go to growth and we scroll down to, say, EPS, forward EPS growth, it has an A-plus. The Ford EPS growth rate for Merck is 80 % versus the sector with just an 8 % growth rate, hence the A-plus grade.

18:46So you can see the earnings per share growth is absolutely tremendous for Merck at this time. So from a valuation standpoint, it looks great. From a growth standpoint, it looks great. From a profitability standpoint, it's an A-plus. If you look at the EBITDA margin, it's 49 % versus the sector at 9.2%. If you look at the return on common equity, it's 39.5 % versus the sector at negative 34%. So, Merck looks really good there. And if I go back to the main stock page, you can see the yield on this stock is 3.36%. So, that's almost more than three times the yield on the S &P 500. And it's also about three times what you would get on the VIG, which is the Vanguard Income and growth ETF, which is commonly used as a benchmark.

19:36So, Mark looking really good there. I am going to take us to Alpine Income Property Trust, ticker symbol P-I-N-E. So, this is a smaller REIT. The market cap is about$252 million, but it is a quant strong buy. Within the REIT segment, it ranks 9 out of 172 REITs. And within its industry, which is diversified REITs, it ranks one out of 12. The forward yield on this is 6.94%. That is a whopping yield. It is a diversified REIT. They own and operate a portfolio of 128 commercial properties across 34 states. So, that certainly provides a lot of diversification. Current occupancy is currently at 99%, with 48 % of those occupants being investment-grade tenants.

20:25In terms of metrics that we look at for REITs, We typically look at FFO or AFFO, and then we take multiples on that. So the Ford price over AFFO multiple is 9.1 times. That puts out a 40 % discount to the sector. The Ford AFFO growth is 9%, which is a 277 % premium to the sector. And the AFFO margin is 48%. So really great stats there. If you look on the far right, you can see the rating summary for both valuation and growth. It has an A, A minus, an A, profitability at B minus, momentum very strong. And then you can see the dividend safety grades are fairly solid in line with the sector. Can you take us through for a second the metrics that you're using for the REITs specifically, like the AFFO?

21:20Can you talk to us for a second about why those matter for REITs? Alpine Income Property. You can see today it's down about 2.66%. And today, we had a bit of a rotation actually back into technology stocks. So, some consumer staples and REITs sold off. So, just a lot of confusion with the markets. Year-to-date, this stock is flat. But the really cool thing about it is you can see over the last month, the stock is up 15.64%. And you can see, even with the stock being up that much in the month, the dividend yield, as I mentioned, is 6.88%. Now, to answer Arena's question, metrics that we utilize for REITs are different than stocks.

22:03So, we basically look at 11 sectors in a very similar format, but REITs are a horse of a different breed. So when we look at valuation metrics for REITs, we will see, we try to make it very centric. So you're not going to see this for stocks where we have AFFO and FFFO. That is really solely for REITs. So what we're doing is we're looking at the metric compared to other REITs. And you can see from a valuation standpoint, it is attractive. The multiple is 9.3 times for the stock versus the sector at 14 times, putting it at a 34 % discount for price over FFO. When we look at price over FFO, it's still dirt cheap on a forward basis.

22:53It's, again, 9.12 times versus the sector at 13 times, a 31 % discount to the sector. And we do look at some of the other conventional metrics, such as EBITDA or price of sales, where it comes in. The valuation grade is made up of the underlying metrics. But again, these are a bit different than you would see for stocks. If we look at growth, you can see we're looking at AFFO growth and FFFO growth, along with a lot of dividend data as well, and EBITDA data. So again, there's a mix of metrics there. We're taking a combination of these metrics to come up with the overall growth grade for the REIT.

23:34But again, very centric towards REITs with the metrics that are used here. I might add to, I'm going to go back to Merck because I actually want to show the dividend grades. So, dividend grades are something that's really unique to Seeking Alpha. I'm not familiar with any other platform that shows it. When we look at a stock, we are looking for capital appreciation. So, that quant rating signifies the potential or lack of thereof for appreciation. and we use the factor grades for that. But many investors look at dividends and they want to know when they buy a stock, is that dividend safe and is it growing?

24:12So, we take a look at that. We have underlying metrics that we've used and backtested to indicate to us if that dividend is going to be safe. So, as you look at this picture, the cash dividend payout ratio, the dividend payout ratio, cash flow ratios, dividend coverage ratio, interest coverage ratio, and we have backtested these to 2010. And we know some of these metrics are more predictive than others. So, these aren't equal weighted. Some have a higher weight. And you can see some of the ones that have a higher weight contribute to the overall A-minus dividend safety grade. And just to give you a little sense of what that backtest looks like, if you were to take a look at our stocks that had a dividend safety grade of A plus to B minus, 98 % of the dividend cuts would have been averted by owning a stock that had that dividend safety grade, anywhere between that range.

25:08Conversely, going back to 2010, 70 % of all stocks that had an F had cut their dividend. And 93 % of stocks that cut their dividend had a dividend safety grade of C plus to F. So, it's really a very, very powerful system. If you are a dividend investor, I would highly recommend that you use the dividend safety grades. We have a portfolio tool, easily allows you to load your stocks up to it just with the ticker symbols, and then it will show you what it looks like. And I can probably give you a picture of that right here. So we're going to take, let's see, Berkshire Hathaway. There are a number of tools that we could use here.

25:47You could look at performance. You could look at profitability. and what I want to pull up here is dividends and see if we have that. Yep, dividends. And when you click on dividends for Berkshire Hathaway, you can see which companies have a dividend. I can actually sort it by the strength. And some have a dividend safety grade of A +, some have a C. Purpose being here that you could load up your stocks and see what the dividend grades are. So, it's really a great tool. Taking us to our third stock, which is One Main Holdings. That is a financial company. It's got a market cap of$6.7 billion. Within the financial sector, it ranks 25 out of 683 stocks.

26:26Within its industry, which is consumer finance, it ranks 3 out of 38. This has a whopping yield of 7.36%. This company provides personal loans and credit products to non-prime consumers. So, a little bit more risk there, hence probably the higher yield. But you can see with a dividend safety grade of A-, our quant system is not concerned regarding the safety of that dividend. And if you look at the valuation and growth grade on the far right side, you can see it has stellar metrics with A, A-B +, momentum being a B, and analyst revisions being an A. So, some great stats here. A company has a return on equity of 21%.

27:06It's got a PEG, which is a combination of PE and growth. Its PEG ratio is 0.4, which puts it at a 62 % discount to the sector. And in terms of the revisioning rate, you can see it's an A, as I look at the far right. And what does that mean? That means we're looking at the number of analysts that have actually revised their earnings estimate up. And in the last 90 days, 15 analysts have revised their earnings estimate up for this company, and zero have revised it down. So, that's our three dividend stocks. Now, I'm going to take us to our three AI stocks. One company being Micron Technology, MU.

27:43This is a huge company with a market cap of$271 billion. And as you mentioned early on, a lot of people are seeing AI companies with valuation grades that are F or D - or D. I'm pleased to showcase here that the valuation for this company has actually improved. This stock is up 168 % year-to-date. In the last six months, the stock is up 129%. But despite being up 129%, if you look at the valuation, the valuation grade now is B. Versus six months ago, it was a C+. So, the valuation framework has actually improved with this company as its growth has moved. And it already had A-plus for growth. So, it was already way ahead of the sector in terms of growth.