STEVEN CRESS | from Seeking Alpha

Have you ever considered the difference between small cap and large cap stocks? Small cap stocks are catching the attention of investors for a very good reason. Steven Cress, the head of quantitative strategies at Seeking Alpha, joined me on the podcast to shed some light on the smaller end of the market.

The Index Showdown

To illustrate this point, consider two prominent stock market indexes. One is the S&P 600, comprising small cap stocks, and the other is the S&P 500, which features the 500 largest cap stocks. The S&P 600 index is currently trading at about a 26% discount compared to the S&P 500. Historically speaking, this is a substantial variation, and there's a valid reason behind it.

The Debt Factor

Small cap companies, as Steve highlights, often carry more debt than their larger counterparts. This difference in debt load can significantly impact their profitability. Smaller companies may find themselves facing greater costs. And as a result, they become less profitable.

The Power of Quantitative Analysis

Now, why is all this data significant for you as an investor? This is where quantitative analysis comes into play. Quantitative analysis involves breaking down the numbers and understanding what they mean. As Steve puts it,

This approach serves as a solid foundation for identifying trends and making transparent predictions in the world of money management. If you want to navigate the world of investing successfully, understanding and employing quantitative analysis can be your guiding star.

So, there you have it. Small cap stocks are making waves for a reason. Their significant discount compared to large cap stocks and the impact of rising interest rates make them a topic worth exploring. And, with the power of quantitative analysis, you can make informed decisions and stay ahead in the world of investing.

A big thank you to Steve Cress for sharing his valuable insights on this podcast. Remember, knowledge is your best ally when it comes to investments.

Seeking Alpha are generously offering a 50% discount to listeners of this podcast, making it $189 for the first year instead of the regular $239 price. Try the premium plan for free for seven days. Thank you very much Seeking Alpha and Steve. Find out more about Seeking Alpha in this review.

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EPISODE TRANSCRIPT

Chloe (1s):

Stocks for Beginners, Phil, Muscatello and FinPods are authorized Reps of MoneySherpa. The information in this podcast is general in nature and doesn't take into account your personal situation.

Steve (12s):

One of the reasons why I find some of the small caps interesting is actually they have traded off so significantly compared to the large cap counterpart. So if you were to take a look at two indexes, one being the S&P 600 index, which is made up of small cap Stocks versus the S&P 500, which is made up of the 500 largest cap Stocks. That S&P 600 index is at about a 26% discount compared to the S&P 500. And by historical standards, that's actually a pretty large variation and there's a good reason for it. You know small cap companies tend to have more debt than larger cap companies.

Steve (57s):

So when you go through a period where interest rates are going up, their costs could be greater, which means that they will be less profitable.

Phil (1m 4s):

Hi and welcome back to Stocks for Beginners. I'm Phil Muscatello. What is quantitative analysis? Why Is it important to break down the numbers and understand what they mean when investing? I'm joined today by head of quantitative strategies at Seeking Alpha, Steven Cress. Hello Steve.

Steve (1m 22s):

Hi. Thank you so much for having me today on your podcast. I truly appreciate it.

Phil (1m 26s):

Data analysis and interpretation has been front and center in Steve's career. He believes that the interpretation of data is the process of making sense of statistics that have been collected, analyzed, and scored. This is served as a solid foundation for identifying trends and making transparent predictions in the course of money management. So Steve, we're gonna put your full bio in the blog post and episode notes, but I notice that you spent a large proportion of your career running a proprietary desk at Morgan Stanley, and I think they're often called prop desks. Is that where traders were funded to live and die by their ability to make money?

Steve (2m 6s):

Indeed, they would. Firms like Goldman Sachs and Morgan Stanley would identify who their best traders were and those firms would fund them with millions and millions of dollars to run their particular strategies. I, I had a quant strategy that I utilized. Sometimes they could be traders who would just focus on one sector or industry from a a quant basis. I was more of a generalist, so I would be focusing on Stocks all over the world. But a, a prop trader would've had been using the firm's own capital for investing on the part of just the firm, not on behalf of clients.

Phil (2m 44s):

Sounds like a very high stress kind of career.

Steve (2m 48s):

I think you could say it is. I mean, traders typically have a stressful career. Hedge fund managers have a stressful career. You're spending your time You know looking at monitors all day long. You rarely actually even get vacations and if you're on vacation you're still having to watch your book and how it's Trading because you wanna make sure that you don't lose money and you're attempting to make money. But when markets are very volatile, it tends to be stressful. We used to say when times were good it was great and when times were bad it was really bad and

Phil (3m 19s):

Presumably a high burnout rate.

Steve (3m 22s):

They do have a high burnout rate. Sub traders have a bit of longevity, but a good portion of traders would turn over quickly. Sometimes their strategies would work for brief periods and then they wouldn't. And You know as soon as you start losing capital, an investment banker, brokerage firm doesn't want you away that position. So they are looking to You know, but there are people that make their way through the cream does rise to the top.

Phil (3m 44s):

So let's have a look at quantitative analysis. What is a quantitative analyst?

Steve (3m 49s):

Well, I could bring it down with a technical description and more of a simple description. You know my simple description is quant analysts is someone who basically employs the same methodology that any investment analyst would. An investment analyst analyzes a company, they look to see how the company's the strength of the company based on their balance sheet, their income statement, their cash flow, and then they look at the financial metrics of a company and compare it to other companies in the sector. So as a analyst that works at Goldman Sachs or Merrill Lynch or Mortgage Stanley, they're only capable of covering so many companies and comparing it to You know a small group of like for like companies, what a quant analyst does or strategist is, is more or less the same type of methodology but you power it up with computers.

Steve (4m 42s):

So you take a, an investment strategy that relies heavily on mathematical and statistical models, data analysis and computer algorithms to make the investment decisions for you. But you're basically loading up the same type of information that an investment analyst would at any of the major Wall Street firms. But you have the capability through computer processing to score metrics and compare them to thousands of other companies where an individual analyst, there's no way they would have that capability. It's not with an even balance to be able to do that. But with the power of computer processing you can

Phil (5m 19s):

And the numbers that are plugged into those models, they basically come from the quarterly reports, the 10 Ks presumably.

Steve (5m 26s):

Yeah. So you, what we do from a a quant perspective of what You know many quant Allison and strategists do is they have a data vendor. Our particular data vendor is S&P Global. They're Bloomberg is a data vendor. Reuters is a a data vendor. Backset is a data vendor. So typically we have APIs or files that we receive from those firms and we download that data. So it's a data-driven process. So we download it and we use our mathematical models to score financial metrics. So I should add though that those companies typically get their information from the SEC. So the SSEC has files that are are scanned and that they provide to those data vendors.

Steve (6m 12s):

The data vendors will try to clean up the files that they get from the SEC, but most companies report public companies report to the SEC and then the data vendors get that data from the SEC.

Phil (6m 24s):

I've heard the term, the way it's been described to me is that quantitative analysis and the difference between that and qualitative analysis is quants a numbery and quals a feely?

Steve (6m 35s):

And so that's You know that's not too far off. I write research reports and there are many analysts that write research reports. Typically you're trying to do a deeper dive, but you might talk to management, you might assess what experts within the industry are saying and you're trying to use that to build a story with qualitative analysis. With quant, it's really about the data. It's a data-driven process. As a quant, I do not talk to CEOs or CFOs. I simply looked at the historical financial information that's available and I also looked at future estimates that are provided by Wall Street analysts. And typically what I do is I take consensus estimates for revenue, for earnings, for EBIT o and I will combine both the forward looking numbers and the historical numbers in my data driven process.

Steve (7m 26s):

But at the end of the day what I'm doing is I'm really measuring the strength or weakness of a company's data metrics versus its sector. And when I look at the scores that we create, that's how we come up with a directional recommendation of a company's a strong buy or a sell. So we have a buy on companies where the indicators are coming through a stronger as opposed to those that are weaker where it's weaker You know we will typically have a cell in those companies.

Phil (7m 54s):

So for a beginner investor, obviously it's important to start looking at the numbers that are coming from company reports. Where, what are a couple of the numbers that you would suggest that they start looking at just as a, a way of learning how to analyze those numbers?

Steve (8m 8s):

Great question. And that's You know one of the reasons why I I created my platform not that long ago was to make it more of a user friendly process. So I think the quant model that I utilize there are five core factors and I would recommend that everybody looks at these factors. We're looking at value growth, profitability of Stocks momentum as well as analysts. EPS revisions and EPS revisions are where analysts have estimates on a company's earnings and they constantly are revising those estimates and we're looking for companies where they're revising estimates up where You know we're recommending it for a buy or if it's a a strong seller or a sell, we're assessing where the estimates are revised down.

Steve (8m 52s):

So we basically combine those core factors and that is what we like to look at and that's what I would recommend that people look at when they're assessing a stock. You want to look at a company's evaluation framework and you wanna look at their growth framework and within the context of those investment characteristics there are underlying, so for value, a very common metric would be PE ratio or price of cash flow price to sales. One that I like is called the peg ratio where it actually combines the PE ratio with a company's growth rate and that gives me a good sense of the value of the company and the growth within one metric. In terms of the growth characteristics, I would look at revenue growth and earnings growth.

Steve (9m 37s):

Those are really key metrics there for profitability. You wanna see that a company has good margins and you wanna see that they have good returns. So you'd be looking at gross margins or net income margins and for returns you'd be looking at return on investment or return on capital. Another very important factor which is less looked at is the stock's momentum. And believe it or not, there are studies that go back almost 200 years which show that momentum alone is a very, very important factor and highly predictive of a stock's future performance. So we actually use that as a factor in our model. It's one of the the many core factors that we use. And then something that we've really customized at Seeking Alpha is the EPS revision and we're looking at the quantity of analysts that are moving their estimates up or down.

Steve (10m 24s):

Those are a little bit harder to find if you're not using a platform like Seeking Alpha. But if you are the Seeking Alpha platform, it's a incredibly user-friendly experience because you could go to any stock page, it could be Apple, Google, Microsoft, Exxon. And when you go to that stock page you'll see that the factors have these letter grades which are academic letter grades A through F and we score each of the factors and the value has an a You know that the company is very attractively valued if the growth has an A You know its growth is much stronger than the rest of the sector. And the same for profitability of the, of the scores of the grades are You know that it's weaker than the sector. So the platform really provides you with an instant characterization on the strength or weakness of the investment metrics for the company versus its sector.

Steve (11m 12s):

So that was really the user experience that I was going for when I created the quant system.

Phil (11m 18s):

And what does EPS stand for?

Steve (11m 20s):

EPS stands for earnings per share. So will you look at a company, you would look at their overall revenue and their overall net income, but it matters how many shares a company has and they also can continue to issue shares. So at any given point you actually wanna know what the earnings per share and typically a PE ratio would be the price of the stock divided by the earnings per share and that would give you the evaluation ratio.

Phil (11m 46s):

And it's interesting that you use momentum 'cause momentum's not something that comes out of a company report Is it. It's, this is more something to do with like the price action watching how the price has been moving on the markets itself isn't it?

Steve (11m 58s):

It Is it is and and you can break that price action down to different time periods. So we look at it a one year basis, a three month basis, a six month basis. So our mentum metric is sort of a combination of different time periods. You know we've backtested all of our metrics to see what has the greatest predictability. So we actually, the metrics that we employ are not equal weighted. Some have heavier weights than others and You know that's how we come up with our scores and eventually the directional recommendation which would be a by our sell.

Phil (12m 29s):

I know we've got a whole list of questions to go through, but I just wanna say this Sure at this point that for many beginner Investors they sort of weighed into a market because they've heard the story of a stock and they think, oh You know I like the story of this stock, nobody else on Wall Street has even heard of this story. I'm going to buy it because I've got inside information. But this really speaks to what you're telling me today is really speaks to the amount of study research education that's required computing power to actually do the analysis for coming up with valuations for Stocks that may not even prove correct anyway.

Steve (13m 5s):

Yeah, it's really the great validator. So You know if you, you go to your, your barber and you get a tip from your barber and it sounds like You know there's a great story taking place you can validate like when you go to the platform, you just put the name of the company in and it's gonna show you You know what the company's growth rate looks like versus the sector, what the value looks like, what it's profitability looks like. And in a a nanosecond you get an instant characterization by looking at the stock page and it's, it's a data-driven process. We You know we're not creating that data, we're getting that data from a vendor who gets it through the SEC. So it really lets you measure what your tip is from your barber or from your friend or even from a financial advisor who might by telling you You know this stock has a great story.

Steve (13m 53s):

You could visually see what the data looks like and it will validate what that story is and if it truly is growing you'll be able to see instantaneously that the company has a very strong me rate.

Phil (14m 4s):

Yeah, putting the numbers to the fairies. Hey.

Steve (14m 7s):

Yes.

Phil (14m 8s):

Okay, so let's take a bit of a delve into a single metric and you mentioned the PEG ratio. So what is the PEG ratio, what's it stand for and why do you particularly like it?

Steve (14m 17s):

So the PEG ratio Is it part of the valuation or company. And when you look at value as I mentioned, there are typically the most widely used would be PE ratio and that is the price of the stock divided by earnings and then you'll have like price to sales which is the price of the stock divided by sales. What I'd like about the PEG is it's the PE ratio divided by the EPS growth rate. So you're sort of marrying two different investment characteristics because people will look at a company's growth and it will look at valuation and really like You know the the mother's milk assessing a stock is to be able to look at the company's growth rates, its value and its profitability.

Steve (15m 2s):

These are really three core factors that people look at. And what I like about that PEG ratio Is, it actually marries two of the core factors together, the valuation and the growth. And often a company could look very expensive on a PE basis or price to sales, but when you take a look at that PEG and you marry it with a growth rate, it can actually end up looking really attractive. So by example Nvidia, it is a stock that looks great almost all the metrics and has straight As for growth, profitability, momentum and EPS revisions on our quant system. But it gets an F in terms of valuation. The reason why is the conventional value metrics like pe, ebitda, price to book, price to sales, they all come up, it's like a red C of F's and D's and D minuses.

Steve (15m 55s):

However there's one ratio on the page when you look at it out of the 20 some odd metrics we have there, that's green and that's the peg which gets a grade of a B. And when you look at that metric, the absolute data point will show 1.27 times, which is the multiple versus the sector at 1.75 times. So on a peg basis it's actually at a 27% discount to the sector. So you could say, oh well like You know that is an important factor and that actually makes a good case of all the other metrics of good profitability, growth, momentum and EPS revisions. I can actually make a case to buy the stock on value because this one metric which is pretty important is in the green k`kfrom a quant perspective You know we would pass on because of that overall f.

Steve (16m 41s):

But as an individual I encourage them to look at the underlying metrics and they could see for themselves and try to make a case

Phil (16m 49s):

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Steve (17m 39s):

Not necessarily, I'd be like, I'll put in Coke by example. So that's a very old company and we'll see what that looks like. So overall, if I'm looking at Coke, we do have a quant strong buy on it. When we look at the factor grades, which are value growth and profitability, it does have a D on valuation. So I wanna clicked on valuation and sure enough the PEG does not look great on, so the peg on coke is 3.42 times versus a sector of 2.3 times. So on a peg basis it's almost at a 50% premium so it doesn't look great, but there could definitely be situations for older companies where the PEG ratio could be stronger because the company could be experiencing strong growth.

Phil (18m 25s):

So an area of the market that you are finding particularly interesting at the moment is this small cap sector. What is this sector? What kind of size companies are we talking about here?

Steve (18m 36s):

So small cap companies have market caps act to be anywhere from $25 billion up to about $2 billion. So that would qualify as a small cap. You know larger cap companies will have market caps of a hundred billion. One of the reasons why I find some of the small caps interesting is actually they have traded off so significantly compared to the large counterparts. So if you were to take a look at two indexes, one being the SS&P 600 index, which is made up of small cap Stocks versus the S&P 500, which is made up of the 500 largest cap Stocks, that S&P 600 indexes at about a 26% discount compared to the S&P 500.

Steve (19m 26s):

And by historical standards that's actually a pretty large variation and there's a good reason for it. You know small cap companies tend to have more debt than larger cap companies. So when you go through a period where interest rates are going up, their costs could be greater, which means that they will be less profitable. So as a result of being in this environment where rates have been going up for like well over a year now small cap companies have really taken it on the notes, but we're getting to a point where that discrepancy between the large cap and the small cap is at a standard deviation that is fairly wide. So I actually have highlighted, I wrote an article recently top 10 Stocks under $10 and what I did is identified small cap companies that were actually profitable that did not have a lot of debt.

Steve (20m 18s):

So these companies have traded off in sympathy with the small cap sector that's been hit because of macro reasons. So when the economy does normal add and recession is not such a fear as it has been, these companies should rebound fairly quickly. And some of them, since I've written the article, actually have already started to move quite nicely.

Phil (20m 37s):

And it, it's also important to point out that even though a company is small cap, it doesn't mean that they can be small quality. I mean there's no in a small cap sector that there's some great companies that are profitable paying dividends that have very strong balance sheets as well, just they're just not big,

Steve (20m 53s):

They're not big and sometimes they'll, they'll have sort of a core expertise. You know that you could see faster growth with 'EM than you would compared to a large cap company. So there are many elements of a small cap companies that could be very attractive. Mm.

Phil (21m 7s):

It's also worth noting that when a small cap company has debt that they're often paying more for that debt as well than a larger cap company as well, which is another hindrance to their performance, especially When. it

Steve (21m 18s):

Rates that and that's one of the reasons why they've come off so much over the last year, particularly for that reason it's been factored into the, the small cap Stocks people have sold them off as a result, but at some point You know the fears get fully baked into the Stocks and my feeling is that this You know 26% discrepancy to the large cap Stocks that we're getting close to the point where the fear is fully baked in.

Phil (21m 40s):

So the area of technology that is gaining a lot of interest at the moment is artificial intelligence ai. Sometimes I use the phrase A with a capital A and I with a small I. But anyway, by and by AI is something that the market is becoming excited about because of the possibilities there. What are your thoughts on finding Stocks that provide exposure to AI and any stories arising out of that?

Steve (22m 4s):

Yeah, I'm, I'm actually glad you asked the question. I just wrote an article yesterday on my top 10, really top 13 favorite AI Stocks. And the way I went about generating this list is I went to the largest AI ETFs and it took the four largest ETFs and I downloaded all the Stocks into our portfolio system. So there's about 147 AI Stocks that I have measured based on our quant system. And as a result I was able to identify which ones looked strong based on our, our strong buyer recommendations and which ones looked weak.

Steve (22m 45s):

And I thought it was a fascinating You know list that we came up with. So there were a couple of Stocks that were really well known like Meta and Salesforce and then we had Stocks like super microcomputer, which really have started to become quite popular this year. In fact, earlier in the year I wrote an article on my favorite stock for 2023 and it was super microcomputer and I never, my wildest dreams would've expected it to perform as well as it has. The stock is up 229% year to date and it's because it's gotten so much attention from ai. But other Stocks that came up on the top of the list, which people would never expect for AI are Deere and Company, which is John Deere.

Steve (23m 27s):

People know that and Caterpillar and Emerson Electric and these companies, especially Caterpillar and John Deere are known for their big machinery and their factory equipment and automation. They wouldn't expect it to have an AI component. But what these companies have done so well Is it actually taken a software which is AI related software and they've blended it with automation. And as a result you'll see companies like Caterpillar and John Deere and some of these ETFs that are solely focused on ai. So the quant system that we use, I think this is really a great validator. When we loaded up the 147 Stocks, I measured just over the last four weeks the performance for the top 17 strong buys versus the 17 strong sell.

Steve (24m 17s):

And I think this is a real testament to the quant system. The strong buys over the last four weeks were up 6.5% and the strong selves were down 14.8%. So I think it, while it really validates that the system not only works for energy Stocks or healthcare Stocks, you could take something as focused as a theme like artificial intelligence and apply the Stocks against the bottle and it still works really well. But really the whole point that I wrote the article was many of these Stocks have come off their 52 week highs since the beginning of July. And You know AI is something that really became popular this year in the investment community, yet Nvidia report that their first two quarters and the number of surge for Nvidia and they said it was really coming from a lot of their products that were AI related and simultaneously other companies started saying that their revenues and earnings were really building up from ai.

Steve (25m 17s):

So AI is, it's a revolutionary technology. This is the year that it's sort of starting, it's really in its infancy and being that the market has pulled off a little bit since July, I thought this would be a really good time for people to focus on some of these names I can get in where they may have missed it early. Isn't it

Phil (25m 36s):

Interesting how you can get exposure to a theme from a company that you might not even think about? I mean it's like with John Deere that you mentioned, who, and that this company often appears in robotics ETFs as well. The technology that they utilize for applying fertilizer & pesticides and so forth to crops lend themselves so easily to robotics, artificial intelligence and using this to increase efficiency in growing crops.

Steve (26m 5s):

Yeah, it's really the mar the marriage of sort of You know big data that is derived that these companies are picking up on and being able to sort of assess You know behaviors. So You know it can quickly gain it has the data it's stored so When it tests soil You know it immediately knows through artificial intelligence what type of fertilizers need to be applied. The fertilizers could be right on a tractor that's being run autonomously without anybody driving it because of g p s software that's tied into artificial intelligence as well. So it really is amazing the efficiency that is accomplished through artificial intelligence.

Steve (26m 46s):

And like even on my side, I could write an article and You know I'm probably more of a quant person than I am You know qualitative and You know using You know the English language. But I could take a couple my paragraphs and throw it into chat G B T and it will immediately rephrase my paragraphs in a much better sounding way that I could have done myself. and it adds tremendous efficiency even to what I'm writing articles.

Phil (27m 14s):

So Steve, have you got any advice for new Investors You know people listening to this podcast that're approaching the stock market for the first time and we, we don't want them to make any mistakes. What sort of advice would you give a new investor?

Steve (27m 25s):

Yeah, I have to say like, I don't wanna sound as if this is an advertisement, but we really created a platform for Investors who they could be new, they could be experienced. It's really about the user experience that you get and being able to assess companies so quickly it saves you so much time. And the You know the data is verified You know it comes from the SEC and it comes from data vendors and we scrub it ourselves to put it into that user format. So literally if you are talking to a friend and they're recommending a stock or if you wanna take investing You know seriously and a couple times a month you wanna be able to assess markets and get recommendations, You know the recommendations will be provided on the system.

Steve (28m 10s):

It will either rank You know what our contributors are saying or it'll rank the quant metrics on a stock. It just makes it much easier to identify higher quality Stocks as opposed to not knowing anything or just taking a recommendation from somebody who you barely know.

Phil (28m 28s):

And in terms of say position sizing, what should they take away? I mean obviously you don't wanna put all your money into one stock because you've recommended it Is it. Diversification part of that process as well.

Steve (28m 39s):

Honestly, we You know I can't give personal investment or advice because everybody's risk tolerance is different, their age is different. I have no idea of now where somebody is on the spectrum of capital appreciation or income generation. But what I can say is if I had a superpower, my superpower would be to ignore the talking heads that you see on CNBC or Bloomberg or even ignore You. know what you're seeing in terms of the macro environment where people are saying You know we're going into a recession. The superpower would be is to have the discipline to once a month ignore all that and just invest into either ETFs or Stocks in a very disciplined manner. You know you, you don't wanna put all your AS in a basket at one time.

Steve (29m 22s):

You wanna spread it out. So as you have income coming in maybe from your salary or if you have retirement savings that come in, You know just each month chip away at making an investment. And the the beauty of the Seeking Alpha platform is there's a lot of qualitative analysis, there's a lot of quantitative analysis, so it makes it easy to find investments the same way you could use ETFs which give you much larger exposure. You could look at S&P 500 E T F, you could look at an MSCI global ETF. The point that I'm trying to make is just You know chip away you e month. And that is how wealth creation is created over a while period.

Phil (30m 1s):

And it's also worthwhile considering about your own interests as well in the way that you invest because people get ahead long-term slowly, but they can do it in their own way as well, can't they?

Steve (30m 13s):

Absolutely. And there is also something to be said if you work within an industry, You know as you're making your investments you wanna be diversified. But if you work in a particular industry, you could always You know, take some of your, your capital and You know a certain part of the technology sector or the healthcare sector or the entertainment sector or the food and beverage sector. You know companies that are doing well. Okay. And You know it through You know the growth that a company might be experiencing. So you could take some of your assetS & Put it into where your own knowledge base is.

Phil (30m 46s):

So Steve, tell us where people can find out more and what, what's the best way to approach Seeking Alpha like the the gateway that you would suggest for people to find out

Steve (30m 56s):

More? Yeah, I would say you just go to Seeking Alpha dot com and the beauty of this is we've created a platform that is not expensive at all. And I think when people go through your portal, they might be able to get a discount and a free trial on it and they just go to the platform. You know it could run, I think it's like $249 for the year. Sometimes they'll run specials where it's like $199, but it is just an incredible amount of information that you're getting for that price and that's the annual price. By comparison, if you were to get a Bloomberg that would run you about $26,000 a year and something that I'd love to point out with a Bloomberg, they're giving you the absolute data points.

Steve (31m 38s):

What we do at Seeking out on our platform is we actually interpret the data points for people. So when you see PE ratio, we're actually interpreting it by putting that grade A, if you see it, earnings per share of growth rate we're putting, we're interpreting it by showing you how it compares to the rest of the sector, right? And you don't even get that with the major providers like Reuters or Backset or Bloomberg. So really it's an incredible price and most people they pay for this literally within one tree.

Phil (32m 7s):

And of course Seeking Alpha a generously offering to listeners of this podcast, a $50 coupon, making it $189 for the first year instead of the regular $239 price. So thank you very much, Seeking, Alpha and Steve. And you can try the premium plan for free for seven days and you can do this by going to Stocks for Beginners dot net slash Seeking Alpha to find out more. Okay Steve, thank you very much for joining me today to tell us all about Seeking Alpha and hopefully soon we'll put together a video so we can find out even, even more what it looks like behind the scenes.

Steve (32m 42s):

I think that'd be wonderful. Picture's worth a thousand words.

Phil (32m 45s):

Fantastic. Thank you. Bye.

Chloe (32m 47s):

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Stocks for Beginners is a production of Finpods Pty Ltd. The advice shared on Stocks for Beginners is general in nature and does not consider your individual circumstances. Stocks for Beginners exists purely for educational and entertainment purposes and should not be relied upon to make an investment or financial decision. If you do choose to buy a financial product, read the PDS, TMD and obtain appropriate financial advice tailored towards your needs. Philip Muscatello and Finpods Pty Ltd are authorised representatives of Money Sherpa PTY LTD ABN - 321649 27708, AFSL - 451289.