Why do some stocks go up 100% and others don’t? You might think, “Well, obviously, some companies are better than others.” That’s stating the obvious, but what if you use the same criteria to select the company which went up 100, 200% as you did the one which went down?
And yet, one went down, and the other one went up. How did you get those? Does it matter if the vast majority were up and you had a few dogs, and it didn’t matter because your performance was a lot better on average?
So, I did this experiment. Okay? I think it was around July time, last year. I created a spreadsheet. And I called it my approved list.
It was part of my approved list program. And we listed stocks that were on the approved list. In other words, stocks and companies that met our criteria evaluation.
In other words, is the company’s share price relatively cheap to its profits, to its sales? Is it growing its profits relative to its share price at a good rate? And a few other factors such as discount cash flow, sort of complicated things, which accountants love.
But as a measure of evaluation, did it tick that box? Did it tick the box of, also, earnings growth, sales growth, strong cash flow growth? Was it in the top 10% of companies by cash flow, capital returned on cash invested? Because we knew from Goldman Sachs’s research that those companies generate about 30% per annum, on average, over the long term, 30% per annum share price return.
Did it also tick the box on outperforming the market, having relatively low volatility and consistent outperformance? So, we had to make sure it ticked all the other boxes, and then we put it into our approved list. So, we launched this last July.
I want to show you the 12 months. Why 12 months? Because I hold stocks for 12 months. 12 months ending November because we’re in November now. So, the 12 months ending November, this was our performance.
You can see there’s a whole bunch of stocks which were up, well, this one’s up 300%. That’s 208, 208, 201. And the vast majority were up either 50 to a hundred, and then you had a few which were up, say, 46. And so on. I’ll come to those in a second.
The question is, “Why were there any? Which, given the criteria, were the same. Why were there any which had fallen?” Well, that’s really important. And I’ll tell you why it’s important.
If you could find a set of criteria that excluded the ones at the bottom and only had the ones at the top, you’d only pick the ones that won 318%. Let’s just go back for a moment. What I want to show you is, well, actually, what then happens? By the way, that’s the average performance. It is this phenomenal. It is a funnel of 53.4%.
So, what actually happens if you could pick just one? Well, you can’t. Anybody who had that level of resolution would only pick one stock; even Warren Buffet and Bill Gates don’t do that. So, you choose a basket. So, why do you pick a basket? Now, you know why you pick a basket. And the average return of the basket, great. 53.4%. So, would you care if there were some dogs in that criteria? You don’t keep looking for the ideal criteria.
Yes, top performers, as I mentioned. Now, did I know that ahead of time?
No, I knew they ticked the boxes, but I didn’t know Crocs would go up 209%. I don’t have that kind of sense. Had I known it, I would’ve put everything into Crocs or Elos.
Here’s something important that I want to teach you, as well. Do I know what Elos does or Harvia does or Adesso does or SOLTEQ does, or Flex LNG? Well, LNG, presumably liquified natural gas. But do I know what the others do? No. You see, to me, what’s important is companies are factories for making money. And therefore, the metrics to measure them are profits, cash flow, balance sheet.
So, you’ve got your three sets of accounts. Okay? You’ve got to look at the valuation, growth, income, share price momentum, volatility, consistency of the share price, and outperformance of the market. Are they doing all of these things? Then, whether they’re making sausages or Silicon chips, it doesn’t matter. What matters is the share price and money.
Obviously, all those aspects of money, and if I could predict and get just the one stock, I would’ve just put everything in that one stock. As I said, these were the ones that generated over a hundred percent.
If you had an Alpesh index of my approved list, we launched last July and updated it each month. Why each month? Why not every day? Well, it’s invested for 12 months; why do you need to update it each day? Also, you’re holding for 12 months. So, if you happen to be there in July, you hold for 12 months; you didn’t care about the other list unless more money came along. This list is from November 2020 to 2021.
One of the fascinating things we saw from this is not that the bulk of the stocks or a large number generated so much; there was a tailwind. I can’t take credit for it. There’s a tailwind in the market. And, of course, we pick companies with sound financials. It’s not the first time; we’ve been doing this for about 20 odd years.
By the way, it’s just the first time we made the approved list public. But this price distribution is what blew my mind. When we look at the price distribution of our approved list, which you believe me, we’ve never bothered doing. Sort of had an idea and an inkling.
So what you see down there are numbers one, one, twenty-one. And what that means is all the stocks that were between 1.1% to 21.1%, this box here means 21.1% to 41.1%. And this box means all the stocks which were above 138% return.
The software just picks those numbers. That’s why they’re not rounded numbers. And what you can see, there’s a whole bunch of stocks which were everything above. Everything on this side is above 41%, and 40% is my annual target.
Some years you do better; some years, you do worse, depending on the tailwinds of the markets. Obviously, all of these were above 41%. Of course, I only wanted to pick just those if I could. The ones I wanted were just these. Nobody in the history of the world, other than the lucky gamblers, has ever just picked those alone. And you’ve got to try and get it every year, don’t forget.
So, what about those which were under 40%? Well, look. Some were negative. Yet, the criteria used were the same. That happens. You’ve got to make sure that the negative pegs and they’ll happen no matter how stringent your criteria and ours are taken from, well, Nobel prize winners. We use the research of Richard Thaler, Daniel Kahneman, and Eugene Fama. All three won Nobel prizes in economics.
If you want to know that I’ve been using their research, take a look at the best-selling books that I’ve written. Those economists are mentioned in those, let alone in my Financial Times column. So, we use that research. And yet, out of the same criteria, you still get some bad eggs, as it were.
And then, you’ve got some which are not bad, 0% to 40%, can’t complain. But I wanted to share that distribution because I don’t think many people realize that that’s how things come out.
If you look at the long-term performance of any hedge fund, their return distribution will look like this, as well. Curious little anomaly, as it were, I just wanted to share that with you.
These are the stocks from the approved list from November 2020 to November 2021. And I want you to know if you might look at this in future years, at least you know it’s time stamped.
That’s the performance, and that’s how it happened. Now, actually, in any universe, whether it is school kids in a private school, whether it is products you’re developing, whatever it is, you’re going to get a distribution curve like this. Now, I know you’re thinking, “No, you’d get a normal distribution curve.”
Well, actually, think about it. This is a normal distribution curve of sorts. And this is what it looks like if you put all the companies and the names by performance. Because I could not know in advance that these companies were going to generate the most returns, I effectively would be better off trying to pick all of that index and getting my 53% or a sizeable subcategory.
What’s a sizeable subcategory? I think a sizeable subcategory is about twenty-odd stocks. You think, “Well, Alpesh, you might get unlucky, and you might pick all twenty which are like this.” Highly unlikely. You might get lucky and pick all twenty, which is doubtful.
You’re probably going to get out of a random sample, a sample size of twenty, you’re probably going to get your 53% in any event. Safer, maybe, even to buy all of them. I just wanted to share all of that with you when we launched this approved list, which is now part of the Great Investments Programme.
But that was back in November, last year, roughly. So, about a year ago when we launched it. Three months or four months after we launched the approved list. We didn’t expect the markets to do what they’ve done. And that’s another important point.
My job is not to forecast what the markets are going to do. It is not to gaze into a crystal ball and say to you, “Oh, I think what’s going to happen in the future is this,” and I’ve got a better crystal ball than anybody else. That’s not what it is.
My job is to make sure from our end; we’ve done all we can to prepare for what may come. But like a sailor setting off to see, we’ve just got to make sure whether we have looked at valuation, growth, income, cash flow, everything at our end.
Then, if the seas are choppy or not, or a pilot preparing to cross the Atlantic, it’s a tailwind or a headwind, hey, we’re still getting to our destination. If it’s a headwind, it might take a bit longer. So, we won’t get the 50% this year; we might only get 0%. Who knows? Stock market crash.
We will eventually get to our destination and our destination of actually being 40% per annum, which is over the longer term. We’re not in the gambling business of saying, “This sector’s going to be hot. This is the future technology. This is what’s going to happen.”
And why aren’t we? Well, how many foresaw COVID? Yeah, Bill Gates, apparently. That’s about it. We didn’t. So, why would we want to be in the forecasting business if we can’t even forecast something as big as that? We want to be in the resilience business.
We’re sort of in the insurance business. The insurance business is to try and get a 40% return per annum through valuation, growth, income, cash flow, the outperformance of the market, consistency, low volatility. There are a few other things we’ll look at, like discount cash flows, which fall into that subcategory.
But I hope that gives you a perspective of what is required to be done. What should be done, and how you should be looking at ticking every box and picking from a large universe of stocks. Don’t be racist in your stock picks and just pick British companies. There are 10,000 equities listed on the U.S. And UK exchanges. You are picking out of ten thousand’s enough.
You don’t then need to go and say, “Oh, I can’t get Vietnam.” Ten thousand’s enough of a gene pool of CVs. CVs of companies will manage; that’s what companies do. They manage your inheritance or your child’s inheritance, your pension.
Once you’ve got those ten thousand companies, you narrowed it down through those criteria of value, growth, income to the top half a percent; you pick 15 to 20 out of those. And you can see the ones in our approved list are part of our approved list program, as I said when we launched it last July.
It’s something I invented and created and been using and innovated for over 20 years, but it just made sense to make it, well, draw out. I guess because the technology’s here, you couldn’t actually even do this before and do videos and show people all of this so quickly and record it so easily.
But just give you an insight into how that stock selection process goes. And the funny thing is how many of those companies did we meet? None. How many director’s presentations did we listen to where they’d tell us how wonderful they are, or rather like Warren Buffet, and we agree with him? None.
What are they going to tell me? Just how brilliant they are, of course. How many bottom fishing companies are we looking at, ones that had crashed and burned and speculated that they might turn around? None, we’re not in that business; I like to sleep easy at night. Why should I, when I got ten thousand CVs, pick the one who says to me, “I’ve never been to university, never studied, but I’m going to turn it around this time?” No, none.
And it’s that sort of attitude and framework, which you’ve all got. Common sense, you might call it, in everyday life that we just applied to start picking and finding, well, overall, the winners. Was every single one right? No.
You can see the statistics and the data right in front of you. Will there be some years where there’s more wrong than right? Yeah, if there’s a headwind and the market just falls. Then, of course.
And in market crashes, everything’s correlated to the downside. There is no magic stock that you can pick, which only goes up in good times and bad. That company doesn’t exist.
Maybe you’ll be somebody who’ll invent it, create it, but that company hasn’t been invented yet. But it’s not Amazon nor Microsoft; they don’t go up in good times and bad. If the markets fall, they fall back less; when the markets rise, they rise more. They have times when they pull back, but that’s the kind of resilient company we want, maybe on a smaller scale, so it’s got even more growth.
So, anyway, congratulations and well done over the past 12 months for all the people on the approved program. Those of you who are on the approved program, you are now on the Great Investments Programme anyway. So, welcome on board, all of you. We’re hoping to do a lot more good work as the years go by, as well.
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Alpesh Patel OBE