So it has come up with a sell rating on Chipotle.

Growth is increasingly bought from the existing estate.

Just as a headline, I don't know what that means.

And I think sometimes it tries to mimic the language of analysts that I just don't understand anymore.

This took, what, probably the better part of a half hour, hour, or something like that. But I imagine this is the product of weeks of work and research.

There's one particular company where we put a buy recommendation out, and the company went bust within six months.

Yeah. I don't always get it right.

Welcome to all our listeners. Welcome to this week's episode of "What's the Big Deal?" Graham, please do, as usual, tell us what the big deal is this week.

Ooh, today we're back in your world, and we're talking equity research.

So we're taking a look at an equity research report that you have had, what is it, Claude, I think it's called together.

Yeah, Claude.

What does that- I'm back with Opus because my fable is a bit too token heavy.

So I asked Claude to generate a research report.

I gave it carte blanche on the company that it was going to use, and it came up with an idea for Chipotle. How do you feel about that, Graham? I'm interested. To be fair, I haven't looked at Chipotle as a business, really.

Wow.

I've looked at plenty of quick service restaurants over the decade I was investing money at Ares.

No real strong views, so interested to see what this research report has. From a personal perspective, I'm not a huge Chipotle fan, to be totally honest. I'm sure that's- That blasphemy in our household. It's a firm favorite and it always to take away.

Well, I think the thing is I grew up where there were so many Mexican options that were really good.

Yeah.

Even some quick service ones. When Chipotle came to be, it was kind of like, "All right, why? I don't really need or want this." Yeah.

So I don't really go that often unless I'm in the middle of nowhere, and that is the option.

Okay.

But it's fine.

Interesting that you say that, because actually one of the things that's worth remembering when it comes to research and investment ideas is that the investment thesis is not based on whether you like or don't like the company.

So in theory, you can absolutely adore Chipotle and come up with a buy or a sell recommendation because it's really an expression of whether you think investors should be buying or selling the shares because of mispricing in the market. And that's really important that we're clear on that.

It's not an expression of whether you think it's a good or bad company.

It's about the investment opportunity.

So- Exactly. And also, I do think it's an important aspect of investing to try to sometimes just separate your own personal view on something from whether that's a good investment or not.

I remember having just plenty of investment committee discussions over the years where you can see, including yourself, right? You bring in your own- Yeah ... personal bias because you like something, you don't like something.

It's like, okay, just because I don't like Chipotle does not necessarily mean it's a bad investment. It might be a bad investment for other reasons, but it's not because I don't like it, because plenty of people do, obviously.

Yeah. Absolutely. And one of the things that we used to say when we were starting to initiate coverage, and we'll maybe talk about that in a minute.

But when you're basically providing your first recommendation on a company, if you start with a very neutral view and you start with, well, let's build the valuation, let's understand the company, let's build some forecasts, and then come up with our recommendation right at the end, because you're not then approaching it with kind of, I've got this view that I want to express from the start.

That, as you say, could be very biased based on your own view of the business itself. And it should be that the recommendation is driven by the valuation, the mispricing that you see in the market relative to what you actually think the company is worth. So it really should be underpinned by valuation.

And just on that point, when producing this report, I did ask Claude to build a valuation model to support it so that there's kind of richness in the numbers in the report. We're not going to spend time going into the Excel model, but we can definitely make that available as well.

But what we're going to do is focus on the report, I think, in this episode, so we can just really understand a little bit about an investment thesis and the structure of a research report.

Now, before- Yeah ... we start flipping pages here. One thing I'm just...

Because this is not my world. I mean, I've read- Yeah ... thousands of equity research reports, but I've never actually put one together.

So one of the things I'm interested in is knowing, so when you are initiating coverage at an investment bank or wherever these reports are being put together, what kind of information are you using that is, say, outside just the purely public domain? Because obviously this report, I assume, is put together by Claude, so it's going to pull whatever it can find on the internet effectively.

Yeah.

But are you also getting access to the company? Are you meeting with management? Does that happen in a public venue? Are there private meetings where your asset management team, whatever questions you've got, what kind of information and access do you have that goes into a report like this? Yeah, that's a great question. And the starting point has to be that you are only using public information. You're not allowed to use inside information as the basis for your research report.

Yeah.

But yeah, as you mentioned, Claude is just scouring the internet for very widely available information. Whereas the analysts will have access to not necessarily private information, but they will have access to, as you say, the management team or investor relations are the ones with the key contact at the company. They will be able to ask clarifying questions.

The company can't provide information that's not public, but they can clarify.

Yeah.

And that then helps the analyst to build their own analysis and insights.

And their own analysis is basically their own interpretation, which they then include within the research report.

But yeah, the sorts of information that the analyst will use is, for example, they'll have access to consensus forecasts that they can then use to benchmark against their own expectations. They'll have access to market research as well.

So for Chipotle, that would be information on other restaurant businesses and the restaurant industry. There'll be read across from other companies within the industry. When you're an analyst that covers Chipotle, you'll be covering other food restaurant businesses as well. So you'll have read across from those.

Yeah.

And then you'll have access to all the other research that's available within your own investment bank. So, you'll have access to economic research, you'll have access to other sectors where there might even be read across as well.

So you're kind of filtering a lot, but bringing in lots of different sources together. And we obviously use the expression that you're joining the dots.

And so those dots are all public information, but the way that you join those dots is a new view and a new interpretation that suggests that- Yeah ... the market is maybe mispricing the company.

Okay, so in theory, in the big sandy one, in theory, the access to information for this report we pulled together shouldn't be vastly different from the access that an analyst would have. Of course, you've got access to internal resources like the- Yeah ... economic indicators you talked about.

But there will be public resources for that kind of stuff as well that can be drawn upon for this.

For sure. It should be in a similar kind of region, we're saying? Sure, absolutely. The difference- Okay ... is the analyst overlay. It's their own analysis and expertise.

One of the key edges that you have as a research analyst is that you'll build really deep expertise into a select number of companies that goes above and beyond what any buy side investor would have.

And actually, it's important we draw that distinction.

So sell side research, that exists within the investment banks and brokerage firms, and they are producing research for the buy side.

Those are the firms that manage the money.

And if you work on the buy side as an analyst, you will be constantly scouring the market for investment ideas, but over lots of companies.

And so you don't really have time to know every company in detail.

Whereas the sell side within the investment banks, they will be covering maybe 10, 15 companies max, and will know those in real detail, be constantly monitoring the developments within that industry and the economy, and updating their views to the buy side. And that helps the buy side to make their own investment decisions.

Makes sense. So it's a weird one, because I always remember when I joined research, I was like, what's the point in having both sell side and buy side research? Isn't that just duplication? But it's more about kind of a filtering process.

You have the really deep research on the sell side and then kind of the overlay on the buy side.

That makes sense. It also depends on what buy side shop and team we're talking about. Because the stuff that I used to do was all generalist.

We didn't have any kind of sector experience, and that's very much just volume driven based on what's happening in a private market.

Opportunity comes in, so what do you think? Then you compare that to a more liquid investing role.

And there it does make a bit more sense to have some separation by industry or however you want to carve it up.

Yeah.

So I think about the work I used to do, and a lot of times I'd speak to, say, the liquid credit analyst for a particular industry to say, "Hey, I'm looking at this private thing.

You know this space a lot better than I do because that's what you cover.

So what do you think?" So you've got some separation, but it really depends on what you're investing in and ultimately how big the team is, too.

Yeah, for sure.

Okay. So let's take a look at Chipotle. Yeah.

Yeah. So the starting point I will say is that Claude came up with a neutral view and an equal weight rating.

I pushed back on that because I wanted it to be a little bit more interesting to talk about. So it has come up with a sell rating on- Okay ... Chipotle. I also pushed back on the title because it was the most boring title for the note I've ever read. So it's come up with Guac is Extra, implying that it's overpriced and that you're basically paying a premium, not for guacamole, for Chipotle, without actually getting anything extra for it.

So that's the kind of summary, and it's actually quite important.

Although we're not writing newspaper articles here when we're writing research, it does need to be attention grabbing and a really nice, clear hook for- Mm-hmm ... your thesis, your view on the company.

So a nice clear headline, a nice clear title is always helpful.

So Des, what's the most interesting equity research title you've seen before? So we had some that were blocked. We weren't allowed to use song titles.

Okay.

We did go through a phase of using movie titles, and I published one called What Lies Beneath- Okay ... which was a great note, forensic accounting note on a UK aerospace and defense company.

So yeah, we used to have a bit of fun with the titles of the notes if we could.

Wait, why could you use movie titles but not song titles? I don't know. It was just these arbitrary rules that we had.

Okay. And we weren't allowed to use any puns, which were kind of seen in any way as controversial or slightly edgy.

I think somebody wrote a note on tax called The Joy of Tax.

And they hung them hard about whether that was allowed.

I think it did make it out, that one.

Did they get fired for that one? No, they didn't. And to be honest, if you're going to write a tax note, you've got to make it a bit exciting. So try to- Oh, yeah. 100% ... reference sex at the same time. It's maybe not a bad thing. Sex sells.

Tax doesn't.

To be fair, this one actually, I don't hate. I think Guac is Extra is kind of fun.

So not bad.

Yeah, that one's all right.

Yeah.

So yeah. So headline is important, but also clarity of message.

We always try to make sure that, particularly on the front page, and as I say, it's not a newspaper that you're writing, but the front page becomes really important.

It's a crucial bit of real estate in your research note because it's often the only thing that gets read.

Usually investors will just scan the front page and then move on.

And it's only if they really like your investment idea that they'll go on to read even the next few pages and rarely the full note.

Yeah.

So making sure the front page is really clear and has all the essential information on it is really important. And for that reason, the investment banks will have a very clear template for how the front page will look.

The example that Claude has come up with is not quite how ours would've looked when I was working at Barclays, but not too dissimilar.

So what you tend to have right at the top is the ratings, it's a sell rating.

Mm-hmm. Your target price, that's the price that you think the shares should be trading at.

And as you'd expect, if it's a sell rating, the target price here is below the share price. The analyst is saying that they believe that the shares are overpriced. And then you've got that downside of 15%.

That's just the percentage difference between the target price and the share price.

So if I was to sell the shares today at 33.68 and the shares re-rated, that means repriced, to the target price of 28.5, then I would lock in that downside as a gain for me, 15% gain.

So- Yeah ... that just basically helps to give you some idea about the conviction there.

You wouldn't normally expect a sell rating, or if it's only 1% or 2% downside, it's not really worth it for that. So you want a nice clear bit of downside for a sell rating and a nice clear bit of upside for a buy rating.

Oh, so one more thing just that kind of sticks out to me, just literally in the top block here, is that Chipotle's equity value is lower than its enterprise value.

So it's got a net cash position.

Yeah.

Why do we think a company this big, $40, $42, $43 billion, has zero debt? Yeah, it's interesting, and this is where I completely reveal my lack of knowledge about Chipotle as a business. But what I suspect is either that they have a lot of leases of their stores, or I don't know how much of it is franchise as well.

So I don't know how much debt the company actually needs.

So, yeah, it is a bit unusual that the market cap is higher than the enterprise value. That's not usually the case.

Yeah.

Yeah.

Okay.

So the other thing we've got, so if we scroll down, we'll come back to the text on the left-hand side, but the right-hand side margin is kind of all of your data and stats that you need to support the thesis.

So you've got the share price chart, that just gives you a nice bit of idea about how the shares have traded in recent months and years.

And as we can see, there's been a big drop in the share price, and I think that's kind of tied into the thesis that we'll look at in a minute.

And then we've got the key data, things like the 52-week range, the number of shares. That becomes really important, particularly for a sell rating.

You want to make sure there's good liquidity in the market because we've all heard about short squeezes where investors have shorted and there's not enough liquidity to exit that position. And then as we scroll down, we've got on the right-hand side the analyst estimates. Their own forecasts for how they think revenues and particularly EPS, that's the key metric that analysts look at, how that will develop over future years. And that is compared to consensus.

We have an idea there of the delta versus consensus.

And actually, that's a really important one.

And then just looking at that, maybe slightly unusual that this analyst forecast seems to be ahead of consensus. Normally, if we're putting on a sell rating, we're more bearish than the rest of the market, and we actually don't see that there.

So that seems a little bit surprising.

Is part of this driven by... I guess what we don't have is a comparison of just the overall financials. We have an EPS comparison.

So I guess there are a lot of factors that can go into managing EPS, right? You can buy back shares to- Yeah ... not artificially, but actually increase your earnings per share.

So I wonder if, I guess we need to know what kind of forecast is going into all of that calculation to know really how we're doing versus the Street.

Absolutely. But it is something that, it's one of the first questions you usually get asked as an analyst when you put it on a buy or sell.

Where are you versus the market? Are you ahead or below consensus? And as you say, it's kind of the trickle-through.

Is it the revenue, the EBIT or EBITDA level, and then EPS? How does that kind of tie into your thesis, as it were? Yeah. Okay.

So shall we dive into the thesis? Yeah.

Right. So on the left-hand side, we've got bullet points, which basically give you an overview of why the analyst has come up with a sell rating, okay.

And so the idea is to convey in as succinct a way as possible what has led the analyst to view that basically Chipotle is overpriced.

Now, I would say this is quite a verbose front page.

What we like to do as analysts is usually have two or three key points, and there's actually five or six bullet points.

So I'm going to maybe focus on the ones which have got the one, two, and three here. So they say here that every scenario we can defend values the shares below the market.

So what the analyst, or what Claude has done, is build three scenarios, a bull, a bear, and a base case scenario. And their argument is that even on all of those three scenarios, you still come up with a target price, which is below the current share price. So that provides quite a lot of- Yeah ... conviction to the call. That's what we kind of like to see for a nice, strong sell recommendation.

The second one, I think this is really the crux of the thesis, is to do with the fact that, as we saw, Chipotle's shares have dropped in value.

It's started to recover, and really, I think the price at the moment is, the analysis suggests that the recovery is fully priced in and maybe a bit more, compared with what we see at the moment.

So it says the recovery is in the volume, so in terms of transactions and in revenues, but the margins for Chipotle are still well below where they were a few years ago. So I think margins for Chipotle in 2024 were around 28, 29%.

They're now at- Okay ... I think 25%. So although we've got increase in volume- That's a big change ... yeah, it's huge. It's huge, and I think they've been really struggling with a whole host of things. A large amount of that was to do with a reduction in volume and a reduction in their revenues, and as a company with quite high fixed costs, that immediately hits their margins. Yeah.

Yeah.

They've got operating leverage, which means that if you see changes in volume, it quickly feeds into their margins.

We've now got the recovery in the revenues, but we're not seeing that in the margins. And the argument here is that the share price implies that we've got both volume and margin recovery, and we don't.

So that I think is the crux- Yeah. Okay ... of the thesis. The third point, as is usual, is maybe a little bit weaker and a bit more techy. It says the growth is increasingly bought from the existing ring fence. There's some quite techy point here about, to do with store openings there.

I think the core element is to do with the margin story and that we've got recovery without margin recovery.

Yeah, it's funny. As we've been talking, I've been reading through that third point, and even I was like, "What are we really trying to say here?" Right.

Growth is increasingly bought from the existing estate. I don't...

Just as a headline, I don't know what that means.

Sure. It's interesting you say that.

I think just before we started recording, I was trying to read through this and some extra notes that Claudia provided.

And I was really struggling to understand some of the language used, and I think sometimes- Yeah. Yeah. Right ... it tries to mimic the language of analysts, but it's kind of going a little bit beyond and using language that I just don't understand.

Exactly. Because usually when you talk about buying growth, it means you're acquiring another business or new stores or whatever the case may be.

But you don't really buy growth from your existing store estate.

It just doesn't connect in my mind anyway.

Yeah.

And I was reading through it and I'm like, "I don't really know what this is saying." Saying. No. And that's an important learning point because to be honest, on your front page, you want to be left with no confusion as to what your thesis is.

Yeah. Exactly.

Your clients want to argue the toss about whether or not the margins should be priced in or not, but what you really want is a clear sense of what you're trying to say, and that I think doesn't really come across here.

No.

So- No, exactly ... so I think a few other things to highlight on this front page, and something that we always are very clear on the training research analyst, is that it's all well and good to have a really strong thesis, but there's two other things that you really need to convey to your clients.

Number one is catalysts for the call, and you can see that on the right-hand side of the note. A catalyst just is an event that triggers the re-rating, the re-pricing of the shares. It's when the market basically realizes- Okay ... that it was wrong. And so catalysts, they can be just the next set of results, and that's one of the catalysts here is the next set of results, where if the margins continue not to show any recovery, then that is a reinforcement to the thesis here. But you can get other catalysts as well. It could be investor days.

It could be external data points like, for example, food cost commentary, what's happening in terms of food pricing.

So, anything that is ideally in the near term that is going to help confirm that you are right and the market is wrong.

That's what you're really looking for with a catalyst because ultimately, if investors have to put their money on the table, they want to know that there is going to be a repricing soon. They're not going to be still sat here three years' time with you saying, "I'm right, the market is still wrong," because that's three years- Yeah. Okay ... that they've had opportunity cost of their money on this bet that hasn't yet come good.

And presumably on these catalysts, if you're an equity research analyst and you're covering 10 companies, you are participating in every single event the company puts on, whether that's an investor day or an earnings call, because you just have to know everything.

Oh, yeah. It's completely a live thing.

In fact, when you initiate on a stock, you're effectively saying, "I'm now actively, constantly monitoring everything and anything that is relevant to this company, and that I will respond, updating my views as and when that happens." Yeah.

That you're basically- You know- ... it's a constant dynamic thing.

It's not just a one time, "Oh, this is my view, and I'll come back to it in two years." I wonder if that's something that is getting...

I would assume this is something that's getting easier with the advent of these kind of tools, right, because I think about that style of analysis that I used to do when I was say a first-year analyst.

Mm-hmm.

And obviously I was in equity research, but you're also covering companies effectively, right? So you have your Google News alerts set up to say, "Okay, I've seen this company in the news." Now you can do that a lot more on a much more automated fashion. Or even doing work on a company saying, "Look through all the recent investor presentations, all the earnings calls." A lot of this is just easier and faster to do.

But I guess- For sure ... one thing you still miss if you're just trawling through data is the...

I would assume that there's an element of you get to know the management team a little bit. Even if you don't have a direct relationship with them- Yeah ... you know their presentation style, and maybe you think they're b**********g you or hiding something.

So I could see actually listening to each one of these calls once a quarter being really important.

Yeah, for sure. Interestingly, on the point about the news flow, it used to be the junior on the team's job, on most sector teams, to come in every morning and read through the Google alerts and just basically- Yeah ... decide is there anything that I need to escalate here to the covering analyst.

And yeah, all of that can now be completely automated.

Likewise, we used to do a lot of scrutiny of earnings calls, the transcripts, understanding the language used by management, and all that sentiment analysis can now be completely automated as well.

Yeah.

So I think in a way it makes it easier to filter, but the downside is then it also makes it harder to have an edge, to have something new- Yeah. Yeah. That's fair ... that no one else in the market has thought about.

So I think, yeah, there is that.

I guess it's a trade-off really, isn't it.

I was going to say, what happens on the way is the need to really understand the companies because really, you can do a huge amount of analysis using AI.

It will be able to trawl through all the public sources.

But ultimately if you've got the history and the expertise and the knowledge, you will be able to provide read-acrosses that no one else has provided.

That kind of industry expertise is so crucial.

Now just on the note of earnings calls.

You've listened to, I assume, thousands at this point.

What's the craziest one, funniest one? Have there been any times you're like, "Oh my god, that was just nuts." It's interesting. So not really. So I don't think earnings calls for me are usually where anything particularly exciting happens.

I think unless the company's really under pressure, they tend to be quite formulaic.

I have listened to some investor day ones, which the company is trying to recover from a really tough time, and it's really clear that they're trying to put some positive spin on it, and that's not really hitting home with either investors or- Yeah ... with analysts. So I would say that I find the investor day ones more interesting, if I'm honest.

Okay.

But yeah. And I've definitely had situations where I've made calls which have gone completely wrong. There's one particular company where we got a buy recommendation out, and the company went bust within six months. So, yeah.

I don't always get it right. And on that note You don't.

Yeah. That's just the world we live in.

Yeah. Absolutely. And kind of on that note, at the bottom of the research report on the front page, risks to the thesis.

So ultimately, your thesis is based on two or three pillars that you think demonstrate why the market is wrong.

You have to acknowledge sometimes that you might be wrong.

And so you have to highlight for your clients where the risks are in that thesis or risks that basically that you've got things wrong.

So, it does say that probably the key risk here in this thesis is that they suddenly end up with their margins snapping back, recovering to back to 2024 levels. That completely erodes- Yeah ... this thesis. So you have to acknowledge that.

I think one of the more interesting risks are ones where you've done a load of research on a particular theme or issue.

You're very confident that you're right on that, but there are other risks in the business which you haven't necessarily explored.

I think a really good one I remember was where there was a massive legal case a company was defending itself on, that we'd done a lot of work on the operational side, but ultimately, whatever our view was on the operational side, it would be completely wiped out if they weren't successful in defending themselves against this legal case. So that was the big risk.

The thesis was that the results of that legal case.

So it's important that we recognize that, and then anyone on the buy side who wants to go with your investment call, they can do their own work to reassure themselves on those risks.

Yeah. Ultimately, this is kind of what it's all about, right? No risk, no return.

No risk, no reward. You're always taking some kind of risk.

And obviously, this is something I spent a lot of time thinking about over the years because we can talk about at some point the kind of differences between the equity investment hypothesis and credit investment hypothesis.

Yeah.

But on the credit side, you're really focused on downside protection.

So what are the things- Yeah ... that can go wrong here? And ultimately, you're not trying to say that these are not risks, right? Because you have to take some.

What you're trying to do is say, "Okay, I see them, I understand them, and here's my realistic real-world view where if they all or some of them actually play out, here's what I think it means for my investment position." That's kind of- Yeah ... high level, I'd say, how you think about it.

For sure. And I think that would be a great thing to cover in a future episode because, as you say, the way that we approach things for equities versus credit is quite different. The scope of what you're interested in is actually quite different as well, isn't it? So I think this is really interesting, right? Because we now have...

This took, what, probably the better part of a half hour or hour or something like that. But imagine if you're doing this work as an analyst at an investment bank.

This is the product of weeks of work and research, building models, doing research- Mm ... all the stuff.

Yeah.

How far away are you, or how far do you think away we are from being in a world where equity research is going to get replaced? Where we're going to have fewer equity research analysts, where we're going to turn to these tools and this kind of resource for this kind of work going forward? Based on your view of what this looks like, how far away do we think we are from that kind of world? Yeah. It's an interesting question.

People have been talking about equity research kind of disappearing for a long time. There's been various regulatory changes, sort of about a decade ago.

And just in general, the structure of the buy side has changed slightly.

We've got much more passive investing than active investing these days.

And there's been plenty of chat that equity research is just disappearing, and it still hasn't disappeared. But I do see that AI presents a big challenge, or at least it changes the way that the sell side operates.

And it does allow for much smaller teams. We used to have quite large teams.

It's very labor-intensive poring through results. You just don't need that anymore.

You can have much leaner teams, and you can have teams covering more stocks.

I think there is still room at the moment for really good value-added research.

But that requires expertise that really you know your industry, you know your companies really better than anyone else on the street.

That will help provide value-added research.

And as I say, for, and that's the buy side, who they don't have the ability to constantly know what's going on in every single company that's in their portfolio all the time. So I think there is still scope for sell-side research to provide value to the buy side. But AI does sort of change the way they operate, force the sell side to become a little bit more efficient about how they work.

Yeah. In some ways, you can see it being kind of an opportunity, right? You can do more and cover more stuff with fewer resources.

Maybe you're publishing a little bit more often than you used to.

Mm.

Because obviously, this is indicative of an initiating coverage report that's a lot more fulsome than a typical kind of update note.

Maybe we'll see more fulsome notes on a regular basis.

Which because I remember when I was in M&A, you're using these to put models together all the time.

And of course, you're always looking for initiating coverage because you have the most comprehensive set of info.

Yeah.

So maybe we'll just have better and higher quality access to sell-side equity research that's beyond just the pure, "Okay, here's the update to our consensus EPS estimate." It's everything updated in a slightly more regular fashion. Maybe.

Yeah. I do also wonder if it slightly gives an advantage to the much larger research firms because the sort of joined-up thinking that they can provide.

I think we've seen some really interesting research on AI and data centers.

And if you've got a research team that are able to talk to the credit analysts around their views on the financing for data centers, the economics team on economic growth.

Yeah.

The fact they can do that kind of joined-up thinking across the firm, I think really allows them to provide value in a way that maybe some of the smaller firms would struggle without that kind of richness of data and expertise.

We'll see.

We'll see.

I have to be really careful not to say this is the end of equity research, like Robert just did.

Yeah, exactly. Otherwise, we end everything.

Yeah. Okay. So I think that brings us to the end of this week's episode and our deep dive into equity research reports. I hope you've enjoyed this week's episode.

I hope you found it enlightening. And that's all for this week.

Thanks from me, and over to Graham.

Cool. Thanks, everyone. We'll see you same time here next week.

In the meantime, take care.