Idea Brunch with Myles Kuah of Value Zoomer

Myles is a young, self-taught long/short investor raised in the jungles of Samoa. He is focused on deep value international stocks and shares ideas on his free Value Zoomer substack and @finphysnerd on X. His portfolio largely consists of the A$500,000 he received after winning Survivor Australia in 2025 and he currently resides in Sydney, Australia.

Myles, thanks for doing Sunday’s Idea Brunch! Can you please tell readers a little more about your background, your investment process, and why you decided to launch Value Zoomer?

I got into investing in late 2019 as I started building some savings from my first job bartending. I wasn’t doing valuation, I was reading Motley Fool articles and punting blindly on vibes, and I got lucky enough to get wrecked in my first year, which drove me to actually put the time into learning how to invest properly. I’m still early in my journey but after a rocky first few years my last 3 years have been consistently strong.

My investment process is pretty all over the place. I get ideas from Twitter, from screeners, from reading the ASX and SGX filings every day, and now often like to get Claude to give me random companies or themes to look into. I run long and short. My research process for shorts is honestly very quick. I look at a company for 5-10 minutes and can quickly assess whether I want to short it, but my position sizing for shorts is small (most below .1%). For longs the first thing I do is look at the financials, and if I find the financials interesting I dig deeper. I’m still not a “deep research” guy except with my largest holdings, and even then I suspect I’m going less deep than a lot of analysts. My aim is to figure out what matters in the thesis, and be right about that.

As far as launching the Substack my purpose at the time was simple. I wanted a public ideas track record that I could use to both self assess, and also to be more employable. Writing up an idea forces me to understand the ins and outs enough to present them to a reader. On top of all of this I just enjoy writing up ideas that I find interesting. The substack has been amazing both for building a community of readers who give me feedback on ideas, and also being able to self assess critically my previous ideas.

I’m obsessed with your research on leveraged ETFs, which you’ve called “the highest alpha I’ve ever put out.” Can you please share your main research points on leveraged ETFs and whether you’ve been able to put on real money trades to profit off your findings? Why do individuals keep investing in leveraged ETFs if they are destined to underperform?

The leveraged ETF stuff all started with me reading a paper by Hendrik Bessembinder breaking down the sources of underperformance for leveraged ETFs. One source of underperformance is volatility drag, which is the decay in a leveraged instrument due to volatility (eg 1*1.2/1.2 doesn’t equal 1). While I knew about volatility drag, I (and most people) wasn’t aware of the extent to which financing costs and other unspecified costs cause these single stock ETFs to underperform. Essentially, your traditional leveraged ETFs would leverage an index, and would have access to cheap (50bps above the base rate) financing to build these products. However, the riskier single stock ETFs get charged significantly higher rates, with areas like crypto and meme stocks being charged well upwards of 2000 basis points above the base rate. I haven’t really seen anything else online written about this.

When borrow fees are low enough (and I track the borrow vs underperformance for upward of 170 ETFs) you can short the 2x ETF and long the underlying, and with the right risk management and trading rules make a very decent, low risk, uncorrelated return. I have been running these strategies for around 6 months now and while I’ve had to tweak and adjust at times, they have provided a very reasonable (>10% annualised) uncorrelated, low risk return. As far as why people keep buying them it’s because your average retail investor has no idea how they work. Many of them don’t even know what volatility drag is, let alone embedded finance costs that aren’t disclosed anywhere (which to be honest I think is pretty gross from the ETF providers). Most people see 2x ETFs as too complicated and avoid looking at them altogether, however I suspect that somebody has started paying attention as I have noticed the spreads between underperformance and borrow cost have compressed recently.

Can you tell us a little more about your research, investment, and writing process?

My research process focuses around identifying the core driver of the stock, while assessing the downside. I think I’m very downside and risk focused, and will always prefer a decent return with limited downside to a high return with moderate downside. I will always read the filings, the quarterly and annual reports, transcripts, etc. I try to read about and understand the industry in decent depth as well, and this is a particular area where AI has been a major factor. I don’t like to get into the nitty gritty, I don’t have the time, money or energy to be out there talking to suppliers or employees, and generally avoid approaching management unless I have a specific question. I think most of the best investment theses are pretty simple, and I’m happy to occasionally miss some little detail as long as I’m getting the core drivers of the stock correct. To be frank, as an individual investor with a social life I have to be deliberate with how I allocate my time. For longs, I have 5 different sizes which are speculative .5%, starter 1%, base 2-3%, core 4-6% and conviction 9-10%. I have around 100 long positions, though I’m trying to cut that down a bit at the moment, and I’m open to all types of ideas at any size except conviction positions, which need to have limited downside.

As for the writing process I imagine it’s a bit different to people such as yourself who do it professionally. For me writing is a hobby, so I write when I feel like writing, and I write when I have an idea worth writing about. One common theme across my writeups is that most of them are interesting companies. If I don’t have any good ideas I don’t force anything, which is why I think many of my writeups have performed very well. When I do sit down and write I kind of just shoot from the hip. I write pretty colloquially, and try to keep my ideas succinct and to the point. Most people don’t care about the 50 year history of the company and what the CEO’s mother ate for breakfast last year. My focus is what they do, why they’re interesting, a breakdown of the financials, and a breakdown of the risks with my favourite question in investing “why is this stock cheap?”.

A big theme in your tweets is the impact of AI, especially among your short ideas. What sectors or companies do you see being most hurt by AI?

The AI revolution is probably the most significant technological development we’ve had since the development of the internet. I do find it hard to assess the long term impact. To be honest I don’t really understand how most people have any level of high conviction on how AI and the world will look in 5 years. With regard to AI my focus has been on separating out the obvious losers from obviously defensible companies that are down with the losers, from the stuff that I don’t have a strong opinion about. I try to short all the obvious losers in small size, even as they continue to get cheaper because most people historically underestimate the impact of a declining terminal value on a stock (look at newspapers in the 2000’s). On the other side I’ve been tactically long companies like $SPGI, $MCO, $V, $MA, $ADP, $RDDT which have been sold off on AI fears that I believe are unwarranted due as these businesses have genuine moats protecting them from disruption.

I think one underdiscussed area of AI impact is advertising. Advertising is a natural beneficiary of AI as margin improvements and efficiency gains in other areas will potentially lead to higher marketing budgets. While there will be a huge amount of low quality advertising space generated through low engagement, AI produced content slop, higher engagement targeted content like affiliate marketing ($ZD, $FUTR.L) will see significantly less clicks as people consume them through AI. As an example, when someone is looking for a credit card, instead of them reading a sponsored article comparing credit cards, the AI will read it with no chance of an ad click. Even something like Google search ads could see less engagement eventually as AI disrupts search. The clear beneficiaries here are any companies that hold high quality, targetable ad space like $META and $RDDT, both of which I own. On the other side, companies that use that kind of content to generate leads like LendingTree, EverQuote and MONY.L in the UK could see significant increases in customer acquisition costs.

Another specific area I want to call out here is Australian software. The Aussie share market has been overvalued for a while as superannuation flows prop up our best large cap stocks. Due to a lack of quality growth, any remotely high quality Australian stock has been bid up to the moon historically, to an even greater extent than in the US. While we’ve seen a derating, I believe that the opportunity set on the short side in software is more attractive than in the US due the lower quality of the companies at comparable prices. One specific example of this is Seek, Australia’s dominant job listings website. While Seek does have network effects, it’s not a monopoly with cashed up competitors LinkedIn at the white collar level and Indeed for blue collar jobs. Seek is already at an expensive 22x earnings with low growth for a business that I believe is going to deteriorate due to AI. Employers are already getting steadily inundated by low quality AI presented candidates hurting the value proposition for employers and candidates. Meanwhile, if candidates end up using AI agents to research and search for as we are expecting in many other industries then the value of listings, especially paid ones disappear. Classifieds businesses worldwide are being slaughtered, and Seek is lower quality, lower growth, more expensive, and more exposed to AI disruption than many of them. While Seek is my largest and highest conviction short within this bucket, there are many examples of these kind of lower quality at higher valuation software stocks in Australia that while down a lot, are still being overlooked.

You’ve said your favorite answer to “why is this stock so cheap?” is “nobody is looking.” What are the signs that tell you a stock is overlooked rather than ignored for good reason?

The core of my investment process is built around turning over rocks, with a focus on rocks that aren’t being turned over often. I’m not against investing in large caps, but I need to have a really clear, differentiated view on why the opportunity exists. “Nobody is looking” ideas are my favourite type of idea as they are the only times when you get presented with actual free money, where you get good opportunities without having to take a contrarian view to the market. These kind of ideas pop up most commonly in niche markets like Asian and European microcaps, and occasionally in Australian, Canadian and US microcaps (though less often as even these areas have so many eyes looking over them). I like to look for a lack of twitter comments and substack articles about an idea, but even more notable is watching how it reacts to news. I’ve seen takeover offers, profit guidances or other transformational announcements that have barely moved stocks, and that’s the sign that people aren’t paying attention. The best ideas I’ve had have been cheap, dead money value traps where a catalyst finally arrives after everyone has stopped caring

You have a diverse portfolio – ranging from a small French holding company to Japanese SaaS companies. How are you able to come up with off-the-beaten-path ideas in an industry with so much groupthink?

This is going to sound a lot like me blowing my own trumpet, but I do think I kind of just think differently about the world compared to most people. I’m a pole dancing, finance obsessed, nerd who likes roleplaying games, live music and rugby, and won one of the largest reality tv shows in Australia last year. It’s not just investing, everything I do in life is outside of the box and it’s never really been weird to me, I just do what I want to, how I want to. More specifically with regards to finance I’m self taught. I studied a physics degree and while I picked up a few finance classes, most of my investing ideas have come from a combination of listening to people smarter than me and personal experience. I’m still early in my investment journey, and I’m finding new lessons to learn every year, but I think I go into this whole process a lot more open minded than a lot of people who figure out a specific style or sector and decide that that’s their focus. My investing style is malleable, which makes me able to bounce around between different types of ideas easily.

To be honest, I don’t understand why so many investors gravitate to the same kind of ideas. I’ve always just turned over rocks and gone where I’ve found value, and it just happens that I find a lot more value off the beaten path. One of my largest positions currently is Reddit, so I’m not opposed to owning more popular stocks, but there are thousands of stocks on the market and I find the higher return on time when I’m looking at ideas that are undiscovered so that’s what I naturally gravitate towards. When you hold a large cap stock like Reddit you need to have some serious conviction around what the collective mind of the market is getting wrong because I do believe that while dislocations do happen regularly, as a whole the market is reasonably efficient.

What are some interesting ideas on your radar now?

In the US a stock I see as the anti-AI stock is Reddit (NYSE: RDDT — $30.0 billion). At 25 years old, I like operating in stocks like Reddit where I feel I have somewhat of an advantage in understanding the product and user base over the generally older finance community.