PM @ LRT Capital - Always be optimistic.

Austin, TX
Joined April 2009
LRT Global, Sep 2026: +6.94%; +38.23% YTD; +25.18% since inception. All numbers net. More at lrtcapital.com
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Lukasz Tomicki retweeted
again, this poll comes from @YouGovAmerica. I see that a lot of people with anonymous accounts don't like it.
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Lukasz Tomicki retweeted
Under @mmpiatkowski’s post comparing Poland 🇵🇱 and South Korea 🇰🇷, there was a surprisingly large number of salty Korean replies: “Poland is just Europe’s version of Vietnam”, “its productivity is an optical illusion due to R&D by foreign companies”, “if we were located in Europe, we would have smashed the heads of Western Europe”. The post was hardly meant to diminish Korea’s success IMO. A lot of it is simply wrong. Yet it is worth exploring how the two countries got to the same place in very different ways. 1. East Asian vs post-communist development model Korea is a textbook case of the East Asian model, pioneered by Japan and later followed by China: suppressed consumption created high savings, which were funnelled into investment through state-directed credit to build domestic industrial champions. In its catch-up decades Korea also bought foreign technology on a massive scale and ran large current-account deficits, with investment peaking close to 40% of GDP in the early 1990s. Even today it invests around 30% of GDP, against 17-20% in Poland. Korean households consume 48% of GDP, Polish ones 57%. Koreans save and invest far more of what they earn; Poles spend more. Poland instead opened up to foreign investment and plugged into European, largely German, supply chains, importing technology through foreign firms. So yes, the “foreign companies” point has something to it. But crucially, neither country could have taken the other’s path. Korea industrialised from scratch, with no rich single market next door and no EU funds. Equally, after 1989, and certainly inside the EU, state-directed credit, capital controls and protected industries were off the table for Poland. The two simply responded to very different conditions. 2. Korean juggernauts attached to a much less productive economy Korea indeed produces world-renowned tech mega-corporations with massive innovation output. But the rest of the economy lags far behind. Business services employ 41% of Korean workers, yet a service worker is less than half as productive (48%) as a manufacturing worker. In Poland, they are more productive (115%). The same split shows up by firm size. SMEs employ 80% of Korean workers, but their productivity is only 44% of that of large firms, one of the widest gaps in the OECD (Poland 58%, OECD average 65%). Samsung alone accounts for roughly a quarter of all business R&D in Korea. This concentration is also reflected in Korea’s low number of so-called hidden champions (mid-sized world market leaders): Poland has 37, Korea 22. Per person, that’s 0.96 vs 0.42 per million. Both are tiny next to Germany’s 19 per million. Poland and post-communist Europe certainly need more homegrown champions, many of which are already growing, and more R&D to keep converging. But they will hardly match Korea’s R&D spending, which no country in Europe, nor the US, comes close to. And their champions will look more like the German Mittelstand than Samsung: inside a single market, not every country needs its own Samsung; that is the point of the model. So far, it has delivered the same productivity with less investment, more consumption and an arguably more balanced economy, which may yet prove the more efficient path. None of this diminishes Korea’s achievement: rising from poverty to the technological frontier largely on its own is one of the great economic stories of the last century.
Poland 🇵🇱 and South Korea 🇰🇷: two global growth champions with two different growth models and social outcomes. Over three decades both grew fast (4.2% vs 3.7% a year per capita) and reached the same productivity (~$52/hour), but with very different R&D spending: 1.4% vs 5.1% of GDP. On social outcomes, Poland ranks #24 in world happiness vs Korea's #67, with half the suicide rate and a third of the old-age poverty (13% vs 40%) 👇 The shared challenge: among the lowest fertility rates in the world, 1.07 and 0.80. @Noahpinion @KoreaEconInst
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1/ $FCFS (FirstCash) is one of the more interesting compounders in financial services. It operates 3350+ pawn shops - serving consumers largely ignored by traditional banks. A fragmented industry, strong unit economics and a long consolidation runway.
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10/ The long-term thesis for $FCFS is straightforward: a scaled, well-run consolidator in an enormous fragmented market, with attractive unit economics, recurring demand and international expansion opportunities. If management compounds earnings while maintaining capital discipline, shareholders should benefit.
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Lukasz Tomicki retweeted
Kto wpuszczał imigrantów do Polski?
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Lukasz Tomicki retweeted
The Theranos CEO and convicted fraudster reveals all — or possibly fools the world again — in a shocking, hilarious, sad film from Nathan Fielder and Lance Oppenheim. Tap here for our film review: ft.trib.al/v0lJrdr
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Lukasz Tomicki retweeted
Happy 5-year anniversary to those who celebrate. $UPST
Omg too funny he likes $UPST but doesn’t even know what they do..😂😂😂 This is why I never watch CNBC…makes you dumber!!
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Lukasz Tomicki retweeted
Every time I go to Europe I feel better about the prospects for America. A few thoughts:
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Lukasz Tomicki retweeted
There are a legion of posters now putting out AI quant trading models. Most are crap. Here’s a quote from this post: “Betting Against Beta, a classic from every textbook: minus 7.78% a year while the market rose 14.86%. A corpse.” Of course I can’t find how it’s constructed or what period he’s referring to (or what paper he claims to base this design on). Welp… There is no period starting from today and looking back any decent amount of time that has BAB significantly down (available on our website). It’s been flattish in the USA for a bit but still good global ex USA. Its long-term record is still great. The chief challenge to BAB comes from Robert Novy-Marx where he says it’s empirically subsumed by the profitablity. This is an interesting debate (we still prefer a portfolio of both, partially as the economic story for BAB is better than the one for profitability). Again, economics not just AI. Economics with AI can be super powerful. AI w/o economics, or any understanding of the literature, in a “small data” problem like investing *at all by high frequencies) is a recipe for silliness. Like the post below. I suspect what has happened here is a mistake I’ve pointed out in other papers. The BAB factor needs a hedge ratio. You short less than you long as the shorts are (this is the point) much higher beta. If you do it dollar neutral you are running a very short the market position, and not doing the BAB factor as anyone serious has learned in the large literature. Thus in a bull market you wrongly think it stinks. Or they just did it all wrong in some other way. They don’t explain a lot. This is why AI in the hands of people who don’t know economics, haven’t read the literature, etc., is handing a nuclear weapon to those who should only have a butter knife if they pass a test and get a license. And it’s why I think these people are suppliers not consumers of alpha for the foreseeable future. One day that may change. Hopefully whoever takes over for me at AQR in my coming dotage (not for a while!) can deal with that. Oh, and “corpse.” Rude as well as wrong. Cool graphics though.
Ken Griffin, who runs Citadel, just admitted that the most expensive skill of his quants, the one he paid them millions for, now costs nothing And for the first time in history, that skill belongs not just to a hedge fund, but to anyone with access to AI A fund's entire quant team runs one cycle: come up with a strategy, turn it into code, test it on history, deploy it to the market Every step used to cost separate people and years of training. Now AI does the whole cycle You describe an idea in words, it writes the strategy itself, runs it on years of real data, and if it's alive, deploys it straight to a broker But the speed isn't the point. The point is what the retail trader doesn't understand You take a strategy with a beautiful chart and you believe it. But a beautiful chart is no proof Run enough versions and a profitable curve will appear even on random numbers. One just got lucky, and you decided you found gold Funds don't trust any curve until they test it on data the strategy has never seen. There the fit falls apart, and a real edge survives I ran two of the most-cited quant papers through this cycle Time Series Momentum on Bitcoin: +1,537%. Alive Betting Against Beta, a classic from every textbook: minus 7.78% a year while the market rose 14.86%. A corpse One still prints money, the other died long ago. And trading blind, you'd never know which is which until it took your deposit If you want to run your own idea through the same test, it takes minutes here (free trial after signing up): join.horizon.trade/qwinsiiii The entire hedge fund is six steps. AI already ate four of them. Which ones, I broke down in the article below
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