Andreas Clenow: Simplicity, Momentum, and Systematic Trading | In The Money by Zerodha Podcast 06

ELI5/TLDR

Andreas Clenow is a Swiss fund manager who started cracking games on cassette tapes in the 1980s and ended up managing nine figures. His core lesson after decades in systematic trading: the entry and exit rules matter far less than how you build the portfolio around them. He thinks most trading books are useless, most technical indicators are pen-and-paper relics, crypto is worth zero, and the single best thing a retail trader can do is manage other people’s money alongside their own.

The Full Story

From Cassettes to Capital Markets

Clenow got into computers at eight or nine, back when starting a game required actual technical knowledge — loading from cassettes, bypassing copy protection, cutting floppy disks with scissors to double their capacity. He studied finance at Gothenburg, got inspired by the 1986 Wall Street movie (the one Oliver Stone made to discourage people from entering finance), and naturally combined his IT skills with markets.

“Everybody thinks they’re a genius in the bull market. I thought I was clever back then. Of course, I wasn’t. I was a lucky kid. Right time, right place.”

He started investing during the dotcom boom, did the classic naive math — compound your best month over ten years, calculate when you buy your island — and eventually realized his “brilliant strategy” was just buying stocks in a bull market and hoping for the best.

The Shift to Systematic

Skepticism drove the transition. Clenow started trying to quantify the claims he read in trading books — Elliott Waves, Fibonacci ratios — and found none of it held up under mathematical scrutiny.

“If somebody tells you that the universe is based on predictable waves where it’s five waves up and three waves down… it’s some sort of pseudo-religious nonsense. If you believe in these things, go join a cult.”

The things that did work turned out to be simple. He launched his first trend-following futures fund around 2005-2006, trading 50-100 futures contracts across stocks, bonds, currencies, and commodities. The math was not complex. The edge was in portfolio construction — what you include, how the markets interact, how much risk you allocate to each.

2008: The Best Worst Year

Managed futures had their most profitable year ever in 2008, riding crisis alpha while stock markets lost half their value. But Clenow describes it as PTSD-inducing. When your entire fund swings 15-20% in a day, you override your models and cut risk — even if staying in would have made more money. The real nightmare was cash management: spending every afternoon analyzing which major investment bank was least likely to blow up in the next 24 hours, then placing overnight deposits accordingly.

Trend Following vs Momentum

Clenow draws a deliberate line between these two. Trend following works on diversified futures — uncorrelated instruments, heavy leverage, both long and short. It does not work on stocks because of two structural problems: extreme correlation (everything is beta — stocks all fall together in a crash) and leverage being expensive and dangerous in equities.

Momentum is the related but distinct approach for stocks. You are loading up beta, full stop. You are figuring out where beta is worth taking and concentrating there. His momentum model from the Stocks on the Move era has been running for over a decade and recently produced the best performance of his career.

“It’s not rocket science. We’re just figuring out where the beta is worth taking and we’re loading up a lot of beta.”

Portfolio Construction Over Trading Rules

This is the interview’s central thesis. The specific entry/exit signals — moving averages, breakouts, whatever — are almost irrelevant compared to how you compose the portfolio. You might even include instruments that lose money individually because they improve the aggregate risk-adjusted return by diversifying when gains and losses occur.

“It’s never a matter of the best possible rules, the best possible system, the most profit. That’s not how you build a professional trading strategy.”

The car analogy: you could build the fastest car in the world, but that is not a business strategy. A handful of Saudis will buy it. The money is in building Toyotas.

Regime Filters and Downside Protection

For equity momentum, Clenow prefers not to react to short-term volatility — sharp drops usually bounce back. The real danger is a prolonged bear market, where momentum stocks fall harder than the rest. His approach: scale out gradually as conditions deteriorate rather than using a binary on/off switch. Multiple indicators vote together — overall market volatility, dispersion, the pattern of individual stock momentum across the index. At the extreme, when everything looks terrible, you start scaling back in.

The Counter-Trend Model Born from Frustration

After a rough year of getting stopped out repeatedly on trend-following, Clenow reverse-engineered where the large trend-following firms likely had their stop losses. He placed entry orders just below those levels, picking up the exaggerated bounce after mass stop-outs. It has worked remarkably well on futures.

The Managed Futures Industry Today

The business side killed the fun. In 2006, you could explain trend following to institutions and watch their eyes light up. Now it is commoditized. Fees are down, compliance costs are up, and the game is brand management — like trying to sell a slightly better toothpaste against Colgate. Either you become a massive player (Winton’s David Harding at $40-50 billion AUM) or you find a different niche.

Crypto: Price Target Zero

Clenow has held the same Bitcoin price target for 13-14 years: a donut. No real use case for Bitcoin, blockchain, or NFTs. Every few weeks the crypto world invents new words to pretend there is innovation; it always turns out to be a variant of the same thing. Blockchain is a solution in search of a problem — slower and more expensive than existing tools.

The one concession: if you view crypto purely as trading stupid money (psychology-driven, no fundamentals, strong herding), momentum strategies can work. Just do not fall for the narrative.

“Where else anywhere can you find as much stupid money as in Bitcoin?”

Why Trading Your Own Money for a Living Is Bad Math

Not an insult to retail traders — a structural argument. If you quit your job and live off trading, you take all the risk for limited upside. You need to withdraw for rent and food, shrinking your capital base. You start aiming for unsustainable returns (50% a year) to make the math work, which forces you into extreme risk. The best people in the world compound at around 20% over long periods.

The fix: manage other people’s money alongside your own. You collect management fees (income floor), aim for realistic returns (12-15%), and your clients are happy. Free option on the upside, much lower downside.

Key Takeaways

Portfolio construction dominates signal selection. How you compose and weight positions matters far more than whether you use moving averages or breakouts. This is the single most under-appreciated idea in systematic trading.
Including loss-making instruments can improve portfolio performance. If an asset’s losses are uncorrelated with the rest, it can improve the overall risk-adjusted return profile (better skew).
Trend following and momentum are not the same. Trend following requires diversified, uncorrelated instruments with leverage (futures). Momentum works on correlated instruments (stocks) by concentrating in high-beta names. Different risk profiles, different mechanics.
The S&P 500 is itself a momentum index. Stocks enter because their price rose, then rise further because they entered. Market-cap weighting is momentum by construction.
Simplicity is more stable than complexity. Clenow built complicated models 20 years ago. The simpler ones lasted. Many famous technical indicators are pen-and-paper approximations from an era without computing power — there is no reason to copy their shortcuts.
Scale, do not switch. For downside protection, gradually scaling out of positions beats a binary on/off regime filter. At the extreme bottom, start scaling back in.
You can build a counter-trend strategy by reverse-engineering competitors’ stop losses. If many trend followers stop out at similar levels, the resulting exaggerated move creates a short-term mean-reversion opportunity.
Managed futures is now a brand management business. The trading is the easy part. Raising assets, compliance, and competing against multi-billion dollar incumbents is where the game is won or lost.
The best compounders in history did roughly 20% annualized. Anyone aiming for 50%+ over multiple years is implicitly accepting catastrophic risk, whether they realize it or not.
Clean strategies sell better than multi-strategy bundles to institutional investors. A pension CIO wants building blocks, not a black box that does his asset allocation job for him.

Claude’s Take

This is a solid, experienced practitioner talking shop. Clenow has the credibility of someone who has actually run money through 2008, managed real client capital, and survived long enough to develop genuine perspective. The interview rewards patience — the host asks good follow-up questions that pull out specifics rather than letting Clenow coast on generalities.

The strongest material is on portfolio construction vs signal selection, and on the business realities of running a fund. These are insights you almost never get from trading books because most trading book authors have not run funds. The counter-trend strategy built by reverse-engineering competitors’ stop losses is a genuinely clever idea that is worth thinking about.

The crypto section is entertaining but unsurprising — Clenow has been saying this for over a decade and has not changed his mind. The “trade stupid money” concession is the most interesting part of that segment. The Hush Investments promotion toward the end is forgivable given the platform.

What holds this back from an 8: it is a wide-ranging interview that covers many topics at surface level rather than going deep on any one. If you have read Clenow’s books, much of this is familiar. The novel insights — the counter-trend model, the regime filter details, the institutional product design philosophy — come in flashes rather than sustained sections.

Score: 7/10 — Experienced practitioner with real insights, but breadth over depth. Worth the listen if you are interested in the business side of systematic trading, not just the math.