Podcast Summary: Merryn Talks Money – "What Can Quant Trading Strategies Teach Us About Markets?"

Host: Merryn Somerset Webb
Guest: Simon Judes, CIO of Winton
Date: March 2, 2026
Theme: Demystifying quantitative (quant) trading strategies, with a focus on trend following/CTA approaches, and exploring what individual investors can learn from them.

Episode Overview

In this episode, Merryn Somerset Webb interviews Simon Judes, Chief Investment Officer at Winton, a prominent quantitative investment management firm. Their conversation unpacks what quant investing means, its differences from traditional investing, the mechanics and appeal of trend following (CTA) funds, the empirical results and risks of quant strategies, and why—and how—these approaches matter for everyday investors in today’s market.

Key Discussion Points & Insights

1. What Is Quant Investing? (00:55–03:30)

• Traditional Investing:

  • Analysts do deep dives into select companies, requiring significant effort and high conviction bets.
  • “If you want to make that decision not about one company but about 10 companies, you need to have 10 times as much discussion… and that leads you to scale those organizations quite heavily…” (Simon Judes, 01:25)

• Quantitative Approach:

  • Relies on rules-based decisions, automated by computers over large asset baskets.
  • “What if… instead of doing all this… you come up with a rule… you can get a computer to do it for you?… You can do that with a much, much larger portfolio.” (Simon Judes, 01:54)
  • Historical backtesting is used to increase confidence in these systematic rules.

2. How Durable Are Quant Rules? (03:31–05:07)

• Rule Erosion (Alpha Decay):

  • Successful quant rules often lose their edge as more traders discover and exploit them.
  • “Many types of rules… work for a while and then… gradually start to work less and less well… almost certainly because many more people are doing it.” (Simon Judes, 03:44)
  • Some rules based on broader behavioral patterns (like momentum) are more resilient.

• Innovation and Research:

  • Quant firms must continually find new data sources and ideas to stay ahead.
  • “A big component of our activity as well.” (Simon Judes, 04:30)

3. CTAs and Trend Following Explained (05:38–07:22)

• What’s a CTA?

  • CTA = Commodity Trading Advisor, historically a US regulatory term, applied to a strategy using systematic trading in futures across macro asset classes (equities, bonds, currencies, commodities).
  • “Predominantly… looking at recent price momentum... if they've gone up… long; if down… short. That is the algorithm…” (Simon Judes, 05:58)

• How It Works:

  • No attempt to “spot the turn.” Instead, aim to ride established trends.
  • “If the price has been going in that direction, that is more likely than not to continue going in that direction.” (Simon Judes, 06:39)
  • Need large number of positions to diversify since conviction per position is low.

4. Making Quant Tangible for Investors (07:40–10:52)

• Retail Investor’s Challenge:

  • Quant funds are “black boxes” compared to familiar styles like value or growth investing.
  • Simple rule examples: classic value approach via P/E ratio sorting.
  • “All you do is you look at the price to earnings ratio of every company... long on the lower than average, short on the higher than average.” (Simon Judes, 09:09)

• Evolving Complexity:

  • Basic value strategies (like vanilla P/E sorting) are too simple and less effective today.
  • More sophisticated, but still rules-based, enhancements are now common.

5. The Role of AI and Technology (11:22–12:41)

• AI’s Value-Add:
  • Helpful for processing more data and developing new strategies, but not a total game-changer.
  • “Before AI, it was machine learning and… big data. Very important for us to keep up with the way that all of these ideas develop.” (Simon Judes, 11:30)
  • The “edge” from new tech decays as more adopters pile in.

6. Portfolio Construction & Diversification with Trend Following (12:42–17:09)

• Why Investors Care About CTAs:

  • Provide diversification, especially when traditional bonds/equities don’t diversify (e.g., 2022, when both fell).
  • “People started to look around for what things had done well. And at that time, the two things… were bonds and CTAs.” (Simon Judes, 13:10)

• How CTAs Add Value:

  • Trade multiple, often uncorrelated, futures; ability to go long or short with equal ease.
  • “Just as easy to be short as... long.” (Simon Judes, 15:24)

• Long-Term Performance:

  • Adding CTAs reduces portfolio drawdowns and improves returns, especially in equity bear markets.

7. Performance Attribution & Trend Example Stories (18:03–21:01)

• Both Sides Matter:

  • Trends exploited on both long (e.g., 2008 bonds) and short (e.g., 2008 equities, 2014 oil slump) sides.
  • “Being short oil is as easy… as being long oil, but it's not so easy to do in other contexts.” (Simon Judes, 18:52)

• CTAs vs. Consensus:

  • Many big winners occur when CTAs’ signals contradict dominant market narratives (e.g., oil/“peak supply” narrative in 2014).
  • “Very often you can be doing precisely the opposite [of the herd].” (Simon Judes, 19:14)

8. What’s Trending Right Now? (21:01–26:52)

• Current Major Trends:

  • Precious and base metals (gold, silver, aluminum, copper), cocoa, US natural gas.
  • “The big trends that we've seen recently have been in the precious metals … equities have been going up in general... cocoa.” (Simon Judes, 21:18)

• Dynamic Position Sizing:

  • Trend following funds may hold positions in hundreds of assets, but most returns in a period come from a handful of big movers.
  • “At any given moment there'll be a much smaller number of things… really contributing.” (Simon Judes, 22:15)

• Counterintuitive Selling:

  • As trends accelerate and volatility spikes, quant funds may reduce positions, locking in profits.
  • “As that market is accelerating upwards, we are selling again… you are locking in the profits that you make as you go.” (Simon Judes, 26:44)

9. Passive Investing: Hidden Momentum? (28:45–30:52)

• Are Passive Investors Momentum Traders?
  • Merryn: “Everyone in a passive investment is effectively a momentum investor just on the long side.”
  • Simon: “There's an element of truth to that… but the nature of the portfolio is very different.” (Simon Judes, 29:25)
  • Index rules can be backtested like quant rules.

10. Quant Diversification Impact: The Numbers (30:52–32:49)

• Empirical Results:

  • Winton research: “A 10% allocation to trend following would have improved the returns of an equity-bond portfolio in 87% of 10-year periods since 1972... return improvement nearly doubled in the bottom decile of 10 year periods for the equity bond portfolio, highlighting diversifying properties and portfolio resilience.” (Merryn (reading PR blurb), 31:04)

• Reasonable Allocation:

  • 10% CTA allocation is reasonable, but actual amounts should reflect investor preference and tolerance for deviation from standard benchmarks.
  • “The right level… depends on what your preferences are.” (Simon Judes, 32:08)

11. Crypto, Risks, and When Quant Doesn't Work (32:49–36:58)

• Crypto in the Quant Mix:

  • Winton adds major liquid cryptos to the trend strategy via futures.
  • “There are futures traded on cme, on Bitcoin and Ether... So it's fairly straightforward to add them to a momentum system.” (Simon Judes, 33:20)

• Strategy Weaknesses:

  • Trend following struggles in sideways markets or during sudden reversals (‘whipsaws’).
  • Examples: sudden reversals around tariff announcements (34:30).
  • “The case where it does well is when markets move steadily and consistently in a particular direction...” (Simon Judes, 35:08)

• Best Approach:

  • Don't try to time when quant (trend following) works: “It works best if you don't try and time it. If you just regard it as a permanent allocation and live with it.” (Simon Judes, 35:38)

12. Trust, ESG, and Product Options (36:58–39:36)

• Not Just ‘Trust Us’:

  • Unlike discretionary managers, quant funds can point to long backtests and track records, not just subjective judgments.

• ESG Overlay:

  • Limited to futures on ESG indices where available and liquid.

• Retail Products:

  • Winton offers multiple UCITS funds:
    • Winton Armor Diversified Fund (multi-strat)
    • Winton Trend Fund (pure trend)
    • Winton Trend Enhanced Fund (adds trend overlays to 100% equity exposure)
    • Quant Multi Strat Hedge fund

13. Automation, Jobs, and the Future of Quant (39:36–42:54)

• Automation’s Impact:

  • Tasks may become more efficient, but Winton aims to redeploy talent to spearhead more research/ambitions.
  • “If we can do the tasks… with fewer people, then… we will keep the same number of people and we'll do more.” (Simon Judes, 41:31)

• Study Advice for Kids:

  • Emphasizes the benefits of both STEM and humanities (his son likes both maths and classics/history).
  • “I took… physics and philosophy and… benefited from having both.” (Simon Judes, 42:48)

Notable Quotes & Memorable Moments

• On quant confidence:

  • “You can get confidence in quant investing… because you can do a back test where you take that rule and you test how it would have performed over a much longer time horizon.” (Simon Judes, 02:25)

• On alpha decay:

  • “That's people call it alpha decay, where the idea stops working… you combat that by doing a lot of research and continuing to find new ideas.” (Simon Judes, 04:30)

• On trend following’s role:

  • “People started to look around for what things had done well. And at that time, the two things… were bonds and CTAs.” (Simon Judes, 13:10)

• On the “black box” problem:

  • “They're told the theory, but it's not possible for them to be told the practicalities, because that's your model, your proprietary data.” (Merryn Somerset Webb, 05:14)

• On trend following and narratives:

  • “Very often you can be doing precisely the opposite [of the herd].” (Simon Judes, 19:14)
  • “The algorithm doesn’t have a theory it’s trying to follow—a massive strength.” (Simon Judes, 23:38)

• On living with quant strategies:

  • “It works best if you don’t try and time it. If you just regard it as a permanent allocation and live with it.” (Simon Judes, 35:38)

Important Segment Timestamps

• 00:55 — What is quant investing? How does it differ from traditional?
• 03:41 — The problem of rules losing value as others join in
• 05:38 — CTAs and trend following: how do they work?
• 09:07 — Simple model example: P/E ratio sorting
• 11:22 — Role of AI/ML in quant finance
• 13:10 — How CTAs performed during bond/equity bear markets
• 17:20 — How much value does CTA allocation add to portfolios?
• 18:21 — Sourcing performance: long vs. short contributions
• 21:01 — What’s trending now in the markets?
• 26:44 — How systematic funds lock in profits as volatility rises
• 29:02 — Is passive index investing just momentum investing?
• 31:04 — Empirical finding: CTA allocations since 1972
• 33:01 — Crypto in quant: how and what Winton trades
• 34:30 — When does momentum investing struggle?
• 35:38 — Best approach: permanent allocation, don’t time it
• 37:26 — ESG and quant: how they intersect (or don’t)
• 38:19 — Winton’s retail-friendly product range
• 39:36 — The automation of quant: will we still need 200 people?
• 42:43 — What should your kids study? Simon’s advice

Tone & Language

The tone is collegial, accessible but clear, alternating between technical explanation and relatable analogy. Simon frequently uses analogies (“like insurance,” “the algorithm doesn’t have a theory”), while Merryn pushes for specifics and challenges jargon, keeping explanations grounded for retail investors.

For Listeners: Takeaways

• Quant strategies aim to systematize the investment process via backtested rules, favoring breadth over conviction in individual picks.
• Trend following is a resilient quant approach providing diversification when traditional bonds/equities fail to diverge.
• Most quant edges decay as they get crowded, necessitating constant research and adaptation.
• CTAs can both short and long with ease, making them unique in diversification.
• The “black box” nature is real, but many rules (like those used in CTAs) are public and understandable.
• Optimal quant allocation is individual, but historical evidence supports 10% as a robust diversifier.
• Ignore trying to time quant funds; systematic allocation works best over the long term.
• Evolution in tech and AI doesn’t eradicate the need for human expertise—it just changes its nature.

End of Summary