Podcast Summary

Top Traders Unplugged: Systematic Investor Series

Episode: SI393 – The Illusion of Control in Modern Markets ft. Yoav Git

Host: Niels Kaastrup-Larsen
Guest: Yoav Git
Date: March 28, 2026

Episode Overview

In this deeply analytical episode, host Niels Kaastrup-Larsen is joined by systematic investing expert Yoav Git for a wide-ranging discussion on the unpredictable nature of modern markets, the limitations of control—even for systematic traders—and the mechanics that drive price and risk in periods of extreme volatility. Oscillating between current market events, foundational machine learning concepts, trend following, risk management, and a critical look at influential quant finance research, the episode delivers frank, practical insights for investors aiming to build resilient portfolios in chaotic times.

Key Discussion Points

1. The EM Algorithm, Arthur Dempster, and Machine Learning Roots

(01:19 – 04:12)

• Tribute to Arthur Dempster: Yoav starts by honoring the late mathematician for inventing the Expectation-Maximization (EM) algorithm, the precursor to much of modern machine learning. He emphasizes how overlooked contributions like Dempster’s underpin the very foundation of current quant and machine learning approaches in finance.

  • "A lot of machine learning is predicated by his work. So rest in peace, Arthur." (03:00, Yoav Git)

• Explaining the EM Algorithm:
  Yoav explains its significance in statistical classification problems (e.g., distinguishing between ‘cats or dogs’) and relates its iterative process as conceptually similar to backpropagation in neural nets.

"It's an iterative process, a little bit like the back propagation process that we have in machine learning these days." (03:37, Yoav Git)

2. Recent Market Dynamics and the ‘Illusion of Control’

(04:12 – 14:40)

• Narrative-Driven Markets and Unpredictable Outcomes:
  Niels shares the surprises of a Danish election campaign, highlighting how supposedly pivotal geopolitical topics were displaced by unpredictable narratives (animal welfare and clean drinking water), drawing a clear parallel to market narratives.

"It shows you how unpredictable things are, even at that level... as investors, it's not always that what we expect is what happens." (06:19, Niels Kaastrup-Larsen)

• Gold, Oil, and War:
  Both discuss recent pronounced volatility in commodities—gold and oil—against the backdrop of new Middle East conflicts, observing how price moves often run counter to prevailing narratives or even logic.

• Rules-Based Systems and the 'Luck of Entry':
  They stress that in fast-moving, headline-driven markets, systematic (rules-based) investing helps eliminate the tendency to overfit narratives, though even systematic approaches cannot always mitigate sharp, intraday dislocations.

"It just keeps on giving us all these examples of how difficult it must be to be anything other than a rules-based investor." (08:53, Niels Kaastrup-Larsen)

3. Liquidity, Execution, and Correlation Breakdown

(09:07 – 15:27)

• Examining Asset Behavior During Geopolitical Shocks:
  Yoav discusses how different market curves (oil’s front end vs back end, bond sell-offs, and EM curves) have diverged, showing how supply constraints and risk-off sentiment can manifest differently depending on asset class and tenor.

• Market Dispersion and Manager Performance:
  Both note that extreme intraday moves make execution timing critical this month, and systematic strategies have faced challenges just tracking their own models. A significant ‘surprise volatility’ event occurred, something not seen since 1998 historical data.

"The surprise volatility we have seen this month has been staggering... more surprise volatility than we've seen in decades." (12:13, Yoav Git)

• Bond/Equity Correlation Flip:
  For allocators, Yoav’s key warning is that traditional negative bond/equity correlation flipped positive during this crisis. Both assets sold off—nullifying conventional diversification.

"If you thought one of them was actually acting as a defensive mechanism for you, then think again." (13:44, Yoav Git)

4. Fixed Income Stress and Analogies to 2022

(17:29 – 19:49)

• CTAs and Fixed Income:
  Discussion centers on the violent reversals and indecisiveness seen in bonds since 2023, contrasting with the ‘easy’ shorts of 2022. The recent US 2-year auction signals fiscal stress in Western economies; private credit is showing cracks as some funds start gating redemptions.

"Certainly feels a little bit... the world is feeling a little bit on edge, let's put it this way, right? Fragile." (19:45, Yoav Git)

5. Alternative and Core Market Dynamics, Capacity & Trends

(24:58 – 33:31)

• Trading the Curve—Weather vs Climate Analogy:
  Yoav explains trading longer-dated oil contracts insulates from short-term news, focusing on fundamental supply/demand rather than tumultuous spot prices.

"The nice thing when you trade the back of the curve is that it's really about fundamental supply and demand, not about the short-term shocks." (25:22, Yoav Git)

• Capacity Constraints & Liquidity:
  The hosts highlight how risk management and trading costs sharply diverge between core highly-liquid markets and alternative ‘local’ markets, especially during crises. For alternative markets, risk management can become expensive due to widened spreads and illiquidity.

"The cost of, like, closing the book, the long/short book is like 5% of performance. That's actually quite expensive." (32:16, Yoav Git)

• Rules-Based vs Discretionary Risk Management:
  Discretionary traders may rapidly adjust exposure using liquid instruments (e.g., US Treasuries), while CTAs typically scale both longs and shorts—which can be inefficient in extreme scenarios.

6. Flow Dynamics and Market Microstructure in Crisis

(37:07 – 40:31)

• Narrating the Crisis Flows:
  Yoav breaks down the actual sequence of ‘flows’ during the March crisis:
  • Initial price gaps (e.g., oil) on new conflict headlines.
  • Systematic CTA flows as volatility signals trigger risk-off moves.
  • Value managers gradually closed out as losses mount (‘long squeeze’).
  • Noise traders and market-makers amplify volatility, especially via news/tweets.

"As the crisis progressed... as a value trader, at some point you're just being closed out, there's not much you can do." (38:48, Yoav Git)

7. Academic Review: Revisiting the Excess Volatility Puzzle

(41:23 – 55:59)

• Paper in Focus:
  "Revisiting the Excess Volatility Puzzle through the Lens of the Kirella Model" (Jean-Philippe Bouchaud et al.)

• Market Structure Model:

  • Three 'players': Value traders (mean-reverters), noise traders (random volume), and trend-followers (CTAs).
  • The model uses the EM algorithm for calibration, attempting to explain market price moves as a function of these players.

• Key Findings:
  Most market volatility is noise, with value traders the next largest source, and CTAs/trend-followers making only a marginal impact on volatility.

  • "We do not contribute that much to the volatility... we are a very small part of the market." (47:40, Yoav Git)

• Pendulum Analogy:
  Yoav recasts the dynamic as a pendulum: trend-followers provide momentum; value traders provide pullback; noise traders provide agitation.
  Markets spend more time overpriced or underpriced, oscillating around value.

• Critical Appraisal:

  • The paper, he argues, downplays ‘real’ fundamental jumps in value (e.g., sudden geopolitical shocks) and assumes all variance is from trading activity or random noise.
    • “A lot of the price change can happen without any trading whatsoever. There’s a difference between why close price on day one and open price on day two are very different.” (52:35, Yoav Git)
  • Value trader reaction functions (in the model) are unrealistic, not accounting for eventual forced liquidations (‘being called out’).

8. Capacity, Portfolio Design, and Diversification

(56:35 – 62:14)

• Discussion of Yoav and Tom Babbage’s LinkedIn Paper:
  Key question: How does portfolio construction cope with capacity constraints—should you bother including small, illiquid or alternative markets?

• Findings:

  • If underlying market correlations are high, fewer markets suffice—little diversification added by further inclusion.
  • If you have a much more diversified, low-correlation universe, capacity limits on illiquid assets can sharply reduce actual diversity in stressful times.
  • The debate between ‘fewer core markets’ (for replication/high correlation) and ‘many alternative markets’ (for diversification) must account for liquidity, practical trading constraints, and performance impacts under stress.

"If you have a portfolio where the underlying correlation is high to start with, then actually if you have more markets, you don't necessarily gain that much of diversity." (59:13, Yoav Git)

Notable Quotes & Memorable Moments

• On Control:
  • “It just keeps on giving us all of these... examples of how difficult it must be to be anything other than a rules-based investor.” (08:53, Niels Kaastrup-Larsen)
• On Execution Timing:
  • "Depending on what time of day you've executed your trade will make a huge difference to your performance." (11:43, Yoav Git)
• On Fundamental vs. Trading-Driven Moves:
  • “A lot of the price change can happen without any trading whatsoever... the weekend has exposed ourselves to an Iran war.” (52:35, Yoav Git)
• On Model Critique:
  • "You want your models to be as simple as possible as long as they actually describe reality." (54:45, Yoav Git)

Segment Timestamps

| Segment | Timestamp | |-----------------------------------------------|------------| | EM Algorithm & Tribute to Dempster | 01:19–04:12| | Markets, Narratives, & Election Commentary | 04:12–06:51| | Commodities Reactions & CTA Dispersion | 06:51–15:27| | Fixed Income Volatility & Private Credit | 17:29–19:49| | Market Liquidity and Risk Mgmt Challenges | 24:58–33:31| | Flows and Market Microstructure in Crisis | 37:07–40:31| | Excess Volatility Paper (Bouchaud et al.) | 41:23–55:59| | Diversification, Capacity & Portfolio Design | 56:35–62:14|

Final Thoughts

The episode underscores the persistent unpredictability and messiness of financial markets—even systematic rules can’t erase the “illusion of control.” For investors grappling with volatile, story-driven environments, the advice is clear: capacity, correlation, liquidity, and underlying structural choices matter as much as signal quality. Theoretical models are valuable but always incomplete; real-world trading reveals nuances, especially under stress. The conversation’s pragmatic, honest tone offers humility and clarity to both systematic and discretionary investors in today’s complex market reality.