SI343: CTAs: The Unexpected Heroes of Market Crises ft. Yoav Git

Summary

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Top Traders Unplugged: CTAs—The Unexpected Heroes of Market Crises

SI343: Systematic Investor Series with Yoav Git

Date: April 12, 2025
Host: Niels Kaastrup-Larsen
Guest: Yoav Git

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Overview of the Episode

In this episode, Niels and Yoav provide a deep dive into recent turbulent market conditions, focusing on the surprising behavior of bonds and traditional safe havens, and how systematic trend following (CTAs) have performed during this period. They examine the reliability and adaptability of trend following strategies, the structural challenges facing CTAs, the myth of "crisis alpha," and how portfolio diversification—and correlation—affect managers' results in times of stress.

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Key Discussion Points & Insights

1. Market Stress: Bonds, Yields, and Safe Havens

Timestamps: 02:58–11:50

• Unusual Bond Market Moves:

  • Niels reflects on the historic spike in US 10-year yields, the biggest three-day jump since 2001, despite expectations of Treasuries as a "safe haven" ([03:00]).
  • Yoav explains the impact of global debt ownership and trade tensions on the bond rout, noting that US financing heavily relies on foreign buyers ([05:16]):

    “If you start a trade war, this can quite happily escalate into capital war.” (Yoav, 06:00)

  • Sharp divergence in yields across countries: yields up in the US and UK, down in Japan.

• Crumbling Correlations:

  • Discussion about how traditional correlations—stocks down, bonds up—failed, especially in 2022 and now ([08:29]).
  • Investors relying on 60/40 portfolios face challenges when inflation becomes a dominant market driver, creating positive correlation among asset classes.

• Evolving Perceptions of Safe Havens:

  • Gold outperformed other commodities as a relative safe haven; cryptos discounted as too volatile ([11:06]).
  • Niels argues that CTAs/trend following, by virtue of adaptability, may now function as modern “safe assets.”

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2. Recent CTA/Trend Following Performance in Crisis

Timestamps: 11:50–21:29

• Portfolio P&L Breakdown ([11:50–15:14]):

  • Equities and currencies hurt CTA portfolios; fixed income mixed, with massive divergences between countries.
  • Energies were a relative bright spot—longer-term managers may have benefited from holding shorts as the selloff hit.

• Volatility, Risk Management & Positioning:

  • Sudden reversals forced aggressive risk reduction among CTAs.
  • Many managers, particularly slower traders, held onto long equity exposure amid rapid moves ([19:16]).

• CTA Indexes Update

  • B Top 50 Index and Soc Gen CTA/Trend indexes suffered large losses for April and YTD (e.g., Soc Gen Trend Index down almost 10% for the year as of Tuesday) ([17:10–19:48]).
  • Short-term trader indexes were doing better but still negative.

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3. The Crisis Alpha Debate: When Do CTAs Actually Shine?

Timestamps: 21:29–33:01

• Performance During Drawdowns

  • Citing Twitter research (attribution: Tyler Loving), Niels summarizes how CTAs tend to lag in the initial leg of equity crises ([21:29–27:12]):

    “What’s very clear is that when it happens very quickly, CTAs are struggling the most.” (Niels, 25:04)

  • Over 10 S&P 10% drawdowns since 2000, average CTA performance was ~-3%. The “crisis alpha” typically emerges in the -10% to -20% S&P drawdown leg.

• Structural Evolution

  • Yoav elaborates: CTAs today trade slower than in the early 2000s and often can’t turn positions quickly when crises start from all-time highs ([27:12]):

    “It’s not just the speed of the crisis, it’s also the speed of CTAs…The bulk of the money has migrated to trading slower.”—Yoav (27:58)

  • Value of diversification: In a “cross-asset” crisis, even highly diversified futures portfolios can’t fully insulate from sharp, correlated reversals.

• Portfolio Structure Lessons

  • The old “commodities provide the best offset in equity crises” lesson is reaffirmed ([30:04–33:01]).
  • Need for rigorous risk management and real diversification, especially when crisis correlation spikes across traditional “safe” assets.

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4. Trade Execution, Market Impact, and Diversification

Timestamps: 34:26–45:00

• Reflections on Diversification Within CTAs ([34:59–45:02]):

  • Yoav highlights two ways to lower market impact: mixing signal timeframes and occasionally trading further out the futures curve ([34:59]).
  • “Correlation at Entry vs. Exit”: Exits are highly correlated due to risk management triggers—everybody de-risks together when volatility spikes:

    “Entry is rather smooth, but exit, we all tend to exit at the same time.” (Yoav, 35:39)

  • “Unexpected volatility” when trends are extended is a measurable sign of CTA crowding and impact.
  • Wide dispersion among trend signals: adapting the type of trend following predictor and time frame to the market context can improve alpha.

• Capacity as a Source of 'Alpha':

  • Smaller managers can deploy meaningful risk to less liquid, diversifying markets (metals, ags), whereas mega-CTAs are forced to concentrate in the most liquid (and correlated) sectors.

    “Having 500 markets or 50 markets is less important than having volatility reduction. That’s really what is key.”—Yoav (45:15)

  • Alpha from trading “off the beaten path” is as much about lower correlation as about higher returns.

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5. Are All CTAs the Same? Manager Dispersion & Correlation

Timestamps: 50:06–57:26

• Manager Dispersion Data ([50:06–56:04]):
  • Recent CFM and Goldman Sachs analyses show that pairwise CTA correlations remain ~50–60%—far higher than in most macro investing.
  • Despite industry expansion and more tradeable markets, the majority of managers are highly correlated, all exposed to the same core trends:

    “If you look at CTAs…it’s completely shocking…We end up very highly correlated.” (Yoav, 53:10)

  • Key to differentiating: willingness to allocate risk to off-benchmark or “non-standard” markets, though capacity becomes the limiting factor for large players.

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6. Expectations, Trend Speeds & the Misconception of CTA Positioning

Timestamps: 57:27–69:18

• Banks' “Front-Running CTA” Reports ([57:59–64:16]):

  • Investment banks regularly try to “predict” CTA buying/selling flows. Niels and Yoav are skeptical of these simplistic model-based calls, given model diversity and real-world uncertainty.

    “I’m not a big fan of [front-running CTA positions]…they probably have some idea of how these models are built, but they don’t have the full picture.” (Niels, 63:25)

• Why Aren’t CTAs Short Equities Yet?

  • Time vs. Price: Most trend-followers, now slower and coming from all-time highs, wouldn’t have flipped their book short despite sharp drawdowns ([60:41]).
  • The design of signal lookback—one month to three months—means the fastest, largest reversals often occur before the models are able to react.

    “Trend following is really about two things. It’s about the price, but it’s also about the time.”—Niels (59:07)

• Practical Takeaways for Investors:

  • Set expectations: Don’t expect CTAs to deliver “instant” crisis alpha in rapid market meltdowns.
  • Diversification and robust risk management remain the core strengths of managed futures, over time.

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Notable Quotes & Memorable Moments

• On safe havens:

  “I was very thankful that it wasn’t crypto that would have been insane as a safe haven.” (Yoav, 11:10)

• On structural market risks:

  “If you start a trade war, this can quite happily escalate into capital war.” (Yoav, 06:00)

• On the “myth” that CTAs protect instantly in a crisis:

  “It is super important…people should not expect CTAs or trend followers to be the first responders. We’re not the ones who can deliver the first positive offset when a crisis begin. It comes later.” (Niels, 25:18)

• On the reality of dispersion among CTAs:

  “It’s like Alice in Wonderland. You have to run twice as fast just to stay, just to make any sort of progress.” (Yoav, 56:04)

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Key Segment Timestamps

• [03:00] – US bond market turmoil, yield surge, safe haven inversion
• [08:29] – Correlation breakdown, 60/40 obsolescence
• [11:06] – Gold, CTAs, and evolving safe havens
• [15:14] – Country-by-country fixed income/FX behavior in crisis
• [21:29] – “Crisis alpha” and trend follower performance in S&P drawdowns
• [34:59] – Moritz’s Substack post: execution, market impact, timing of trades
• [45:02] – Capacity, portfolio construction, and true diversification
• [50:06] – Dispersion between managers, persistent high correlations
• [57:27] – Explaining “time vs. price” in trend following exits and expectations
• [63:25] – Skepticism of “frontrunning CTA” narratives

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Tone & Language

The episode is frank, data-rich, and attentive to nuance—consistent with Top Traders Unplugged’s style. Niels and Yoav blend industry humor with technical detail, offering both strategic insight (“what matters isn’t the number of markets, it’s the correlation structure!”) and practical portfolio lessons. Their tone is skeptical of simple narratives, especially around “crisis alpha,” and they encourage listeners to look beyond headlines and focus on real-world risk management, structural diversification, and strategy design.

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Summary Takeaways

• Traditional safe havens (bonds) can fail—and have recently.
• CTAs are not “first responders” in fast equity selloffs—crisis alpha materializes if downturns persist.
• Trend following performance is highly path-dependent: signal speed, market structure, and correlations matter.
• Capacity constraints drive mega-CTAs into correlated, less diversifying trades; smaller managers can find extra alpha in “off-index” markets.
• Portfolio risk control, robust signal design, and adaptive diversification are more important than chasing short-term performance.
• Despite much talk, actual dispersion among major CTAs remains low. The “trend engine” remains resilient, but investors must be realistic about how and when it works.

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Next episode: Dr. Kathryn Kaminski returns to discuss new research on Crisis Alpha and the role of CTAs in turbulent markets.

Transcript

[A]

You're about to join Niels Kostrup Larson on a raw and honest journey into the world of systematic investing and learn about the most dependable and consistent, yet often overlooked investment strategy. Welcome to the Systematic Investor Series.

[B]

Welcome or welcome back to this week's edition of the Systematic Investor series with Yoav Kit and I, Nils Kastrelason, where each week we take the pulse of the global market through the lens of a rules based investor. Yoav, great to be back with you this week. How are you doing? How are things where you are?

[C]

Not too bad, thank you. Great to be back on ttu. I'm actually on holiday at the moment. We are getting ready for Passover. So Spring Clean is in full swing at the moment. We are hosting about 20 people for sort of Saturday night and of course my in laws, both sets of in laws are here with us over the weekend. So if you think there is stress in the market, I think think again, there's much more stress around here. So that's my life at the moment.

[B]

That's your life at the moment. Fair enough. Yeah. No, absolutely. I think we will, we'll have to talk a little bit about what's going on at the moment and we've got a great lineup of some papers we're going to be talking about as well that you brought along. So quite a lot to tackle this this week. But of course, before we do all of that, I'm always curious to hear what people have been thinking about what's been kind of crossing their radar. So what's been on your radar the last couple of weeks?

[C]

So the market's being so quiet. I've taken the time to read a little bit about mcp, which is a new essentially protocol, an API for machine learning. So this has been actually gathering a lot of strength in the industry and there's a lot of development there. So I think machine learning and being useful is becoming sort of much more industrialized. So MCP is a protocol that allows ChatGPT or other machine learning to speak to website and that allows you to create applications essentially straight out via ChatGPT. And I think that's a really nice development if you're interested in that sort of thing. Have a [e-mail] that's a new app that allows you to essentially create apps on your own. Really impressive technology. It's actually becoming very useful. Yeah.

[B]

I'm not sure how I feel about all this AI, whether I should just embrace it and go all in or whether I should be a little bit Worried about it. So I haven't adopted. I'm not full in on this just yet, I have to say.

[C]

Yeah, we don't use it for trading at the moment, but I think it's important to keep abreast of what's happening and it is actually becoming very powerful as a way of prototyping technology and really, really nice.

[B]

Yeah, no, absolutely. Now people might think that what's been on my radar is what's going on in the stock markets. And of course it has some, had some influence on what I've been, you know, thinking about. But actually for our conversation, I think there's something that's probably even more important. Oddly enough, even though everybody has been talking about the wild swings we've been seeing in equities and there have been historic in many, in many ways. But I also noticed that the long term yields have been soaring and that the US 10 year note saw the biggest three day jump since 2001. That is impressive at a time where you would think people would use that as a safe haven. Now, I'm not an expert in this area as much as you are, although I did start my career in trading government bonds. But, but I would love to hear kind of your perspective, your thoughts on this because I truly feel that this is very important for investors, especially because we have been, or investors I would say to a large extent have been relying on a certain correlation between stocks and bonds, especially during crisis periods. We saw in 2022 that you couldn't completely rely on that. We had been talking about this actually on the podcast for a while because we felt that there was the anomaly was the first two decades of this century and that we would go back to more normal times. But actually even during sort of the last couple of weeks worth of extreme market moves to some extent, including yesterday, we were recording Thursday. So including the historic pivot we saw in the markets when Trump a pause to the tariffs on most countries with the exception of China. Yeah, I mean, maybe there was more to it than what meets the eye in terms of why that pivot came. So I'd love to hear your thoughts and your insights on all of this since you follow these markets much more than I do.

[C]

Yeah. So it's actually been fascinating the way that the bond market reacted as well as the dollar for that matter. So you're absolutely correct in that the usual response that you kind of expected running as a safe haven to the U.S. treasuries, that certainly did not happen. What we're seeing is that the bond market in the US actually retreated, yields were spiking and the dollar as well, the dollar retreated and you saw quite a nuanced behavior across different countries. So in Japan you saw unprecedented drop in yields, whereas in the US you saw unprecedented rise in yields. And in many ways that was more painful actually the long end at the 30 year it touched the 5% briefly. And that means that sort of somebody trying to remortgage their house will be facing an extra 50, 60 basis points of cost on their mortgage. And that's very painful for American citizens. I mean the important thing to remember is that the US has about 30% of its debt is being owned by foreigners, by the likes of China, by the likes of Europe. Used to be Japan got a lot more China and Europe these days. And that means that if you start a trade war, this can quite happily escalate into capital war. So we saw that in a statement in France saying, well, if these guys are going to war with us, why are we investing in their economy? And what we saw, we saw a route in the uk, in the US bond market and there was a lot of doubt about the auction, the 10 year auction yesterday on Wednesday, thankfully that actually went well. But certainly in terms of long term, the US needs to refinance or to re auction about 2 trillion worth of debt every year and they will need to do that essentially for the next 10 years. So that means that they rely on foreign support for the bond market, for the US bond market. And I think the route that we saw in the bond market in the US was actually much more, potentially much more influential in causing the pause in the tariffs that we saw because you can cope with temporary reduction in sort of a price of goods, in the price of equity but yields. The bond market collapse was actually very worrying and luckily that hasn't happened and we are probably getting back to normality, hopefully.

[B]

Now we talked about yield spiking and all of that stuff. Now I didn't follow it that sort of deeply in terms of liquidity. Did you know if liquidity actually kind of dried up and even to the point where we as managers in the futures markets would have felt some change.

[C]

So the US market stayed fairly liquid. So I don't think there was a huge issue there. If you go to the emerging market, it was certainly the case that spreads were all over the place. It's been very tough. South Africa, for example, was affected by local news as well. And that was very tough to trade. I've got to say this week has been remarkable in many Many ways. And it's certainly just tough to trade and tough to see the effect. And it's really, I think the bond market and the equity market correlation is something that investors should understand that when there is concerns about inflation, then you actually get POS correlation. And that really has implications in terms of your portfolio construction because if you're relying on the 6040 to essentially to have negative correlation, that is not always the case anymore.

[B]

Yeah, but as you say, I mean even within the fixed income and even within developed markets fixed income, to me it seems like there's a lot of divergence within the signals that we get as trend followers right now compared to what we normally see. And certainly all also between the long end and the short end. And so it is interesting times to say the least. The other thing, I think it opens up for when you see something like this and we'll see what the fallout is and how investors might rethink their strategies. But from memory, I think we've touched on it a little bit on the podcast in more recent years, but without fleshing it out completely. And that's this big question, you know, what is a safe haven assets today? Right? What, what I mean, has this, is this also changing right now? People might say well actually it looks like it could be gold. That's the safe haven. I even wonder, and of course completely biased here, but I even wonder if trend following could be quote unquote a safe asset because of the adaptability. And of course, yeah, we've taken some pain this the last few days, but nothing out of the ordinary compared to, you know, what we normally see in, in these type of periods. And, and it has been pretty extreme certainly in terms of the speed of these changes. So but I really think that, that people that large investors need to rethink what they classify as a, you know, risk free, quote unquote asset for them to, you know, hold significant levels of investments in.

[C]

So I mean gold this time outperformed other commodities. So it went down just a little bit, but actually was very good. I mean I was very thankful that it wasn't crypto that would have been insane as a safe haven in terms of long term allocation. It's definitely the case that CTAs offer a much more diversified portfolio. And in the presence of inflation, when you have one factor which is driving the correlation for all the other asset classes, so commodities, equities and bonds, you do need more set of diversifying strategies. And CTA certainly offers one of those, one of those paths to diversification.

[B]

Yeah, well, let's stay with the CTA and the trend following space as we normally do at this stage to kind of jump in. And for me it was kind of, it was kind of hard to prepare for our conversation today because there's so much, there's so much going on. Sort of just this section where we normally talk about, you know, where managers might have made money or lost money, whatever I'm going to say now, it's probably not very accurate because I think this time around because of the way it's played out, the speed at which it's played out, the part of the portfolio it's been playing out in, I would expect that managers who are normally fairly highly correlated will have seen very different results in the last few weeks. Now if we look at a portfolio of markets, where is it likely that Trend followers and CTAs would have lost money? I'm talking mostly, sorry, I should say from a trend following perspective. Well, I think it's fair to say that it's probably equities that's been hurting in the portfolios, maybe with a combination of currencies as I suspect a lot of longer term managers were along the dollar going into the last few weeks. So I would expect that those two areas have been challenging. Fixed income could be kind of anywhere, so to speak. Although I do think on balance probably a slightly positive part of the portfolio, albeit as you said, Japan saw some extreme moves in their interest rates, bond yields. So that most likely will have caught some trend following models on the wrong foot. But the short end in particular probably did okay for managers. If there's one thing where I think there will have been some bright spots in most trend following portfolios, it's actually energies. Now again a little bit tricky because energies actually traded higher during the month of March. So if you were a little bit too short term, you may have been exiting your short positions or even flipping long and then you get, you know, the big sell off coming when tariffs was announced. But I think if you're a longer term manager, that's probably the, that the area that's given you some offset in your portfolio. Yeah, grains, softs, probably not where people have seen the most action, so to speak in terms of P and L. But then you get into the metals area and here I think again very much depending on time, so sort of speed of models, you know, you could have had a very different outcome. But I do think things like gold and silver and interestingly enough for the month of April, not necessarily great until we get some bounce Back, which may be happening now, but of course they have done well leading into April. So very interesting period to look at now. I know you trade just fixed income in your portfolio. Love to hear what your view is from a trend following perspective within fixed income because as we started out by talking about, this has been a very, very interesting part of the financial markets right now.

[C]

Yeah, absolutely. I think one area of fixed income which has definitely been very painful for us has been credit. So not just government bonds, but if we look at corporate debt that really got hit as well. And in fact the hit was delayed. Equity started trending lower earlier. Well, credit held fairly well for a while and then in the crisis really really didn't do particularly well.

[B]

And do you trade that as a trend from a trend following perspective?

[C]

We trade it as a trend following perspective. So that has been, that has been painful and that is essentially an equity beta. So that's large part of it. I think the different countries reacted very differently to the crisis. So Australia and New Zealand for example, bonds retreated, yields were on the rise. Japan was exactly the opposite direction. Europe as well. So what we're getting is actually an interesting dispersion amongst different countries. We saw a lot of EM countries really suffering and in fact the more you traded with the U.S. the more you got hurt by the tariffs. But even countries like Mexico and Brazil were in principle weren't really that affected. Mexico was really excluded. Brazil only got about 10% tariff, so you might have thought would have traded nicely. But actually both currencies retreated very aggressively. So it was very strange. Not always driven necessarily by sort of just by what the tariff was. But we saw a huge dispersion in terms of behavior across the fixed income and FX space.

[B]

I imagine it must be very hard to hide from what's going on when even islands that are occupied by penguins are part of the the tariff war. So there's absolutely no, no place to hide right now. Okay. So on a serious note, my own Trin barometer interestingly enough finished last night at 50 and has actually been pretty strong. And so I'm very curious to see how the shorter term managers are doing because the trend barometer has some much shorter time frames built into it compared to most long term trend followers. So they might actually have been okay except for what happened last night. I think that could be a really tricky one for a short term manager because you probably would have been short equities again and so on and so forth. Maybe even also in the energy markets. So we'll see about that when I looked at the performance numbers, so this would have been. As of Tuesday night I saw that The B top 50 index was down for April, 4.76% and down 4.5% so far this year. Now that's a big number. 4.76. That's a big number for that index. Also in a historical context, interesting to see what the bounce is from yesterday because I do think yesterday was probably on balance a little bit of a positive when I look at the managers that I can have access to. Soc Gen CTA Index down 5.53 for the month so far as of Tuesday, down almost 8% for the year. Again, big number doesn't mean this is where we're going to finish the month, but so far it's definitely showing up. The SOC Gen Trend index down 5.89% and now down about 10% for the year. And the Short Term Traders Index as I mentioned, certainly doing better, down about 69 basis points, down 71 basis points so far this year. So doing a lot better as you would expect for sure.

[C]

I think the CTA index is not going to bounce that much. I think one of the problems for us as CTA is that we manage the risk very aggressively. So certainly I would have expected a lot of the positions to have been cut. So that sort of volatility where we have a large sharp down move will be followed by CTAs across the board cutting their risk. And that means that they will not be benefiting as much from the recovery that we saw yesterday.

[B]

I agree with that. I agree with that view. We'll see. And I'll just add to that because you're absolutely right. But actually, you know what might be cutting position size even quicker than that? The fact that markets are changing direction is actually the expansion or the explosion of volatility. Yes, I think that's going to be really kicking in these days. Yeah, yeah, yeah, for sure. MSCI world index down 4.52 as of last night, down 6.5 or so for the year. The S&P US aggregate bond index. I kind of flip around with different indices every week. I'm not really wedded to any one of them. Here's one. You might have some better ones I should hear from you. But that's down about 97 basis points for the month, but still up 1.63% for the year. What in your mind? Something that actually reports daily data on the Internet, everyone can look at. Do you have a favorite bond index that you look at?

[C]

I've got to Say I've got to come back to you because I normally look at the Bloomberg indices myself in terms of. So I'm not sure exactly what's available on the web.

[B]

I used to look at the World Government Bond Index but they stopped publishing that free of charge so I had to find another one. Anyways, S&P 500 total return index down 2.73 as of last night. Down 6.89% for the year. But listen to this. Up 9.52% yesterday. That's the third biggest one day move since 1950.

[C]

Yeah, it's unprecedented. Really unprecedented.

[B]

It is unprecedented. And so in a sense we, we are writing history at the moment. Anyways so I want to stay with trend for a little bit longer because there will be people out there listening to us and say mmm, I knew it. Trend following has stopped working. It should have made money. It's a crisis alpha strategy and so on and so forth. Luckily, luckily we have Katie Kaminsky coming next week to to dive into some new stuff on that. But in the meantime I did notice on Twitter and I hope I'm contributing these statistics to the right guy, but I think it was a guy called Tyler Loving as far as I'm aware. If it's not, I apologize. This is a little while ago, but he had looked at The SoC Gen CTA index performance through the first 10% of an S and P drawdown. Okay, now the first 10%, it's a little while ago but it's not, you know, that long ago we hit that mark. In fact we hit it on the 11th of March. Right. So the first 10% was from the 19th of February to the 11th of March 10% down on the S and P. At that time The Soc Gen CTA index was down 3.56% so actually that's not too bad. Now he does a great job. He goes through, I think there's 10 of these events since year 2000 where the index has been down by 10% and he looks at how the Soc gen CTA performance has been. What's very clear is that when it happens very quickly, CTAs are struggling the most. The two worst occurrences or the two worst periods of a 10% drawdown in the S and P in terms of soc gen CTA performance was Volmageddon in 2018, February of 2018 and also what took place just before the. Or maybe it was during the the great financial crisis. So back in July through mid August 2007, those are the worst ones. But if you look at the average soc gen CTA index performance during a 10% drawdown. And as I said, I think there's like 10 of them that he featured. The average is down 3.18% and the median down 2.81% for the so in a sense you could say well that's actually not bad because and this is super important as some papers have highlighted a couple of years ago, the name escapes me. I think it was Mickey, the consultants that did the report. I'm pretty sure that they were the ones who brought it out. They talked about first and second responders during crisis periods and made it very clear that people should not expect CTAs or trend followers to be the first responders. We're not the ones who can deliver the first positive offset when a crisis begin. It comes later. So what I really liked about what as I said, I believe this guy Tyler did was he then went on to say well let's look at the performance when the S and P index goes from minus 10 to minus 20 so the next part of the leg. Now there are actually not that many times in the last 20 years where that's happened, but there are four that he highlights and what's interesting, so in 2022 this happened and the performance of the soc gen CTA index during that minus 10 to minus 20% of the S&P was actually positive 20.38%. So great. That's exactly what we would expect in 2020. There was a relatively quick period, late February to mid January obviously Covid where it went from 10 to minus 20. During that period of time the index was pretty flat, down 89 basis points. So no big deal. But. But there was no positive performance in 2007 through July 08. It happened again during that period of time the index was up almost 8% so did exactly what we would expect it to do. And then in 2000 this is part of the tech bubble. It happened between I think April and 2000 and February of 2001 and the index was up almost 11%. So I think what Tyler managed to do was to perfectly describe and kind of confirm what you should expect from a trend following CTA during a crisis period because it all comes down to the speed of the crisis because we know that the positioning of a trend follower when an equity crisis starts, it often starts actually from an all time high. It really does. And at that stage we know that we're going to be super long equities because that's what you have to be as a trend. Follower. And so positioning in general, not just in equities, but in other sectors is incredibly important in the initial stage because there's no way we can adapt ahead of time, so to speak. And I think, I think his little analysis shows that. Love to hear your, your thoughts on this. I know you write a lot on your, on your LinkedIn profile. I don't know if you've ever written about this.

[C]

So it's, it's right what you say in terms of CTAs not being the first responders, but it's not just the speed of the crisis, it's also the speed of CTAs. So what? In the early 2000s, I think CTAs were generally trading a little bit faster and they have migrated the bulk of the money. So the soc gen index has migrated to be trading slower. So that's one of the reasons why I think the soc gen CTA has suffered is because although we saw equities retreating in February and maybe a faster manager would have switched position by then, a lot of the CTAs still had residual long position in equities going into the crisis. Here it's not just speed of the crisis, but CTAs have migrated to the slightly slower speed month, you know, month to three month horizon trend following. And in that speed you kind of, you don't necessarily expect to turn over your position after the 10% drawdown, especially after like hitting an all time high in February. I think what it highlights is really for us as practitioners, the importance of diversification. So the way that you construct your portfolio is you have to be aware that although CTAs have positive convexity on a month, 2 month, 3 month horizon, they have negative skew. We tend to own negative skew positions in all of our asset classes of light in any point in time. And when a day one crisis hits, that's actually when you suffer. You have your position and you have to live through that position. No amount of adjustment will get rid of it. So the trick is creating a diversified portfolio so that when that crisis happens, you just get hit in one part of your portfolio. It's actually very difficult in a situation like what we saw here, where the crisis essentially across the board, where it's not an idiosyncratic challenge because some political turmoil in South Africa, some political turmoil in Japan or elections in some other part of the country, but when you have such a across the board crisis, where we see oil tanking, right, you see that in equity, we see that in effects, we see that in bonds, I think it's actually very difficult to create a diversified portfolio at that point regardless of how many sort of futures you trade. But I think this really highlights the importance crisis like this. The importance of I think very rigorous risk management which actually CTAs are very decent about doing it so that on day one you don't get hit so badly.

[B]

Yeah, no, I think the point about risk management is super relevant and I'm hopeful that we don't see any big fallout of this because this is truly something we have not seen in our historical data. And whatever backtest you did, you probably would never have seen anything like this showing up. So it's a good test, it's a good stress test once again for these strategies and hopefully they'll come out okay. There are many lessons actually we can learn from this. You talked about diversification so it'll be interesting to see at the end of the month people who trade the 4 to 5 to 600 markets better. Have they done better or worse than the people with concentration or more concentration in their portfolio? Again it's going to come. Also one thing that I think, think we'll, we'll, we'll segue into shortly is this discussion about maybe some niche portfolios. That leaves out some of the may, perhaps some of the financial markets instead of having more commodity exposure. And it's the, and, and once again I know this is early days, we have no idea where this crisis is going to go. But it confirms a study that was done a while back where the company had looked at which sectors are actually more consistent in performing during equity crisis. And it was very clear from that paper there was the commodities which is also why we had done, we put a lot of weight into the importance into having a large number of commodity markets relative in the portfolio because we do believe that they're so important. But again, once again we talked about it already. I mean things like gold and other metals have done okay during this energies have done really well from a trend following perspective offsetting some of the fallout in the financial sector. So again there are new lessons to be learned for sure. But there are also old lessons to be confirmed during events like this. So it's tough for many investors and that's unfortunate of course but it's also super interesting from a intellectual point of view to go through this sort of in real time and just see how portfolios react. And as you say that the speed of the models and I wonder even Joav, even down to the type of model I would Imagine that some models by design are faster to react. I don't mean the parameters in terms of speed, but even in terms of whether you are more a continuous system or whether you're more like a breakout type system, there could be some differences in that. So it's, it's super interesting to monitor closely how this all shakes out.

[C]

Yeah, I think that it's not going to be that. I don't, I don't think we're going to see a material difference between managers to trade 250 futures. I think the paper from Quantica three weeks ago that you discussed with Alan, it's not really about the number of markets, it's really about the correlation structure and which markets are less correlated. And that's, I think, very important. The diversification for CTA doesn't come actually from the number of markets. We always say square root of the number of markets, but that's actually not where diversification come from. And as you say, being overweight in assets which are less correlated to the rest of the market is going to be much more material in terms of how this market, how this crisis played out, I think. So if you were overweight in the, in the commodities, that probably has done quite well for you in that respect. What I think is interesting is that when you see a shift in correlation structure, that's very painful, actually. So one of the problems that you have is that if you think that you're, you know, diversified to a certain amount, but then everything becomes more correlated very quickly, that is actually very painful. So that's where we might see more pain.

[B]

Yeah, yeah. There was something I was going to say to you and I forgot it while you were talking you up. Maybe it'll come back to me, but let's jump to the first topic now. Again, this was written by one of our friends, of course, on the podcast, Moritz something he posted on Substack. So I don't want to make it specific about his business, but I just want to make specific about the topic that he raises because I do think it's an interesting topic. And that's this thing that you also picked up on and that. Well, maybe I should let you explain what interested you about this particular article.

[C]

Thanks. That's a great substack. So if anybody wants to go into two quants substack, I think they write really well and they write well about things that we don't normally talk about when we talk about clients. And it's about attention to details, which I think is really, really important in the CTA business. And they're talking about two ways that they are getting diversification. And not in terms of position diversification, but in terms of the way that they trade, the trade diversification, the way that they can ensure that they trade not at the same time as other players in the market. Okay, so to put that into context, that's not going to be a big impact to your portfolio. P and L we know that trading costs are not that big, not that great. We're talking about five basis points of Sharpe per year, give or take. So improving that is not going to make a huge difference to your performance. But it's still very important. And they are talking about two ways in which the fund and which CTAs other CTAs can potentially reduce their market impact by mixing a collection of signals. That's the first way that they are thinking about it. And the second way is they saying, well we might be trading the second contract rather than the first contract. Okay? And both these methods are a nice way of saying let's trade at different time to other people or potentially in a slightly different market. But the one which is co integrated with the first contract so we can trade in a different market. So we put making a little bit less of a market impact. And both methods are perfectly valid and it's really good. But it's actually the throwaway comments that they make which I find really interesting. Okay, so the first throwaway comment that they make is about the way that CTAs congregate during exit rather than entry. They say entry is rather smooth, but exit, we all tend to exit at the same time. And you're thinking about this and you think, hang on a second, why is that? I mean signals are signals, price is price. Why is that? And I think that plays out to exactly the discussion that we had today. In reality, that correlation of Trade happens for CTAs for two reasons. The first one is about the signal, the signal changing. So if price goes up, we all tend to buy. But the second method, which is actually very significant is about risk management. So if volatility spikes then what you expect, you expect all CTAs that risk manage. If you have a position on, you will trade at the same time. Of course, at the beginning of a trend you don't have any risk on. Okay, so you don't have correlation due to risk management because nobody has any risk. There's no trend. So there's no correlation. The only correlation you see is to do with sort of entry signals. But when we look at exit. By the time we have a long trend and Everybody, all the CTAs are in position, then you see exit correlation not just to do with signal changing but also exactly as you said to do with volume spiking. We risk manage, we take down the position that we take the time size and that's very interesting. And we can actually measure market impact based on that. So what I mean by that is if I try to estimate volatility in the market, suppose we use 30 days volatility, historic volatility to try estimates tomorrow's volatility. And suppose this is actually an unbiased. This is exact. If there is no trend, what we find is that if there is trend, if trend is overextended, this same measure will tend to underestimate volatility. There is additional volatility tomorrow that we will see which we have underestimated because everybody that we have an extended trend and everybody is in that position. So actually you can measure CTA impact on the market by measuring the sort of unexpected volatility in the market that we see when trend is extended. And that's actually what we saw in the crisis. What I mean by that is the CTAs were in position. The crisis happens. We've all traded down our positions regardless of, you know, whichever CTA that you're trading, it doesn't matter.

[B]

Can I interrupt you in your flow. Sorry to do that. I think that what you're saying, it makes sense but we can't be sure that it's the CTA is necessarily right. I mean.

[C]

Oh no.

[B]

Could have been anyone who just uses some kind of completely.

[C]

Yeah, it's a closet. It's. So there's plenty of closet CTAs, right? Closet trend followers. A lot of micro traders are closer.

[B]

Or just people who want to de risk because things are going absolutely craz crazy.

[C]

Absolutely. But from a mathematical, I'm looking at it from a mathematical point of view. When we use prediction of volatility, what we have to be aware is actually the level of the trend also gives you quite a good extra 10% accuracy in estimating 5 to 10% accuracy. And that's another way for us to measure our impact in the market or the impact of whatever is whoever is trend following it in the market market at any one time. So that's, that's one interesting throwaway comment that they make which I think people don't really appreciate in terms of correlation between CTAs. The second almost throwaway comment is that they look at the various performance of the trend indicators. And they say, well, we're going to use it, we're going to use a mixture of those in order to ensure that we trade at different times. And what I find very interesting, they're showing the performance dispersion between trend predictors. And it's huge, right? It's somewhere between up 100% to up 400%. So what is very interesting is that although we all trend followers and we all have different styles, we tend to think, oh, it doesn't really matter, but actually it does. And if you look at the average overall, if you actually put all those together and you mishmash them, then you get to a long term average where we kind of know what the expected performance is. You can actually do a mathematical formula for what that performance should be. But what it does mean, it means that there is a big dispersion in which trend predictors you're using. And if you're just able to tilt it slightly to the predictor, which is more appropriate at a given time, at a given market, then you can actually potentially improve your performance. So that is one area of research which actually is very interesting in terms of, as you said, which predictor has done well, are the breakout styles, is it the speed, is it the breakout style versus moving averages? So there is scope, you know, they don't make that point, but actually it's very interesting in that paper.

[B]

But, but how, how? Okay, so I think a lot of people out listening to us right now are thinking, well, I mean, how do you know which one to use? Because we don't know the future.

[C]

No, absolutely right. So, so part of it is to do with what are you trying to achieve? Okay, so if you're trying to achieve sort of long term trend in the market, then what are you trying to harvest? Which alpha? And there are two sources of alpha in a market. The first one is sort of long term trend. So if you look at fixed income like long term secular trends and the second one is short term auto correlations between price moves. So a market can be trending a secular trend which is very long term and actually short term correlation to be quite flat and vis a vis some other markets which are driven by sort of successive auto correlation in the short term. And I think the design of what you use for which market really gets affected. And the third component is of course costs. So the way that you construct your portfolio and the way you construct the predictor really impacts the cost and cost of the market. So these three things like what are you trying to harvest out of that market is actually quite important.

[B]

And I think that the final thing I want to maybe touch on in terms of this write up was I guess the question of also a little bit about capacity, meaning the type of markets you can put into a portfolio that is, you know, a few hundred million dollars instead of 5 or 10 billion dollars will make a difference. And I guess the question becomes, and I think Moritz has kind of raised that, at least on things that I've come across, which I think is a, is an interesting question and that is in some way shape or form, can capacity equate to some level of extra alpha? Meaning if you decide that you're not going to overstep your capacity, you're not going multi, multi billion dollar fund, meaning that it gives you the ability to trade certain markets, commodity markets for example, at a full size instead of just saying it's in your portfolio. But in reality it's very little. Can that be somehow regarded as a little bit of extra alpha that you can get from these not multi billion dollar managers?

[C]

100%. 100%. And let me just explain, right, so for CTA, the average market sharp is important. But then you look at the diversification in the portfolio and diversification is, we say diversification for CTA means very different to what it means in English. In English, diversification means I've got 500 markets in my portfolio. But for us, what we care about is the reduction of volatility that you get by investing in the, in multiple markets, I. E. If the diversification factor is three by, by investing in 100 stocks rather than one stock, you, you're able to get your, your volatility down a factor of three. That bumps up your sharp by a factor of three. And that number is really, really crucial for us. So that's why, because if we think about the average market sharp being say 25 basis points, if you get it factor of three, you get a 75 basis point sharp. This is how we do that. So having 500 markets or 50 markets is less important than having volatility reduction. That's really what is key. And what is interesting is that diversification does not come at all. It's nothing to do with the square root of the number of markets. This is really funny. So normally you would come on the, and the way you try to explain to an investor, you will come on and you will say square root. If you had 100 markets and they were all diversified, you will get a diversification factor of 10, which is absolutely right. But it is actually not what is the dominant factor which affects our own diversification? And what is that? And what is the dominant factor? The dominant factor is actually the average market beta to the first component to the index. Let me just explain. This is really. Please do, please do. Right, so let's take an example. Suppose I have, let me do it in stocks rather than in the CTA space. So suppose I have $1. I want to have $1 of risk in an equity in a stock. And let's suppose it has a 30% beta today index. So I have 30 cents of risk in, in the index and I have 95% in idiosyncratic risk. That works out together 95 squared plus 30 squared. That comes up to essentially $1 of risk. So I've got 95% of my risk is in idiosyncratic and 30 cents in the index. And now suppose I'm investing in 100 stocks. Okay, okay. Now what is my loading on the index? My loading on the index is like $0.30 times 100. Okay, so it's $30. I've got $30 of risk on the index. What is my idiosyncratic risk? Well, the idiosyncratic risk is the square root of 100, right? So that is 10 times 95 cents. So that's $9. So after I've invested in 100 stocks, I've got $30 in the index and less than $10 in idiosyncratic risk. So what is my risk dominated by? By my index. Okay, the risk has reduced. I don't have $100 of risk. I have $30 of risk. But it's to do with the beta, the original beta of the stocks that I had to the index. So if I'm a stock picker, or if I am a cta, if I'm a stock picker, I will get a much more diversified portfolio. If I'm able to pick only 20 stocks but where the beta is only 10% to the index, it's a much higher quality portfolio than just investing $1 in all 100 stock. You are much better off investing in only 10 stocks which are genuinely diversified because the beta to the index is the thing which dominates, becomes very dominant very, very quickly dominating the sort of the, the reduction of volatility that we see. Okay? And in, in our CTA universe, it's exactly the same in the commodities. If we, if we are able to allocate more meaningfully two markets which have low beta to the rest of the CTA universe. Okay, so as you said, ags, metals, energies, okay, energy is less so these days, but argent metals, then what you are able to do is you're able to reduce your overall average market beta to the CTA index and that gives you a better quality portfolio and much more diversified lower beta to the first factor.

[B]

Now we had two more topics. I think we may only get to one, but it's very fitting to what we've been talking about today because it's regarding whether or not there are more or less for that matter dispersion among managers at the moment than what we've seen in the past. I think even I've made some comments saying well there's a lot of dispersion between returns at the moment. But obviously I never sat down and did the math and looked historically. Luckily we have good friends in the industry who did that. Not long ago, our friends down at cfm and you had a look at that paper and maybe you can tell us a little bit about what they found and what you think about their findings and so on and so forth.

[C]

Yeah, absolutely. So I like cfm, they are very much data driven. And it's a short note, it says everybody's talking about dispersion of performance and I think this month will probably show some dispersion. But actually if you look at the SOC chain index and you look at various.

[B]

Is that the trend index or the CTA index?

[C]

The CTA index. So then I hope I'm getting it right. And if you look at the members, so they said we're not picking the members, we're just going to use the members that SOC gen picked for us and we look at the dispersion of performance is actually not that great. And if you look at Pairwise 6 month correlation that hovers at around 50%. And by the way, this is not just them. I think there was a paper from Goldman recently that looked about three months ago looked at dispersion between different managers. So if you look at the macro managers, the pairwise Correlation is maybe 30%. If you look at multistrad, if you look at long short equity, you see reasonably low correlation between different managers. If you look at CTAs, Goldman came up with about 60% correlation pairwise correlation between managers. And that's like completely shocking. I mean in like if you think about it, you know, I've been in, in macro managers and they will concentrate in trading, you know, maybe the G10 universe. Okay. And we go into huge lengths to trade, you know, 50, 100, 200, 400 different markets and what do we end up. So you might expect we should be much more diversified internally to each other. Okay. And yet we end up very highly correlated. And just to put it into context, 50% correlation pairwise basically means that we all have 70% loading on the SOC gen index. And that's like a big number. And I think that's part of what I think very much related to what we discussed just a second ago. Why are we getting such a high correlation between CTAs is because we all load on the same first factor as everybody else. So it's not just that you're getting a more concentrated portfolio. You're not necessarily getting a more diversification is you're also becoming more closely to your peers. And I think that's part of the reasons why people don't necessarily like to invest in CTAs, because they're kind of used to investing in multiple macro managers. But when it comes to cta, they will say, well, if I've talked to one, I've talked them all, they're all the same. And essentially it's our fault for making it because it's true. We are 70% correlated to the index, we are 50% correlated to each other. And I think that discussion about trading off capacity to be able to allocate to markets which are slightly off the main path is helpful not just internally for you in terms of getting a better quality, more internally diversified portfolio, but what it will also help you is to get away from the rest of the package in terms of being correlated to the SOC chain index to the other big managers. Right. What am I offering in addition to sort of the standard CTAs? So being a slightly offbeat is very helpful. And I think the trade off you will have to do is capacity is exactly what the Quantica paper is talking about. Can you turn that into alpha? Alpha. You first of all can turn it into alpha. But also it will make you more distinguishing and different to others. But you will have to content yourself that a certain market can take just so much risk. So if you have only 10 stocks, if you're a stock picker and you have 10 stocks which are truly diversifying, that's great. But you have to put 10x of risk in each of the stocks. Right. You can't do $1 in each one of the $100, you have to put $10 in each of them. And that means that you have to start thinking about capacity and you have to have to basically run a smaller shop.

[B]

Yeah, I think that those are all very important and relevant Questions for people looking at this space. Certainly if you're a larger institution now, just maybe to summarize all of this because you may have read the paper from CFM them more closely than I did, but their conclusion is as far as I remember that actually there is no more dispersion today than what we're used to seeing. Is that correctly remembered?

[C]

Yeah, I mean they go back all the way to 2011 or thereabouts when they start doing the. Which is to do with the index. Actually if you go back historically and that 50% correlation has stayed fairly stable in some sense that's indication that the industry has become a little bit more diversified because we've actually have. You might have thought we would have converged by now, especially with the large aum. So the industry has done work in order to essentially maintain. We've done a lot of work to stay in the same place. Right. It's like Alice in Wonderland. You have to run twice as fast just to stay, just to make any sort of progress. But yeah, that's sort of 50% correlation, pairwise average correlation has remained remarkably stable. And that's a testament to the fact that momentum is really a macro factor which can dominate a lot of your performance. So that's. Yeah. That the state constant.

[B]

Right.

[C]

Yeah.

[B]

So the main takeaway is actually not that, you know, it's not really dispersion that's the story here. It's the fact that the trend in the trend engine still works, so to speak.

[C]

Oh yeah. I mean trend works for many, many good reasons. Right. For many good. And we see that in the autocorrelation of returns. Right. It's not just a way of transforming the payoff but it's also, it also allows you to buy, you know, buy an option that's as realized falls rather than implied Vol. And it allows you to harvest auto correlation which we see in the data, you know, going back hundreds and hundreds of years.

[B]

We're coming up to the hour mark. So I, I would like to save the last topic for another day but one thing I would like to maybe bring up and see if you. You've noticed this as well. And I'm not going to name any names here but you know investment banks, they love to quote, unquote. Well, this is my quote, I guess front run CTAs by coming up with these research announcements about. Oh but in the next two weeks CTAs have to buy $100 billion worth of equities or they have to sell $100 billion worth of equities. Because so and so is happening. And some of these calls have been recently called out on Twitter where some of these investment banks have come out with these very firm statements. But of course what turned out to happen was the complete opposite thanks to the, the little tariff tantrum that we've been going through. So, so every time they came out saying oh, they have to buy, in fact we're probably selling because of markets, because of volatility and, and, and so on and so forth. Now, one thing maybe as a final little challenge for you, Yoav, something that I picked up in my own correspondence recently with investors and prospects and that is I think people would have assumed at this stage that a lot of our equity signals would have been short by now. And at least from my vantage point, I would have had to remind them of saying, well you know, trend following is really about two things. It's about the price, but it's also about the time. And although prices have moved, time is not really long enough for these typical look back periods. You mentioned it as well. In the old days maybe we were a little bit shorter term in our models, but nowadays we're certainly more long term. So my expectations are that for the most part many long term managers are not, not, you know, not close to getting real short equity markets. Let's leave out what happened last night. But even, you know, if it had stayed down 4 or 5% last night, it's not really something that's long enough in duration for our models to react to that. What's a good way, because I'm sure I'm not doing a great job at this, but what's a good way to kind of explain to people this symbiotic relationship between time and price within the trend following strategy to help them better set expectations in terms of what our models would, how they would react in what we've just gone through?

[C]

Absolutely. So I think there are two effects here. First of all is time. But also the fact that you started off at very much an all time high. What we've seen is, I mean ridiculous performance of the S and P for a very long period of time. So any, any normal manager, the strength of the signals would have been many standard deviations from normality going into February. So you of course you update your prior se as as the price starts trickling down. But yeah, I completely agree with you. I would, I will, I will have expected most, the most of the CTA money to be very much in the sort of still the equity. But I think you explained it perfectly. In terms of time and in terms of the level the signal where we started with, I will say that a lot of those predict the predictions by the investment banks about what CTAs will have to do. I think there is something in it. Obviously we don't know the future, but we do know the past. So and what I mean by that is if I look at a signal which is a moving average 30 days, okay. Then I know that in 15 days time the last 15 days will be in that sample. Okay. And that gives me a good value. Like it's not assuming I don't know what the market is going to do. But I actually have a very reasonable idea about where I'm going to like if you're a 30 day trend follower, I actually have a very good idea where you will be in expectation in 15 days time because you know 15 to 30 days will disappear but you are still left with the last 15 days of performance. So actually that's something that the industry doesn't do that much. But you can actually play forward our own positions and especially as we become slower trend following. If suppose we're a one month to three month horizon, you can, you have a very good idea about where your signal is going to be. Okay, in 15 days time, in two weeks time. Obviously I suspect the investment banks are not doing a very good job at predicting it because for a start they don't really know exactly the models that we trade. But certainly from our perspective, if we design our trading, we kind of, we should be able to think ahead and say, oh, where are we likely to end up from a single perspective and can we get better cost based on that? Can we trade smoother into that path?

[B]

But you know what I mean. So two comments to that, Yorav. One is, I think it's a dangerous game because it sounds like we're now starting to predict something which we shouldn't do, right? So we're kind of trying to predict where we might be but instead of just saying, well, well this is where we are today and we don't need to worry about where we might be in two weeks time. So that's kind of one thing about it. It doesn't mean that it's not happening. I'm just saying that I'm not a big fan of it. And the other thing I'm not a big fan of is essentially people trying to front run our positions and trying to, you know, gain an advantage to themselves by encouraging their clients to trade, quote unquote ahead of CTAs especially as you say, they probably have some idea of how these models are built, but they don't have the full picture.

[C]

I think first of all it's being done, so it's 100% being done. I was sitting in a macro shop and I was given the prop traders were interested in the CTA model, playing it forward so that not necessarily in order to front run the CDAs, but in order to understand the dynamics of the trade, to say how is this trade likely to play out? What happens like as a Monte Carlo simulation, what happens if price does go up? What happens if price goes up down? Where is going to be the buying pressure at that point? So sure. So the first thing is people definitely do that and we are in the market with everybody else and we're in the business of making money. I think from our perspective, thinking about where our signal is likely to be is not necessarily about trying to game ourselves or front run ourselves. There's not a lot of risk you can put in that trading system. But in terms of being able to trade better into a certain position, how is that likely? Let me just give you an example. Suppose that our short term trend has spiked through the roof, right? But you know, it's coming back very quickly because it's a short term trend, okay. And there is a trading cost of putting on that trade, okay? Because you have an expensive market, say then you might say, well actually this signal is not going to stay positive for long enough to me to recoup my trading costs. So actually I don't really want to put on that trade simply because it's just becoming too expensive. Where, okay, so being aware of where you're going to be is actually important. Not for me in terms of predictive power, but in terms of knowing thyself and being able to incorporate costs into better way into their own trading.

[B]

Now I don't want to disagree with you Yorv, because you're much smarter than I am. But when I hear that and I hear the words like a throwaway comment saying because you know it's coming back, this reminds me of these, you know, what were they called in the old kind of, you know, type one era, type two era, not just doing the trade and then it runs away from you. Oh no, no, no. So every time, so every time I hear this is the words and you know it's going to come back, I'm thinking, yeah, well until the day it's not.

[C]

No, no, no, no, no. Let me, let me put this way. So there's certain Aspects that we don't know. We don't know what the price is going to do, definitely. Okay. But what we, what we do know is that all our trend predictors have a mean reverting property. Okay. So if the signal is. There's something called, like if you look at the, there's something mathematical called the OU process, the Owenstein New Lenbach process. So our signals for example, are designed so that they will, they're not going to hover at free standard deviation unless they are being supported by price. Okay? They will turn to zero unless they get supported by price. And that pullback to the origin becomes stronger the higher the most, the stronger your signals, right?

[B]

Sure.

[C]

So that tells you that you have to fight costs more the stronger the signal is. So what I mean is committing capital. If I'm at the signal, the signal strength is say 0.2 and it's going up to 0.3. Okay. That you commit into that trade, that's likely to stay, that trade is likely to stay for longer. But if the trade is going from 3 to 3.11, okay. Because the pullback, there's a stronger pullback for very strong signals, you know, that trend is likely to stay for, for shorter. So it's just essentially a cost, a cost versus alpha balance. And that is slightly different depending on the strength of trend because the pullback to the origin is different where you are in the strength of strength. So that, I mean it's, it's a, it's, it's you. You're absolutely right. If you, if you're running a, if you're running for example, a breakout system, then that's not how you work at all, right? If, if you do breakout, you put on the position and you stay in. Okay? And then that's related. If you're doing a moving average crossover sort of type of predictor, then you kind of know that you need a certain fuel to maintain the trend at a certain level. Okay. And, and on average, the stronger you are away from the origin, the more the pull back to the origin is. And therefore you need to take your, you are more cognizant about cost.

[B]

Fair point. Fair point. This was great. I think in a world in a week of chaos, I think hopefully people will be feeling a little bit more, how should I say, maybe making a little bit more sense of it from at least a trend following perspective. I'm not suggesting we can make any sense of what's happening in the real world.

[C]

I don't think we can.

[B]

Or anything to do with terrorists and trade wars, but super fun, super interesting, Very much appreciate all the time you put into preparing for this and of course if our listeners feel the same, show some love for Yoav by going to your favorite podcast platform, leave a rating and review. It's definitely the best way to support the work that we do here now. Next week, I think I already mentioned, we are joined by Katie Kaminsky who just is putting final touches. Maybe she's already put final touches on a new paper, funnily enough, relating to Crisis Alpha, which will be very timely, very insightful, fun as well. So I can't wait for that conversation. I hope that we'll maybe encourage some questions from the listeners and send them as usual to info toptraders on block.com and I'll do my best to bring them up with Katie that's it for now from Joav and me. Thanks ever so much for listening. We look forward to being back with you next week and in the meantime, take care of yourself and take care of each other.

[A]

Thanks for listening to the Systematic Investor podcast series. If you enjoy this series, go on over to itunes and leave an honest rating and review. And be sure to listen to all the other episodes from Top Traders Unplugged. If you have questions about systematic investing, send us an email with the word question in the subject line to infooptoptradersunplugged.com and we'll try to get it on the show. And remember, all the discussion that we have about investment performance is about the past, and past performance does not guarantee or even infer anything about future performance. Also, understand that there's a significant risk of financial loss with all investment strategies, and you need to request and understand the specific risks from the investment manager about their products before you make investment decisions. Thanks for spending some of your valuable time with us, and we'll see you on the next episode of the Systematic Investor.