Shownotes
This episode examines markets through the lens of uncertainty rather than prediction. As the Federal Reserve delivers a rate cut amid dissent and conflicting signals, Alan and Mark explore what it means for systematic investors navigating noisy data, fragile liquidity and shifting regimes. The conversation moves from Fed credibility and term premia to bubbles, leverage and the limits of valuation in an environment shaped by narratives as much as fundamentals. Along the way, they return to a core question at the heart of systematic investing: when uncertainty rises and explanations multiply, should prices remain the final arbiter of risk, signal and portfolio design?
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Episode TimeStamps:
00:00 - Introduction to the Systematic Investor series
00:23 - Market context and recent CTA performance
02:41 - Initial reactions to the Fed decision and rate cut
03:12 - A messy Fed and the problem of dissenting signals
06:48 - Inflation, growth projections and policy uncertainty
08:31 - Signal versus noise in systematic trading models
11:22 - Employment data revisions and confidence in fundamentals
13:10 - Bond valuation, term premia and the question of safe assets
16:30 - Fiscal dominance, inflation risk and portfolio fragility
19:29 - Prices versus value and the limits of interpretation
22:47 - Narratives, reflexivity and momentum in markets
28:07 - Bubble dynamics, leverage and wealth effects
36:51 - Credit markets, AI investment and systemic risk
41:07 - Momentum, trend following and persistent market behavior
54:36 - Total portfolio approach and adaptive asset allocation
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Transcripts
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.
Speaker A:Welcome to the Systematic Investor series.
Speaker B:Welcome back to the latest edition of Top Traders Unplugged where each week we take the pulse of the market from the perspective of a rules based investor.
Speaker B:It's Alan on here this week sitting in for Niels.
Speaker B:Niels is away on his travels in the US and I'm delighted to be joined by Mark who's in Chicago today.
Speaker B:Mark, how are you?
Speaker C:Not too bad.
Speaker C:It's, it's a little early in the day but it's, and it's cold out here in Chicago so as what you would expect in December.
Speaker C:But, but, but I'm ready to have a good discussion.
Speaker B:Good stuff.
Speaker B:I was there but six weeks ago it was pretty, pretty pleasant at that stage.
Speaker B:But yes, you would expect it to be getting chilly now and appreciate you getting up early to make, make time for this.
Speaker B:So we've got plenty to talk about.
Speaker B:We've had the Fed out this week, we're recording on Thursday so Fed was last night.
Speaker B:So that's, that would be a focus.
Speaker B:But we've got a number of other interesting topics but maybe just to kick off and to leave time for the remainder of the conversation just to cover performance.
Speaker B:So we're a little bit away through the month at this stage.
Speaker B:The stockchain CTA index is down 78 basis points as of 9th December and soccer trend index down 62 basis points.
Speaker B:So soccer CTA now down 2% on the year, 2.06% and the Soc Gen trend close to flat down 0.16%.
Speaker B:So not a whole lot I would say to talk about in terms of December performance.
Speaker B:Mark, any observations on performance this month or the general trajectory?
Speaker B:Obviously we've seen generally better performance over the last few months.
Speaker C:Absolutely.
Speaker C:We've seen a lot better trends in some key markets as we moved into the end of the year.
Speaker C:We're seeing performance for a number of CTAs that have improved over this period.
Speaker C:But now that the Fed is done, usually now we're starting to get into holiday mode and that has a big impact on liquidity.
Speaker C:It has an impact on what signals you receive and you have to start making some decisions on whether you should follow all signals as we get closer to the holidays and trading volume starts to dry up for sure.
Speaker B:Now you mentioned we had the Fed done and it was an interesting meeting last Night, obviously the fed cut rates 25 basis points, which was broadly expected then to 3 and a half to 3 and 3 quarter percent.
Speaker B:That did announce some new liquidity injections and T bill purchases and there were a number of descents to the 25 basis point cut on both sides.
Speaker B:So what was your take overall on the Fed, Mark?
Speaker C:Well, before we started this call we were asking you asked what kind of Fed are we seeing?
Speaker C:Is it a hawkish Fed, is it a dovish Fed?
Speaker C:And I said my description, it's a messy Fed and having dissents, which in some sense I think is good.
Speaker C:It shows that there's independence on the fomc.
Speaker C:But at the same time that means that the Fed is not speaking with one voice.
Speaker C:And so that sends a really messy set of signals on what people should take away from what they've heard now in general is that I've looked at the Fed announcement dates very closely and what we found is that while over a longer term obviously interest rates will have a big impact on a lot of different models, on stock markets and other markets because it's the cost of capital.
Speaker C:But at the same time is that right around the Fed announcements is that you get some high uncertainty.
Speaker C:When you have high uncertainty you could have large reversals in price.
Speaker C:So for short term models it's sometimes good to actually avoid the Fed.
Speaker C:In this period of time you might have an expectation on what the Fed is going to do going into the FO fomc.
Speaker C:They then do what is expected.
Speaker C:But then Chairman Powell gets in front of an audience and you don't know what's going to happen.
Speaker C: what are the expectations for: Speaker C:When you have descents it's less clear what is the direction going forward.
Speaker C: wide set of expectations for: Speaker C: oing to actually see hikes in: Speaker C: hat there will be six cuts in: Speaker C: certainty fed environment for: Speaker C:And I think that that's, that's even more problematic when you look at what is their forecast.
Speaker C:One is that even though they're cutting rates, we're at a three year low.
Speaker C:This is the third cut this year.
Speaker C: basis points in: Speaker C:So that's not close to our 2% target.
Speaker C: going to actually come in at: Speaker B:Yes, I mean it is an interesting mix of projections and comments and as you say, a lot of uncertainty and I mean even, you know, we were chatting earlier, you know, before we came on was it a dovish or hawkish?
Speaker B:And I mean my sense watching it last night was, you know, coming into the meeting there was an expectation maybe of a hawkish ease but maybe having considered everything, the market concluded it was less so and maybe even a dovish ease.
Speaker B:Granted it is messy and I think a few points.
Speaker B:Obviously the next meeting is in January and we've had this lack of data and we will have a lot more data by the time January comes around.
Speaker B:But even Powell said himself that some of the data that comes through there will may be technical factors that will distort it.
Speaker B:So that is another source of uncertainty as you say.
Speaker B:And then the sep, interesting they're forecasting higher growth but not translating into improved unemployment.
Speaker B:So they seem to be buying into the productivity story related to AI, et cetera.
Speaker B:And Powell was asked about that.
Speaker B:He said he uses himself, he can see how it could be productivity enhancing.
Speaker B:So many dimensions to it.
Speaker B:And obviously the news around additional T bill purchases to ensure there are sufficient reserves in the system, you know, we've gone from QT to some form of QE again, so hard to model all of that systematically when there are so many kind of subtle messages coming from the Fed would not be fair to say.
Speaker C:Absolutely.
Speaker C:And I think at very high level and some of what we like to do, I think on these calls is to talk about, you know, the specifics of how to build models and how models work.
Speaker C:But at the same time you want to try to step back and say, well, what's the high level of what you're trying to do?
Speaker C:And when you're building systematic models, you're always thinking of signals versus noise.
Speaker C:So how do you extract a signal?
Speaker C:And in the case for, let's say, a trend follower, it's usually going to be a price signal versus the amount of noise that you face at a given amount of time.
Speaker C:Now, noise can come into two forms.
Speaker C:One is, we'll call it the volatility, which is measurable.
Speaker C:So we could sort of say like, well, what's going on with the volatility of markets?
Speaker C:And then we could look at the strength of our signal divided by our, our volatility.
Speaker C:We could get a signal to noise ratio and we could sort of say like, well, now we can measure how strong that signal is relative to some scale.
Speaker C:The problem comes in is, is that, you know, when you think of risk, it's not just the volatility, which is measurable, but it's also what is not measurable, which is the uncertainty.
Speaker C:So when you think about, okay, we have three dissenting opinions, well, how is that measurable?
Speaker C:We, we do have some data where we can look at dissents and then see what happens in the future.
Speaker C:But that's, but we have a very small sample.
Speaker C:The switch from when we look at, you know, we'll call it the new qe, which we'll call it just more reserve balance management.
Speaker C:Is that what they've said?
Speaker C:Is that our quantitative tightening or qt may have overshot.
Speaker C:Now we're going to allow for about a $40 billion into treasury bills because we think that there has been some disruptions in the repo market.
Speaker C:That's harder to, we can hear the words, but it's harder than to translate that into measurable noise and then second into a measurable signal.
Speaker B:I guess you can, you can ignore all of that and just look at how the markets trade in the day as was the days after.
Speaker B:As you say, it can be choppy.
Speaker B:I mean, so far the dollar is a bit weaker.
Speaker B:Stocks were up than they were down, probably.
Speaker B:Dollar weakness is probably the most notable feature in the last maybe 12 hours or so.
Speaker B:But as you say, there are kind of a number of different dimensions here.
Speaker B:And also, you know, the Powell even mentioned the unemployment data as well, which I think is shown around maybe 60,000 on average.
Speaker B:But they felt that in reality that might reflect, you know, job layoffs.
Speaker B:So, you know, even on the data side, you've got that Uncertainty as well.
Speaker C:Well that certainly was another bomb that was dropped on us.
Speaker C:And you talked about Paul often sort of upsetting the apple cart so to speak, that if you said that, you know, job creation was overstated by 60,000amonth and what we've gone from a positive job market to something that is negative and certainly not very attractive.
Speaker C:Other labor market signals are more mixed and they say that we have, we'll say a balanced labor market.
Speaker C:Now when you add this all together it's, you say Mark, you're listening, you talk, you know, it tells you this, that the only thing you should use is prices.
Speaker C:Once again, forget all this fundamentals, forget of trying to determine what the Fed is doing or what's going on in the, in the unemployment number.
Speaker C:Just, just go back to prices and, and that becomes the, the key balancing act is, is that how much other information should you use in models beyond price?
Speaker B:I mean it's interesting, you know, you could say looking at the market here from a pure, you know, rates perspective and what's priced in etc.
Speaker B:You know, are, you know, would you say bonds are decent value now, you know, say 10 year yields are, they've been stuck around 4.1, 4.2% for a while.
Speaker B:Obviously one of the notable things is the Fed funds has now come down to about the level of the two year yields.
Speaker B:I mean taking that perspective, any observations on do markets?
Speaker B:I suppose regardless of what the trend is, does the fixed income market look reasonably priced at the moment?
Speaker C:Well, you can always use some simple rules of thumb and the simple rules of thumb is they say let's look at what real GDP is.
Speaker C:Let's look with expected inflation.
Speaker C:So we had expected inflation.
Speaker C:That's going to be, we'll sort of say 2.6 or so.
Speaker C:Even if you, and then you add in real GDP for next year, they're projecting 2.3.
Speaker C:So now you're at 4, 8.
Speaker C:Then you said well should there be a term premium associated with the bond markets right now?
Speaker C:If you think that there's a positive term premium, well then you sort of say like you're at a, at a high force at best.
Speaker C:And you know, you would sort of say that the term premium was, you know, was knocked down to something close to zero because the bonds were such a good hedge.
Speaker C:Now we're probably saving a different view on, on what is the role for bonds in a diversified portfolio and with high debt numbers.
Speaker C:This is that debt may not be the same kind of safe asset.
Speaker C:It may not be the same kind of hedge that we saw before.
Speaker C: g theme that when you look at: Speaker C:Because a safe asset should be a diversifying asset.
Speaker C:If bonds are not a diversifying asset, then what is and what should you do with your portfolio?
Speaker C:Now not saying that for every time a trend followers say that, there's only one answer to the solution.
Speaker C:It's always being a, you know, hold some, some trend following assets.
Speaker C:But this is an important point in time where if, let's say bonds aren't providing the diversification that you thought well, then you have to try to look at other diversifiers and try to find something else to be able to support your portfolio.
Speaker B:Yeah, I mean it's interesting, I mean you talked about the term premium and obviously that is reflecting a number of things.
Speaker B:Supply, demand, imbalances.
Speaker B:As you say, the term premium kind of went to zero, if maybe even negative when there was a shortage of safe assets.
Speaker B:Now things have changed.
Speaker B:And positive term premium reflecting that change dynamic.
Speaker B:But also I guess big theme this year has been are we moving into fiscal dominance?
Speaker B:And then big picture, could we have financial repression?
Speaker B:Obviously we've got a high level of debt to GDP in the US and the question is ultimately how does that get managed?
Speaker B:The easy levers to pull are or inflation inflate your way out of it.
Speaker B:But in the extreme, default could be a possibility.
Speaker B:It mightn't be an outright default, but you could have, if we got into some kind of fiscal crisis down the road, you could have debt swaps or maturity extensions, all of these kind of things.
Speaker B:So in theory the term premium should start to capture those, I suppose, you know, absolutely.
Speaker B:Miscellaneous factors.
Speaker B:Is that fair?
Speaker C:Yeah, absolutely.
Speaker C:I think that if there's been a change in the relative safety of some assets.
Speaker B:Yeah.
Speaker C:If it's change in the role of that asset within a portfolio, then that, then there's going to be a term premium associated with that.
Speaker C:Now you know, and I think that we still have very large deficits and in some sense the only way that you could solve those deficit problems outside of a default, this is that you can inflate your way out of that.
Speaker C:Then at the same time this is that, well, how are you going to get an inflationary environment?
Speaker C:Well, you can engage in some kind of financial repression or keeping rates low so which reduced the financing costs.
Speaker C:And it's not so much that the US treasury is going to default, it's a matter of relative safety.
Speaker C:Because what does it mean to be a safe Asset?
Speaker C:Well, there's nothing, there's no such thing as a truly safe asset.
Speaker C:It's just a matter of what is safe relative to the set of all alternative safe assets.
Speaker C:And I think that I would argue that there should be a greater term premium in the US market.
Speaker C:And at the same time we'll sort of say why are we seeing such a strong price movements in, in gold and silver and some other commodities?
Speaker C:Partially to do is because if relative safety in the US has gone down, then the demand for other potentially safe assets should go up.
Speaker C:And if, let's say the supply of, of, of gold is constrained because it's, you know, how much are you going to be able to mine in a certain period of time?
Speaker C:You don't create it by fiat.
Speaker C:So consequently you could have these strong movements in gold because of a reduction in relative safety.
Speaker B:I suppose you've got maybe conventional approaches to valuing bonds based on all of the known factors.
Speaker B:But then we have these kind of tail risks that you have to think about as well, which we don't know how that will play out.
Speaker B:But one thing that you did touch on there is kind of the signal we get from prices.
Speaker B:And I mean, I know this is something you wanted to talk about as a theme.
Speaker B:I mean sometimes one thing I grapple with, obviously prices reflect the supply and demand balance or the relative strength from a financial markets perspective.
Speaker B:You've got the idea of, you know, the wisdom of the crowd and the price reflects that as well.
Speaker B:But at times we also get herding and trends and moves that may be less wise.
Speaker B:So I mean, how do you think about those two conflicting interpretations of what the price is reflecting as in the wisdom of the crowd at times, but also prices getting distorted by extreme sentiment, irrational exuberance and hurting from time to time.
Speaker C:Right.
Speaker C:Well, think about when we started out our conversation.
Speaker C:The argument was is that look at all of this data that's giving us a lot of noise.
Speaker C:So then you sort of say like, well, in a noisy world, maybe I should just focus in on prices.
Speaker C:And, and, and I probably that's, that's always been my go to position.
Speaker C:And I've used a phrase that prices are primal, that you know, regardless of what happens with other data, you always have the prices telling you where there's a, some balance between supply and demand.
Speaker C:I'm not really sure what that balance may be at any one point in time or whether it's telling me, but, but prices are primal.
Speaker C:The problem is, is that sometimes it's really hard to unpack what the primal price is and to, to break this down a little bit deeper is that prices are primal but that's not the same as value.
Speaker C:So I can have a price in the market at any given time, but that's not where the value is or that's not the true value of a given assets.
Speaker C:It just tells us where there's a balance between supply and demand.
Speaker C:And a perfect example is this, is that let's take a look at some of our bubble prices.
Speaker C:We have individual stocks that have, you know, had some tremendous moves.
Speaker C:We've had, you know, gold have a significant move.
Speaker C:We got silver that, you know, touched above $60 an ounce.
Speaker C:Well, the price is telling us that there's a true supply demand imbalance.
Speaker C:But does that price tell us what the value of gold is right now?
Speaker C:Yes it is because that's what people are willing to pay for.
Speaker C:But at the same time is, is it, is that it's true price that may not be this, those may not be the same thing.
Speaker B:And from a, I mean from a trading, systematic trading modeling perspective, I mean with that observation, what does one do with that?
Speaker C:Well, this is the reason why is this, is that when, when you know, we've talked about is this is that I could be a, a trend following person, I could be believe the prices are primal.
Speaker C:But then I might also use some other indicators to try to tell me is, is that whether something could be overbought or oversold to say, to say is there an anchor with something that's called value?
Speaker C:And, and, and this is also why we try to smooth prices because at any one point in time this is that you may not want to take the actual price but you wanted to use some kind of smoothing mechanism.
Speaker C:And that could be a moving average at the very simplest form.
Speaker C:But there are other mechanisms we have to try to say is, is that because there's noise in just the price process, how do we smooth that process out so we can get a better signal?
Speaker B:Yeah, I mean obviously prices reflect narratives as well.
Speaker B:But, but then price can be part of the narrative too, you know, and obviously we can have feedback loops, reflexive processes.
Speaker B:How do you factor that in and do you see that in current markets?
Speaker C:Well, you know, I think that the narrative is, is very interesting because there's a recent paper that was written about narratives in the FX market and what they, what they found is, is that then prices follow narratives as opposed to lead narratives.
Speaker C:So in some sense is that if you use some type of LLM or if you use some type of mechanism to try to extract narratives within news stories.
Speaker C:You could sort of see that the narrative starts develop and then there's a carryover in prices as we see the narrative develops.
Speaker C:And this is the one thing that you know, is really important for people to think about when for trend following or any systematic price based system is that there are trends in price.
Speaker C:But what is causing those trends in price?
Speaker C:It could be a trend in fundamentals, it could be a trend in narrative.
Speaker C:So that there are, there can be other it's prices move, but there's a rationale for that move and that could be trends in other mechanisms.
Speaker C:It could be, you know, a narrative, it could be the fundamentals.
Speaker B:Yes.
Speaker B:I mean there's all manner of things obviously, you know, when you get into that, there's seasonals as well, which will influence markets at certain times and then structural factors, etc.
Speaker B:I mean quants know about this and can adjust for that.
Speaker B:Isn't that fair to say?
Speaker C:Well, this actually becomes an important issue when you build models because every model has to a degree a personality because when you start looking at all the different choices you make, the modeler has to start making choices and decisions of what to include or exploit loot in a model.
Speaker C:So, so a perfect example is right now when we're, as we get closer to the end of the year, what we see is, is that, you know, volume starts to dry up.
Speaker C:So that means, is that there's more likelihood that a small change in, in.
Speaker C:In trading and volume will have a big, a bigger impact on price.
Speaker C:So your signals are going to get noisier as liquidity declines.
Speaker C:We also know that liquidity and the quality of signals intraday is U shaped.
Speaker C:This is that we get a lot of activity in the morning.
Speaker C:You have a lot of activity on the close, less so in the middle of the day.
Speaker C:That has an influence on the price signals.
Speaker C:To get more specific is that.
Speaker C:And, and here's an example that I was grappling with.
Speaker C:In the last two weeks you have the Thanksgiving holiday in the United States.
Speaker C:So you have that Thursday off.
Speaker C:Okay.
Speaker C:You know, the other markets are still open.
Speaker C:They're not, they don't have a national holiday.
Speaker C:So what do you do about those prices?
Speaker C:Then you have Friday, which is a open market, but usually a lot of people take that, that day off.
Speaker C:So there's not going to be a lot of volume of trading.
Speaker C:This particular November was the last day of the month.
Speaker C:Okay, so now in this time do you use those prices?
Speaker C:Because it's the end of Month, but they're probably, and there's probably going to be more volume.
Speaker C:But normally you might ignore prices that occur on a Friday after Thanksgiving.
Speaker C:And just to make this more difficult for you, in terms of how we have to deal with these problems, you had the CME 11 hour outage of the market.
Speaker C:So you think that some of their servers overheated and so they actually shut down the market.
Speaker C:So what do you do if a market shuts down for a period of time and you're inputting prices into your model?
Speaker C:So do you follow just blindly whatever happens when the market sort of kicks back in?
Speaker C:Do you try to smooth, do you drop out signals?
Speaker C:So there's a lot of nuances in how you look at prices and what prices to use.
Speaker B:One of the interesting themes and topics that's obviously getting a lot of attention in markets, the moment is, is bubbles and are we in a bubble?
Speaker B:Hard Marks was out with a piece addressing that.
Speaker B:I mean, he had written earlier in the year, I think bubble watch and he had a follow up to that.
Speaker B:We can touch on that in a minute.
Speaker B:But it's certainly one of the big topics.
Speaker B: le drawing parallels with the: Speaker B:What's your perspective?
Speaker C:Well, let's go back to when we talked about prices as signals.
Speaker C:This is that, well, if a price of a given asset goes up, then actually, and you're holding a certain amount of that asset, well, you know, by, by definition your wealth has actually increased.
Speaker C:Okay, so the question is that do prices reflect wealth?
Speaker C:And that's not always the case because if, let's say that you are holding a certain amount of gold and the price has gone up to $4,000 an ounce, do you feel wealthier or more importantly, should you feel wealthier under that scenario?
Speaker C:And I would sort of say that, you know, a mark to market and an economist would say your wealth is determined by whatever the price is at a given point in time.
Speaker C:If you believe prices are primal, it says that your wealth has increased.
Speaker C:At the same time is that if you use that wealth that's been created as collateral, well, then what happens is that you could actually increase more leverage in the overall, you could, you can gain more leverage and you could actually sort of make the overall economy more fragile.
Speaker C:And that's one of the fears when you see these bubbles, whether in gold and individual stocks, is that it actually increases the market fragility.
Speaker C:Now, now that being said is this, is that as more people talk about a bubble, I've been, I don't want to say worried, but I've been actually looking at the data fairly closely for central bank behavior and what you find is that the central banks, beyond their increases in mark to market this is that they've just been strong buyers of gold.
Speaker C:So and specifically certain central banks have been very strong buyers of gold and that's putting a lot of the demand pressure.
Speaker C:Also you're seeing this is that a lot of buying is coming from certain areas of retail outside the United States.
Speaker B:I mean gold is an interesting case by itself, but more generally in terms of wealth effects and some of the effects bubbles form, I mean there's multiple dimensions to this.
Speaker B:Obviously as you say, when if the market goes up, you know, values increase.
Speaker B:So there is a kind of a wealth effect for people who are stockholders.
Speaker B:Very often volatility goes down, so margin requirements are lower.
Speaker B:So people can lever up to the extent that they have levered portfolios that they need to add more risk to maintain the leverage.
Speaker B:The stock value of certain companies goes up, so their cost of capital goes down.
Speaker B:So there's the reflexive process that Soros talks about.
Speaker B:As long as there's no chink in the argument supporting all of this.
Speaker B:And I mean maybe it's part of the explanation for the K shaped economy.
Speaker B:Obviously people who own stocks say in the US Economy the wealthier cohort are feeling wealthier, whereas people at the lower income levels are more challenged by the affordability crisis.
Speaker B:So as you say, perhaps it increases market fragility, but also economic fragility.
Speaker B:If the economy now has become more sensitive to the market, the equity market, if it's more leveraged, I think US households are own about $40 trillion of US equity.
Speaker B:So if that market has a significant downturn, those positive wealth effects, those positive reflexive processes go into reverse.
Speaker B:Any thoughts on that?
Speaker C:Well, first is we do know that leverage is higher, especially for hedge funds.
Speaker C:Now there could be other reasons for why there's higher leverage with hedge funds.
Speaker C:It's could be because they're more especially the largest hedge funds are multi strap, you know, pod based, you know, they're better diversified so they could actually take on more leverage.
Speaker C:But we're seeing that there's more leverage over overall in the economy.
Speaker C:The latest research on bubbles and, and this is from some professors at the Harvard Business School talk about that.
Speaker C:It's co.
Speaker C:It takes an academic to do this.
Speaker C:It's closely linked to optimistic analyst expectations.
Speaker C:This is optimism and fundamentals serves as a catalyst for greater optimism about the underlying assets and that increases the likelihood of a crash.
Speaker C:So the more optimistic analysts get, then probably there's more fomo and then that actually increases the likelihood of a particular crash.
Speaker C:So yeah, that seems to make pretty.
Speaker B:Seems reasonable.
Speaker C:Yeah, seems reasonable.
Speaker C:In fact, they say like, like, like.
Speaker C:Well, it took a lot of research to figure that one out.
Speaker C:But what you really, what you really are worried about is this, is that this gets back to the issue of uncertainty is that when it's harder to value an asset, then it's more likely to have a bubble because we don't know what is the true value.
Speaker C:Okay.
Speaker C:The other thing is that we're always worried about in, in, in bubbles is if there is a regime change or if there's a potential story of a regime change.
Speaker C:And you know, we'll sort of say individual stocks is a little bit different.
Speaker C:But let's take a.
Speaker C:The issue with, with gold.
Speaker C:Is there a regime change going on with gold?
Speaker C:Well, central banks are changing their behavior.
Speaker C:That seems like a regime change, a reduction in the safe asset of let's say US Treasuries.
Speaker C:So that people are looking for other alternatives that could be a regime change.
Speaker C:Retail buying, especially in some countries where they feel that there's a high government uncertainty, you know, outside the United States.
Speaker C:I don't want to say that's a regime change, but, but certainly this is that that's adds to it.
Speaker C:And a lot of the things that we learn about bubbles don't always, you know, hold true.
Speaker C:For example, this is that, you know, retail demand in the US through ETFs is not as strong as what it.
Speaker C:As it has been in the past.
Speaker C:So this is not, you know, sort of retail driven gold increase.
Speaker C:And then when we look at some of the other things in terms of speculation we usually expect is is that.
Speaker C:Or the view is, is that that it's the excessive speculation that drives, you know, bubbles prices into a bubble?
Speaker C:Well, surprisingly is this, is that we don't really have that excessive speculation in some of these markets.
Speaker C:Especially is it, are you saying that excessive speculation is coming from central banks in the case of gold?
Speaker C:I don't know.
Speaker C:I actually did some close analysis of the cocoa market when it everyone talked about that being in a bubble.
Speaker C:And the view is always is that well, bubbles should be more volatile, bubbles should be driven by speculators.
Speaker C:Bubbles will see more volume of trading because there's more churn in the Market, there's more people entering in the market.
Speaker C:In the case of for example cocoa, which is not, you know, we'll say representative of everything, but it's an interesting case.
Speaker C:We saw that the commitment of traders show that large speculators were actually declining before a lot of the big move in the cocoa price.
Speaker C:We saw that the volatility was actually, you know, declining, not, not increasing during that period.
Speaker C:We also saw, saw that volume of trading was as the cocoa prices were getting higher, higher were actually dec.
Speaker C:So some of the we'll say our conventional wisdom, how we think bubbles behave don't always apply.
Speaker C:And that's what makes some of this so maddening to try to analyze.
Speaker B:Well, one of the things you touched on is leverage and I suppose debt but I mean with respect to the current AI boom now we are seeing increasingly debt issuance in relation to the build out of data centers, et cetera.
Speaker B:And that was definitely part of the focus of Howard Marks's piece which I mean to simplify, he saw as kind of a part of a bubble narrative.
Speaker B:He didn't definitively say it's a bubble but he kind of suggested that when you see this kind of debt issuance combined with rising asset values that inevitably there are issues.
Speaker B:Would that be your read on it too?
Speaker C:I think that there are things going on in the debt market that should give investors concern.
Speaker C:We've had a number of different issue with first brands and some other factor financing that was problematic, which we're not even talking about the AI issues is that what should be sort of relatively simple type of credit financing is actually now looks like there may have been some kind of fraud.
Speaker C:Now John Kenneth Galbraith when he often talked about the issue is that when you have very frothy markets or when you have market extremes, you have something called it called the bezel.
Speaker C:So it's combination of bezel with embezzling or fraud.
Speaker C:And I think that this is something that that's one issue we have to look at in credit markets right now.
Speaker C:Second is that when you find that even though credit spreads are extremely tight, we're seeing that the spreads now are reflecting the added risk in the case of let's say financing for data farms and AI.
Speaker C:Some of this is that given it's a high uncertainty, we don't know what the payoff is going to look like in a traditional world that should become as equity financing as opposed to debt financing.
Speaker C:Because debt financing says you have to pay back that principal at some point and you're going to have to pay interest.
Speaker C:So, so I think that the credit markets are at a market extreme and we're starting to see cracks in the behavior where we're seeing issuers trying to access credit markets or we see investors saying, I don't know if I really want to pay, I want to pay the, the average price.
Speaker C:I think I'm going to ask for a premium.
Speaker C:Now you sort of say like, well if I'm a systematic trader and I trade mostly futures markets, why should I care?
Speaker C:Okay, that's not, I don't trade that stuff anyway.
Speaker C:Well, I'll take it, take more of a holistic view on how you should look at even a set of futures markets.
Speaker C:You trade markets are a complex system and so there's interactions across markets and assets.
Speaker C:And what you're having a situation, especially if there's cracks in the credit market, this is that that'll have an impact on people's risk aversion.
Speaker C:It will have an impact on where people will reallocate capital.
Speaker C:And what we'll sort of say from that network perspective, there can be a movement of capital into more safe assets, Treasuries or some other sovereign debt.
Speaker C:And so that's going to cause the systematic changes in prices which could be reflected in a lot of the models we look at.
Speaker B:Yeah, I mean, just shifting gears.
Speaker B:Obviously we're talking about bubbles, boom, bust cycles.
Speaker B:And all of this is often a justification for momentum strategies, trend following strategies.
Speaker B:The fact that these are recurring patterns, recurring features of the financial market landscape, that they are moves that are somewhat, you know, unlinked from fundamentals, but the way to play them is by focusing on the price, as we've been saying.
Speaker B:So yeah, is moment.
Speaker B:Are momentum strategies, trend following strategies the way to play these kind of market environments?
Speaker C:Well, I think that there's, it's interesting to look at the history of trend following momentum and I'll put those two together.
Speaker C:Even though there are distinctions between trend follow, which is more absolute versus momentum, which is, you know, cross sectional relative.
Speaker C:That being said, this is that, you know, we probably sort of say that went into the early 80s.
Speaker C:This is that if you said you were a trend follower, you trade on momentum, you know, people would sort of think of you as almost a some form of Neanderthal because the markets are efficient and certainly is that you just haven't been aware of what all the advances in finance that we know about now we're seeing.
Speaker C:And even in the last couple of months I've, you know, read two interesting P papers that looked at momentum and the interesting way, or to, to sort of cut through all of the research is that momentum is everywhere.
Speaker C:It works, you know, across all time periods.
Speaker C:There might be periods where it doesn't work for a period of time, but if you look at, you know, very long history, momentum works is that you look at sub periods.
Speaker C:Mostly it works, it works on, you know, markets, countries, industries, you know, factor momentum, individual stocks.
Speaker C:Momentum is everywhere.
Speaker C:And as you, you know, peel back the onion, you're going to see that it's everywhere.
Speaker C:But that being said, is, is that we find out is, is that some places momentum does better than others.
Speaker C:So we'll say beta and country momentum, you know, not as strong as what we're going to find in industry or factor momentum.
Speaker C:So, so when, when there's factor tilts, you know that, that there could be momentum in that, in that importance of that factor for industries.
Speaker C:There's much stronger momentum effect than what you'd find in individual stocks.
Speaker C:So what you'll find is this, is that, you know, if you're a statistical Bayesian, you'd say momentum is everywhere, but you could sort of like tilt your way, you place your momentum bets and you could do better.
Speaker C:Do better.
Speaker C:So stocks show, for example, intermediate persistence, but not in the very short run.
Speaker C:When we look at, you know, what, what a lot of times for momentum strategies, you lag one month because you, you get sort of reversals in the very short run.
Speaker C:Now the other thing what we find is, is, is that momentum is not just a price mechanism.
Speaker C:So there's another interesting paper that looked at the history of momentum and what they showed is that there's momentum in news, there's momentum in fundamentals, there's momentum and surprise effects in earnings, and that each one of these are slightly different.
Speaker C:They're not always, always correlated.
Speaker C:So the momentum that you see in price may not show up or may not be fully correlated with the momentum that you might see in earnings.
Speaker C:So that there are a number of ways in which you can exploit the idea of momentum.
Speaker C:And you say, like, well, what is really going on here?
Speaker C:If it's so why does this persist?
Speaker C:And you know, we could sort of say that behavior is adaptive in the sense that people take time to digest information.
Speaker C:It takes time for people to gather or to process information.
Speaker C:And because of that is that there could be a piece of news or some change in news or regime takes a while for people to digest or gather their attention.
Speaker C:And so there could be an elongated response in prices.
Speaker B:You're talking about the different ways Momentum plays out and you see, as you say, momentum everywhere, but it's not as strong everywhere.
Speaker B:So in theory, you can combine different sources of momentum in a strategy.
Speaker B:I mean, would you be confident enough about those differences to say that they are significant or just and persistent?
Speaker B:I suppose, as you say, the fact that industry and factor momentum is stronger than country momentum and stronger than stock momentum.
Speaker B:Do you think there are good reasons why that's the case and likely to continue to be the case?
Speaker C:Well, I think so.
Speaker C:I've been willing to bet my career on it.
Speaker C:But we'll say that there are a few things that you can sort of say that.
Speaker C:And, and again, we want to look at a higher level, is that if an asset is higher, harder to value.
Speaker B:Yes.
Speaker C:There will be more likely to be persistence or momentum.
Speaker C:Okay.
Speaker C:Because if we can't, you know, understand what the value is, then it's going to take us time to figure out what true value is.
Speaker C:So there's more likely to be persistent.
Speaker C:Okay.
Speaker B:Okay.
Speaker C:When we bundle stuff together.
Speaker C:So an individual stock, there could be a lot of noise, but if I look at the industry, there may be actually trends.
Speaker C:If, for example, is that those assets were.
Speaker C:It's harder to.
Speaker C:Or there's less analyst attention.
Speaker C:There's more likely to be persistence.
Speaker C:So, you know, if there's no analyst following in, in a small cap stock, you know, there could be a strong reaction, but there's probably going to be more persistence in some of its behaviors.
Speaker C:So if you sort of classify assets or strategies or factors based on some guiding principles, you could sort of say there, there may be some strong theoretical reasons for why persistence may occur.
Speaker B:Yeah, I mean, if we were to think about, say, momentum as in trend following futures, trend following versus momentum as opposed to applied to stocks, whether it's single stocks or baskets, I mean, at a high level, are the mechanisms by which it works the same?
Speaker B:Obviously, they won't necessarily work in the same period, same environments.
Speaker B:Are they good complements from that perspective?
Speaker B:Is that part of what you're saying?
Speaker C:They can be good compliments, but they may require different approaches to different types of asset classes.
Speaker C:A perfect example would be, is that we know that there's persistence in, or, you know, after earnings announcements, we also know that there's probably, you know, these periods of punctuated information that might cause a change in prices.
Speaker C:So when you know that, that, that has a different influence in how you should trade.
Speaker C:If, let's say that you know that, for example, is that you get earnings announcements, you know, four times a year, and we know that it could be punctuated where there's a lot of focus on those four periods of time.
Speaker C:And there could be strong revisions in the business based on that.
Speaker C:There could be short term, you know, earnings momentum afterwards, you know, because of bad news or good news.
Speaker C:So you have to take into that account if we look at, for example, you know, sort of commodities, is that we know, for example, there's certain seasonality, you know, associated with, with certain markets.
Speaker C:But again, it's harder to make valuations.
Speaker C:You don't have the same punctuation of earnings.
Speaker C:So.
Speaker C:So in some cases you might have a different signaling approach or a different way to approach those markets.
Speaker C:Foreign.
Speaker B:A little bit away from prices.
Speaker B:Momentum bubbles.
Speaker B:I mean, what comes with, with that, to an extent, is uncertainty.
Speaker B:I know that was something you wanted to talk about.
Speaker B:Shocks, uncertainty, dealing with that in, in optimization, et cetera.
Speaker B:How does this factor in?
Speaker C:Well, let's go back to what we originally started with.
Speaker C:We always talked about signal versus noise.
Speaker C:And so, so the.
Speaker C:No, always your risk or the uncertainty.
Speaker C:And so not saying I need to get a better life, but I was looking at some book on stochastic optimization, so I keep it right next to the bed at night.
Speaker C:So he's tossing and turning.
Speaker C:I think I'll just flip through a few pages of stochastic optimization to sort of calm me at the end of the day.
Speaker C:But the author of this book is actually made a really insightful comment and actually made me sort of like, you know, jump up and say, like, wow, you know, I've thought about this, but I didn't put it in a precise way.
Speaker C:He talked about all the types of uncertainty that might exist.
Speaker C:And, you know, I won't go through, you know, all of them, but let me just list the names and then you start.
Speaker C:I want, you know, all of our listeners should start to think about this.
Speaker C:He said there's observational uncertainty, there's prognostic or forecasting uncertainty, there's experimental noise variability uncertainty, there's transitional uncertainty, there's inferential uncertainty, there's model uncertainty, there's systematic exogenous uncertainty, there's control implementation uncertainty, there's algorithmic noise uncertainty, and there's goal uncertainty.
Speaker C:So he listed all of these types of uncertainty, saying, like, I never really sort of like categorized it as such, but all of those have influence on the signals that we have and how we react to that.
Speaker C:So, for example, this is that, you know, and I'll just give one, you know, simple example to have, you know, listeners think about said.
Speaker C:So we had the cme, you know, outage in the market.
Speaker C:Okay, so there was a period of 11 hours where there wasn't no trading.
Speaker C:Then we start up again.
Speaker C:Okay, so if you're a modeler or if you're looking at prices now, the market starts up after an outage.
Speaker C:You didn't know what it was, what, what the cause was.
Speaker C:Now you're at month end, you had this period of time the market started up.
Speaker C:Surprised it wasn't disruptive.
Speaker C:But if in real time you had to make a decision, what do you do?
Speaker C:What do you do with the uncertainty that you're now facing?
Speaker C:Is that the market was closed down for a period of time that you didn't expect it was supposed to be closed down.
Speaker C:So what do you do about that?
Speaker C:Or as we get into the holiday period, let's assume there's very low volume in certain markets.
Speaker C:This is it.
Speaker C:Well, should you treat those prices the same as you would in other parts of the year?
Speaker C:Or let's say the third, you know, third example is that if, and this is one is a real life is, is that if you looked at copper prices In New York vs London, London copper prices, there's a big divergence between the two prices.
Speaker C:A lot of that had to do with tariffs for a period of time.
Speaker C:So how do you use those prices and how do you trade something when you have the uncertainty across those different prices because of these regime or structural changes?
Speaker C:So those are just some examples.
Speaker C:But you know, even when we talk about observational uncertainty is that, well if we have Powells telling us that our unemployment numbers or employment numbers were off by 60,000amonth, well how do we, how do we do do that?
Speaker C:Or even now they find that there's measurement problems with a lot of the fundamental data because people don't respond to the surveys that they're asked to respond, you know, concerning unemployment.
Speaker C:Well, if people don't answer the surveys, well then how do we know that there's not more uncertainty in those prices?
Speaker C:So, or even now what they find out is that consumer confidence we have is that if you break it up between Democrats and Republicans, you get very different views in terms of, you know, the survey results based on politics or another example would be, is that if you look at expectations in five year, five year forward prices, it looks like they're fairly well anchored at around two and a half percent.
Speaker C:If you look at consumer surveys, it shows that they're all over the map with people thinking that inflation is much more rampant.
Speaker C:Those expectations are unanchored and that has a big impact on consumer behavior in a way that you wouldn't think.
Speaker C:So there's a lot more uncertainty going on in many different types.
Speaker B:Good stuff.
Speaker B:Just one topic I wanted to get to before we get to wrap up and it's certainly something I was talking to Niels about last week and it's been very topical.
Speaker B:It's the total portfolio approach.
Speaker B:Obviously since Calper has announced they were moving to a total portfolio approach, it's definitely been in the headlines in the investment world to a greater extent.
Speaker B:So how do you link the TPA with other approaches to asset allocation or even simple benchmarks like 60 40?
Speaker C:I'm still trying to figure that out.
Speaker C:And then for those listeners who may not be familiar with this is that they're starting to do in the consulting world, a number of firms, I think that the new head of at CalPERS came from New Zealand, was a believer in total portfolio approach.
Speaker C:And so we'll sort of say a traditional approach that you would have if you're a pension and an endowment is, is that you try to, you set up, you know, sort of a, a diversified portfolio across different assets.
Speaker C:You pick, you know, sort of what you think that the weights you should have in stocks, bonds, alternatives, maybe real estates, you know, other types of alternatives.
Speaker C:And then what you do is you have your, the staff actually trying to hit that model portfolio which is supposed to be diversified across all assets.
Speaker C:And the total portfolio approach says that, well, you need to be a little bit more nimble, you need to not be constrained by, you know, a sort of fixed weighting strategy, but you allow for more of adjustments in the assets you hold to reach some overall goal of know, the return or controlled volatility.
Speaker C:And so a total portfolio approach would be, is that allow for flexibility to reach longer term goals.
Speaker C:Now I don't know if there's a single definition with that, but I think that that's one way to, to pick that.
Speaker C: , at the simple case that the: Speaker B:And I think this is, I mean a good segue into how trend following and systematic strategies blend.
Speaker B: looking at, I think it was a: Speaker B:If you added a, I think it was a 30% overlay to the SOC gen trend index, you achieve a 4% tracking error, which is what CalPERS are trying to achieve with their TPA approach.
Speaker B:So it's a very quick and easy way to move a static portfolio into something that does automatically respond to market conditions.
Speaker B:Obviously trend following achieves a lot of what TPA is trying to do already.
Speaker B:I mean if you think about a trend following program, you know, it's already deciding should we go long crude or heating oil or a combination.
Speaker B:And also looking at the energy complex relative to the metals complex.
Speaker B:So these are the kinds of issues where strategic asset allocation came short because in strategic asset allocation they had allocations to everything.
Speaker B:Now they want to try and weigh where are the strongest, where are the best risky just returns.
Speaker B:But as I say, isn't that what trend following quant strategies already do?
Speaker C:I think you're absolutely right in the sense is that there are things that we could do in terms of overlay, in terms of being nimble and adjusting which occurs in trend following that could improve portfolio performance.
Speaker C:Whether the TPA approach I think still needs to have more definitive definitions and make distinctions between strategic asset allocation.
Speaker C:But that being said, as I think the idea of being able to say like let's adjust our portfolio based on what might be the market conditions, maybe an improvement and then fixating on set weights when those weights, you know, should respond to changes in volatility and correlation covariance.
Speaker B:Absolutely.
Speaker B:I mean one of the interesting things about tpa, they still have a reference portfolio, effectively a benchmark, which I think in the case of CalPERS is 70 30.
Speaker B:It does leave open the question where does that come from?
Speaker B:Why is that the appropriate benchmark?
Speaker B:I mean they're not, they have tracking their flexibility from that.
Speaker B: But yeah, why it's: Speaker B:I guess it comes from some consultants somewhere.
Speaker B:But any thoughts on that?
Speaker C:Well, that's the.
Speaker C:I get to use the word primal again.
Speaker C:So we always said prices are primal.
Speaker C:But we'll sort of say, you know, diversification is primal to portfolio construction and to stock start with you might sort of say total portfolio approach is a, a corollary or a variation.
Speaker C:But you need to start with a strategic asset allocation somewhere.
Speaker C:And, and yes.
Speaker C:And then you sort of say how do I adapt or adjust to changes and should I be more adaptive to my strategic asset allocation?
Speaker C:And the answer is yes.
Speaker C:If that's total portfolio approach then and then I can be comfortable with that.
Speaker C:I think that we just need to sort of better define what where we're starting from and what, what this process of TPA is.
Speaker B:Yeah, for sure.
Speaker B:No, I mean, I think there is a lot of debate in markets.
Speaker B:Is TPA genuinely something different or is it just a new label or maybe a combination of the two?
Speaker B:But I think that's something that, that we may be talking about for a bit longer to come.
Speaker B:But we've just run over the hour a little bit, so I think that's a natural point to wrap up.
Speaker B:Nils will be back next week, back at the helm, and we'll be recording our Christmas specials soon as well, so keep an eye out for those.
Speaker B:But from all of us here at Top Traders Unplugged, thanks for tuning in and we'll be back again soon with you and more content.
Speaker A:Thanks for listening to the Systematic Investor podcast series.
Speaker A:If you enjoy this series, go on over to itunes and leave an honest rating and review.
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Speaker A:If you have questions about systematic investing, send us an email with the word question in the subject line to infooptradersunplugged.com and we'll try to get it on the show.
Speaker A: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.
Speaker A: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.
Speaker A:Thanks for spending some of your valuable time with us and we'll see you on the next episode of the Systematic Investor.
