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- [00:00]
Brandon Mitchell
Meta's open source AI available to all, not just the few. Here's Brandon Mitchell, CEO of Rightsy.
- [00:06]
Marco Kolanovich
We use Llama Meta's free open source AI model to build an AI tool that helps people get their dream job.
- [00:12]
Express Employment Professionals
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- [00:45]
Brandon Mitchell
Bloomberg Audio Studios Podcasts Radio News.
- [01:01]
Tracy Alloway
Hello, and welcome to another episode of the Odd Thoughts podcast. I'm Tracy Alloway.
- [01:06]
Joe Weisenthal
And I'm Joe Weisenthal.
- [01:07]
Tracy Alloway
Joe, in your history of being a financial journalist, what are you like, most proud of in terms of coining phrases? Oh, I gave you a hint just then. Cause I assume it's mint the coin.
- [01:20]
Joe Weisenthal
Yeah. Oh, good one. Yes, sure. Mint the coin. That's right.
- [01:23]
Marco Kolanovich
Okay, thank you.
- [01:24]
Joe Weisenthal
Yes.
- [01:25]
Tracy Alloway
Uh, so I have a few. I have China's great ball of money.
- [01:29]
Joe Weisenthal
I like how you're like, what are you most proud of? And this is going to be my saying, it's what I'm proud of. But keep going, keep going.
- [01:35]
Tracy Alloway
Thank you. You called me out Europe's sovereign bank loop, although no one believes that I invented that one. And flows before pros, which has come up quite a bit on this podcast. So the idea that, you know, when valuations are extremely high and everyone's buying everything no matter what the price, that it's kind of momentum that matters more than fundamentals. Today, I'm very happy to say we are going to be speaking to a pro who knows flows.
- [02:03]
Joe Weisenthal
How's that? Extremely well done, Tracy.
- [02:06]
Tracy Alloway
Thank you.
- [02:07]
Joe Weisenthal
Excellent setup. Of course, I appreciate all of the Tracy neologisms. Man, what a time in the market to be talking about flows, to be talking about momentum, et cetera. I feel like I, you know, it's always chaotic, it's always uncertain. You'll never get an answer. But, man, things feel really noisy right now.
- [02:26]
Tracy Alloway
They feel super noisy. So we are recording this on January 30th. It is a week that has seen a very sharp sell off in tech stocks thanks to anxiety over deep seat coming out of China. We're going to talk about that and more generally, we're just going to talk about what's going on in the market right now, how investors might be handling it and how the market structure might have changed over the years. And as I said, I'm very excited because we do have the perfect guest, the pro who knows his flows. He has a lot of nicknames actually, Gandalf being one of them as well. Actually I didn't realize one of our colleagues at Bloomberg kind of coined that name for him. But of course we are speaking with Marco Kalinovic. He is JP Morgan's former chief global market strategist and co head of global research. And now he's with us to talk about the market. And Marco, thank you so much for coming on Odd Lots.
- [03:22]
Marco Kolanovich
Thank you so much for having me.
- [03:24]
Tracy Alloway
I'm very excited. I know I've said that three times now, but I guess we should start with the recent sell off like the Deep Seq Deep stock sell off. There are all these superlatives that you can use to describe Monday's action. Like the biggest single stock plunge in history in the form of Nvidia and like eight of the top 10 biggest one day drops in the S&P 500, et cetera, et cetera. And actually as we're recording this on January 30th, Microsoft is down 6% after earnings. So maybe the tech sell off isn't over yet. But one of the interesting things about this week is there hasn't really been broad contagion. So most stocks in The S&P 500 were kind of like meh, we don't care. When would you expect some of the anxiety over Deep Seq to maybe start having a bigger impact on the broader market?
- [04:17]
Marco Kolanovich
So as you said, there was not much contagion. And if you look at the different stocks in S and P, many of them were actually up and many even in the tech sectors sector were up. If you look for instance Facebook yesterday or today or a bunch of other names that sort of were perceived that they might be sort of benefiting from the sort of open architecture type of things that can come at a cheaper price and can be still implemented in their business model when it comes to AI models. So it was fairly contained. I'm a little bit surprised just because there were like three or four names that really got hammered and that can only be explained with not just with the panic, but some of the sort of forced selling maybe coming from options. If you're selling Nvidia puts for the past few years you could make a good living out of it, but then you'll have a day like we saw this weekend and basically you might get forced out of these positions and maybe have a catastrophic loss. So it was fairly limited. I'm a little bit surprised just because we didn't really have a meaningful sell off since last summer sort of at the back of bank of Japan. So I do think we will see one. Perhaps it's a little bit too early in the year. There's still quite a bit of an optimism post election. There's a little bit of seasonality in January. People put money to work, they get paid, they allocate the capital. So maybe it's a little bit too early. I was somewhat inclined to see that we will see a bit more at the back of it. It's perhaps not over. We still have a few important earnings to come. So remains to be seen what happens maybe another week of earnings, whether there is any sort of follow through. But I do think that it's going to be some investors will burn clearly and a little bit of a tarnish on the sort of this thesis that some of these stocks like Nvidia just go up every day. You can't lose. So I think people will think twice if something can drop like 20% in a day. You got to also think of it what it does to your risk.
- [06:14]
Joe Weisenthal
Well so Tracy asked about contagion and anxiety spreading across the market but I guess I would flip the question which is as I've said before on the podcast, I'm a boring index investor. So like I look at a random American company that is like General Electric, it's doing fine. I'm not very exposed to General Electric because they're a small part of the index. I am very exposed to Nvidia and Microsoft and so forth. We did a recent episode about market concentration but I'm sort of like curious your take on this fact that like so many of these flows they go into broad market indexes. But we're really all very exposed to a few concentrated market bets.
- [06:57]
Marco Kolanovich
Yeah. So the concentration is the highest, you know, sort of 60s or 70s. So we're looking at 50 years half of the century history. And concentration is, is. Is sort of at the highest point. It's been a while for staying there this level like maybe past past year. So it's a weird market. You know this concentration came for two, two reasons. You know, one is clearly thematic investing in technology. Then you also have investing in large company. You have a theme of momentum sort of that is basically self fulfilling. You know, more something goes up, more money it attracts becomes bigger than index. You know all the passive flows into it. So there's a technical aspect, there's thematic aspect, there is even geopolitical aspect. A lot of money went outside of the other parts of the world. Europe is doing worse when it comes to sort of economy. China has been, we've been sort of at the brink of this cold war with China. So money has left there. You know, Latam has its own share of sort of issues. So money has been also geopolitically moving. So it's a moving in the US it's moving into indices, it's moving into tech, you know. And then you end up with these, give or take 10 stocks that, that really sucked up all the older capital and valuations got, got very, very high. Now you know, tech investors, they do have a sort of their rationalization so what's going to happen in the future? This thing is just grow and grow and grow. And that's when we saw with the deep seek, we saw a little bit of a dent in that thesis. But these stocks didn't go up for the sake of, for the thesis. They went up some of these other flows. So unprecedented concentration is not gonna stay there. The big question is when will we see that rebalance? Do we need to see some cyclical downturn first to purge and to normalize some of these valuations? Because historically these PEs were never this high. I mean in 2000 they were this high. And we know how it ended. But a lot of people got burned my with some of the call, we were more negative last year, you know, and, and basically, you know, market has this tremendous momentum. So the timing is, is going to be challenge.
- [08:54]
Tracy Alloway
What does it take to I guess turn momentum at this point? Like what, what are the catalysts that actually work here? Because it does feel looking at the market so much of it is now technical or systematic in some way. There's a lot of options selling as you mentioned, lots of multi strat funds that basically, you know, just have to sell or buy to rebalance their exposure. What actually changes directions like how do you get enough to change a trend?
- [09:24]
Marco Kolanovich
So you know, so there's a technical aspect, sort of the mechanical aspect of it and there is a sort of catalyst or more fundamental angle of things, you know, so to get things to start moving or to stall, you usually do need to have some fundamental driver of it. So perhaps there is concern about economy slowing down. You know, perhaps there is a concern about something geopolitically, maybe trade war with China or some sort of blockade of Taiwan's trades or something like that, right. So first you need to have a little bit of a catalyst. But if the market is technically very strong, the catalyst is not going to change in momentum. So what that means more specifically. So when you look at the trend investors, they have a range of signals. So they can look at a one month price momentum, three month price momentum, six month price momentum, 12 month price momentum, maybe 18 months, but that's about it, you know. And there are some very short term momentum players that look intraday or on a daily basis. But most of these signals are concentrated around 12 months and 200 day moving averages. Right? So that's why when people look at the 200 day moving average, they first when I, you know, 20 years ago when someone told me, I said what is this magic? Why would this work? Right? But it's reality is that many models, you know, systematic models primarily, you know, computer driven, but also psychological investors look at these things and become self fulfilling. So you need to actually come close enough to these levels to break them. Right. So for instance, earlier this week S and P got below around 6,000 or a bit below. We were close to breaking 20 day moving average and 50 day moving average. So you can think of it as about 1 month and 3 month price momentum. So that's about a third of a signal. The big Signal is really 12 months, you know, or 200 day moving average. Right. But when you start moving things, you can actually unravel. It's like a little bit like a snowball. So I thought like if the market is going to stay below 20 and 50 days, at the end of the day you may get enough selling from CTAs or DE risking from CTAs that they may get you to another leg lower. Right? So it's basically you need to have set up that you're close enough to these triggers on the downside to move it. And again, I think this week we got very close. But there was also other flows like rotation. You saw like selling on Nvidia, but Apple and Meta went up, you know, like. So at the end NASDAQ dropped, but did not drop a lot.
- [11:51]
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- [12:16]
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- [12:49]
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- [13:50]
Tracy Alloway
Of reminds me of like structured credit notes where there's that knockout, knockout level and then you get this massive cliff risk and the whole thing kind of unwinds, right?
- [14:00]
Joe Weisenthal
You have all these rules based investors and something happens like oh the model says to sell. It is worth noting that as we are talking 10:19am Jan. 30, Nvidia is basically right at its 200 day moving average. I know this isn't the broader market, but it's a big part of the broader market. So yeah, it might as it might as well be. One thing that struck me on Monday, which I was a bit surprised about in the sell off is that even on Monday you mentioned that Meta actually closed green and they are a maker of a competitor to Deep Seq. They have their open source llama, but they're seen by the market as a consumer of AI services because they don't sell their product. They use it to do things like better ad targeting, etc. Were you surprised that even on this day in which there was this sort of exogenous shock to the market, everyone wakes up to some new thing that actually investors showed a fair amount of discrimination in terms of what they dumped.
- [15:01]
Marco Kolanovich
Yeah, so I mean that was, that was against, you know, January sentiment is still pretty positive. Economic data are strong. So people are saying, okay, this is not the beginning of economic downturn. This is isolated sort of event whereby some companies will get hit, you know, their sort of revenues will get hit.
- [15:17]
Joe Weisenthal
Yeah.
- [15:17]
Marco Kolanovich
And some will be able to do things for cheaper, you know, like so you had a salesforce I believe as well. And so, so it ended up not a macro day, but more of a rotational day. You know, there is also a so called quant factors where you know, even within technology some stocks are higher multiples, some stocks are lower multiples. You know, some stocks are more momentum, less momentum, you know, like, so there was a bit of rotation. So Apple, which was a laggard also kind of caught a bit. Although I don't think there was much fundamental stuff going on for Apple. It was probably just rotation. So market kind of held up, you know, and I was sort of at the fence whether these like technical levels, 2050 will, will get broken and will go lower or not. We didn't, you know, but I, but I do think that sort of, you know, valuation positioning and some of these technicals are a bit stretched, you know, like, so I don't have, I don't see like a huge, huge upside for the market. So maybe I'm switching the topic a little bit, but.
- [16:09]
Joe Weisenthal
No, no, that makes sense.
- [16:11]
Tracy Alloway
Can I ask you a sort of procedural question which is, you know, you were at JP Morgan for 20 years and you were in the industry even before that. How did your sort of research and forecasting process change throughout those years?
- [16:26]
Marco Kolanovich
Oh, thank you. And it did change and it's an interesting good question, you know, so, so I got my PhD in Physics in theoretical physics. So there was a lot of coding, there was a lot of modeling, there was a lot of sort of trying to understand why one thing leads to another. What is the cause, what is the concept, what's causality and what's the noise. What's statistically important, what's statistically not important. So in physics you build this type of models, you try to understand what's significant, what's not, what you can neglect which factors you have to take into account and most importantly how to simplify. The complex market is extremely complex system, as many as physical assistance. So you need to sort of move the noise on one side and drivers on other side and try to recognize those patterns. Right. So although I really never used any formula from the physics in my. Almost never really in the finance, but the way of thinking is similar. So I started Merrill lynch in derivatives, in derivatives research, where I started looking, interestingly, we are now in earnings season. So my first models were impact sort of of earnings on a stock price and what can you read from options market? So I published some papers, come up with some formulas, and we were kind of backing out. Okay, what option market is saying? And then we would go to analysts and say, hey, do you think it makes sense or doesn't make sense? Right. And then if you think that options are saying too much of a move, too little of a move, you could trade these options and stuff like that. So that was one example of, okay, how do you sort of, you know, you have a catalyst, you look at different markets, you see, are these markets aligned? You put some model together and then you find a discrepancy with the model. It's not always going to work, but if you do it for 100 stocks, maybe on average in a portfolio level, you'll, you'll be fine, you know, like, so that derivatives research and quant research. I did a lot of quant research. So you try to process the data, you try to look at the measures, and at that time, like 20, 25 years ago, it was beginning really of trading of VIX, of volatility, swaps, of correlation, of dispersion, you know, like, so you kind of try to see, okay, you look at the vix, you look at the market volatility. What's driving market volatility? Well, people say, well, it's a panic or it's not. But let's be more quantitative. You know, you can see how correlated stocks are, what individual volatility of each stock is, you know, which part is due to the macro factor, the market, what's idiosyncratic. So you can kind of break this down. Then you can look at the sector, what's correlation between sector, what's correlation within sector. So you can kind of quantify these things and analyze and get some insight. You know, like 2008, for instance, we look at 2007, 2008. I look at how the hedging of options impacts the market. So you basically need to look at how many options are out there in index. Let's say you try to assess what's the positioning from the flows from the sort of knowing of industry hedging flows. And then you see okay, what are the hedging requirements at the end of the day and 2008 and then 2011 and low hanging fruit you could see sometimes these flows would be bigger than market can absorb, you know and, and, and they would all go same way from lever ETFs from options, you know. So you see like okay, there's like $20 billion to sell and market can't absorb that. So you know market towards last 10 minutes will drop. And that's, you mentioned Soro Gandav. That's where, where, where some of these things because people, you know, if you look from the outside you say oh how, how, how can he get that right? You know and, and but it is really understanding a bit of technicalities which is flows, option convexities, liquidity and how they, how they sort of interfere. But you know, after 2015, 16 people figure it out, you know and then people put it in their models. They create like a structured product.
- [19:56]
Tracy Alloway
After 2018 everyone sort of woke up to the Vix especially, right?
- [20:01]
Marco Kolanovich
Oh yeah, 2000, February 2008 Vomageddon. Yeah. And you know, stuff like that. So you kind of analyze causes and consequences in the market. Something that is new that's not been yet look at, you know and I have focused on things that were new in the market like products, options, futures, CTAs, those type of things.
- [20:21]
Joe Weisenthal
It's not particularly technical. But another thing that seems to be true about the market right now is at least maybe up until a week ago, just an incredible amount of optimism in any sort of measure. So if you ask there's consumer measures. Do you think stocks are going to be higher in a year from now? Very high levels. If you look at things like the bank of America sell side analyst sentiment, very close to euphoric levels. If you look at fund cash levels, extremely low right now, everyone is overweight. Long tech, how do you ingest this information? Because on the one hand you say oh everyone's all in. This is negative. On the other hand, people have been very optimistic for a while. How should we as consumers of this information think about what it says about the fragility of the bull market.
- [21:10]
Marco Kolanovich
So you know, clearly in the markets things are mean reverting, you know, like so when things reach some very high levels, you know, eventually they go on a long time. Yeah, exactly. So there is this mean reversion, but there's also trend. Right. You know, like so you know, figuring out the timing of that is hard. Right. You know, like I mean if there is A sort of a limited set of drivers, like in some of these technical markets, you know. So for instance, CTAs, you know, you know, once when the, all the levels are positive, all the signals are positive and then volatility drops a little bit. You know, they're maxed out so you know, they're not going to buy more. Right. You know, like, and so you can, you. That's a, that's a self contained, isolated system where you can say, okay, optimism is too high. So there's the only downside. Right. With the entirety of market. Right. You know, with, you know, you have a crypto, you have a fiscal measures, you have like monetary stimulus, you have a sentiment shift. It's hard to handicap all of those, you know, so it's hard to say that for all of the investors to be able to know exactly when this thing is going to stall. Right, sure. And there are developments that is hard. Like this whole AI. And I see. I wrote a book in 2017 about AI with my colleague Rajesh. 2018. So we were early on on AI and six years ago. Right. Nobody was talking really about it at that time. So it's not that I don't understand it, but I'm a little bit cynical about it now. I think it's too hyped up. Right. But it's hard to assess how long people will be excited about it. Right. You know, and yeah, so. And then you have a changes, you have political changes that can bring deregulation, that can be change in tax regimes. You have like a wild card. So it's hard. Your question. I started like there is a reversion always, but where you're going to pick it can be very frustrating and very sort of, you can be wrong for a long time.
- [22:54]
Tracy Alloway
Wait, can I just press you on that point about AI? Because I think, I think the difficulty that investors are having is AI has a great story right now and there's this idea out there that it's this revolutionary technology that's going to change the world. Joe keeps referring to it as inventing God when it comes to AGI, at least. And at the same time, there is also a feeling that people are maybe getting a little too optimistic about it. There's too much hype in the market. You've started seeing companies that, you know, just put out a press release going, oh, we're looking into AI and their stock price goes up. How should investors handle their exposure to AI? Like, how do you actually play it at this point in time, given that you were early to the topic.
- [23:40]
Joe Weisenthal
And now cynical.
- [23:41]
Marco Kolanovich
You know, I look at it from theoretical side. I look at it more how to apply it sort of in finance, in quantitative trading, you know, how to use large language model to assess the sentiment, changes in sentiment and those type of things. Right. So you know how to read quickly things and summarize them and derive some signals out of it. So there is obviously bigger question of AI, which you said, it's kind of philosophical questions like are we going to be replaced? At which point what's going to be role of human once when we can kind of break down our way of thinking and effectively train it and replace it. So there are a whole host of other questions. So I'm not skeptical that this is going to be hugely important. And it is hugely important. It's not very, very different of what people have been doing, you know, five years ago or 10 years ago or 20 years ago. Obviously big progress in computing power, big progress in the models as well, you know, like, so it's. But I see it like more as an evolution, you know, than something that changed with chat GDP in 2023, like two years ago as a kind of like a step function. I see it as an evolution, always important, right? Like 10 years ago when we use our smartphone to take a picture, like, you know, camera would recognize the face, it would zoom into face, it would, would kind of do the proper focus and stuff like that. So that's also, you know, that's also AI and things are advancing, right? And we'll keep on advancing. Now question is going to be winners, losers, how to monetize, you know, does, does that suddenly re rates all of equity market multiple, you know, like suddenly, okay, people are not going to work. These companies go to all the work. So we're just going to value them. Like who am I to say that? And also who am I to say that that's wrong as well, you know, but there's a lot of speculation and a trust. You know, people often tell me, well, imagine just how my way to search Internet has changed, you know, like, okay, like we were searching Internet for 25 years the same way I used to use like a Netscape like 25 years ago, right? And the same thing, you type in a bar and you find something. So for Christ's sake, of course it's going to change, of course at some point it's going to be, we're going to tell something to computer. Computer will have its own ways of parsing and finding what's relevant and giving us back information. So I'm not as excited about that change. I think it's a way overdue change, but there is a lot of optimism now.
- [25:55]
Joe Weisenthal
Well, I was wondering because I was looking at your LinkedIn and you mentioned you have a PhD in physics graduating from NYU in 2003. Theoretical high energy physics, cosmology, string theory and finance. I guess a two part question. A, do you think there's a world in which if you graduated today, you would have gone into AI instead of going into finance? Because I imagine they would have hired you at those skills. But B, like when you think about, and Tracy mentioned, you know, like the true AGI, do you think that the current AI research is on a path to that sort of AGI inventing God that a lot of the proponents believe?
- [26:35]
Marco Kolanovich
So, you know, I think eventually it will get there in a sense that it will sort of address some very important, you know, questions which are kind of deeply what every person fears or wonders or sort of seeks, you know, kind of meaning of our lives, like, you know, you know, future after we die and stuff like that. So they're definitely interesting, interesting things there that can be done. I mean, people are doing with these like assistants, right? Like you train. And I believe really this AI will have to be a lot more personalized, you know, like so you will train it really on your life experience, you know, like so if AI can see every image I saw, if it can read every email, you know, I believe AI will be able to tell me when did I make a mistake? When should I do something different? You know, did you overreact in this life situation? Did you not? Right? And going further, right? Like that will stay and my kids can, after I pass away, they can say, hey, what would that say in this situation, right? Maybe I'll be able to in some way talk to them, right? So you blur all these things which were sort of not blurred in the past, right? So you'll start having these very, very interesting developments. But I would kind of not look at them from the sort of P and L perspective, earnings perspective. There's also going to be a lot of issues as we have already now. I mean, sometimes AI can give you wrong answers, sometimes it can be used to do bad things, to impersonate, to deceive, to manipulate. So there's going to be a lot of, lot of interesting, I would say philosophical issues, you know, technological issues and investing issues. But I just don't think it's going to be as simple as like 7 companies are going to have PE of 50 and everyone else will have PE of 10 and it's going to persist that way. Yeah, I don't think it's going to be like that in finance at least. Yeah.
- [28:14]
Tracy Alloway
The other thing I wanted to ask you is, you know you left JP Morgan in July and then pretty much a month later we had a very sharp sell off. When you look back at that particular sell off, you know, we never got to hear from you your thoughts on that on that particular week in markets. What did you actually see and observe there? Because there are still differing opinions out there about what the proximate catalyst was for some of those moves and what was exacerbated.
- [28:43]
Marco Kolanovich
No. So the catalyst was definitely moving rates related to Japan and the currency. Right. That was a sort of catalyst. But you always have like a spark and a bucket of fuel. Right. And the bucket of fuel as stretched CTAs stretched volume targeters, systematic investors. Too much optimism and then you start basically hitting the stops across these strategies, right? CTAs hit their sell signals. Volume target is Vix goes up, volume goes up. They need to sell. If you were selling puts on AI names you suddenly need to kind of close. So VIX was very. VIX behaved most phenomenal. So it was a lot of Vol. Short volume covering as well. But again I think what was missing for this to be the turn in the cycle was I guess gdp employment still fine, right. Still hope that Fed is going to cut.
- [29:32]
Tracy Alloway
Right?
- [29:33]
Marco Kolanovich
So it didn't. There was a little bit of conflagration but didn't kind of burn everything down. Right. So it was a little bit of satisfaction but didn't last too long.
- [29:42]
Joe Weisenthal
It is pretty markable because even with we got a little sell off but it's a very minor sell off. We're basically the stock market is more or less at all time highs. This is despite a pretty big repricing of the expectation of the short end of the curve where people were expecting deep cuts to continue through last year and to this year. We might not get any cut this year and yet still the market is close to all time highs. It must be nice on some level to be out of the game of having to come up with an end of your price target. Because that sounds like a job I would never want to take. But I also wonder, you know, do you wake up in the morning and.
- [30:17]
Tracy Alloway
Still like yearn to give end of year target?
- [30:19]
Joe Weisenthal
Like talk to us about, you know what you have a market outlook for right now. Like give us some, give us what's on your mind.
- [30:26]
Marco Kolanovich
Sure, sure. Like so, so look, it's nice once in a while that you can be somewhere away and not look at the Fed parse every single word. Although I did it yesterday, but a few months ago I didn't. So it's nice to make a break or maybe it's necessary. Ultimately markets are a little bit of a sort of compulsion thing of compulsion when you feel like you need to understand what's going on in the world. So I think becomes part of your DNA if you do it for a long time. So I do always think and, and I do have an outlook.
- [30:56]
Joe Weisenthal
Give us a.
- [30:58]
Marco Kolanovich
So, you know, you know, on a sell side you kind of need to put a price target. And I, and I think it's a kind of poor way to summarize everything into one number. It's basically almost you're telling, you're trying to forecast probabilities in the world, you know, because world, real world actually works in terms of physics. Deep, deeply works in terms of probabilities, not just superficially, you know, in a quantum physics. So you need to sort of have a sort of that hyperbolistic view and you're forced to have one view like 100 or nothing. Right. So it gets oversimplified. I think media, you know, and not referring to you, but media does a bad job. They say, oh, what's your price target? They just want to talk about that and they say, oh, you're right, you're wrong. Yeah. So no, so I would say like, you know, if I can move away from price starting, I do think we'll go back down in the 5000s this year. Sometimes I think at that point in time we will, we will see whether the cycle is still strong or it's not. I think we need to see the whole new political climate, whether it will lead to turmoil. And I believe more likely than not it will. So those things I think will get us lower right. At that time. Whether it becomes an end of a cycle and you go much lower into 4,000, I don't know. I think there's some probability of that. And then conversely on the upside is everything goes. If really this is what they call it, golden age, golden age of America, you know, then market will stay in 6,000. It can go a bit higher. I just see, I'm hard pressed to see it going much, much higher. Right. Because valuations are there, positioning is already there. As you said, Fed is not cutting right. So it's a little bit of a chicken and egg. I mean I have been scratching my head like at These level of rates which I do think that are restrictive rates for now more than two years with the commercial real estate here and there we saw a few hiccups, you know, like but you know, I do think that is sort of under the hood of economy. Some damage is being sort of built up and down. So I don't think like market really you know, going to 7,000 or you know, 6,800 or something like that. So I would say maybe it can go 65, stay range bound, you know, like so I would sort of formulate the view in terms of okay, you perhaps want to sell upside, give yourself a little bit of room for some more excitement first few years of the, of the first few months of the year but then also be ready to assess once when you go into, you know, let's say 5500 or 5700 to assess is the cycle potentially ending, you know, or that's going to be buying opportunity. And I wouldn't want to sort of say hey like it's going to first there 6100, then it's going to pull to 55 and then you buy with both hands at 55 and like that will be too predictive, you know. But I think some variation of that path will be whereby sort of the depth of a pullback will depends on trade war, China, domestic political situation rates and like one off things like we had on Monday.
- [34:04]
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- [36:03]
Tracy Alloway
Mentioned domestic politics, because one of the other weird things about this week when we had the deep seat sell off was everyone was focused on that and tech stocks went down as we mentioned. But then on Tuesday everything started rebounding. Even though we had headlines lines coming out of the White House about cutting what amounted to a pretty big chunk of federal spending, the entire market seemed to look through that, which is kind of ironic because one of the things we've heard for the past four years or so is this idea that, you know, deficit spending is driving the entire economy and stuff like that. I feel like political risk is one of those things that investors really struggle to to price in because there's so much uncertainty. A lot of it seems very binary. How do you deal with that?
- [36:53]
Marco Kolanovich
So you need to sort of put some scenarios, you know, what can happen in terms of taxes, regulation, tariffs, trade wars, geopolitical conflict, and then see how can they impact specific stocks and industries, countries and maybe overall market sentiment and maybe put some scenarios that's a kind of a blueprint and market never goes by that blueprint, but at least gives you some framework to try to understand if it doesn't go by your sort of assessment, what have you missed and what else you need to take into account. But you put some blueprint sort of what can happen. So you know, I think you pointed very well. He was talking about Nvidia, Taiwan export, sort of I said like so those type of things, right? So market, that's then market has its minds of its own, which is tied to sentiment, you know, and it's tied to momentum. You know, most people think momentum, you know, they don't calculate by the thing. They just Feel good about market, they see good news about market, they, their taxi driver or friend or family feels good about investing, right? And they choose then to ignore. You know, like so on Monday I was watching CNBC and every single guest was saying, oh, take your shopping list out, take your shopping list out, take your. Buy this, buy this, buy this. Right? So you know, it creates a little bit of a sentiment. You know, it creates a sentiment and people say, okay, you know, I'll make a punt, I'll buy if it's 20% down, maybe next day it's going to. That cat bounced them. So people buy, right? Some people rotate, say okay, like I'm getting rid of Nvidia. But look, Apple has been, you know, underperforming so maybe I put my money there. So, so the, the sentiment overall was still pretty strong. There's this aura of momentum, psychological momentum that is harder to break. You know, you do need to have a few, few punches for it to break for people to sort of give up.
- [38:30]
Tracy Alloway
So one of the other things I want to ask you, you know, just again looking back at the sort of long term changes in, in the market and we, we touched on this earlier, but we've just seen an absolute types of options trading and volatility trading. And now you even have TikTok influencers who are like pitching options investing as passive income. Like, oh, don't buy a U.S. treasury bond, do an options bet. Which is kind of crazy. How has that impacted the market? And how have you seen people, you know, trying to handle some of that new I, I guess dynamic that's been introduced?
- [39:07]
Marco Kolanovich
So that's a very good question. And it started sort of around the COVID time people were locked in. They got these stimulus checks, they started trading, right? Proliferation of these online brokers, no commission fees, options being traded as a sort of very short and shorter maturities, right? You know, options used to be sort of leaps and then maybe like a monthly options, you know, second and third, second and third month quarterly options moved to weeklies and dailies and then in the single names. So you had sort of people locked, they got money and they got these instruments, these extremely powerful instruments with leverage about 100 times leverage. So you suddenly can make a bets of millions of dollars even if you have 10,000 or $5,000 to invest. So that changed a lot. And for most of these people actually it worked, right? Because since 2020 we had that pullback when the Fed started hiking. But for most of it it worked. So speculative trading activity, especially on the long side, it worked then you also had in parallel sort of crypto markets growing. Right. So if you think of it, a few trillions of dollars of wealth was created there with probably some of these similar type of investors and similar type of people. So it changed so there is less leverage in terms of borrowing money when interest rates, but more, a lot more leverage in terms of option trading activity. You know. So as you said, I'm always also surprised. You go on, on some of these social media and then you see all kind of strategies that can't lose money, that are making like tens of thousands every day. You just need to follow him and, and it becomes really kind of bizarre. You have like these people who are at the same time performer or like women who are like, you know, in the like underwear suggesting how to trade.
- [40:53]
Tracy Alloway
Options buy zero day.
- [40:55]
Joe Weisenthal
They're all big fans of mine. They follow me on Twitter and then they DM me. I'm very flexible.
- [41:00]
Marco Kolanovich
So it's kind of crazy. And we try to handicap it by looking at flows from Robinhood, see which names are being sort of bought, which names are being sold, try to see where the retail may be forced out or something like that. So we did some quantity of work. We did a lot of the sort of language, large language models sentiment wise like from Twitter and those type of other social medias which we could get permission to do. So we're trying to incorporate it, but I think overall it's hard to 100% handicap it. But for sure it added leverage to the market, added speculative element to the market. And at some point it's not going to probably end up well, right? At some point, but it's hard to say when exactly.
- [41:42]
Tracy Alloway
Right. It's again one of those things that can go on for longer than you think. Since you mentioned getting data from Robinhood just then, this is the other thing I always wanted to ask an equity derivative strategist because you alluded to this earlier. Lot of, I guess misunderstanding or lack of understanding of what an equity derivative strategist actually does and exactly what data they're looking at in order to make some of their conclusions. Can you maybe give us like a quick 101 in where your data comes from, how much of it is from official sources, like I don't know, an EPFR or someone like that versus like color that you're getting from the market?
- [42:23]
Joe Weisenthal
Good question.
- [42:24]
Marco Kolanovich
Yeah. No, so there are all kind of data, so there are price and volume data, all kind of technical data that can be derived from those type of things, which can also be a Different time horizons. They can be daily. Mostly they are daily, right? But increasingly you also want to look at the intraday data, intraday correlations, intraday momentum volumes, large blocks that are traded. So there is also higher frequency one day, but most of it is daily, I would say. And that there are longer term data when you look at the sort of, you know, some like a monthly statistics on positioning or up to the sort of filings, you know, 13F filings like holdings and stuff like that, you know, like so. So different sort of frequencies of positioning, volume data, price data. Then so directly market observable data like open interest, you know, options, volume and options, those type of things, right. Then you have sort of fundamental data, you know, and fundamental data, you have fundamental data for stocks, you know, which are related to earnings. But increasingly you have a data which are derived from non traditional sources, so called big data that can be sort of sentiment measures, but quantitatively derived measures, objective, not sort of guesswork to some very specific niche data like satellite, all kind of like data that we didn't.
- [43:40]
Tracy Alloway
Have, how many cars are parked out.
- [43:42]
Marco Kolanovich
In shops, parking lots and in front of Walmart and those type of things, right? So you have these stock specific data, earnings derived, news derived, sentiment derived, and then also non traditional ones, you know, and then you have like macro data, you know, typically lower frequencies, but increasingly also with some of these alternative data sets, big data sets you can try to figure out like you know, shipping and again sort of storage and oil tank tanks, how full they are and stuff like that. So it's a whole host of data, you know, like as a quant and there are this person you probably focus most on the market data, you know, so open interest, price volumes and all stuff that is derived from that. But you also want to supplement that with all these other data. And then some of the data sets you derive it on your own. So for instance, got my imbalance in S and P options put minus call. So I was running that for 15, 20 years and first people tell me what's that? You cannot know what's. But then now everybody has it actually. And same thing with a CTA stuff and Volt targeting exposure. I was getting so much sort of critique in 2011, 12, 13, you know, now everybody has it, you know, kind of CTA positioning percentiles. So you can derive some on your own based on your understanding of the markets.
- [44:53]
Joe Weisenthal
All right, I just have one take and I bring it up a lot and I sort of feel like the Kool Aid man. It's like every conversation. I have to jump through the wall and interject this. But you know, there's all sorts of like quant techniques and there's the definition of quant and changes over time and obviously there's an incredible amount of data that we can use now. And then there's sort of like old fashioned quant where you're just like we're going to buy that I sort of associate with like AQR from years ago or like we're going to buy the cheap stocks that are exhibiting momentum, right. And we're going to short the expensive stocks that are declining momentum. And you know, why doesn't this work anymore? And all these sort of hand wringing in the traditional quant industry, why has, why haven't things been reverted? How much is the fact that like so many of these sort of ideas about how the market should work have been broken by the simple fact that a handful of American companies that are very big exhibit year over year earnings growth that are truly remarkable. And this is a fact not about the market world, but about the real world that for whatever reason these big tech companies just keep getting bigger despite their size.
- [46:04]
Tracy Alloway
Wait, Joe, you have to end that by saying the Kool Aid man catchphrase.
- [46:08]
Joe Weisenthal
What did he say?
- [46:09]
Tracy Alloway
Oh yeah, oh yeah.
- [46:11]
Joe Weisenthal
As long as the Metas and the Googles and the Nvidia's and maybe the Apples of the world just keep growing earnings like crazy every year, how much does that bust any sort of notion of mean reversion in market?
- [46:22]
Marco Kolanovich
So I think it busts the notion of a value as a factor. But value is a factor has been struggling for a long time. So sort of probably since you know, decline in interest rates post 2008, a lot of these, you know, and growth of indexation, right. Growth of taxation kind of sparked the momentum and changed the structure of the market. So some of these quants models or quant factors work less and less. You know, there is also another aspect which is, you know once when you put money to work in these strategies, you kind of squeeze out the alpha, you know, and these things are fully priced in, so they stop working. So sort of growth of, of quant funds, traditional quant funds, you have quant ETFs, you have like broker dealers doing quant strategies, kind of squeezes out returns. Right. You know, on your question, sort of like these big companies that keep on delivering. That's also a very good point. You know, quant strategies are designed for sort of steady state situation when kind of things are fluctuating around something which is in a steady state. And we had sort of, you know, big sort of big changes in the world, right? In technology.
- [47:27]
Joe Weisenthal
Yeah.
- [47:27]
Marco Kolanovich
And also geopolitically sort of, you know, capital move to us and it move into this sectors of innovation, right. You know, and now, so you may, so you may constantly be out of equilibrium, right. You know, where some of these mean reversion or quant strategies would work. Certain type of quant strategies have value based strategies, right. Question is how long, you know, how long can going back to the concentration, right? How long can it go? The my question becomes like, let's say if you have like a social media company, like a meta, right? I mean once when they have all the users in the world, I mean like, you know, they can go much further, right? They can go to the.
- [48:04]
Tracy Alloway
Right. There's limits, there's limits, you know, by.
- [48:06]
Marco Kolanovich
Number start creating fake AI or go like to Mars. Like there's no one there. So, so there's some, some limitations, right? Like, and then there's some sort of also historical when you look at the weight of stocks in an index, right? So, so you take Nvidia percentage rate in S and P and you know, you run back history and you see that this basically never happened. And even if it happens, it never lasts forever. Right. But to your point, it can last, you know, one or two or three years is enough to, to ruin a lot of investment strategies. Yeah.
- [48:32]
Tracy Alloway
All right, Marco Kinovich, thank you so much for coming on Odd lots. A real treat for both of us.
- [48:37]
Joe Weisenthal
Yeah, that was great. Thank you so much.
- [48:39]
Marco Kolanovich
Thank you so much.
- [48:53]
Tracy Alloway
Joe. That was really fun. I'm so glad I finally got to ask him a bunch of questions about just being an equity derivative strategist. I had on my mind for a while.
- [49:02]
Joe Weisenthal
I love those questions so much because they're the sort of like dark fiber or the dark matter of how this industry actually works. But everyone just abstracts over them. It's like, oh, you look at the data and then you do this thing.
- [49:15]
Tracy Alloway
But like, right, like what data, what.
- [49:17]
Joe Weisenthal
Are you looking for actually come from? Like I could listen forever to someone and we should do more of that, just like talk about these aspects like paying for data and data costs and all that stuff. I really like Marco. It's a nice conversation.
- [49:31]
Tracy Alloway
The one thing I would say is, you know, you asked that question about like, well, The S&P 500 overall didn't do too bad on Monday. And like, you know, if I'm an index investor, I have exposure to ge and so that's Good. Because I don't have to worry about AI, But I think the question really is, like, how much is GE exposed to AI in very indirect ways?
- [49:51]
Joe Weisenthal
Yeah, that's correct. Right. And you do so. I mean, you know what? I think I saw a tweet about this, so I'm just going to say it and it may not even be true, but if it's not true, it's truthy. Someone tweeted that apparently there was like a Sherwin Williams earnings call and someone asked about how much paint data centers are going to need to paint their walls. I don't know if it's true, but if it. Because I just saw the tweet. But if it's not true, it doesn't really matter because it is true. Like every company is like, are you doing something that could supply. Do you sell some product that someone building an AI data center is going to need at some point? But my point about ge, though is kind of the opposite, which is like, GE did fine on that day, but I wish I had more exposure to ge. What I really have is a bunch of Nvidia and Microsoft exposure through my index fund.
- [50:42]
Tracy Alloway
Right. But you don't know how much exposure, indirect exposure you have to Microsoft through ge. This is true.
- [50:49]
Joe Weisenthal
This is true.
- [50:50]
Tracy Alloway
Skanda wrote that excellent column in the Odd Lots newsletter about how more and more of the economy is being driven by AI. We actually saw on. On Monday the Treasury market move a little bit.
- [51:01]
Joe Weisenthal
Yeah, yeah.
- [51:01]
Tracy Alloway
Which, you know, okay, Treasuries will go up when there's a market sell off. But a lot of people were saying, well, this impact growth expectations as well. And so that's why you're getting this reaction.
- [51:13]
Joe Weisenthal
Totally. I think the degree. I mean, especially you go back and Trump announced the half a trillion dollar Stargate project. And I don't know what's really going to become of that, but I believe the data centers and AI specifically through the data center channel is a meaningful important. Is a growing important part of the real economy right now. And if suddenly they're like, you know what? This is a dead end. Or suddenly, like, we don't need this because we can get AGI so cheaply that it's just like on our laptop, that would raise some real econ concerns.
- [51:50]
Tracy Alloway
Yeah. Shall we leave it there?
- [51:51]
Joe Weisenthal
Let's leave it there.
- [51:52]
Tracy Alloway
Oh, yeah. This has been another episode of the All Thoughts podcast. I'm Tracy Alloway. You can follow me at Tracy Alloway.
- [51:59]
Joe Weisenthal
And I'm Joe Weisenthal. You can follow me at the stalwart Follow our guest Marco Kolanovich. He's at Marco in NY. Follow our producers Carmen Rodriguez, ArmanArmen, Dashiell Bennett at Dashbot and Kell Brooks at Kalebrooks. For more Odd Lots content, go to bloomberg.com oddlots where you have transcripts, a blog and a newsletter and you can chat about all of these topics 24. 7 in our Discord Discord GG oddlots.
- [52:23]
Tracy Alloway
And if you enjoy Odd Lots, if you like it when we discuss the dark dark magic of equity derivatives, then please leave us a positive review on your favorite podcast platform. And remember, if you are a Bloomberg subscriber, you can listen to all of our episodes absolutely ad free. All you need to do is find the Bloomberg Channel on Apple Podcasts and follow the instructions there. Thanks for listening.
- [53:13]
Brandon Mitchell
Join Bloomberg in Atlanta or via livestream on February 11th for the future investor finding the opportunities this 2025 event series will examine how companies are investing in their businesses to create efficiencies, innovate their products and services, and improve the customer experience. This series is proudly Sponsored by Invesco. Q. Q. Q. Register@Bloomberglive.com futureinvestoratlanta.