Big Ideas 2024 | ITK with Cathie Wood

[Music] greetings everyone this is Kathy Wood uh CIO CEO of arch invest and it's employment Friday well it is employment Friday and we're going to talk about that uh and then afterwards uh we'll I'd like to introduce you once again to our chief futurist uh Brett Winton and we'll go over some of the slides from our big Ideas we launched our or we published Big Ideas this week H and you can find it at ark-invest do.com all 163 Pages uh lots of work uh and original research uh going into a piece uh that has become very important uh to us as um sort of a staging ground for uh communicating with you and and then we'll go back into economics as usual um focusing especially on monetary policy all right so employment Friday uh the headlines uh were very strong uh non-farm payroll employment came out at 353,000 um and uh that was nearly double what was expected uh 185,000 and even more important perhaps if you believe these numbers uh is that there was an upward revision to the previous month 117,000 uh upward revision to 333,000 uh that's pretty astonishing so the the two months together December and January which are very seasonal months of course uh when you combine them uh the employment was up 686,000 that's a booming economy or is it well household employment so non-farm payroll uh it surveys corporations companies and household employment surveys households and tends to capture more small businesses uh so household employment was down 31,000 in January and the previous month December it was down 683 th000 so the combination of those two months down 714000 so which is right honestly it's uh this is a schizophrenic report um hedi put out a report today on I think they called it a ridiculous uh employment report and they noted that full-time employment over the last year the past year has gone nowhere in fact it's down a bit part-time employment is up 870,000 uh this is not this is not a strong sign out there unless everyone's going into the gig economy uh Uber Airbnb and so forth now the other controversial uh statistic that that came out with this report was average hourly earnings it was up 0.6% so 5% at an annual rate uh it had been running 0.3% or roughly 3 and a half% at an annual rate uh on a year-over-year basis it now is up up 4.5% previous month it had been up on a year-over-year basis by 4.1% so the fed's not going to like that unless they focus on the productivity numbers that have come out recently which are extremely strong and would suggest to us that many of the breakthroughs in technology especially AI are starting to impact the economy on a year-over-year basis uh the nonfarm productivity is up 2.7% so 4.5 uh minus 2.7 is uh roughly I guess one let me do the arithmetic there uh 1.8% so that's below the fed's 2% Target uh so that's very interesting another interesting statistic in this report which may have been weather related um was that the average work week dropped 610 of a of a percent the only time that uh steep a decline happens is either in bad weather or a recession and uh so we may have both in this rolling recession that we've been talking about um I'm taking this one a little more seriously because in December meaning seriously than just weather in December it also was down 0.3% so that's two consecutive months um and we're also very focused on real world data that's been coming out uh you see that UPS is laying off 12,000 people you see a lot of layoff announcements uh and you see and one of the reasons you're seeing these announcements is revenue growth for many companies has gone negative in fact in what I would call the traditional world or the old world the non-digital world um we're seeing negative Revenue growth 3M minus 4.5% % year-over-year that's volume and price down that's the equivalent of nominal GDP um UPS down 7.8% on a year over-year basis and these companies touch the world and maybe that's what's going on right now China seems to be uh in a downward spiral certainly its stock market is is looking that way and and the statistics are are disappointing perhaps the debt load associated with 20 years of buy the dip property um transactions in China um reached an untenable Point uh many many statistics out of China are are negative and Europe by some measures is in recession so maybe these mult multinationals are suffering more because of what's going on in the rest of the world um but I do think we are not isolated from the rest of the world so again lots of confusion and anyone who's been listening to in the no for a while um knows that uh I've been saying it's going to be very confusing very confusing and uh this is just one indication just one more thing before we uh before I introduce you or reintroduce you to Brett um when I first started in the business um in the late 70s I was in college um I Heard portfolio managers back then talking about the worst mistake they had made in their lives their professional lives um in the early 7s after after we went off the gold exchange standard and all hell broke loose prices started going crazy we had the Oil Embargo quadrupling of oil prices um most economic indicators were in nominal terms they didn't break out real from Price or real from inflation and uh because of that they looked at earnings exploding and they could not understand why the market was going down and they kept buying the buying the dip it was a big mistake because what was happening back then was uh inflation was the only reason earnings were going up and the market doesn't pay for uh earnings caused by inflation and so that's when we started separating inflation from real growth and we've been there ever since today we might be on the opposite side of that problem now most uh portfolio managers as they're gauging the health of the economy they look at real GDP and and inflation is just a separate uh metric that they know uh the market doesn't pay for so you know um well that's okay until you run into negative money growth caused by I mean negative Revenue growth caused by uh falling prices companies losing pricing power and uh unit volumes not being that strong so um again we're in this uh Topsy Turvy world and we think we're there because of a a a lot of BEC because of what is going on with disruptive innovation which is highly deflationary H and and is going to create a lot of of creative destruction which will also be deflationary one is good deflation deflation associated with Innovation and the other is bad deflation so um we do think uh that the price indicators the broad-based indicators like the CPI and the PPI will enter NE negative territory this year we've been talking about the bigger risk being deflation for quite some time and uh uh the companies are now starting to report uh some of them both inflation and and prices coming down and weakness in underlying economic activity uh and we always say Innovation solves problems and we think Innovation is going to solve uh one of the biggest problems that companies are going to have in the next few years and we think that's deflation uh def is going to hit margins and could hit them hard uh and we think Innovation um will uh will help corporations who embrace it aggressively especially in this new AI age so with that I'd like to uh introduce you to Brett Winton um he's been on uh in the know once before so maybe this is a reintroduction Brett is our chief futurist Brett and I have been working together since uh 2007 we worked together at our previous firm and uh and with just a short break there um uh Brett came and joined me at uh Arc invest in 2014 uh so 10 years into this Brett here we are and here you are uh to take uh our viewers into uh this techn technological explosion that we're experiencing and is part of the reason we're going to be debating about economic statistics for the next few years so uh yeah why don't we start with uh this chart yeah I think I think it's interesting to hear kind of like you talking about how choppy the macro environment is because I I think over a longer time frame actually there's you know profound reason for optimism and kind of like the technology and the and kind of like the optimistic kind of macroeconomic impact it'll have um creates the near-term choppiness it in some ways you know because like the the the statistics coming off the companies that are being disruptive disrupted might kind of overwhelm the underlying um productivity gains and and price trends that we'll we'll see clear through the end of this decade uh in some ways you know there's this saying in text the the second half of the chess board and the idea is that if you've ever heard the um analogy of um or it's like a a story an allegory of a king who um accepts a service from an adviser and the adviser says oh you can just pay me by putting a a grain of rice on this first chest square and then doubling it for each subsequent square and um the K's like this sounds like a great deal and it only begins to get burdensome as the compounding continues to happen As you move into the second half of the checkboard where suddenly he needs to produce grains of rice that are you know equivalent to number of like stars in the sky or atoms in the universe like it it just totally overwhelms um kind of like the equation and I do think in technology we're actually this decade is going to feel like the second half of the chessboard where we've been getting gains technologies have been developing somewhat independently uh and now kind of we've reached a stage where Technologies are ping ponging off each other converging in a way that is creating kind of explosive growth and opportunity in multiple different technology areas at once uh and that's captured in in this chart that's in our big Ideas deck that actually goes back and looks at all general purpose Technologies which follow steep cost declines they cut across sectors and they're themselves platforms of innovation and kind of systematically identifies them in history uh and then highlights the general purpose technology platforms that we think are are really at a sweet spot of inflection today so today it's energy storage public blockchains robotics multiomic sequencing and of course artificial intelligence they're all hitting critical stages of inflection and if you look at how they Stack Up in superposition um we think that this is the most technologically momentous decade in history and and even exceeding kind of 120 years ago or so when you had the telephone internal combustion engine and electrification happening at the same time and I think like crucially AI is accelerating even beyond our internal very aggressive expectations for how quickly it would happen and AI serves as kind of like the central Catalyst for all of these Technologies sometimes in really profound ways and so what is what it's doing is it's actually pulling some of those things that were going to happen maybe in the 2030 forward into the 2020s uh robotics in particular this year versus last year our expectations for kind of like robots that can operate in the world and and deliver profound productivity advances have increased uh and so you can see this chart you should read it as those five platforms that I mentioned yellow public blockchain green multiomic sequencing purple AI uh that blue color energy storage and then red robotics um from the bottom those are the categories that are catalyzing the Technologies coming across and so that Central dark purple box is kind of the the um the AI catalyzing other AI Technologies but then um AI there's a strong purple Central stripe going through because AI serves as a catalyst across the different technology categories so from the perspective of hey I would love Innovation to be really remarkable and meaningful um if I had a choice of any technology that could essentially turn up the velocity on it would be artificial intelligence and low into hold actually it's happening faster uh and so this chart shows kind of um a forecasting site's estimates for when artificial gener intelligence will be available and demonstrated and it has a a very specific definition for artificial general intelligence because people tend to go move the goal posts here but it's basically like could you be in conversation with one of these things for two hours and you couldn't tell whether it was human or not conversation or images or typing or text can it put together like a really complicated kind of model car u meaning like you go from Instructions think of this like the IKEA furniture test could an AI system like actually take the a the Ikea instructions even more complicated Ikea instructions and successfully put together the cabinet for you because I fail on that you know call it 50% of the time uh and then the third is like how in a bunch of different expert areas can it pass the equivalent of um certification tests for like the medical licensing exam for for um lawyers uh and and so is it basically at a higher than human level or 90th percentile human level in a bunch of different expert areas and so in the chart you can see just in 2020 we thought this capability was 80 years away and with each subsequent advance in gpt3 and what uh Google is demonstrating through Deep Mind in gp4 Suddenly It's like oh gosh this is closer it goes from 80 to like roughly 30 years to 20 years and now here we are today and it's by the end of the decade and that's even if the forecasts are well tuned now but you know the odds of meta coming out with a model that blows people's minds or the next open AI model coming out and being like whoa this is even more performant I mean they seem roughly higher so um like if you adjust for the way the the forecasters um expectations have drifted it's really you know before the end of the decade 2027 2028 you should have these wildly performant models that don't just impact hey I can chat with a chatbot and it's compelling but also will improve the capabilities of humanoid robots also will make it um more likely that we can identify the key molecules in any um rare disease and Target a drug right after them efficiently that will make it um you know more likely that we can develop an audit like broad-based smart contracts that will allow Financial functions to Auto execute without needing kind of a central counterparty like a bank to extract its its viig for facilitating that transaction and so kind of it should accelerate certainly Ai and our expectations for AI and kind of all the technologies that we focus on uh and so Kathy do you want to talk about kind of like the macroeconomic potential impact here sure yes uh it's very exciting uh this actually this chart came out of our big Ideas last year and what you see here are um is the impact of technology on real GDP growth when there are big breakthroughs and so as Brett mentioned the the breakthroughs in the uh early 1900s telephone electricity internal combustion engine um created a step function increase in growth and you can see it here um uh the the previous years back to the 1500 the average uh real GDP growth rate we think was and and Brett did this research uh 0.6% there was a five-fold increase in growth thanks to those three major platforms and we ended up at 3% growth on average uh for the past 120 years and um you can see now what uh forecasters are expecting um from now until the year 2040 they expect a deterioration in growth from that 3% range to 2.6% um and what do we expect well we we believe these five platforms are much more provocative and especially with AI the primary Catalyst or the biggest Catalyst uh that that the grow the the step functioning growth could be quite significant we've held ourselves back here this is a log chart we've held ourselves back here and uh you see 8 and a half percent is the expectation but just think about that do you hear any Economist out there this is real GDP growth do you hear any analyst or uh Economist out there uh assuming that real GDP growth will move to the uh upper single digits uh in the years ahead no I don't hear anyone saying that now one way it could happen uh that would take nominal GDP growth lower is if prices uh uh were to come down fairly dramatically and we're seeing in a in artificial intelligence on the training side um costs are declining 75% per year we thought just two years ago we thought it was 60% now 70% and then on the inference side we're seeing cost declines per year of something uh north of 85% so uh these this is a massive deflationary force that we think is going to sweep around the globe and maybe nominal GDP growth will be you know 6% uh with prices falling um by 2 and a half% per year and getting us to that real real GDP uh growth of eight and a half percent um Brett I don't know if you wanted to add anything more to that slide yeah I I think just generally it is consistent with economic history that in you hit a technological transition and then the natural rate of growth of the economy shifts in a structural way uh and and um so just on the long historical perspective you'd say hey it looks like that could happen now um and you could have also said that 10 years ago and it didn't yet so the reason I'm more confident now is not just because of the long historical perspective but also because of the Practical impact of the technologies that we are seeing today if you look across like if our expectations about Robo tax you're right and now it's very clear to me that this is a when not if um system and it's a question of how quickly they can scale and can Tesla do it on its footprint in which case they should be able to scale very quickly that would be um number among the most meaningful macroeconomic impactful Technologies of all time uh including like comparable to the steam engine in terms and and and it fits into a framework where it will clearly be recognized into the macroeconomic statistics where it's like consumers will decide rather than you know driving the vehicle they have in their garage they'll pay for this service and so a a previous Behavior driving that wasn't recognized in markets because I'm not getting paid for being a driver even though I'm an amateur driver all the time suddenly becomes something that people are paying for and so it'll flow through into uh kind of the production output and into the income statements of those autonomous platform providers and so um kind of you stack up that and expectations for Robotics and even marginal much lower than we have expectations for AI and AI software and you end up with um a GDP growth that's that's consistent and even in excess of what's implied by this slide uh and so I I think that there's a there's a lot of compelling evidence that this decade is going to be remarkable from a macroeconomic perspective right and it should translate into um very nice returns for these Technologies as you can see uh we if you look at the market today um roughly 19 trillion of the 117 trillion in global Equity market cap is associated with disruptive innovation so let's let's say a little more than 15% um if we're right and and with Brett's guidance our analysts have uh you know built the building blocks uh for us to be able to say this uh if we're right that 19 trillion is going to scale to 220 trillion uh during the next really seven eight years seven years so that's a 42% compound annual rate um of return um and whereas the rest of the world we see appreciating little or nothing at all why would that be it's back to that creative destruction the the the traditional World Order is going to change radically and uh the the traditional benchmarks the broad-based benchmarks whether it's the S&P 500 msci world and um uh the NASDAQ for example um they're they're not going to be able to keep up with this and and one of the reasons we learned an important lesson from from Tesla the SMP did not put Tesla in that index until it had hit 500 billion Dollar in market cap why well uh two of their criteria uh are uh four a four quarter moving average of profitability with the last quarter uh profitable well Tesla didn't hit that I think until 2020 or 21 I I forget I think it was 21 was it Brett that sounds right yes but and just think think about that how many companies are bigger than that 500 trillion and know by the way most people who waited until the S&P gave them permission to move into Tesla are underwater right now because they're as as is always the case with disruptive innovation there's controversy and it has taken uh taking the stock down so um anyway so so we're pretty excited and as you can see uh we delineate uh those growth rates by Major Innovation platform with robotics being uh the the fastest uh the fastest uh growing uh it's also at a very very low base industrial robots in particular very low base um whereas AI 37% uh that is off of a substantially larger base and just to give you a sense of the drama here even for us and all we do is focus on disruptive innovation um in I believe this was 2020 our expectation for the market cap of artificial intelligence out there um in five years from now was I think $40 billion now it's up to $400 billion I know there's been a ai ai Hardware uh is what the spending on artificial intelligence uh Hardware um and I think it includes the software too am I right no this is this is just looking at the accelerator so if you look at the accelerators in the data center and what we were expecting to be spent on accelerators in the data center um we you know we previously approached it and said okay well this is how much is spent on servers and uh this is the share of servers that are going to be devoted to accelerators and then the subset that's going to be spent on accelerators uh and we ended up with a a $40 billion number now AMD is saying that hey we think that there's going to be 400 billion um by I think it's 2027 spent on accelerators and we have a you know we have an in excess of I think $ 1.4 trillion dollar on accelerators by 2030 is our official forecast or 1.3 perhaps but and part of that is like we we opened up the model by saying well how much value is going to be delivered with AI software and um you know if I can just like if I can deliver a robot to an an Amazon or to a Tesla and that can increase the productivity of their manufacturing Base by X they'll spend some fraction of x to install that robot and then they'll get great Roi it's the same with software and how it improves me and all of our analysts as knowledge workers people pay for software that improves worker produ it uh and if you look across all knowledge workers there's almost $30 trillion in knowledge work wages that is going to be paid in 2030 so if you can improve their productivity by multiples and just pay a fraction of that you still end up with trillions of dollars and in fact more than 10 trillion dollars in our estimation of AI software spend to help knowledge workers and therefore you need a trillion dollars plus of AI chips to create that AI software uh and and so um kind of rather than approaching it from like hey this is uh this is it spend and what people are going to do we approach it from this is the output of the technology that's going to be installed and therefore the amount of kind of um justifiable really Roi positive Hardware we need to support that uh and you end up with a much larger market so that begs the question and before you leave us we're going to show one more quite provocative chart it says it all but before we go I know this begs a question you know we have been shifting our emphasis from um in our various strategies from uh Hardware Centric that would be Nvidia uh AMD depending on the portfolio um it towards software and towards companies that are going to capitalize on the productivity gains that um that uh we're going to that AI is going to deliver um why would we be pulling away well it's a little bit back to uh the question we're talking about and the confusion that we expect to uh see in in in the next year around the cycle um because believe it or not even though AI is a force it really is we are seeing what we saw during uh covid there's double and triple ordering uh in a shortage uh situation or or perceived shortage POS situation uh in covid we're we're still suffering from uh the aftermath of that uh and you know even though this is a huge SEC secular growth story there are there's so much in the way of expectations now being built into the check the box uh AI and believe me it's an important box uh Nvidia has done a magnificent job we bought it from uh you know from from from the time we started the company we're involved with it when it was $5 and just when we understood we built it enormously uh but the but it is subject to cycles and and and the last one was the crypto cycle 2017 couldn't get enough gpus uh and uh and there was double and triple ordering and the stock in the fourth quarter of 2018 was cut by 2/3 now that's not going to happen this time because this AI wave is just so powerful but the expectations do get ahead of themselves we saw that with you know uh uh alphabet I guess uh earlier this week and AMD just the expectations had gotten ahead and uh you're going to have the the the two and fro but before we let uh Brett go this is a chart that he drew to try and help people understand uh how provocative uh this these breakthroughs in AI are and so here it is yeah so um we talk about cost declines a lot at ARC and and on AI in particular it's the cost decline is happening more quickly than anything we've ever studied so Kathy alluded to it but um cost to train a model we think is going to fall by four times now last year we thought by three times per year prospectively going forward through 2030 and on a real-time basis costs are falling even faster than that for AI training which is separate from the cost to actually deliver an AI model which is called inference and that's following at you know 85 Plus percent per year but then that's also separate from what it means for the cost to do something within the business or human context at an in application basis and so here we looked back and said well what does it cost to produce written material and if you go back to it was 1894 uh and looked at what the pal mul Gazette was paying its professional writers to write essays it was inflation adjusted around $400 $500 a word and then as you track kind of this data point of what do magazines pay people to write over time it basically stayed in that spot or 400 $500 per thousand words I should say for so you know a thw essay you get $400 to $500 and it's been that way all the way to to a a few years ago if you wanted to pay a writer to write a corporate blog post you know a thousand-word corporate BL blog post You' pay $400 to $500 for it's kind of like at the higher end of the the Spectrum for what you'd pay for a a you know a qualified experienced WR or somebody that would score well on the on the graduate level exam the grees for example well uh then gp4 scored basically like 50th percentile on the Gres and it cost uh call it I can't remember what's on the chart 12 cents 16 cents 16 16 cents per thousand word so you've gone from $4500 to 16 well then anthropics Cloud 2 model uh scored 90th percentile on the Gres it cost four cents so we went from something it was the same amount to produce written content for more than a century suddenly it falls 10,000 fold and is now going to be on a cost decline trajectory it's not like it's just going to Plane off essentially written authored material is going to both be ubiquitous and abundant with all that is good and bad about that as in you will have your own personal chat bot that you can chat to that will be you know really compelling and interesting and have all kinds of information to share with you uh and you will be at risk somebody you know kind of like infiltrating you pretending to be human when they're really not and so I think that the the implications for like businesses um humans like all of these systems that we use where like kind of written and oral speaking ability is a mechanism by which we verify that this person is a person that I should pay attention to uh is just going to get totally um turned upside down by this and it's not just going to happen in the written word context text it's going to be image generation it's going to be kind of ability to look at data sets and forecast the direction that they're going so kind of like the the the ability to take like an idea and convert it into something that amplifies and spreads is going to be massively magnified here with all kinds of interesting implications right and uh on balance what you just said sounds like oh no you know I'm going to be bombarded this is a disaster I think the bottom line is we do think all of this will sort itself out we'll we'll figure out ways to uh verify and all of that but I I I think this is a a true Force for good Technologies the history of technology is we are very happy that uh we're very happy that um Elon Musk and others are are warning us about nefarious actors and what could go wrong here half of the solution is understanding the problem uh and we know cyber security is booming so a lot of people are paying uh a lot to try and figure out the risks Associated but the opportunities Associated uh with AI are transformational this this is going to be the biggest um Catalyst behind wealth generation uh during the next 5 to 10 years and the and the super exponential uh growth opportunities that it will enable and if you want to learn more uh check out our uh Big Ideas it's on ark-invest do.com so thank you Brett very much I want to add one I I want to add one more thing because it's an important that that cost Decline and the ability to generate written language you can also invert it and say what is the cost to process written information and so like it's transferable to one like written language is also code so what is the cost to create software what does the cost to like how many times have you clicked through an agreement on some very long document and been like oh yeah this user agreement whatever without really having a mechanism by you don't have the time to read that thing but um if you have an AI agent to be just basically like how is this contract going to put me into trouble and what kind of like term should I avoid uh or even if you think about all of the ways in which organizations structure contracts with each other to to to interc commmercial relationships and how often that still ends up in the court where you're asking a judge to adjudicate between kind of gray areas in the Contracting language all of that will get like more completely filled in um by Ai and so like the one of the promises of technology is to reduce the friction between interacting between agents corporations everything like you can imagine there's like the transaction friction is going to collapse in all kinds of different ways both with AI and blockchain I think that should like have a profound macroeconomic effect and thank you Kathy always love coming on in Theo and yes everybody download Big Ideas absolutely thanks so much Brett okay uh so we'll go quickly through these other charts now because uh time is short uh so I'm going to focus on um a subset of what we usually discuss uh and so let's start with money supply we usually talk about this I showed this uh last month um but you can see M1 grow M2 growth year-over-year is still negative again we haven't been here since the uh since the 1930s and this is another deflationary Force at work we believe what's interesting about this negative number now is that it's against a it's against a flat to negative number last year and so this is now we're entering the second year uh and uh I think that's very significant especially now um you're hearing about the Regional Bank crisis again um there's another shock to the system uh uh more and more analysts are doing the work to figure out you know which comp compes are at risk here as um as defaults proliferate and um and and that's a big problem uh deposits continue to leave the banking system uh and uh that's not healthy That's not healthy um so uh very important consideration as we think about uh inflation coming down uh using this very rough correlation uh you can see inflation will come come down into negative territory um if we are right and uh we just gave you some very good examples of uh collapsing prices uh next chart uh here's the FED funds rate uh which is what the FED controls in the green and the CPI rate and so you see the FED um took took its time uh before lifting rates as inflation was taking off because they thought it was transitory and um many of people saying they are are saying they made a terrible mistake we don't agree with that uh we do think the the rise in inflation was the function of not monetary policy but a massive Supply shock to the system called covid and two Wars now so um we believe that the inflation rate will go negative so you can see the zero line there which means that if the FED funds rate stays at this level and on this next chart we're doing a ratio of those two you'll see what's happened already just soaring after deep negative that was covid um in real interest rates and and this is what the markets really do respond to real interest rates have moved up sharply they're above I would say they're above the certainly above the average since uh uh 1990 uh they may be right in line with the average going all the way back here but if we're right and the and the the price I mean the the yes the price indices turn negative on a year-over-year basis uh then we're talking about north of 5% and we've only been there during the early 80s uh and remember back then inflation was 15% inflation expectations were very high inflation expectations we just got the University of Michigan report today 2.9% back then they were in the high single digits uh so if we are if we believe that uh prices are falling this will go to 5 to 7 a half% within the next year if the FED does not change it spots and uh chairman pal this week came out and basically said um March is probably not a a cut uh so we'll have another few inflation readings and some people believe that CPI will be stuck here for a while um it may be I don't know there are lags in the CPI it's quite the lagging indicator um but uh I'll show you in a moment a chart that says Watch Out Below in terms of those PR prices and and maybe the price indices are going to drop by much more than anyone now expects on a year-over-year basis um this is one reason that might happen this is the yield curve uh it's still inverted it got into the minus teens and now we're back down at minus 30 uh and as you can see we have not been there since the uh early 80s as well again that uh was very stringent uh monetary policy uh it did get inflation down but again the starting point back then was 15% um today we're still negative uh uh money growth on a year-over-year basis and inflation's 3% um now here is a a me a metric that suggests that the CPI is going to go perhaps deeply negative uh this is the new tenant rent index uh and the source here is macrobond and you can see on this basis this goes back prior to the te uh to the uh Financial meltdown in 0809 and rents are falling um more significantly now on this realtime metric uh than they were back then uh now I believe in the CPI rents are still up on a year-over-year basis is something like I'm going to say 5% roughly could be a little more could be a little less uh this is uh minus 5% and uh we also know that there are a million uh units in the multifam uh apartment space that are in the pipeline they are they're not on the market yet uh and if you look back through history the last time we saw that higher level was in the very speculative real estate days of the 70s uh and uh during that time inflation really did um absorb a lot of those units uh but if we're right and rents are coming down here uh region to region it may be different but uh if on balance Nationwide they're coming down the assumptions that a lot of private equity made uh pushing into real estate uh in order to uh in a in in a search for higher yields and leveraging up even more to boost those yields some of those assumptions are are not going to be bailed out by by rent inflation they're just not uh and so uh watch out there uh and then um here just to make sure we have a balanced View um the the turmoil in the Middle East and and the Red Sea with the hooes and and so forth has caused a backup in the freight uh rate Benchmark uh so you can see how big the dislocation was during covid now interestingly in the last few days uh this index has come down um so so we will see I think it's a a a a race between the turmoil in the Middle East and uh perhaps inventory Corrections here globally um because of the severe weakness in China um weakness in Europe and even at the margin in the US as well uh and then on the next chart uh next page you can see this is the global supply chain pressure index uh and you can see it's basic basically in line with where it has been historically um so again uh that may not be as big a problem it certainly won't be as big a problem as covid was and then just a few more charts here just want to I keep going back to this chart because so many people think we are in an inflationary period but if you look at this chart this is a commodity chart and commodities are some of the first places you'll look for inflation and you'll see the big inflation was actually uh after the Tekken Telecom bust into 0809 that's when oil prices hit $147 and we believe that happened because uh during the late 9s there were a number of reasons the FED hit the accelerator a number of times um uh after the Russian uh debt def default I think that was in 97 or 98 um we then had long-term Capital Management implode and many people thought that could um uh cause a global financial crisis the FED included so it eased for that reason and it also eased because of Y2K uh the fear that as we hit the Millennium that computers around the world would shut down activity would shut down because uh they weren't set up to transition from a one handle to a two handle in terms of Millennium uh and so the big inflation was back then if you look at this chart there there's been a deflationary undercurrent out there since then and uh we are today where we were in the early 80s in terms of this and uh someone said to me the other day surely you're you're saying this is adjusted for inflation no this is not adjusted for inflation you can only imagine how low these commodity prices would be and in fact we'll do that for the next in the know adjust this for inflation to to show you uh how how deflationary this is and then uh this chart again um remarkable uh the correlation since especially since uh 0809 many would people would say of course the correlation is there uh at 0% interest rates but the metals to gold ratio um has correlated very highly with the 10-year treasury bond yield and so when the purchasing power of gold has gone down relative to Metals the purple line goes up interest rates go up when the purchasing power of gold uh uh goes up relative to medals uh the the purple line goes down and interest rates have followed it until the FED started tightening this relationship broke down in early 22 uh it has the the ratio has been falling or the gold the purchasing power of gold relative to Metals has been increasing and and that's very often in a risk-off environment uh as longterm treasury yields have been rising or as they are right now elevated relative to to this uh ratio if you were just looking at this ratio and nothing else you'd say well long-term interest rate should be closer to 2% than they are today to 4% uh so continue to be struck by that uh chart I'm going to show the Bitcoin to gold ratio um um many people call Bitcoin digital gold uh we would put it in that category a store of value uh a risk off asset uh and last year during the Regional Bank crisis in March uh Bitcoin uh shot up 40% as the K the Regional Bank index was imploding and here again the Regional Bank index is acting up uh and after uh a little bit of a correction uh after 11 ETFs were introduced um we are seeing Bitcoin catch a bid again uh so this idea that it's a flight to Quality or a flight to safety uh is reasserting itself here uh the reason we believe Bitcoin went down after the ETF um after the ETFs were introduced is because there was a lot of anticipatory buying before uh before Bitcoin or the ETFs came out uh there was a bit of the sell on the news these these are the trading types who uh just are are very opportunistic in that way um as you know or if you've been listening to in the no uh 15 million of the 19 A5 million Bitcoin outstanding are in what we call strong hands they're they haven't moved their Bitcoin in more than 15 155 days uh so um and and this chart uh just shows you that even relative to Gold uh Bitcoin has been rising it is there's now a substitution into into Bitcoin and uh we think that is going to continue now that there is a much easier way less FR friction filled way to access Bitcoin and uh uh you can check out in our big Ideas uh what we think the impact of instit institutional participation in this market is going to be on on bitcoin's price and then just to throw a another wrinkle into the discussion we are struck that credit default swaps both for investment grade and high yield are coming down in this environment where for many companies they're beginning to see revenues go down that's very interesting to us um but you can see how sharply this can move in in uh late uh 2018 there was a serious correction in uh in the stock market I think it was the fourth quarter and in actually back then inidia led the decline it was uh cut as I mentioned earlier by 2third and there was just this reverberation through all kinds of markets what's going on here uh and uh credit credit default swaps uh shot up pretty pretty um sharply and you can see what happened during covid and then again you can see what happened in 21 and 22 as the Fed was talking about in 21 and then actually um raising interest rates in 22 lots of fear out there now there seems to be complet lcy building in and it has to do with this soft Landing uh that seems to have become the consensus forecast we do think that's going to be shaken up as companies lose pricing power and start laying more people off and so we think this will reverse and uh and and the flights to Quality will get uh another bid out there um and we do think also I'll just continue to give a plug for in Innovation based strategies they were absolutely creamed in here certainly paid their dues while the the NASDAQ and others were hitting all-time highs um we think that uh that innovation-based strategies will hold in much better uh because as Brett uh described we've hit prime time for uh a lot of um Innovation and uh we think that uh earning and and revenue growth rates are going to be protected from this rolling recession that we see because uh our companies for the most part help companies with margin pressure solve that problem so I guess I'll end there um encouraging you once again to take a look at Big Ideas uh 2024 it's Chu full of our original research you you're not going to see this research in many other places and certainly not concentrated in one place so with that I'll wish you a happy weekend happy February and I will see you again uh next month employment Friday at this [Music] time

Channel: ARK Invest

Views: 137,518

Keywords: innovation, investing, cathie wood, cathy wood, kathie wood, kathy wood, cathie woods, cathy woods, kathie woods, kathy woods, ARK, market news, fintech, Big Ideas 2024, ai, artificial intelligence, brett winton, bret winton, convergence, technological convergence

Id: hFg1TMACw4I

Length: 59min 51sec (3591 seconds)

Published: Sun Feb 04 2024