 Okay, hello and welcome to episode 109 of the market maker podcast and we've got a couple of different things We're gonna talk about on this episode Gonna talk about Tesla because there's been a new price target circulating this morning My I remind you Tesla currently trades at $162. There's a price target that's come out today that their share price is gonna hit 2000 So we'll delve into the timeline of that and the rationale of that business is gonna try and persuade me Why should be buying Tesla shares right now? and then we're gonna talk a little bit about AI and chat GPT in the world of financial markets because there was a report this week talking about how Researchers at the Federal Reserve are using chat GPT and also how it's being used for predictive stock movements So we'll have a look at that. We'll also talk about Goldman Sachs. We've had a number of banks this week Morgan Stanley GS Bank of America Bank of New York Mellon But we're gonna focus on goldman's because actually they've been the one that has disappointed the most out of all of the big banks Often seen as the most prestigious. They are facing some serious headwinds at the moment So we'll look to explore a few of those things and then finally UK CPI, but before we begin Piers busy week. I hear Yeah, what's a busy week here over at Amplify HQ? Yeah busy week just because it's some All of the banks are doing their spring spring insight programs at the moment So, yeah, we've been we've been helping deliver those with city group and credit Swiss And Morgan Stanley actually that one was a couple of weeks ago But yeah, the big one actually this week was was in terms of our involvement was Bank of America. So, yeah, we we we spent our the whole of Wednesday On site Bank of America with the yeah 120 spring insight candidates Yeah, it's a big one because we were running three of our simulations in parallel After out the whole day. So, yeah, it's really cool really cool to To kind of work with these new eager young Candidates. Yeah, really super impressive a couple of shout outs from my side because I don't know if you You had what I had but kind of walking around during the day like every now and then And because I spoke at the start of the day to the whole group to kind of introduce the structure and the simulations We were running a global market sim. We were running an investment banking M&A sim and we were running A risk management sim. So I was just explaining it all and then afterwards during the day I had a few people come up and go, oh my god, you're I listened to your podcast and I was like, yeah, how do you know I'm on the podcast like because people listen to it They don't Look at my face. Well, unless you watch this on youtube, I guess and they were saying yeah, it's your voice I recognized your voice. Oh, wow So two in particular, um, I want to give shout outs to uh, felsi felsi kesi acquiru And also amy stewart box Those in particular were talking to me about how they love the podcasts and how they really used it to kind of Improve their well, I guess commercial awareness and what's going on out there in markets and they said it really helped them Well to kind of you know impress in the application process for the spring insight program So yeah, really cool to to meet to meet those guys and yeah good big shout out and Well done and good luck. Good luck to those two because they got interviews today Yeah around interviews. Yeah to try and uh get a return offer for the summer So right now as we're recording this there's going to be a couple of stressed individuals, but I'm sure they're going to smash it Absolutely Good stuff. Well for for those people and everyone else that listens Um, please do share the love get it out to as many people as possible tell your friends about it Share it on social if you liked an episode or the actual podcast channel itself Or just drop a rating or a review because it really helps kind of boost up the algorithm on apple spotify and so on So yeah, be much appreciated. But look, let's dive in first subject I'm not going to say my favorite or my worst. I'm just going to say tesla It's my favorite They finished the session. Well, let's start on a positive footing They finished the session down 10% yesterday So yeah, the reason for that was they had there was a double whammy they had their earnings and they've kind of slashed prices again so one of the main things I wanted to talk to you about was Um margins and also economic headwinds at the moment. So gross margins That was something that investors really latched onto when they were looking and trawling through these numbers And one of those was that it dropped from 29.1% to 19.3% You were over a year after the company rolled out a series Of recent price cuts a couple of other numbers before we latch on to that Area the ev makers net income was down 24% from last year While gap earnings were down 23% from a year ago. So that That's all I'm going to say about the negative numbers so far Well, I'll come on to the earnings call in a moment Well, hang on what about the any positive numbers? No, I Incidentally, they're all negative Well, okay, I'll finish off on the earnings call because musk Um, he's now kind of if you remember was it 12 18 months ago. He was kind of like right I need to start moving away from tesla letting it grab his company So that it doesn't become so dependent on me. Let it find its own feet Then obviously tesla got whacked when he started buying twitter getting caught up in that saga He's come back and now he jumps on the earnings calls And kind of dominates them So he's a he said a couple of things he said he emphasized an uncertain macroeconomic environment That could impact people's car shopping plans Adding that he expected 12 months of stormy weather in the economy And then he went on to blame the federal reserve drone power So it's exactly Taking a page out of the donald trump book It's look It's their fault And if they keep hiking interest rates, he was saying how that's going to hurt consumers So, yeah, very very non-political as always, but um, well, I was um, it's interesting with tesla and the medias the media for sure has a bit of a negative agenda Against musk and tesla. I think specifically But but I think musk generally was hilarious that bbc interview. I don't know if you saw it um, that was about twitter, but where the bbc In journalists was was grilling him About hate speech basically on your for you page And how it's gone up since he's taken over twitter. Did you see this interview? And basically musk said to the journalist, okay, give me one example Of what you're talking about And the interviewer goes, oh, well, yeah, I'm not yeah, I actually haven't been on the for you page For a while. So I can't Give you an example He's like what I mean, you've just told me that hate speech is going up on the for you page And yet you don't go on that page. So how do you know it's going up and the the journalists have no response He must absolutely destroyed him But it was a good indication of this. I think negative bias my point is Like I was reading the ft like reading up on the tesla earnings and like Pretty much what you've just said there, right? It's like List out all the negatives. I mean It took me I think it was about three quarters of the way down the article Because I was going well, okay, I get I get this the we'll talk about gross margins in a minute and how that's gone down and profitability down and Obviously that's linked but um, but then what's what's happened to revenue? I mean, do you know Was there a revenue up or down or year on year any idea I'm not going to do what the bbc journalist did and try to pretend I've gone on gone on site and read that Yeah, so I guess this is my point in the It it it literally it was about three quarters of the way down the article that I finally found The revenue figure And revenues. Yeah revenues are up and they're up quite strongly But a year on year. I can't now that I'm speaking. I actually I've lost the figure I think it was like 20 up or something. Um So So fine, but look, yeah Generally speaking, the earnings numbers are worse than expected. Of course the share price is down 10 To to reflect that. I mean, I will just caveat But it was the share price was up 65 percent Yeah, on the year Like since january But for sure off 10 percent. Let's talk about this gross profit margin thing first. That's definitely the big one The big story of these earnings and So and this is a key kind of metric for the You know, measuring the competitiveness of each company within the automotive sector This building cars Is super labor intensive? It says a very There's a very high cost of production and that's why when we're looking at an automotive business and trying to judge Um its success against its peers. We always look at the profit margins. So the gross profit margins Probably the the most important metric when you're analyzing the automotive sector Historically tesla but an incredibly high Gross profit margins. So this is obviously a good thing like best in class By a country mile. Well, when your car is the worst in class for reliability and quality that makes a lot of sense, right? Uh, well, there are other reasons why they've got a high relatively high gross profit margin Which i'll come on to In my bullish case, uh in a minute, but for sure take the bearish situation Their gross profit margin has dramatically dropped in the last Year it's gone as you said from 29 percent down to 19.3 percent Okay, huge drop a lot of that is because of the big price cuts deep price cuts that Tesla have been pushing through to try and just Well increase sales obviously to try and you know get get get some money coming in to shift some stock So they've had like for example price cuts of up to 20 percent on some of the model 3 and model y Vehicles, they're the kind of two best sellers, right? So 20 percent price cuts is obviously Stinks a little bit of panic with regards to you know I guess the challenge Tesla has which is that now the entirety Of the automotive sector is now In this kind of peloton Behind them trying to now catch up. It's all EV Everyone's EV everywhere and so finally now everyone's chasing and hunting Tesla down who were You know the pioneers in this space, of course, but um But 19.3 percent gross margin, right? But that is still higher Than all the others. It's just that the gap Has dramatically shrunk for example um Volkswagen Their gross profit margin is 18.84 percent Okay, now actually that's been quite stable. So in the so Volkswagen's gross profit margin is lower than Tesla's however The gap has gone from being about 11 percent difference to now 1 percent difference Be a Toyota's gross profit margin 17 percent BMW's in around there as well about 17 percent So they're still best in class, but their massive advantage in this area has almost entirely vanished So Musk's point is look we have this amazing gross profit margin So let's sacrifice a bit of that to win market share So he's cut prices, which obviously Immediately drops down onto that gross profit margin line in order to win market share. That's his strategy So that's why the numbers were a little bit Shocking and why the share price is is kind of down 10 percent and then obviously his macro View he's setting us up for weak demand for the next 12 months So what happens over that next 12 months then let's say The situation we do go into a us recession And more of the kind of bearish economic situation unfolds his margin is now Has shrunk he still got space obviously Even though he dropped within to the peloton. Yes, you say What what's the next play after that because there's no new major XY models coming out. Is there that's going to like Reignite new enthusiasts demand for a new model So when you look near term next 12 months he's Played his ace card already That's done He's used all of his gross profit margin advantage almost all of it That card is on the table played Okay But if you're thinking so I agree in the next 12 months Yeah, it's probably going to be maybe a bit challenging and it and obviously entirely comes down to what is still a big unknown and the big debate on the street is Is there going to be a us recession? When will it start and how deep will it be? You know, ultimately it doesn't matter what you're investing in Tesla Or any other sector anywhere ultimately that's the big Conversation and there's a lot of uncertainty around this really really hard to predict that but you know in musk's words You know, obviously he's blaming the fed because ultimately the very sharp rate hiking cycle is going to cause damage So yeah, I think in the near term, you're right, but I think with tesla the bull case So what were you saying? He would Oaks updated open source tesla model yields an expected value per share of two thousand bucks by 2027 teslas perspective robo taxi business line Is the key driver as they said and that's going to contribute to about 58 percent of expected enterprise value And 45 percent of expected ebitda in 2027 Okay, so is that is that is that the game plan then as a business strategy? It's not so much You kind of you continue selling cars continue trying to grow that business But what they're saying half of the business is going to come from this new tasks model So long term look I don't go here on cattywood $2,000 price target in four years. I mean I personally is laughable. I mean that's just It's probably fantasy land, right and she's obviously talking massively talking up her own book Tesla's her biggest holding right in her arc fund So, yeah, very sensational. It's very, you know, click bait call it whatever you want. I think it's a bit crazy But I will say there is a bullish argument for tesla Not near term as I said, they played that ace card short term ace card But they've got a lot of long medium to long term ace cards, which sets them out Sets them apart from The rest of the sector pretty much by and large. So here's here's a few examples So, yeah, cattywood's main point is around their technology, right and their innovative technology So they've got and this is the thing tesla is built from the ground up Right, they don't they don't outsource anything. They've literally created tesla really whilst we see it as a car Kind of driving along the road. It's really like six or seven different businesses In that they have created from the ground up every single product that goes into that vehicle Including all the kind of machine learning and ai around, you know, driverless, you know vehicles and so on Which is why the robo taxi thing which Kathy wood is talking about yes tesla do have ultimately A huge advantage against all other automotives Because they've got their own data center And they've got their own ai model to kind of build out and be the leader You know in a race don't get me wrong. There is a You know, there's multiple players in this race like the big guns We've talked about this in the past like google and the rest of them They're all trying to Practice driverless vehicle thing right but tesla are in the lead because they've got the data because they've got Hundreds of thousands of cars millions of cars on the road Right now driven by humans right but all the data they're getting is pouring back into their own built from the scratch From ground up their own ai machine learning model That's then feeding into an ever improved system. So yeah, I think they do have the advantage there But look, they've got advanced. Yeah electric power trains. They've got their own battery technology They've got their own software systems, you know, and this is all then as I've said that autopilot Currently semi-autonomous driving system You know They've got it all and it's they've outsourced none of it. Okay The other things that's quite interesting about them and because of that, right? They've got what you might describe as a vertically integrated business model So they've got a control over the majority of its supply chains. So when it comes to let's say the geopolitical Direction of travel Where you've got the superpowers of china and the us very much kind of You know, moving in opposite directions and that sort of globalization in reverse then, you know supply chain Risk If you want to call it that is definitely up there and I'd say that tesla are a better place to deal with that than other automotive The other the other things are like that. They've got a direct sales model. So tesla use direct consumer sales Okay, so they bypass tradition and the traditional dealership kind of networks, which is good for their margins The supercharger network, I mean their their charging network is obviously best in class globally Which gives them a big advantage as this ev revolution You know continues to rev up and then they by the way, they don't just build cars either I mean, well, we've got maybe a truck coming along, but it's not just vehicles Did you know that they also they're an energy company? They produce solar panels. They produce Um solar roofs and each energy storage solutions, you know, so they have they have got Diversification within their product mix outside of vehicles as well, which might be something that you know in time You know helps to diversify them out and and that's a positive for the medium to long term So in terms of valuing them as a business then Isn't it not unfair that they're in this category of automotives? Which are very let's let's face it dull businesses in terms of their competitors Is it not more fair to put them in some of these more? High growth related peers, which then make them a less favorable looking company when basically putting them in a sector that's not really appropriate Well, I think this is the thing right when you Sit down and go right. Let's start a company and our product is going to be to start with a car But let's not outsource anything that's literally start from build it from the ground up in every single aspect Then the thing is it takes a huge amount of time And a huge amount of investment because you're starting from scratch with everything So right now today this huge amount of time this this product evolution if you like Is still just a car That's driving on the road So right now that's their revenue their revenue is coming from selling cars that get driven on the road by human beings Their key advantage is still to come in the future of the evolution of their their their kind of product And so all of the groundwork is laid but I think The benefits from most of that work and investment and efforts efforts probably still lies in the future I would say which is what pathy woods argument is I think you saw a flavor of that with tesla share price Like in 2021 but that was more caught up in the tech Tech share price bubble to be honest and then it all kind of came crashing down But I think we've had the bubble and it's burst So I think now with tesla. It's okay, you know, maybe we can Get back to a thousand dollars right, but it might take years But it could be that we get there if I'm right in saying that The big value in all the work that's been done most of it still lies in the future question and I don't want this to sound too morbid but This is something that you would do right as a trader you'd think about lots of different Outcomes of certain scenarios when you're taking a position of risk Um, you think about the base, but you'd also think about fringe cases, which could happen. What would I do in that situation? If something happened to elon musk And he's not around anymore What's the value of that business? I I think it's now I think you'd get a short-term kind of negative shock impact to the share price. I don't think the business Medium to long term suffers. Um, I think the best examples are look steve jobs Right when he left apple it was like, oh well, then that's apple gone like in terms of its innovative Roots that has changed people's lives or that that's that's gone. There's no more upside and of course that was proven entirely incorrect So, yeah, it would be a significant moment, but I don't think it would alter. It's too mature now I don't think it would alter tesla's um, trajectory over the medium to long term as a business Okay, why are you uh Are you looking to knock him off? I mean, I know you dislike the man, but I didn't realize your hatred was was quite that extreme Well, we'll see when um, I'll just keep an eye on the um when elon starts offloading some more shares than All right, well, let's let's move on and let's talk about um another technology piece actually as a kind of segue into what we've just discussed so um first wave of academic research Has come out this week applying to chat gpt and finance And it was talking about two again academic papers and actually I think these were citing the federal reserve Because actually if you think about federal reserve as let's say a company They have thousands of employees And yet the ones that we focus on it's just a very small tiny portion Which is the the policy committee that make interest rate decisions, for example But actually there are thousands upon thousands of researchers people work in research Regulations supervision that generally is what makes up a workforce at a central bank, but they've come out. There's a couple of pieces They've been since this technology has kind of gone viral They've been doing a couple of studies. So the first one is Can chat gpt forecast stock price movements? Return predictability and large language models to study prompted chat gbt to pretend to be a financial expert and interpret corporate news headlines And they use the news after late 2021. So a period that's not covered in the chat box training data As to just see what the outcomes would be And the study found that answers given Showed a statistical link to the stock's subsequent movement And I'll give you an example and see what you think So the example they had the Bloomberg picked out was the headline that Raminie street find six hundred and thirty thousand dollars in a case against oracle Oracle who you'll know the software company in us Um was good or bad for oracle and that was the question chat gbt explained This is positive because the penalty could potentially boost investor confidence in oracles ability to protect its ip and increase demand for its products and services and so For me when I was reading that I was like that's seriously flawed Yeah, because that's a very one dimensional view Of ascertaining how that's going to react now. I can imagine what chat gbt would have done. It would have gone back Through its huge data set and gone. Okay. Was there something similar that's happened like this before and what was the subsequent price reaction And just average that out. What does that kind of look like? Yeah, but the problem with interpretation of news is you and I know all too well Is the how it is impacted one day can be significantly different than next because of What's discounted into the price of the product with trading but also in the context of the broader Asset class the macro environment There's multiple variables that you would need to run in order to determine that and so just looking at history If that's not applying the current price data of news information flow of right that moment Then I can't see how that could be anything other than just a System that you would deploy in order to basically cover your back And if something happens, oh, there's a little trigger alert. That's something I should investigate And that's how we used to use it on the desk. I used to work on similar types of methods that we'd set up where keywords would get highlighted or flagged or if a price movement breached or an average um Options volume breached a certain five day average You would get flagged. You had no idea what the news was all you knew that there was something going on And then you investigate So do you see that similar in this scenario or do you see it? Well, I think so with um You know algorithmic trading systems have been in the business of trying to Let's say interpret news and place a trade based on that information As fast as they possibly can So this has made the efficiency around how price reacts to breaking news the efficiency has been Driven ever higher and higher and higher. Um, I know this firsthand because I used to trade As a human manually Our job our edge our strategy was really to trade the inefficiency but there was between prices of assets reacting to certain scenarios. Um so this is like Prefun it like I started trading in 2002 right 2002 three four five Okay, those years were great years where there was huge inefficiency. It was arbitrage trading Okay, and you we would trade I don't want to get into too much detail But we would trade like let's say for example different German government bond maturities We would trade the two-year bond the five-year bond the 10-year bond But we we wouldn't trade them outright. We wouldn't be saying. Oh, I think that Bond's yield is going to go up Okay, I'm going to short that bond because the price is going to go down. We weren't really I mean there was a bit of that, but it was more we were supposed to be hedged Right, we were supposed to have an ARP trade where we would Buy one bond and sell the other and we're trading the spread and we're really trading the idea that the prices of the two relative to one another is currently incorrect Because there's been inefficiency in how one of the bonds has reacted to a scenario compared to the other one And that inefficiency won't last and we're going to trade The fact the inefficiency gap is going to close and that's how we make our money And it was great, but then Algorithms came along that basically did that job faster than I could Okay, so one of the algorithms is to take trade economic data So this is numerical and it's very easy for an algorithm So you have let's say the us non-farm payrolls number is announced And then a computer Algorithm can go okay. What's the data? How does that compare to the expected figure? Okay, it's higher or it's lower than expected. Okay. I'm buying or I'm selling Whatever asset it is. Okay, and it became a race really it wasn't really trading The hedge funds entered into a race of who could build the fastest machine And they've got it down to literally like a nano second Where they can execute a trade automatically obviously Following an information release. Okay, but that's that's numbers And it was we still had an edge as a human Because it was like, okay fine you you algos you you crack on if you want to trade on those data releases That's fine. I've still got other stuff that's more nuanced I can trade the federal reserves, you know Monetary policy statement or the press conference when Jerome Powell speaking live Me the human being all right. I've got a higher level of intelligence compared to the algorithm where it's a it's always an if then Kind of statement. Okay in that algorithm So I as a human could be above that and I could interpret things in real time Particularly around language. So I was still very much at an edge and that's how we would trade based off These federal reserve statements and Powell speaking live. Okay, but but then Systems advanced and there's one called Google's Burt's model The next evolution was okay. It was language recognition. Okay, and but it was very much what's called a dictionary based System so you as the human would build the algorithm and you'd feed the algorithm with words key words And so let's talk about the federal reserve What words that a fed reserve member Might say what words would we categorize as being hawkish? What words that they might say? What would we categorize as dovish? And then you set the model up and then the model is scanning literally scanning for these words And then are there more hawkish words being said or are there more dovish words? Okay There's more hawkish. Therefore. This is a hawkish statement Okay, right markets should now react Like this x y z based off of hawkish scenario and the algo goes ahead and starts trading. Okay so What we're talking about here now a chat gpt is the next evolution in this journey Now you say what I'm interested about what you just said was the human still has the edge because We can take that nuanced argument and say well Yes, okay on the face of it if you're analyzing this in the first dimension fine Let's keep it on the fed right the fed is hiking interest rates Okay, that's hawkish. Let's buy the dollar Okay, that's the first dimension There's then the second dimension. It's okay. Well, they're hiking interest rates, but By how much? And are they hiking interest rates as much as expected or not? That's the second dimension. Okay And I think that's pretty easy for an algorithm to do as well because you've got an expectation versus the reality Okay, but then it's the third dimension. It's like, okay. It's not just that they've hiked rates What's the language they're using about how they might change interest rates in the future? And how does that compare to people's expectations, you know future interest rate hike expectations And what are they saying about inflation and what's the kind of macro sentiment and all of these things? And so it might be that they're hiking rates, but actually you should sell the dollar Because of this more nuanced multi-dimensional analysis that you can do but I would So you're you're I think you're suggesting that the third dimension the fourth dimension however many dimensions you want to go The ai is not yet clever enough to do that in a reliable way Not not in a reliable, but certainly not in a way that you would ever allow it to make the end decision Yes, there is a co-pilot to make that assumption Possibly faster than you can to guide you for yen you to make the judgment called pull the trigger In that scenario from a trading perspective But there is there is one thing that you've not considered which you might not have ever seen In your career given that you are sat on the other side of the table trading I was sat there aggregating information So when i'm sat there on a desk for 12 hours a day watching all these different news terminals, so I'd say I probably would have seen scan my eye on Seven to eight thousand headlines in one day Just sat there looking at Bloomberg Reuters everything in between So there's 30 screens on the desk that three of us were looking at at any at one time basically now the number of human error mistakes that come from the source of data Whether that's Bloomberg journalist makes typo whether it's Bloomberg someone's inaccurately Inputted the wrong figure Whether it's the bureau of labor statistics Has an error right i've seen it all and believe it or not when you watch 8000 headlines a day I would say they happen those mistakes on a frequency of about five times a day Wow, they happen a lot and you see Bloomberg all day long Or run headline that's obviously wrong They've put too many digits or the decimals in the wrong place or they flash something and then Five seconds later they put corrected and then the next headline comes up and you're like well, yeah, of course It's wrong So How do you account for that? Because the machine is reacting to its input Yeah Right. No, absolutely. Well. Yeah, but you could argue that the market will react So the inaccurate information So you'd have to build the model to make an assumption that if the incorrect Whatever it is is Is wrong within a certain Deviation then it could be accepted as believable by humans who might trade it But if it goes beyond that it's obviously so far wrong that no one would actually look at that And I know this from the time when I squawked Hike 100 instead of hike 25 for a bank of england decision very early in my career and not one trader out of thousands Listen to what I said because it was so far wrong Yeah, but you've you've seen scenarios Well, remember like talking about journalists getting it wrong. So the remember when the FT tweeted But the ECB I'm going to get this the wrong way around now. Did they say that they weren't cutting interest rates? Yeah, so the expectation was they were going to cut it was going into the end of the year 2015 And then they FT seven minutes before ECB leave rates unchanged Right now did react sharp. Yes, right the market that's because it was the FT Okay, so it's coming from it's coming from a source that Is global globally disseminated instantly and it's a reliable source Right, so markets react, but then fine. They pulled the tweet and they corrected it, right? So your algo needs to be clever enough So then pick up on the fact that that second scenario has happened and and Realized that the initial market reaction is not sustainable and needs to be reversed, right? But the value add in that sense is not only did that not would that not happen at this point in time? Likelihood is because the models haven't been trained that way Yeah, in that situation I called my contact at Bloomberg and I called my contact at Reuters And within I'd say 30 seconds to a minute Then I've got the intel that That's not come out. That's not official. No one's said anything. We can't actually say anything yet but It's BS, but then So then yes, the algo can react in the first part But the multiple parts thereafter what I'm saying is is that There's always another Unforeseen I sat there for long enough where it was like just when you think I've seen every single Thing that can go wrong. Yeah, the other thing happens and it's what about that one time There's something completely. You know what it's like to trade Let's say you're in a massive position And it's that one time When something just completely odd happens from a news perspective And then the algo Does something wrong Well, I think this this conversation I think is a very Good one that speaks to them the more broadly about where we are with AI I think you used the right word earlier co-pilot, right? I think right now in terms of this it's so brand new, right? You're right. You shouldn't it's not good enough and it's not mature enough to just Let it entirely Do the job of a trader? But it's a great co-pilot that can help the human being I would say also A lot of the examples we're talking about here are human errors But surely the number of errors Will dramatically reduce Because we won't rely on humans to input Data Type in a number and then hit post and it drops onto the Bloomberg terminal. It won't be a human being doing that So those types of jobs will be eliminated and then the human errors will reduce. But yeah, I think AI Is disrupting obviously will disrupt everything When finance is certainly right in amongst that for sure Okay, well, let's let's you got two more subjects to cover off. So let's talk about goldmans And their first quarter results came out earlier in the week on tuesday. They missed Missed expectations on revenues after taking a $470 million hit tied to the sale of consumer Loans, so they're still trying to reverse out of that business So to speak and feeling the pains of that process their company wide revenues This is the interesting part and what I wanted to talk to you about the company wide revenues fell 5% That was below expectations. So other than the consumer loan hit weaker than expected bond trading Particularly and asset and wealth management results were also weaker So we're talking like an investment banking fees not getting a mention here because we know the states of that They're already pretty depressed at this point albeit a couple of big deals in the farm space coming through recently um, but fixed income Currencies commodity trading revenues were down 17% Still a pretty chunky figure 3.9 billion, but that was below street estimates So below estimates and also lagging peers in the group Namely jp morgan city group. They had increases over this period. Yeah Yeah, I mean the The bad news just keeps on coming doesn't it for goldmans. I mean they are having a shocker um, and really have been for All right, you would say the last couple of years, but I think it's all coming out in the wash now We've talked about it before they made that major pivot or tried to to enter the the consumer banking market and it has spectacularly failed would not be an overstatement and to the point where they're now reversing out of everything and taking a massive hit in the process Um, I think what was it that green sky company? Yeah, so one of the things that that kind of came out of the earnings was the other than the loan book side of things The banks initiating the sale of green sky Which lends to customers making home improvements And that's just 13 months After they play paid a very toppy fintech Yeah, COVID-19 bubble 2.2 billion dollars basically I mean, so look it's cost this is but you could argue this is short-term Stuff where okay, we had a major strategy idea. We tried to execute it It's failed Let's write it off and let's go back to our core. Okay the biggest problem of all for me in these earnings And we kind of knew this is all bad on the consumer side, but the biggest problem Look, okay, the IBD If they go back to their core Well, what's their core? Well, it's IBD in its markets and you could say wealth management now, but that's still a spin-off Not a spin-off. Sorry. That's still a smaller entity, right? So it's their core's investment banking and markets So let's drop back to the core. Well, one of those two pieces of the core engine Has stalled as it has done for all of the banks. That's the IBD side deal flow has collapsed And fine all banks all IBD divisions is having a really bad time of it revenues are sharply down No fault of their own It's deal flows dried up So then it's the other core part of the engine is the market side and this is where other banks and it normally One balances off the other and other banks have had a really good period for markets They're fixed income trading divisions, for example revenues higher because of all the volatility we've had in markets Over quarter one and it's this volume And volatility that tends to be really positive for markets revenue So the big clanger here in this report Is the trading revenues are down quite sharply Whilst their peers seen trading revenues going up. So I don't know what's going on In the market side at goldman's but at the moment it is just It's just disastrous right across the piece. So We were kind of saying offline before about how Solomon could stay on a CEO in this Given this run of negativity that they've had perhaps from a strategic point of view Um There's still a long process to go through to exit that consumer part of the business So i'm not saying that i'm privy to any special information, but Yeah, maybe you just need I mean, this is a bad period And it's probably going to get a little bit worse given some of the things they have to do in a period ahead and so If you were going to make a change, let's say we are the board or the chair Yeah, wouldn't want to do it probably quite now Ride it out and come with some positivity It's almost like when you have that transition at the helm You need to pick the moment where there's some momentum in a positive fashion coming out of it I don't know about that if I was on the board I would definitely be looking for an alternative to davis solomon right now I think Yeah, I think he's done I think he's just not Managed The company well and not well enough. I mean, all right They had a major strategy on the consumer banking side Which has failed but it looks like that in the meantime they dropped the ball everywhere else as well And I think I don't think You know, it's like a football team right if if you've just lost 10 games in a row But you've only got 10 games left to the end of the season. What do you do stick with the manager? No Get him out. We need someone else to come in and we need you know Start from start from fresh new fresh set of eyes And that can give you know the market's confidence that all right fine. You it's a new chapter I think they need a new chapter now And that requires solomon to go again Is one of the issues there that using the football analogy If you're running a major champions league contender These there's only a finite number of managers who can run at that elite level. So who do you replace him with? So I guess you've got to look internally, right in the interim at least as they do in football Well sticking to the football analogy. We are in a very weird scenario where actually the number of Champions League Qualified managers that are available is like a record high There's a lot of like a Tottenham of Sackler manager Chelsea of Sackler manager Why realm of journal may be looking to change why because all of a sudden you've got five or six managers who are Top of you know top of everyone's list permanently and actually they're all available So weirdly That's a very unusual scenario. You're right on the banking side. Well, don't you look internally? But then I guess you could say well If they've been part of the team, right that's failed Well, then Yeah, so no, I do agree. It's it's not easy to change CEO And so particularly when you're taking over like a man united Yeah, indeed organization of the banking world of like pedigree history Yeah, yeah, but that doesn't mean you shouldn't change though Because it's hard to replace doesn't mean you shouldn't replace Yeah, even Vengu got it in the neck in the end All right, UK CPI just a wrap Um, probably quite quick on this one because I don't think it was massively surprising but inflation UK consumer price index did drop from 10.4 percent in February to the latest reading of 10.1 The problem there was that analysts were hoping for a deeper drop to 9.8 The core reading so x food and energy remained unchanged as 6.2 percent Thoughts on that Well, yeah, just higher than expected I think yeah, what's that what was key about 9.8 and this is very human behavioural 9.8 was the forecast, right if it had to have been 9.8 Then that would have been the lowest reading Since june of 2022 because it But because it's 10.1 it stays It stays quite the chart looks quite flat Right rather than what you want to see is a downtrend you want to see evidence, but the downtrend Is in place And you can see that if you look at the US CPI chart you can see that clearly the UK CPI chart is still flat There's no trend. I mean, it's not trending higher anymore great But it's not trending lower either And I think that's quite key here with this data the trend stays flat We were hoping to see evidence that the downtrend Had begun and that evidence didn't materialize So I think that's the that's the takeaway. So yeah, the Bank of England may well Hike more and continue to hike so Yeah, not a good week for a Rishi though So can't really bang on the drum of inflation finally Falling in fact worse because food price inflation Hit a record at 19.1 percent That really hits at the heart of the voter right in terms of cost of living crisis And then I just saw Dominic Rab The UK's deputy prime minister resigned over the second case of bullying Since Rishi came on board. So yeah, just to kind of Yeah, woven a bit of politics into it just to finish then this is why people like musk Are saying that the next 12 months look stormy because inflation is staying high like Go down to the shoot supermarket and buy your essentials prices are crazy high and in the end Interest rates will stay high or get higher and in the end something's got to give here And what will give is consumption It'll drop And that will cause a recession And that's the only way to bring these prices properly backed out to get inflation back to 2% Really the only way that's going to happen Is a recession? It's just that markets are not pricing it yet. They're pricing weirdly. I don't know they're pricing like a a soft landing at worst and and I yeah, I still think That's wrong in my humble individual opinion, but hey, what do I know? It's okay. What I'll do is I'll pop down to curries going by myself a peers current 2.0 latest version Plug it in see what it comes out with And uh, cool. All right, we'll wrap it up there. Thanks very much peers. Thanks for listening everyone and we'll see you next week Have a good weekend