 Okay, hello and welcome to episode 75 the market maker podcast and a little bit different than our usual routine because Piers Curran is on holiday again and Piers, I know you're listening so enjoy yourself, but Come on. You've got to do some work at some point, but instead in his place We're gonna change things up a little bit and I'm joined by millen deep Bassie and And hey millen and millen is part of our technology team and what we're gonna do is I'm gonna quickly wrap up All of the things that have happened in markets as quick as I can because I'm just conscious of there's a lot has been happening I don't want anyone to go without and then we're gonna bring millen into the conversation and We're gonna talk a little bit about his background and his expertise Where he helps design and deliver some of our most advanced quant related training to the likes of Citadel for example And so really want to pick his brains and get into that subject matter because I know it's a real Growth area for a lot of students and future applications. So first off What's been happening in markets this week? So Mega cap tech earnings have really dominated and actually I guess summary they weren't as bad as feared Can't be said for all of them meta Facebook Continuing to fall on rough times, but let me just go through a few of them. So Amazon last night We're recording this on Friday 29th. So Thursday night their shares went up 12 percent post market We are talking about one of the biggest Companies on planet Earth going up 12 percent So that's a that's a huge move strong sales and a strong outlook lifted their shares Apple will also up 4% last night beating on revenue and profit early in the week We had Microsoft that she turned in their slowest revenue growth since 2020 at Just 12 percent year over year growth in the quarter, which is quite insane on the conference call more importantly So although their revenue growth slowed on Their outlook they said they expect revenue operating income to increase the double digit pace for fiscal 2023 and the shares rocketed after that alphabet missed on most numbers I think when you're watching those coming out earlier in the week, you're thinking who doesn't look too good But their advertising revenues came in at fifty six point two nine billion and that was above expectations There was a lot of anxiety in the market about these online advertising Stocks because of the precedent that's been set by snap and Twitter who had disastrous figures Because of marketing budgets generally just being slashed with the looming recession But Google's stranglehold on that digital spend being what is ultimately? I guess a necessity for businesses is keeping that ticking over nicely But meta as I said reported their first year-over-year revenue decline in Q2 and It's gonna get worse and so they expect a range of 26 to 28.5 billion US dollars in Q3 revenue and That was against the street estimate of over 30 billion. So they've downgraded their future outlook They cited continuation of weak advertising demand environment We experienced in the second quarter, which they believe is being driven by broader macroeconomic Uncertainty, I think I read on their their press statement and then listening to a conference call I think I heard the word tick tock more than I heard the word Facebook So that kind of is a summation of their fears. I guess at the moment Bringing earnings a little bit closer to home shell the oil major there to accelerate their share buyback program They reported record profits for the second consecutive quarter obviously Beneficent from surging oil and gas prices Francis total energies, which is their other I guess competing Big company within that space reported this week their second quarter profits that had almost tripled so whilst a Majority are suffering at this point these energy stocks have really benefited from that energy squeeze on the macro side The European gas crisis is going from bad to worse that is influencing then and Really destabilizing consumer confidence in the eurozone, which is now at a 17 months low The key factor there is flow on the Nord Stream one pipeline that critical pipeline Servicing then gas flows coming out of Russia particularly to Germany That's now been cut to just a fifth of normal capacity and there's a lot of pointing fingers between Who's blamed that lies on in that sense so other things Q2 advanced GDP in the US at fell 0.9% on an annualized rate and that came after 1.6% decline in the first three months of the year meaning two Back-to-back periods of contraction now for the US so All the different terminology aside This is a technical recession and so a lot of pressure now for what are the Fed going to do next and We had the Fed decision. They delivered back-to-back 75 basis point rate hikes, but they surprised with the dovish Hint that the Fed could slow the pace of rate hikes Actually, if you were looking at your US equity charts, I think we're up over 7% in the NASDAW 100 in the last 48 hours or so so kind of The worst case averted for any fears that might have been present for these big Megacat tech earnings in combination with the looming slowdown With the commentary from the Fed in the US has meant that then rate hikes have been paired back And in fact, European stocks are now looking at their best monthly gain since November 2020 and the NASDAW 100 It's just hit a seven-week high Talking of risk appetite if stocks are rallying so is crypto It's a mill and you'll be happy Bitcoin ether heading towards their best month since 2021 Ethos up about 72% on the month alone so Seeing of their movement there as well, but undoubtedly the biggest news of the week, of course was McDonald's raising the price of their cheeseburger. Did you see that mill? Yeah, that's all right How do you feel about that? Well, I'm at the point where I've noticed near me. Anyways, I have three McDonald's on the same road I've got to each one. They have different prices now There's one in the middle, which is the most expensive and that's now going to be like over five pounds for a meal And I don't want to go there. Okay. No, we've got an arbitrage opportunity here I reckon we should buy some at the cheap place will park out the expensive one and sell them on discount So look, we've got a business idea there. But yeah, the cheeseburger in the UK has gone up 20% And and it's the first time in 14 years. So Yeah, the cost of living crisis is real folks But look, let's let's delve into a conversation then with mill and really happy that he's taken out some time to talk to me And really it came about because at the moment, we've got our summer analyst training program happening and millen runs some really cool Simulation sessions with them that particularly around python and programming and quant trading and I jumped in and it's the complete other side of the air of markets I work in and I was in the office the other day looking at millen's screen And it made me feel it made me feel sick if i'm quite honest because it was just full of code But millen perhaps you can tell us a little bit about yourself and your background your rollout amplifier and then we can go into Perhaps a bit more of a conversation about The kind of tips and tricks about the quant space Yeah, of course, I think I found amplifier. I think back in 2018 now My dad showed me and he was like you should be a trader traders. You know, they have nice cars. They live the lifestyle, you know Uh, the the stuff that used to kind of get sold around back there. So I was like, okay, you know what this sounds good I'm gonna I'm gonna check these guys out. Maybe I'll have a Ferrari or a Lambo or something by like 25, right? I was hooked on the dream at 18 And I was studying computer science at the time. Um, I roll a hallway Um, and I was like, I remember telling people I was like, I'm gonna shift, you know I don't want to work in these fine companies. I want to I want to be a trader. Um, that didn't go very well, but Uh, the point was I guess is My dad got me hooked on finance. Uh, and then from there, obviously He did the program with you guys for three weeks and Back then it was in person and uh, it was an unreal experience to still, uh, you know I still talk about it with with people today. Um, and then Things clicked in place and I started out as an intern and I used to do a lot of the the grunt work I guess and no programming back in the days I used to Little things like fixes excel. She had a formula or something here um, and then As I did more of my degree, I guess I found out where where my passions I would like java and python and things like that And then I've kind of transitioned across many roles So I think my my current title right now is like a a full stack DevOps engineer Um, which basically means I can do, you know, your front end, which is like your html your css You know making things look pretty Um, but then I can also do the back end which is all the logic and you know all all the complicated things And then on top of that most people's careers can normally confined there I now also do networking and things so I can set you up serve as I can set up all all this other stuff as well with internet Um and things and yeah, I basically do what apparently three jobs I guess it but I get the title for it. So it's worth it. Um, and then you deliver of course Yeah, yeah, so so that's the next thing my title also says i'm the fintech product lead right now, which is Basically like like aunt said, um, I create the corn oil or even algorithmic trading products now and then We go to our clients and deliver them because I want to help other people program I think it's a it's a great skill to have and You know, I think the more people that understand how code works and hopefully they don't get headaches from looking at it Um, it just makes everyone like life easier and kind of good for the future, right? could could you Have done what you're doing now without studying computer science I I don't think so. I think um It's a very difficult thing because I never touched any code until I was 18 And I think a lot of people have this misconception where if I don't do my My like programming a level for example, that's my my career gone out the window So back in a levels. I was primarily into economics. That was my my my strong subject, right? Um, and and I only went out kind of went to clearing on that day I decided I'm going to go from accounting and finance as my degree to computer science just Like that on the day because I didn't get the results I wanted for accounting. Um, and obviously I think You know kind of to get to the point where I am at. Yeah, I think I need my degree and the only reason is because a lot of uh Like probability and statistics and kind of the way you problem solve is what gets taught at uni I think that's the most valuable thing you walk away. It's not Kind of knowing how to code is the the way to look at a task and break it down And go from there, but it's not something you can't just you can I mean you can learn it online I guess it's just there's no real structure when you learn online Obviously with with a degree you just get that that kind of structure and path Yeah, that that kind of structure way of thinking you just mentioned Is we talking maths then? No, so I don't use too much maths, but it's more of like if you pose a question to me like These simple things like I want this button to do something I think a lot of people would get fixated on on the wrong thing. They might look at it and say Um, you know, I've seen in the past with some people they get focused on the end result rather than how they're going to get to the end result So I think when I say structured thinking, I mean you need to be able to Look at the task say I need to do x y z. I need to go in this order And and the problem with with with our jobs, I guess when you're in your engineers, it needs to happen now I don't have you know a week. I can't say to Manager I'll be back in a week. I'm gonna go and see what this button does You know, I need I need to look at it and say, you know off the top of my head This will take me a few days. Maybe you're you know a couple hours and I think That's that structure thinking because I need to be able to quickly say, you know, I need a E&C completed before I can do, you know, whatever whatever I need And I think that's the hardest thing that they find that a lot of people can't get is If I you know when I run the sessions is a lot of people get stuck on the How does this go to that and then go to this and it's just because they feel like there's a lot of magic in between um so It's a bit of a difficult one. I guess And is there any way in your mind to improve that way of thinking like things you can be doing like even outside of That actual task that are just general using that same memory muscle or brain muscle Yeah, I think um, well, that's where the kind of the you know, like a business analyst kind of role comes in I think one of the the lucky things of doing my my placement year with with amplifier was I had a small time where I was a business analyst and my main job was kind of You know to talk to someone like yourself and and say what do you need done? And then obviously I need to convert what you need done to what what the engineers need And being that kind of middleman translator almost from you know, just like One or two sentences to maybe a whole paragraph detailing what needs to be done is what builds that skill And I guess how do you do that yourself at home? Well, it's like if if I say to you I want to build an alga strategy the first thing I need to know is where do I get my data So googling where do you get the data reading up on it? You're putting that into maybe like a notebook and saying, okay, I can do x y z And then from there you have to pick which one I'm going to use and It's kind of just building projects from from Start to the end without kind of cheating Um rather than just saying go to a youtube video, right? Or watch this for four hours. The guy's going to teach me everything I need to know Um, I used to do that, but there's no fun, right? Because you don't have that research phase and you're looking around and figuring things out yourself Hmm Okay And then I'm just thinking about then you mentioned before just going back to computer science because I know a couple of people are I kind of thinking of that as subject To to potentially study or study further But I heard you say before about you've got a friend who was studying at a different university and he was The difference between having good algorithm skills or good programming skills What do you mean by that like how is that different? Yeah, so I think this is one of those things where when I got to uni I thought you know you get taught the same thing everywhere, but with slight differences But what I found with with my friend he went to to Loughborough Um, and the way they taught his degree and the way he's kind of come out at the end of the three years is If you had a question about algorithms or any more of a mathematical Kind of problem I would say You can ask me but it might take me a bit longer than than him Likewise when it comes to to programming basically You ask me I'll I'll get the code written and Working quicker than he does and the reason being is I think he had more mathematical modules So he learned more about like the theory and the the key understandings behind computer science like what makes things tick and um, you know But for example execution time, you know, there's a whole Maths and a bunch of formulas behind how fast or something being how do you calculate that? um And things like that But I had I think maybe two terms of kind of lessons on that Um, whereas he might have had maybe I know like for in my final year. I didn't touch a single bit of maths um, my primary kind of Modules offered to me were around information security So I have a lot of knowledge in terms of being very like safe on the internet, you know Like hacking and things like that whereas he was offered more Like it's algorithmic stuff. So His knowledge on that on that stuff varies and I think that's the One of those things when you're 18 and you pick a uni, you don't know what what are they going to teach um, and it just happened to be Raw Holloway caught a lot more programming So I think when it comes to he's come to me in the past Actually, when it comes to writing code, he'll come to me and pose a question Me like can I do this in python? Can I do this in java even though on paper? We're the same person in terms of our degree and what we achieved um I'm better at that unfortunately and he's better at the the algorah side of things and That's the tricky part is when you're kind of looking for for talent I guess is you've got a batches in computer science. You've got one Who's the better programmer? But then okay, I might be the better programmer But then I could be absolutely rubbish at my algos, which is not going to do well like a place like citadel, right? So what was the most common then is it that? Most people are specialized in an area like that rather than a generalist I mean in a typical like Citadel team then you have multiple different specialists covering them What would those areas be? Yeah, so so citadel just from a Top-level breakdown. I guess they kind of split people into investment and trading These are they still have computer science degrees But these will might be people who are on kind of the front desk any trading job, right? And they'll be good at risk management and actually reacting to markets at the same time And then another role is is your quantitative research So a quant research is pretty straightforward It's going to be someone who creates these algos and researches them and and finds all the maybe, you know discrepancies in the market through statistical analysis and models, right? So this might be someone who's really good at maths But they'll like I said, they'll still have the same background They know how to program they did computer science And then you'll have software engineers and then software engineers are those who can program And kind of create the systems for the other two to use perhaps And then you can see like everyone would have the same background almost but they've split them into kind of these three groups of People so you've got your your maths heavy So I would tell my friend for example If he got the if he understood finance a bit more you go for a qr all because right you'd excel there Myself personally, I'd probably be split between software engineering and investment and trading I'd have to kind of try both out, but um, you know other people are kind of Program more than anything I'd say go do a software engineering wrong, right? Because investment and trading is a very I guess that's the hard one to find because you need someone who can program Manage the risk and understand the finance and and react to things Like you would as a trader because you're basically managing live live code Yeah, I remember being pulled in because there was a market event that had happened and They wanted me to come in and give a quick sound bite I think when one of you guys were training with them And I remember I was talking to one girl and she was previously interning at nasa And I was just like some of these series are my mind my mind's blown now I used to work as a 16 year old in mcdonald's Yeah, I worked at toby carvery so Humble beginnings, I guess But but talking of these people then when we're talking about These kind of elite level financial institutions From your experience then because I know that's not the only one that you you've dealt with What's been your your experience at your interactions with these people because I think there is a degree of mystique around Particularly the quant side of the the industry Yeah, I think um Like obviously from my my cohort at uni I can't think of these people that would work at these companies because uh, they're they're kind of more I don't know how to describe it I couldn't pick someone from my whole cohort and say, you know, he has the skills for sister though And like you said because there is a I don't know where they find these people Uh, they're like the the talent and the way they you know, they come across is Very much like, you know, you I'll speak with peers once I was like you look at them and you think there's your average geek and Kind of um, you know, you'd expect them to work in like a fang or whatever right do it do it kind of a more compsci stereotypical job And then you speak to them and you realize these guys have immense knowledge about finance already at this such such a young age um And I think that's obviously that's why it's such a lucrative role almost right you're you're you're looking for A needle in a haystack that can kind of do something that's not I mean, I I can't I was looking at masters for example It's very hard to find a degree where they'll teach you compsci and apply that to a finance background So computational finance for example, there was only a I mean it's taught widely But there's only a few places where it actually taught well Um, and I think that's the tricky part right like I can go do a masters and compsci But it doesn't mean I'm gonna get this job at that citadel because I need that specific kind of Angle I guess and then that's very hard to find and I think the way you'll find someone like that is someone who Like myself, I guess is someone who's been interested in finance for a long time and kind of you know in their free time You know what watches the news and keeps an eye on things like markets like You know, we've got what 10 15 engineers now at the firm and I tell only myself and one other Actively keep up with markets just because we yet we have a shared interest I guess in that and the rest are just you know, they do their engineering things and And whatever interesting So the key that you're saying then is that Um, if you want to apply that technical knowledge to the financial industry You've got to still have like in any other traditional role like in global markets as an all standard trader You've just got to have that curiosity and interest in the subject matter itself as well as the technical sure I think if you like obviously if you're applying for software engineering I don't think you need it as much right because you're you're mostly going to be in a back office Um, but these lucrative Front office roles I'd say it's the skills are the same Um, which is why I think you know without bragging. I think I I do pretty well and because I did the program with you guys went back when I wanted to do finance, right? So I I took all the knowledge in and and and everything that we teach and and kind of You know, I I guess I I owe the pro if it wasn't for the the internship. I guess Uh, I wouldn't know half the things I do and I wouldn't be able to do it. Um Because I got in early. I guess when I was 18 and in my head and you had to carry on, right? Because you know well Let let let's talk a little bit about what you've got cooking in the background then because I know you've always got your fingers and a couple of pies and I know you uh You were early on the whole crypto move. You were early on the whole busting out of a lot of the game stop action when coveted hit From from uh, just general market interest point of view. I don't know nfts or just any algorithms you're working on Is there anything at the moment? that's floating your boat Uh nfts and and crypto I've kind of left behind. I think uh, I think I've told you a few times I'm kind of I burnt myself out on On that and I think it was uh the the peaks kind of you know last year around march, right? It was when I had my nft. I had my crypto hype back. I was like I was in this I'm gonna hold this for the next 10 years And then just suddenly I have nowhere one evening. I think I told you right I was like I was sitting here at 4 a.m. In the morning. I woke up and I was like I should sell my ethereum. I don't know why but I looked at the price and I was like I've been watching this for a couple days. It's not moving and since I sold it. I haven't touched Yeah, you're you're so you're the ethereum whale who got out at 4 000 or whatever it was then the drop the market Yeah, yeah, yeah, that's the thing. It's quite funny because I remember Especially I just woke up randomly in the middle of the night and I was like getting rid of this It's I have my hype has just disappeared during my sleep So have you actually run any models over the crypto data And what was that? What has that told you if any information is? Um, I had a few algos Um, they were primarily technical And the reason being is I don't want to go into the fundamental side of algos because When it was fundamental analysis, I guess in terms of news is I can't compete in speed You know, like the oil release for example All right, cool. I could probably get the number as fast as you can read it but You know, there's so many people out there who and this was one of the interesting things I guess when I spoke to a sister one of the engineers, he said they don't care about Seconds between trades. They care about like the nanoseconds between trades Um, and he because it you know to the point where you obviously, you know These these firms have their exchanges in the same building as the actual exchange when they're executing these trades. They're like Maybe across the corridor from them In terms of myself with the models, I guess I most of the strategies I've had kind of Uh, they used to work, I guess up until this year Um, you know, they they looked good on paper, but unfortunately I developed them this year So when I when I I've let them out and and I was expecting them to do things They just they just failed and I think that's that's the hard part I think a lot of people forget is you know, I well, I've been working on algos now for four years technically on and off But you know, you you need to to keep trying because and even when it does click it might work for a week And then you know markets change and and then it'll stop working even though You'd think oh, it's it's the same strat. You know, I might be looking at something like, you know Whatever you're doing and I think that's the the bit where you get frustrated you get annoyed You feel like, you know what I've wasted my time almost You know countless hours of coding and you're like, I'm just gonna shelve it So I have like on my I have a folder that has a lot of code in it and different strategies over the years and The problem is one of them might be working right now And I and I don't know because there's so many right and that that's why you have these Now it clicks in my head why they have these massive teams because you need people to Go back and look at these strats and say, okay, it used to work But what's slightly changed and obviously a one-man job on on that is quite difficult So just just a kind of general Question and I'm not expecting like a definitive answer but take like where we're at in the market at the moment where We got an inflation situation where it hasn't been this high in multiple decades Now from a data perspective, what would be interesting is to go back and look at color kind of fed rate behavior when inflation was last in in modern history at these types of Um levels in order to then calculate what might the fed do in the future How do you like from a data perspective? I can kind of see how that would make logical sense But how do you start to then overlay in like the aspect of That was 1980 we're now in 2022 the market dynamic is incredibly different now in terms of You know the dynamics of who's involved and how they're executing and managing these positional trades. So What would be your first kind of go-to then when you're looking to try and like um, I guess spec out that type of question Yeah, I guess um when when it comes to analyzing the future and things um, obviously this is when You throw in machine learning and things like that. Um, and the reason being is the machine learning You know, it's a buzzword and it gets thrown around and literally everything has machine learning these days, right? apparently But you want to take your data like you're saying and just basically just extrapolate it into thousands and you know hundreds and thousands of different outcomes. It's kind of like, you know, um When you for example in the movies, right when when doctor strange does something and Timeline goes into, you know thousands of different ones or or anything like that. It's the same thing you want to um Take this data and say, you know predict You know a million possibilities that that can happen And then the thing is then hardest part in my opinion is then you have to rank them and you have to And that's I guess your your your secret sources, right? How do you look at these a million possibilities and say? This is the best one or or you know, this is the worst one, you know I guess if you can crack that that's how you'll you'll you'll make the money and I haven't cracked that yet Uh In terms of being able to say like obviously because the problem is right you might google it and you're like, oh, no There's there's an answer right there, but it's on google. It's that answer is not going to work, right? I guess it's like like anything if you want to make a good algo even You need to it needs to be your own and and that will be your edge It's just like trading right every trader might have their own edge The same thing applies here. I guess is I can google it and I can tell you oh, yeah Let's apply this model onto it But if it's on google that's not going to be the one that That works and and there's a reason I guess it's publicly available I'm sure like sister. They'll have have stuff that would rank things and yeah These models and and that's where the the value is I guess so that that kind of again that terminology like machine learning or ai Well, I mean Is this just fanciful to like to be talking about because I know what you mean like You get the sales team involves and all of a sudden your product has ai machine learning like Potential but what's the reality of that in your eyes in terms of where we're at at the moment and then to where it's heading over a Longer period are we like in the infancy part of it at the moment? Or is it more developed than that? No, I think we're still in the infancy like obviously If you look at nvidia, right? There are graphics cards up just now putting the power I guess of being able to actually do like lost computations in the hands of your average average joe, right? You know as we progress and I've seen this, you know, they're focused less on gaming these days and performance and focus like You know our our graphics card can also do xyz in computational power I think as time goes and and you know this computational power trickles down to your average joe Um, then I guess is is is when you know machine learning makes more sense like, you know, even with the iphones, right? Like only the the new iphones have those, you know, they obviously they added that dedicated chip just for like machine learning and things like that in your phone um Only now that because this stuff's happening I would say that machine learning makes more sense to put into a product But like you said they slap the title and let you everything and sometimes the machine like machine learning is I'd say It's misunderstood because there's different ways and different levels Like you can slap a label and I could have the smallest amount of machine learning Which is which might just say and likes coffee someone else likes coffee like that's a trend um, you know That's all machine learning is right. It's like, okay five people like coffee now and they all live in one area You know, there must be good coffee or something there Well, like that's not the machine that you think of of in your head, right? And same with AI. I think At the end of the day, I think, you know, it's an oversimplification for all AI But I probably might get some slate for this But it's just a bunch of conditional statements at the end of the day Um in terms of decision-making, right? So I could make a robot and you could ask it like five questions It'll make decisions. I can I say that that's an AI You know, you you asked it five different questions and it made a choice Obviously, then if you try and do other stuff we'll see it's it's not implemented yet. Yeah You saying that then in that kind of more narrow structured way and being a consumer of Netflix content So then at this point, how do how how I know this is a massive question but How do you then start to counteract then the designer's influence on the struck instructions that create the underlying architecture of these Of these systems. I understand these systems can grow out and then design their own pathways, but the core architecture has to come from like a you for example, and You will have Some degree of biases. No, so how how do people address? Where's that conversation at the moment because I know that's a big one um, I think that's that's a tricky one like, uh, even Yeah, I don't know like if I make an allegro like you said I will have bias because I think one way is right And and obviously you might think another way is right. Um, that's why most of the time when when you see these people, um Making say AI that there are rules kind of in place, you know, it's not officially in place but you know like guidelines that kind of an ethical programmer would it would adhere to and you know, uh in terms of You know, you don't want to make an AI that just hates everyone I mean, I've seen the AI that hates everyone wasn't it on twitter or something, right? Yeah, yeah, so like Like it's a very like it's a very hard question to answer. I guess it depends on it I think like I'm just assuming anyways I'd assume that if you're a massive company and you're working on AI You'd have a team because you'd want to make it as neutral as possible you And that's unfortunately the thing like You're basically just taking someone's brain Hopping it but making it unbiased and that and that sounds so hard to do because You know, even from a from a trading perspective I have to make an algo that I might flinch off to say hitting my stop loss like You know, they say I hit five trades in a row on my stop loss This algo needs to hit those five stops and keep going at the same rate It did the first trade, right? It needs to be unaware rather than I might be like, oh if my algo hits five stop losses I want it to now Use a tighter spread That's putting my bias into the program and then it might make the the the algo worse essentially Um, whereas I should be taking it as the algo has no emotion Every trade is should be the the same trade, right? Regardless of the previous results So, um, yeah, I guess I got two things that I read recently one was Um, just trying to recall the details, but it was Nomura put out a note about They were using AI for ESG scoring And I get that because then that was basically more about just these monumental data sets And it was generating certain pattern recognition that could then identify trends that a human would never be able to see That then similar to the other example I had was when I mean When I started using twitter for markets I mean, this was A long time ago over a decade ago. I guess and back then it was like Not a well-recognized source of information as it is today And there was lots of pop-up companies coming out and I'd have software aggregation tools that would then pick out on the hose pipe and alert then A team of analysts that would basically then add the human layer of then of the million tweets the machine's punching out 500 important ones it beams and then the human picks out the 10 Yeah, there was always like There's always the human element. There's almost like the pilot. It's almost like being in a super sophisticated aircraft Where the plane it can kind of fly itself But the human still needs to sit in it to a certain extent because of the You know the what-if scenario or is this actually the right decision for the context and things like that? So yeah, I mean that's how I've seen it develop in my career And that's what I was still reading with the mirror as well the other day Yeah, I think it's like you said that you hit the nail on the head there It's it's exactly the same still like obviously says they'll hire their investment And trading people and they do what you said like they'll they'll have the strat running But you have that that individual you can rely on and if if something you know goes haywire or It places the wrong trade you need that You know the the pilot in this case. I guess to put things back where it should be Um, and I just had a quick look at this this numeral thing that you mentioned actually. Oh, yeah I attempted this with reddit back back during the Um, I try well, there's other websites that already do this But I was like I want my own one that kind of does it for me Um, and it was just great reddit for every new post coming into wall street bets and just say You know analyze the sentiment because you know, so you have natural language processing, which is basically You look at text and you compare it to a dictionary or you know a library collection of words that will say The word bad is is negative, you know If I said the stock is good that that's a positive sentence Um, so I'd look at a headline on reddit and it might say like You know everyone uses the dollar sign for example just to to make it easier So I'd say okay in this text look for the dollar What are the what's the ticker after the dollar? It might be like dollar amd Um, then what what is the rest of the sentence and then from that I'd give it a score saying okay That was a very positive one. Um, and then I'd add to a counter saying this was mentioned once in the last 24 hours It run, you know constantly all day reading these posts and and all I'd get at the end of the day Still manually like you said right I'd log on to it. I made a web web panel for it like an admin panel I'd log on and it'd say okay He's put in this ticker was mentioned x amount of times. This this is how many were positive This is how many were negative I can click on it and view all the all the different things And the reason being is I guess back then I was like, okay You know Yeah, yeah, who's next what I want to know over the the next couple days Right, there might be something that was mentioned maybe four times and then as it starts climbing and trending and you're like You know, that's the the next one and I hopefully hop on it early The problem I ran into I guess was like I said it as a as a one-man job um I didn't have the power to To to run this thing and and the data, you know, even my computer on 24 seven for example just scraping data and analyzing it um And then I think I had so much data I just didn't know what to do with it myself because you know, it becomes too much and and that's when you know, like Big firms would have these different teams. I guess where I need some I need someone who is a data scientist essentially and takes my data and says Am I analyzing the correct way? Right? Because obviously I did it from a very very simple point of view But like so there are way more intense ways. I guess of ranking things and the problem I ran into was And this is the one that I still bugs me today because I couldn't fix it Uh was what happens if you don't put a dollar sign or You know when wall street bets kind of clocked that people were checking on the red and running these algos they started using code by um for example Like instead of gme, right? They'd write something else. Um How do I get my algos to pick up these ones because it might say that gme was mentioned five times When actually it might be 500 because they're using their their own code, right? Um, and then problems ran into okay. Well, if someone puts two spaces Between the letters g and m and e So the permutation to start building out and you need that's where you need that maintenance. I guess Yeah, and that's where machine learning kind of you want your your algos to get smarter to say, okay Look, someone's wrote gme with one space yesterday, but now they're writing it with two that's it needs to correlate that to the same I was doing it manually. I had a text file where I would add tickers Um, so if I saw something already, I'd be like, okay People are typing it like this. I'd add it to the text file and then my my my program would start looking at it Obviously, that's not sustainable. Um, so that's another one of my many shelved projects I can see I've been there and I I tried it. I guess okay. Well, look just to conclude things I guess a practical element of You get told quite a lot rightly or wrongly if you're interested in finance particularly in markets and trading And this doesn't necessarily need to be quant. This could even be just more standard investment bank sales training That you need to load a programming language. I think finance students now get told that just like vanilla You should learn programming. Yeah Now a is that true and then b If you're going to learn the language which one and then I guess See how much do you actually need to know of that language? Okay, that's fair. Um, is it true? I I think so I think Well, so I like you might learn your programming language and go into your job and you might not use it Um, but I think what it prepare you're preparing for a worst-case scenario where let's say in six years You know, we we we don't know what the landscape will be like but if you already knew now how to code and and maybe have Just just all I ask of people is just have a basic Understanding so when you're talking to an engineer, you don't feel lost perhaps, you know And and what I kind of preach I guess to our interns I guess and just anyone I meet is But learn a little bit and you never know at your job. You might come up with an idea You know, you don't have to code the idea just coming up with the idea Could lead to to you revolutionizing a company, right? But if you didn't know how to think from a Kind of what like if you don't know what can code do for you How will you come up with these ideas, right? You want to Like he said, we're always pushing forward. I guess as a um as a race um, but You know, you need to Yeah, I guess that's my point is, you know, don't think all the millen says go learn to program I never use programming for the next two or three years I'm just preparing you and kind of giving you the opportunities to say Right, this is clicks because you know, people come up to me all the time like I've got an app I'm like because you don't have an understanding of how programming works. Your app is Too ludicrous, I guess for for for me to do anyways on my own or you know You're talking a couple million in terms of development for for your your little idea um If you had a better understanding for programming, maybe you might come up with a different idea and things like that So where do you actually start then what what's like the base language you'd recommend? So I start so I think this Surprises people I actually started with java even though I don't use java anymore That was I spent a whole maybe year and a half at uni learning that um And I did javascript and python and c and everything and I think When it comes to to learning a program in language, I think I always recommend python It's not the fastest You know cc is hands down. I guess the the better one for for for finance But it's the easiest to get into right you download you go to the python website. I think it's like python.org You download the thing You open up a notepad you write code and it just works like when it comes to java and things right there There's a lot more steps involved You know the last thing you want if for someone who wants to get into programming is Have issues installing the language and getting it running right you just want to I just want to point people to this Place and say look download this you get this this little notepad window write your code and crack on um I say python, but I think the the the one thing I always emphasize is Regardless of what language you start you just want to learn the fundamentals so things like variables data types, you know data structures um, you know writing simple conditionals for example and Loops and things like that once you Understand these concepts When you go and pick up another language all you need to learn is how to write it, right? I always say to people It's the same as English uk and english American right it's the same thing at the end of the day, but they they they say aluminum and aluminium um, and at the end of the day like You know you can understand it and my point is if you learn python and Um, I think going on to your question of how much I guess you need to know Um, I I always say to people about I say 50 hours um Would probably make you very not very good like you'd get a good understanding for programming So for example, let's just say with will right I'd say when we started this whole One shenanigans I guess as a firm um, will knew You know very minimal code and it would like kind of wouldn't be able to look at like maybe three or four lines and understand What's going on? Obviously he's been doing the sims with me and and I I remember once when we were meant to go to these states Well, obviously we got denied Um, we went to have lunch and I sat down with will and maybe soon about two or three hours of me just reading line by line Each thing in our quant program and explaining to him. How does this work and and things like that and then kind of will's understanding I guess is Improved and to the point where he was even saying to me He could run the sim almost even though he's you know, he's not an engineer obviously um He doesn't even code for a living right doesn't do it every day But you know repetition and I would probably say I've spent maybe 20 to 30 hours with him just looking at the code I've got to the point where with our quantum anyways that will almost Sometimes answers the questions without even coming to me But when we ran it initially it'd be to the point where will would have his hand up every five seconds being like milling Can you come here? So I think in terms of learning I'd say go for python just the ease of getting into things Um, and then how 50 hours I'd say but so 50 hours. I'm just thinking about the maths there So you I know we're coming to the back end of summer, but you could do it as a summer project, right? Yeah, so I think um, uh The easiest way to learn programming is don't okay, so go do your your code academies, you know Your different courses online don't pay for anything ever In terms of like, you know, 15 20 quid to learn python because you can google how to learn python, right? You know engineers have helped each other out, you know, all the resources are online um but basically pick A topic that you want to do don't just go in with the idea of i'm gonna learn programming and then follow the The course I'd say Say, okay, I want to build. Let's just see a very simple Uh text analysis plot, right? You give it a sentence and it'll tell you if it was bad or good That sounds horrendous and and really hard. I guess from from say for example, you would do it and right? It's very sounds really difficult Um, but then break that down, right? Okay. I need to Get my python code to read text That's now one like subtask on its own, right? Um, okay. I want to read the text from a text file. Okay, then that's another subtask And all I would say is just do that little bit by bit, you know Like lego you're gonna start with one little little piece and and just stop building it up the next thing, you know You'll you'll have your your lego baghati or something made um But like start with that and then you google, okay, how do I read a text file in python? Like, you know, it's amazing. Everything's there Um And you start from that and the next thing you know is you've done that the next toss right now. How do I? How do I score this text? How do I determine if this text is bad or good? Then you go down a rabbit hole of that and then you're you know, I think that's the best way to program because you're not doing it for the sake of Like i'm sitting down to to learn something, right? I'm doing this because I want to achieve something but at the same time I'm going to learn from scratch Um, and I think that's the the biggest difference. I think between myself and many programmers is I spend a lot of time outside of work. I guess just Writing random stuff, right and like I said, I've got hundreds of scrapped projects and just shelf But I learned something doing all of them and and that's what kind of builds you up into to being a good programmer almost And it's just like finance. I'm sure you can agree like you've probably spent countless hours. I guess Um, just researching and reading for your own enjoyment as well at the end of the day Yeah, much as my wife hates that But look, look, we'll wrap it up there Um, Milan, thanks very much for giving up some time and sharing some of your insights and thoughts What I will do is I will put your LinkedIn profile if you don't mind into the show notes on the podcast So if anyone wants to reach out to Milan, I'm I'm sure he doesn't mind Helping that's fine. I've uh, I always tell anyone if you ever need anything Message me. Oh, yeah, I think I had someone from about two years ago. I met and she sent me Uh, an algo she did for for a dissertation or something and I was like, okay, well I had to read a bit and then I gave some feedback. Um, but like I said, my my inbox is always open If I don't reply don't take it personally. It's just quite busy Um, but eventually I I normally tend to try and get get back to people Uh, or you can always yeah message me on instagram if you're really really desperate All right Cool. All right, we'll wrap it up there. Uh, thanks everyone for listening and we'll be back as normal next week All right. Have a good weekend everyone