Working At An Investment Bank: What Makes A Good Analyst And Associate (Part 3)

Okay, hello and welcome to episode 3, the final of this 3-part series with John Normand, where we talk about lots of different things actually, John. But first of all, how are you and how is your Easter break?

Good, it was all good. Went back to the States for a bit, uh, gave my son a chance to see his cousins on the bayou, so it was all good.

Good stuff. Well, look, I'm super excited. We just caught up about some of the things we're going to cover here, but to give the listeners a bit of a preview attributes of good analysts and associates you've worked with. Obviously you spent best part of 25 years at JPMorgan, so I'm sure there's going to be some, some great information there for our listeners. And then entering finance from a non-traditional background, so just namely for those who haven't studied typical things like economics or STEM, but also demographically. So we'll go into that in a bit more detail. Then the value of newer credentials things like quantitative-related methods as well, which are becoming ever more prevalent in the finance sphere. So starting off then, uh, John, I mean, you've not only gone through the pathway yourself, of course, from analyst, associate, and up to MD when you, when you left JP Morgan, but you've— I assume you've worked with lots of them over your career. And I was just interested to know, was there any commonality between those that you really were warmed to in terms of their skill set or even personality, work style, and what did that look like for you?

Sure. So I've hired a lot of analysts and associates to work on my teams. I've trained the analysts and associate population previously at JP because they used to organize, still organize, kind of a multi-week training program and they ask people from the business to teach some of the content of what they do every day. So teaching rates, teaching foreign exchange, teaching commodities. So I've got, I think, a fairly broad perspective on this. And for me, What differentiates one analyst from another, meaning the very successful analyst from another, is not just pure smarts, because obviously all of these organizations are recruiting from probably the brightest, you know, share of the population anyway. So that's really not the big differentiator. I think there are other characteristics that kind of separate the super successful ones from maybe the less successful ones. One important characteristic is resilience, meaning given that stress is pretty endemic in markets, it's kind of the nature of the business. Is the person on the team just capable of anticipating those high stress moments? Do they perform well under time constraints? And if they fail, can they kind of get back on track pretty easily and pretty quickly without getting discouraged? And so if you're someone who's, you know, kind of soft around criticism, someone who's not very good at being, having to kind of deliver something on the spot because that's what market conditions or clients demand, you know, you're probably gonna fail the resiliency test. And I think that's pretty important to know about, you know, your nature going into these kind of roles. Secondly, I think it's incredibly important to be curious, meaning whether you're a researcher, a salesperson, or trader, it's really not enough just to wanna answer the question that everyone's asking right now. It's important to understand what's probably the next question everyone's gonna want to answer. I mean, certainly if you're a researcher and you wanna be someone who's known for having a quite, innovative and creative research agenda that's useful to people, you're gonna need to anticipate what the next big question is and answer it. If you're a salesperson who's trying to make an impact on your client, you also have to think about what's gonna be the next market narrative that you should be pitching into. And definitely if you're a risk taker, if you're a trader, it's not just about what the market is focused on now, but the next phase or next set of issues that are gonna move asset prices. So curiosity is super important. Thirdly, I think efficiency is indispensable if you're an analyst or associate who wants to succeed. Lots of the things that you're going to be asked to do have a deadline, and the deadline could be intraday, it could be intra-hour. So it's not just about being smart enough and industrious enough to get to the answer eventually. You can probably— you will probably have to get to it much more quickly than you had to get to the answer when you were in university. And when I tell the story to, or explain this concept to people, I remind them of an experience I had my first year on the desk in New York working in the foreign exchange business. The head of the business used to use me to write up sort of, you know, outlooks on currency markets for hedge fund clients. And he was very clear about his standard. He said, "John, I want 75% of the answer, by 5 o'clock rather than 90% of the answer tomorrow. And, you know, that's a rule of thumb which is not useful in every situation. I mean, sometimes you actually have to get it 100% right no matter how long it takes. But in many circumstances, you know, getting more than half under a tight deadline is a lot more important than being perfect. I think it's also important to be a very collaborative individual, meaning when people ask for help, whether it's the boss or just a colleague or even it's the one below you, you give it. And even when people don't ask for help, if you've got the bandwidth, you know, you volunteer to get involved in these things. And I realize that over the short term, being collaborative in that way can maybe detract from trying to meet your own performance objectives. But I think what you're gonna find is that over time, being known as someone who's a good partner, a reliable partner, someone who's capable of working with other people and other teams, maybe even external counterparts, you're gonna be seen as someone who's worth investing in. So it's very important to have those collaborative skills and to not be a loner. You know, there are some roles in finance, and I can think of some, I won't name them, where it's okay to be a loner. But I think in big organizations, particularly investment banks, you know, being a loner is not a great strategy for, you know, the majority of the jobs that you'll come across in the markets business or investment banking. And finally, I think it's important to be very responsive to feedback. I had talked in the first podcast about how frequently you're gonna fail because the challenge of, Understanding and anticipating markets is a very extreme challenge. And if you're getting it right 60% of the time, you're pretty good. You can be failing a lot of the time. If you're getting feedback from a senior person that you should probably be doing things in a different way, take the feedback. You know, chances are if that person is senior, they're very competent. You hope they're pretty competent. My guess is that they will be pretty competent if they're senior at, you know, a very reputable organization. Follow their lead and follow their instructions. And then if maybe you're not 100% comfortable with the way they're proposing you do it, you have a discussion about, you know, why maybe you prefer to do it in your manner. But in the first instance and for the first several iterations of this, just listen to the feedback. You know, they're not giving that feedback to you in order to stifle you. Very likely they're giving that feedback to you because they think you've got a lot of potential. They just think the methods that you're following don't realize that potential fully, and they're trying to help you kind of maximize your, your contribution. So, so take it with a, uh, sort of helpful kind of undertone and, and, and follow it.

Yeah, this is so interesting because of all the senior people like you that I'm lucky to talk to, nearly every single one has resilience first in terms of a, of a list. So do you think you can learn resilience in your career? I mean, Or is it something more that's, I mean, in that early part, the analyst associate kind of segment, or is it something that you've learned through life experience and you've had that runway to be able to hit the ground and deal with that environment? Or can you arrive at the bank and learn it, do you think?

I think you can be taught a more resilient mindset if you have a senior person contextualize the kind of things that you're gonna be dealing with. For example, one of the ways that people might feel they're failing with resiliency is they just make a bad call, you know, a trader who lost money on something, a salesperson who didn't do something that a client needed, an analyst who made a bad market call. But if you have a senior person say, look, you're going to miss probably, you know, this many times out of 100, you're not going to feel so bad about those individual misses. So that, that context can help. But I do think there is some value in just having tried things on your own initiative without sponsorship, having failed and having recovered from it in your life before you got to the institution. And, and that's That's why it's important to take, you know, some measured risks when you're, when you're in school. It's important to take some measured risks if you have some employment opportunities before you get out of school. It's a way of just sort of seeing what you're capable of. And unfortunately, I think there's certain demands of a market environment which just don't fit the personality of certain people. It doesn't mean that person is in some way defective. It just means that there are to certain traits you need to succeed in environments that are deadline-driven. If you're someone who just can't stand deadlines, you know, there are lots of other fields that aren't so deadline-driven. You go into that instead. But it's important to kind of understand, you know, what features you have, how much you can kind of develop from the core features you have, what are your red lines in terms of things you just don't want to do or can't do, and making sure all of that is pretty consistent with the demands of the job. Also keep in mind that, you know, what I'm describing is very much the experience of someone who worked in markets, and I particularly worked in markets that kind of traded 24 hours a day. I did foreign exchange for a long time, so I feel like I have certain sort of requirements of an analyst that you wouldn't have if your analysts were doing domestic credit in the euro area or domestic credit in the US. So, you know, hear what I'm saying in that kind of context. Cool.

All right. Well, look, let's move the conversation on and talk a little bit about the entering into finance from a non- traditional background. Love to get your take on that.

Sure. So I think of having a non-traditional background in two ways. One is having a non-traditional academic background, and the other is having a non-traditional, maybe demographic background. A non-traditional academic background to me is someone who didn't study economics, finance, business, or STEM— science, technology, engineering, or math. And I think if you are going to be someone who, for whatever reason, studied something else, you studied something in the humanities, something in the arts, What you need to be aware of when you go to these interviews is that you need to demonstrate, despite having studied those other things that are non-traditional, that you still got some relevant skills and you still got some interest in the content of a markets job or an investment banking job. So how would you do that if you just happen to be the person who studied history, literature, languages, philosophy? One of the ways you can do it is by teaming up with AmplifyCrowd. And even though I haven't worked with you guys formally, I've just done these podcasts and interviews with you guys, You know, what you're doing is providing training to people so that regardless of what they have studied, they still have some basic skills in order to, you know, speak intelligently about their aptitudes and their interests. And, and hopefully they perform pretty well in these training simulations to prove to prospective employers that they can, they can, they can do the, the work even though they started some— study something completely unrelated. So you need to be prepared to answer that basic question of what skills do you have that are relevant, and, and how do you demonstrate your interest in this? One way is by doing these programs like Amplify. I think another way to do it is to be materially involved in some of these student societies around investing, or the Economics Society, or the Finance Society. Most universities have these, some have several of these. Get involved, but not just as the person who takes attendance at the door. You know, if they have trading simulations that the society runs, do one of those so that you've got some material to talk about in the interview. So I think there are, you know, multiple paths into finance. You don't have to have studied something traditional, but if you haven't, you need to be able to answer those questions around skills and interest. The other way to think about being non-traditional is being from a non-traditional demographic. And I think if you are someone who only watches maybe television or movie depictions, or even watches the financial news, you probably think the dominant demographic across finance is white, middle-aged, heterosexual, middle-class male. And as I talked about in the, in the first podcast, that will characterize, unfortunately, some institutions. It will unfortunately characterize senior leadership at some institutions. But that's an incredible stereotype to be applying to the industry. You know, many big investment banks, many big money managers, many small ones, have much more diverse leadership committees. They have much more diverse overall populations, and they have more diverse analyst associate populations. So I wouldn't— I know it's tempting when you come from a certain demographic to feel like you must be the only one who's like that, because all you're ever seeing on TV is this other particular demographic that you're not part of. My message is that, you know, that media representation does not always fit many institutions. You should do your homework on this if being from a non-traditional demographic is something that's very relevant to you. And most importantly, I think you need to ask the questions around what the incoming class of analyst associates has looked like for the past few years. I would be, you know, very comfortable telling someone join the place that doesn't look like you at the senior level if it looks like the analyst associate population has been very different, much more diverse for the past few years. That tells you the organization is committed to this as a value and they're doing something very concrete to rectify it. Diet. So they change the population at the base so that over time, with retention and sponsorship and, and coaching, uh, the leadership looks very different in, in 20 years too. So I think that's really where I focus. Like, what does the population look like, uh, at the, at the bottom? How consistently has it looked like that? Rather than judging everything based on who's at the top. Cool.

So the final question, the value of newer credentials. I'm actually quite quite interested in this one because if you being a researcher and generative AI, and I read those Fed papers that came out talking about how they were using it to analyze— well, we'll see whether it's better and faster than you and I at delving through a statement, uh, at this point. But yeah, if through your career I'm sure there's been adaptation of your skill set and newer credentials, the way the market is kind of evolving, be great to get your take on that and perhaps some useful tips that you can share with the community?

Sure. In terms of newer credentials, I'll highlight a couple of things. One is data science and one is climate science. And I realize we just had a discussion about what it's like if you don't have a technical background. But unfortunately, the field is becoming even more technical. That's partly because of just the change in sort of data creation over the past few years. There's just more data. More of it is unstructured. And alongside that, there's been an explosion and techniques to analyze that. This is largely around natural language processing, and it's also around machine learning techniques, which are statistical techniques. So no surprise that regardless of what field of finance we're talking about, whether it's an analyst, a researcher, a salesperson, a trader, there's definitely a premium on hiring people who have some data science experience and, and, and I say this, you know, with full understanding of what it takes to acquire those credentials. I think if you're someone who is trying to acquire data science credentials, you're competing against a crowd which is really tough, meaning there are going to be people who have degrees in that and advanced degrees and even terminal degrees like PhDs in this. And you're going to be competing against people who not only have taken, you know, a few classes in Python online, but are coding day to day. So I think it's really important as you think about, you know, what job you want in finance— am I going more towards the trading route, am I going more towards the sales route, more towards the, the research route, you know, how future-proof are my credentials— and, and I think it's worth, uh, thinking about how you can get some data science experience. There are different ways to do it. You can obviously do it at an academic standard, which is majoring in it. If you feel like that's not really your passion, you're more of an econ person or something else, at least take one course at your university in it. If for some reason you can't fit that into your curriculum because you've got these other requirements, there's not room for a data science module, there are lots of online courses that are self-paced and self-study. Many of them are free, and you only pay a fee if you want to get a certificate afterwards. So I would really encourage people to do that. And I say this as someone who's done it myself, meaning I'm someone who spent 25 years in the industry, I had a couple master's degrees already before I— or I had a couple degrees, one in econ and another one in economics and public policy before I entered the industry. When I started to make a transition and thought about moving to the buy side, I was very aware that the field had moved on quantitatively. And one of the things that I have done is I've taken data science courses. It's offered by the CFA Institute. And I'm a CFA, so it's very easy to kind of tap into that. But even if you're not a CFA, there are other things you can do. And I've done it at an older age, and I'm not trying to pretend that I'm ever going to be a programmer, but the expectation is that in whatever role I am in, I should be able to read this material. I should be able to analyze it and critique it if a research report is presented to me and the statistical techniques that drive the conclusion are based on machine learning. So I need to be an educated consumer of it, and I've spent some time educating myself. Do it. It's not expensive. You know, you're not too dumb or too old to master it yourself, especially if you're in your early 20s. The other thing I would keep in mind is that if you are someone who's very committed to sustainability as an investment pursuit, and I realize this doesn't apply to everyone on this video, but if you are committed to that, you know, you should try to get some proper understanding of climate science. There's a huge debate in investment management and investment analysis right now about whether or not the people who are making decisions about sustainable investment actually understand, you know, the underlying empirical issues, or they're just people who had some standing in some other part of finance and they've been rebranded as the sustainability officer or the head of ESG research or whatever, even though they have really very little, if no, formal training in the underlying climate science. I feel like this issue is too complex to just give it to people who don't really understand the underlying material. And I think all of the kind of re-credentializing and credential washing that's going on is not going to be the norm in 5 or 10 years' time. In 5 years' time, you know, it's probably going to be the case that if you want to work in sustainable investing and you want to do something around climate, you need to probably have some proper climate credentials. And I think that's worth, you know, thinking about if you're an undergraduate you're kind of aiming for that sort of role eventually, or you want to commit to that sector, and you still got some ability to pick up some university studies in that area.

Final question to wrap it up. Does any podcast you listen to then that cover any of the subjects that we've talked about? Do you have a routine where there's a particular person that you like? Well, it doesn't have to be a podcast, but material that's public source that you like reading. From an enjoyment perspective around markets or from an educational perspective?

Yeah, I'll frame it two ways. One is, you know, when I worked in banking, I worked on a team of 900 other researchers at JPMorgan, which was a phenomenal experience. So there was a specialist in everything around economics and markets. But, you know, of that team of 900 people, there are probably 10 people I read religiously. Because there were particular issues that were important to me. It might be the call on a certain economy or a certain central bank or the call on a particular sector of the equity market or a certain piece of the interest rate market. And not only did I need to know about those, but I really respected the way that those analysts approached the market, meaning they had a very structured way of thinking. They had a transparent framework that they followed to arrive at their views. And hopefully they had a decent writing style. So of the thousands of pages of reports that were coming to my inbox every day, there was a subset that I followed. I won't mention names. It's not necessary. Many of them know who they are. But the point is, if you're in that finance environment, whether you're on the sell side or the buy side, you're going to have access to that entire ecosystem. When you're in your spot, ask the senior people around you, what 5 people should I read? Or make that decision for yourself after reading kind of everything for 3 months. And those are going to be kind of your go-to people for insights. Since I've left the investment banking side of the business, I've had to recreate some of that. And it's been a mixture of reports from public policy think tanks that write on the global economy. I find this to be a pretty useful complement to a lot of the work that you see from investment banks. Investment banks tend to have a bullish bias on asset markets and the economy. It's important to read the work of people outside outside of that ecosystem who don't quite have the same conflicts of interest and can be a little more objective about that. I read a reasonable amount of work coming out of the Fed economists, meaning a lot of people want to poo-poo the work of central bankers because they think their policy decisions are bad. But what's important to realize is that whatever decision is made by those who are setting interest rates, there are armies of economists who work for the Bank of England, the ECB, the Fed, the Bank of Japan, the RBA, and so on. And they publish papers. That can be very useful to you in just kind of understanding some basic issues. And then finally, I read a lot of content produced by sort of independent analysts. So ones who don't work in investment banks, they work for some of the independent shops in the US and Europe. Again, I think because they work in a slightly different kind of commercial setting, their work tends to be a little more objective relative to some of the work that's produced by people who only write on one asset market and where there's kind of a natural bullish bias in that market. So there's quite a lot of content. You can ask people around you for specific names. You can kind of ping me offline if you want some specific names. But yeah, I do have my list of kind of 15, 20 go-to sources.

Yeah. Well, on that note, there's one person I definitely follow on LinkedIn for all things macro, and that's John Normand. So if you listen to the end of this podcast episode, all the series. Can't encourage you enough to follow John's work. You know, it's super insightful, and I'm absolutely sure he doesn't mind you connecting with him or following up with any questions, anything like that. But, um, just a quick recap: we've had 3 episodes. Um, in this one, we've talked about attributes of good analyst associates, uh, that you've worked with. We've highlighted some of those factors about non-traditional background, newer credentials. We've also talked about the perception and reality of working investment banking, work-life balance, all of these super important things to think about to make the most informed decision for your future career. Maybe what you're gonna study and what you're gonna do for the rest of your life. So definitely go back and listen through. I encourage you, but yeah, thank you so much, John, for giving up your time.

It's been a pleasure. Thank you for the invitation.

Myself, the community, super appreciate it. And yeah, we'll catch up soon.

Great. Thank you very much. Good luck, everyone.