continuing from my previous post on possibly replacing traders with coding - these traders really really got to go…IN MY OPINION they are neither front office nor back office but they themselves insist they are part of the investment team…
Me: (after final talk with PM and other analysts) I still believe in the upside potential of this position due to blah blah looking at its competitors blah blah blah.
PM: Ok. I have thought about this quite a bit this week… blah blah blah. let’s go 2mm shares on this. today. Hey trader, 2mm shares of ____.
Trader 1: Ok. but considering blah blah is there really a good upside to this?
Trader 2: been talking to my contacts at ____ and ____ (both are sell side traders) and these guys told me this company might be a bit you know _______.
PM: No. I disagree. blah blah blah. Hey trader, Buy 2mm of ______.
Trader 1: Ok. we bought 2mm at price of_____
The most annoying about traders: they jump into the talk as if they know what they are talking about. They really want to be part of the investment team.
I think the public and the media has wrong idea of “traders”
Yes, prop traders and traders of 80s, 90s, and 2000s are more like PM with discretion. but today’s traders at buyside are not front office and sell side traders are no more and no less than sales people. These guys need to go thanks to coding.
oh yeah they love to sound smart at the same time love this line himself “that guy tries too hard to sound smart”
klaudnine you work at a bank? where will all these sell side traders go now? do they have any other skill set other than clicking few buttons to buy and sell?
I’m at a fund, we trade through them, recently whole departments have been laid off lol, it’s not good. They got no transferrable experience really other than going to another place less shitty doing similar stuff. Some move into more relationship management type of roles, everything is getting automated all you need is really just a few guys so clients can call you if there’s a problem, some do appreciate that convenience.
I think the issue is when multiple PMs might want to do related trades, and a centralized execution function is necessary to prevent unintentional adverse effects to one portfolio or the other. Other than that though, the PM should be able to trade liquid products by himself with little effort.
From what I’ve seen, The good traders on the sell side seem to be sales people, where they generate trades through relationships and information flow. Especially when people are dealing in smaller cap names and need discretion. There is also marketing and getting associated with certain names. But most seem to be former college athlets with no transferable skills.
This is a great thread. Answered a ton of questions that I was trying to address. Was wondering if someone could elaborate on the details of some of the points discussed above re:
Data Science: I get that this is related to mining data for info and then coming up with an investment rec, using technology more intensively. Could someone confirm if my understanding is correct?
Data Science is a very broad term - what are some of the programs that would be helpful in working with “data science”. i’ve heard python is good and am trying to work on it. Any other suggestions?
Any suggestions on how to learn the programs? I’m more of a classroom learner so taking online/in-class courses would be a lot more beneficial than trying to aimlessly do it by myself?
Lastly, with re: to machine learning - completely agree that a lot of functions will get farmed out to the bots. Other than traders on the IM side, as discussed above, what are some other ways machine learning will change the face of IM?
Thanks - and def keep this thread going! Its great.
You should consider a move to asset management. i.e. working for a pension fund, insurance company, private bank, endowment, family office etc. It’s a growing part of the industry with a good work/life balance. Your experience in equity research should be applicable whether you are investing in public equities or other asset classes.
It might seem like a jump to go from equity research to assessing investment options for a pension fund/endowment but it’s not really. The investment process in analyzing a new private equity fund commitment or co-investment for example is quite similar to deciding whether to buy or sell a public equity.
Either you know OP has a decent quant background or you are speaking out of your ass.Data Science ( such a stupid name ) and ML need extensive backgrounds in CS,Math and Statistical techniques let alone domain knowledge. By taking courses online you don’t become a date scientist. If by taking those courses you can win a Kaggle competition or brush up your github portfolio then do it by all means, but telling someone to work in ML is simply bad advice.
I agree that by taking a course (or courses) you won’t instantly become a Data Scientist – but I disagree that you need an extensive background to learn the basics of Data Science and Machine Learning. After all, in today’s world if one isn’t open to learning new skills and technologies then you can expect your career to go nowhere (and eventually you’ll be automated out of a job). Of course you won’t instantly be at the cutting edge of Deep Learning & Neural Networks – but the libraries within Python or R can do so much heavy lifting “under the hood” to the extent that you can run a basic Machine Learning algorithm with literally just a few lines of code. The danger there, of course, is that the user should have a good understanding of the mathematical / statistical underpinnings of the algorithm to make sure that the model is valid – so, I do agree that a mathematical / statistical background is necessary… but I’m not sure that it needs to be “extensive”.
I really don’t know your background but it’s not easy to learn to Code or learn statistics on your own. If it was most people would be doing it and developers wouldn’t be paid like they are paid today. Also if by "Data Science " you mean some basic stat functions in python, then surely you can become a scientist in 6 months. I don’t think however those sets of skills would make you employable. These courses are just an icing ( even less than icing ) on the cake.
been taking python classes. these classes just teach you about the tools. It is your job to use those tools to solve or achieve your goals. I think it is basically learning how to use an ax, saw, hammer etc. Now you gotta use combination of these or all of these with other materials to solve your problem. It is pretty tough and makes one think quite hard.
This is why coders make such good money. Not only is knowing how to physically code is important but also to code with grace and efficiency. you need to find a way to code with clean and efficient lines to problem solve the problem at hand.
Make sure that they cover pandas (dataframe manipulation & summarization) and scikit-learn (where the Machine Learning algorithms are mainly found)… otherwise, I think the class would be of dubious value.
Just talked to a friend who took a data science job and the pay was SUBSTANTIALLY lower (70-80k). Plus i felt that the job itself was “glamorised” middle office- cleaning up datasets in excel file.