Central Risk Book Trading

Hi guys,

Recently got a full time job at GS/MS/JPM at NY for the central risk book desk. Not familiar with the business so I have quite some questions:

  1. How much risk does the desk take, and how much of it is based on personal decision vs. algos?
  2. I heard it is more like a developer position and you dont learn as much on market sense / how to trade flow yourself. Is it true, and is it still a good starting career for someone who is looking to work in a more discretionary trading desk?
  3. Is this a sustainable career, esp comps? 

Many thanks for insights!

13 Comments
 

From my limited knowledge:

  1. The goal of the desk is to minimize cost for traders across the firm. For example, suppose one trader wants to buy xyz and another at the same firm wants to sell xyz. Rather than having the traders go to the open market, central risk would coordinate the trade between those two parties within the firm. Traders are allowed to opt-in or opt-out of CRB, and it's sometimes seen as a point of contention. It is primarily algorithms and hedging going on. Prop positions are rarely taken in the US. In London/Europe, CRB plays more of a traditional market-maker role and due to illiquidity, prop positions are sometimes taken.
  2. Yes. CRB is more of a developer position. You develop programming skills. Not a good role if you are pure interested in discretionary in my opinion. With that being said, you should get the skills needed to transition over to a tech company or to a quant market maker (maybe their CRB?) after a few years in the role.
  3. I honestly don't know about compensation. You'd likely have to move firms/functions after building out CRB infrastructure since you're value quickly drops once the system is implemented. Banks have had varying success with CRB over the last 8ish years, and roles are still popping up here and there. Again, shouldn't be an issue to transition to data science or programming roles. Feel free to DM other options you're considering.
 

Hi, thanks for your insights!

Is there any reason why US vs Europe are so different into taking prop positions? Is it a better opportunity if I can do it (hypothetically) in Europe as that will be more prop?

Also, I am not really from a engineering background, so I am not actively looking to go into data science after the job, but rather staying in banks (lateralling) / buysides. So I want to see if this job is possible to stick to for a long time / transitioning to another more flow job in banks

 
Most Helpful

Worked as  CRB Trader for 2 yrs in BB, though in different region. Just take this as a grain of salt.

  1. How much risk does the desk take, and how much of it is based on personal decision vs. algos?

    -> Depends a lot in how the mgmt view the team, and overall strategy in client servicing. In some banks they would solely view the team as providing best execution service, no matter the loss they incur. As long as they interact more with the flow and maintain bank franchise, they don't care.(Of course, the bad thing about this is that the senior mgmt would see that the teams not making money, hence provide less bonus...so everyone leaves) On the other hand with some luck you'd have mgmt who is very supportive of the desk and let you take more risk, have more discretion(By this I mean, interact more with dumb money and omit the smart money from Citadel, MLP to the market.) and also have larger books for some discretionary position as long as you maintain sane level of crossing rate. About ur 2nd question, it depends on how you define personal decision. One of our main jobs is to develop our own model to be calibrated to our trading framework. So the research based in data analysis is the key to developing our decision. 

  2. I heard it is more like a developer position and you dont learn as much on market sense / how to trade flow yourself. Is it true, and is it still a good starting career for someone who is looking to work in a more discretionary trading desk?

    -> 100% of the work is coding, but personally I think that statement is bs. 

  3. Is this a sustainable career, esp comps? 

    - I think it's a good place to start ur career if ur interested in the Quant trading space. It gives u great opportunity to learn how to think systematically, and the math inside the work is highly relevant to HF, and market making so it gives you good exit opps. And some who are not that interested I. alpha research can choose to exit to quant developer position in HF/MM and they manage/construct the whole trading system there. You can still decide to stay in the bank. My impression is that every bank will still need VRB, but person with relevant expertise is always short on supply. Job stability wouldn't be an issue in the bank.

    Feel free to ask more questions if you want. 

 

Hi, thanks for the detailed reply, really appreciate it. A few follow ups:

  1. I come from a maths background, so not necessarily the best coder out there (able to use pandas etc but not like a full stack dev). Should I spend some time to work on some packages that you'd recommend, or even kdb?
  2. In the long term i hope to have a seat in a more discretionary, risk-taking job like flow desks. Do you think starting at CRB is good for that? I understand that it is better on the quant / dev side but less on the markets side so not sure if it fits my career goals. On that note could you also elaborate on (2) regarding why you think that is non-sensible?
  3. May I ask the reason why you quit and if you are willing to share, your current role broadly? I feel like although this job is stable in a sense, it isnt really aligned with my personal goals and passions (risk-taking per se) and I will also quit in a few years. I am deciding between CRB vs roles that i am interviewing on that is for flow EQD and D1. would you think the latter desks fits more into a career prospect of a risk-taking / flow-type job? again i am not against coding but I am just not sure to committing into a 100% coding job without much learning into macro / markets.

Thanks a lot!

 
  1. No need. No one ever learn KDB before joining a firm, but learn it after you join. If you have some basic SQL, it should be fine. Functional SQL query is quite a pain but you should be able to pick it up as long as you spend more time. If you really want to come prepared, tryreferring to kx website. Or can read Nick Psaris' book. 

    Rather than learning KDB/Q, I would recommend brushing up on ur own language. Either Python or C++ youd realize how much they are going to be used. 

    Obviously good to brush up on Linux knowledge as well.

  2. As I said earlier, it depends on how the senior mgmt views the team. I was lucky to have a senior mgmt who was very supportive of the team, so was able to display more macro views and have some directional bet. (Obviously this would have to be done in the name of pre-hedging). Could trade futures, options for those, I think those banks you mentioned would have mandates for CRB to trade. 

    Other than that, you need to have working knowledge of rates and fx, and for some cases NDF as youd be trading other regions names. (For US, I'm not sure though if you'd trade LATAM stocks) 

    I don't think CRB won't restrict the traders to gain market knowledge nor to have their own view on the macro side..or even some equities(Literally ur managing a book that's somewhat inventory of the bank...how can it be not related  to market)

    3. Forgive me for lack of knowledge on this part, but from my short experience, I think all the equities desk have similar prospect in terms of taking risk(except for some prime desks), and it's exit opps..all the desk you mentioned would have decent amount of risk appetite, while they do have some different exits. (Either to MM or HF). About my current position sorry I can't disclose now...Just ignore my title.

 
  1. the risk taking piece depends on the team. Based on the 3 banks you listed, I have heard these banks do take risk.  I would say a good CRB time has the algo doing the risk-taking, which is the "alpha" you feed. Finding alpha is more of a data science problem. You try to find systematic signals that are predictive of returns. Signals are usually the smart vs dumb money movements or alternative data sources like news sentiment.
  2. it's highly dependent on the structure of the team. if you are sitting closer on the trading side, you should get exposure both to markets and programming. You will be monitoring the book and risk as flows are going in and out, tweaking the algo to trade in a certain way. I would say it's still a great desk to be even if you want to do discretionary trading because it helps you think more systematically of stock returns.
  3. It's a great place to start you career and your career progression depends on how much of your time is focused on the alpha signal generation vs the actual CRB functionality. If you mainly focus on CRB funtionality, exit opps are doing CRB/execution at hedge funds like MLP, P72, L/S funds, etc. If you get to work closely on the alpha signals, then you can work as a quant researcher under a PM. Overall, comp is decent at those 3 banks (heard 100% bonus?) and wlb is great as well. 
 

Thank you for your reply! 

Could you elaborate a bit on functionality vs alpha seeking? As I still havent hit the desk yet I am not sure what I would be doing, only that my manager told me to practice my coding beforehand. But I assume "coding" apply to both of them.

 

functionality is the helping your internal traders save money on tcost. If a trader wants 1million shares of AAPL, they will create a lot of market impact by doing a market order of the full 1million shares. CRB comes here and absorbs that 1 million shares, and then gives the internal trader a price that's better than just offloading into the market. CRB will also try to cross or match the 1 million shares with a different trader on the floor (ideal situation). All of this is done in a systematic way. Your job will vary greatly from building/mainitaing analytics to cailbrating inputs to your systematic trading model. Alpha seeking is finding features or X that has predictive powers of returns. Different firms have different testing process of when something is "predictive", but that's the jist of it. Coding does apply to both of them. Just be comfortable with coding in python, a lot of the learning happens on the job anyways. If you're good on coding, then you can move on to factor models. There's the Barra risk model handbook avaliable online

 

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