Q&A: 2 Years in BB IB -> MM Private Equity -> To launch a quantitative HF strategy

My Background

  • Currently launching a long/short equity hedge fund
  • Previously was an Associate at a middle market private equity firm
  • 2 years as an analyst in a BB bank within the healthcare coverage group
  • Graduated double majored in Biology & Economics

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Given you work at a fund, I'll give you a more specific answer. Unfortunately we did not have access to family money, and given the economics of the business we initially were in discussions with an existing PM around forming essentially a sub-adviser like partnership with their existing fund. We were asked to provide live predictions, and we were lucky enough to have had the results of these calls demonstrate our value prop in real time. Through this exercise we were independently approached by an LP of the fund, who expressed interest in seeding us directly and independently of the existing fund. They were a family office with the ability to move quickly without the logistical and compliance burden one would expect from an institutional LP, so we felt it was a great opportunity to begin building our track record without burning the start up capital needed to build out admin and legal infrastructure necessary for an outbound institutional raise. We have received a multi mm allocation and have strategically sought to remain below $25mm aum in order to avoid increased SEC regulation and related requirements. Is it an AUM that would impress a VP at a tiger fund? Not at all, but as a systematic quant strategy run by a lean team- if we can demonstrate true alpha generation we will be able to more effectively scale than a team incorporating a more value/fundamental stock picking approach.

 
Most Helpful

Rather than trying to answer with something along the lines of "Buy low sell high", or go in depth into our secret sauce on this public profile, I think it is more interesting to address your question itself. . We have a quantitative strategy built upon a proprietary software stack where we attempt to incorporate fundamental intuition within a ML/AI framework. Given this vague string of overused buzzwords, what does this actually mean in practice? This is a question we have had to work on answering well during our fundraising process, as it is remarkably difficult to describe a proprietary approach without giving away our IP in an environment filled with cutthroat competition. What we have learned through our process is that, obviously it is very important to be able to describe why and how you are different, especially as a first time manager fundraising in a volatile market. The best piece of advice we received was to use very simple analogies that clearly articulate the essence of what we do without going into direct detail. Once we embraced this approach we were able to better answer this critical question while protecting our critical IP. Unclear if your question was serious with a username "faceslappingcompilation", but perhaps this response will be useful to anyone out there hoping to do their own thing at some point in the future.

 

I am currently a UCSD management science major going on my senior year.
My projected UC GPA is 3.3 by the time I graduate. WIll I stand a chance of getting hired at your firm?
If my GPA from my community college is also counted as the cumulative GPA then I can get around 3.5 to 3.6 GPA
I have 1 internship as an investment banker intern at a southeast asian boutique level securities.
Another internship at an insurance company.
What could I do during my senior year to increase my chance of getting hired, I know my GPA is not great. How can I make up for this?

Thank you for your time.

 

Not sure if this is a troll or not- but if this is a serious question my advice would be to aim for any finance-related role at a firm that offers a real training program and ideally rotational or lateral opportunities within the organization. Our firm is not looking for candidates with your profile, but if you focus on building hard technical skills for your first few years out of school and put effort into networking you will eventually get to a point where your GPA will be less of a limiting factor for any job on wall street. As a senior I would suggest focusing on finding that learning opportunity for your first job out of school vs, trying to chase prestige. Your career isn't defined by your first job out of school, so try to make longer term goals for where you want to be and figure out the middle steps as you go.

 

Thanks, great question. Its remarkable how much even the essential data costs to get up and running with anything quant related. Would rather not disclose the $ but will say we spent a lot of time and effort getting creative with our sources of data.

As new players emerge in the data provider space, there is an interesting dynamic where recent entrants are all vying to displace Bloomberg through offering a-la-carte offerings at a lower all in price. I think it is great as we found we do not need a lot of the offerings that come with a standard bloomberg terminal. For a lot of market feeds it seems the most popular data is now commoditized (think free stock price data etc.), with the market-wide pricing for the most valuable data contractually set and standardized by the exchanges themselves. The good news about this dynamic is that data providers are forced to offer longer and longer trial subscription periods in order to win share in a consolidating market. We have been able to minimize excessive data costs by focusing on key items that necessitate exact real time data, while negotiating contracts with various sweeteners where pricing may shift contingent on our next raise. It has taken a lot of work to overcome our relatively frugal budget (vs. the D.E. Shaw, Rentec's etc. of the world), but for even $1-$2k a seat you can cover a lot of the essentials with a Refinitiv (Thompson Reuters) or Bberg. Thus said, the more data you have available for analysis the better, as clearly the ability to access daily global satellite imagery etc. provides an informational edge to firms who can afford it. Thankfully, we do not need to do anything that extreme for the foreseeable future..

 

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