Number of positions held by a PM in L/S pod?

In an L/S pod, how many stocks or positions are usually held at once by a PM? I imagine there’s a certain point where you become stretched too thin trying to cover soo many positions. Please correct me if I’m wrong and dunning-Krugering. TLDR: Average number of stocks a PM in a L/S pod will typically have a position in (I.e P72)

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Based on the most helpful WSO content, PMs in L/S pods like those at Citadel or P72 typically focus on a concentrated set of positions. They are often sub-vertical or sector experts, trading within a universe of 30-50 names. This allows them to maintain deep expertise and focus on extracting alpha from a limited set of stocks. Going beyond this range can indeed stretch resources and reduce the ability to generate meaningful insights, which is why they tend to stay within this range.

Sources: Performance of the best PM’s at MM’s?, L/S vs LO from a non-monetary perspective, Credit - Pod Shop/MM vs. Distressed/Special Sits HF, MultiManager PM (Millenium, Balyasny, Schonfeld) minimum requirements, So you want to be a Quant?

I'm an AI bot trained on the most helpful WSO content across 17+ years.
 

Started my HF career at a Big 4 MM. Covered (had a model for) ~85 names (more like 60 that we cared about) of which we traded ~40 at a time. Total book typically had 50ish positions.

IMO that’s WAY too many names. We made money but the models were very detailed (nature of the sector) so it would take entirely too long to get everything updated during earnings and became nearly impossible to do the job well. Eventually left for a role that allowed me to trim my coverage to a more sustainable amount and it’s been much better for my sanity.

 

Semi related question, how much flexibility do PMs have in determining what companies fall under their coverage? For example, if there's a pair trade where one name is outside of their industry coverage, or a company that's marginally within their industry. Obviously tougher to invest in a company they would have less expertise in, but does risk management typically prevent them from investing in some names covered more by other pods? 

 
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Usually depends on two factors:

1. Track record making money in the space - if you’re good at something there should be limited appetite to change what’s been working.

2. The firm / platforms existing industry exposure - the fundamental law of active management = sharpe ratio scales by the square root of the number of independent alpha streams. So n is critical. Just as you build a well diversified portfolio for uncorrelated alpha, so does the firm / platform through it’s portfolio of PMs. Additional considerations are internal flow dynamics (too many trading the same way = alpha cannabalisation risk) and corporate access overload (brokers and mgmt teams are unwilling to give too many slots to the same firm even if it’s different teams / investors)

 

120-150 names. All MM books have target volatility and factor risk limits set by the risk team. Max volatility depends on the MM, but is generally 5-7%. And the only way to sufficiently reduce volatility is by having a sufficient number of positions. If the book is $2bn (vs $500m) you need more positions as you’ll also have liquidity constraints on positions

AlphaGen20
 

So pods with this amount of capital have detailed models built on 120-150 names L/S (whether 60 L 60 S or 75 L 75 S?) how do you keep track of each minutiae thing happening with all these names?

 

Multiple analysts. Each analyst will cover 20-50 names in detail. You’ll have models (individual company level, and also sector level eg alt data and trading data feeds) and be expected to know the companies inside/out. $2bn books will generally have 3/5 analysts with a PM.

AlphaGen20
 

Very impressive - thats amazing. At SM, what do they do day to day if they just have like 10-15 stocks in the portfolio let's say. 

The trading horizon is typically longer than a pod, so the SM research workflow is “deeper” in that it’s more focused on out-year estimates. To some degree, fundamental pods are trading (front running) estimate revisions while SMs are trading “reratings”. I have discussed this in a few other posts (out years vs n/t). 

 

50 ~ 80. but w/ probably 50% of gross on the top 10~20 names. 10~20 extra names might be there for non-profit-making reasons. 

 

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