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Career Resources
Based on the most helpful WSO content, transitioning from SM (Single Manager) to MM (Multi-Manager) can be a significant shift, and here are some insights:
Getting in the Swing of Things: The time it takes to adapt varies, but many note that MM platforms demand a faster pace and a more intense focus on quarterly or even shorter-term performance. Some individuals find it challenging to adjust to the higher turnover and the need for deeper, more immediate research. It’s often a case-by-case basis, but diligence in understanding the PM and platform you’re joining is critical to ensure a smoother transition.
Workload Comparison: Generally, MM roles are known to be more stressful and demanding. Many professionals report working substantively more than in SM setups. The pressure to perform, coupled with the need to constantly monitor and adjust positions, can lead to longer hours and a more intense work environment. However, the trade-off is often quicker access to risk-taking roles and potentially higher compensation if successful.
For more detailed discussions, you might find this thread insightful: url: https://www.wallstreetoasis.com/forum/hedge-fund/qa-hf-analyst-5bn-fund…
Sources: MM to SM is it possible, Q&A: HF Analyst @ $5bn+ Fund - Breaking In and Transition to Risk-Taking Role, Q&A: HF Analyst @ $5bn+ Fund - Breaking In and Transition to Risk-Taking Role, Questions about Single Manager vs Multi Manager HFs, https://www.wallstreetoasis.com/forum/private-equity/then-and-now-compbanker?customgpt=1
Curious as well.
I did long-biased L/S equity SM (20-40% net) → to market-neutral factor constrained MM HF.
TL;DR: Took me a year to "get it" under a new risk model. I worked materially more hours at MM then SM.
SM vs. MM → A different sport:
The biggest contrast was the idea velocity and return profile of ideas. At a SM I was looking for compelling +15% IRR stories where we'd grow into the position size. I'd constantly do first principles type research to get smart on a theme and names exposed to a theme whilst creating models from scratch. I'd frame my valuation as PV of FCF's then think about how Qs alter LT perception and narrative, and when will the market converge to my views?
At multi-manager, I do one "initiation" type research effort and refresh annually or biannually depending on CMDs, leverage up to date models, and then focus on extracting alpha from "incrementals", rates of change, and around the edges of price action within my coverage. My alpha came from my research infrastructure where I meticulously cover every move in my defined coverage and would put on tactical trades.
This was in stark contrast to what I did before. I wasn't chasing themes exclusively anymore. I'm bordering on "systematic" approach to relative performance tracking between names, their correlations, which pairs offers best sharpe adjusted returns. I just don't focus on catching abs returns anymore. I was forced to train myself to a laser-like focus on building conviction around the "slope" of the alpha curve between two names and think hard about position constructions that would yield M-HSD returns and LSD vol.
Different type of role & bets:
At SM the CIO would dictate sizing, entry/exit, risk management, but I'd come with input to all of this. Sometimes he listened, sometimes (more often than not) he didn't. He'd oversee trading and I had limited insights in the the PNL. My exposure in the book seemed to depend on the CIO's perception of how well I could read the market at a given point in time. If I fkd up, I got less names in to the book. If I was on a streak I'd get more leeway. This made no sense as I would usually do better after a bad period then sustaining momentum when I was on a streak. But try telling that to a tenured respected CIO. At a SM, I was 100% focused on bottom-up idea generation and would produce thesis snippets with supporting evidence. It'd look something like the below (note: just making these up btw...):
At a MM, my coverage universe was clearly defined vs. more loosely covering broader sectors at a SM. I now felt like I had context to each headline hitting the tape, or questions asked to the company when I was in a MM seat with defined # of names to cover. I could be on the front foot and be pro-active. At a SM I always felt like "fk have I missed something here?". I was too busy on researching something that my monitoring suffered a bit. With that said, could've also be attributed to me being less tenured and more green during my SM days, but I was never the smartest guy in the room on a name. Took alot of time checking if something has been asked in the past and/or if mgmt answers had changed over time.
With the shift to MM, my job was now to know everything (and I mean everything) about a set of names and track how value chain changes trickles down in to microeconomic mispricings. I found this very labor intensive relative to my SM gig as I was now busting my balls for squeezing alpha % and catch the curve. I have discretion to put on risk, clearly defined entry/exit points and I'd obsess about positioning, vol, where my edge came from, what levels enter, stop out, take profit, etc. My idea construction changed to something like (note: again made-up thesis):
I could no longer just say "this is a good thesis". At a MM, I required better technical setups, favourable positioning, and most importantly, clear near-term catalyst to motivate "why own it now" then before.
Changed how I'd think about holding periods:
At SM I'd look for emerging themes and try the find the best names that would be reflected in that theme, either single names or baskets on both the long and short side. I didn't obsess about the timing of my view, but I did have a "soft view" on it. End of the day "who tf knows right?". In my SM days earnings served as thesis proof point. 1Q+2Q numbers were noise as long as it was tracking towards financial targets. 3Q/9M and FY figs was where we'd get some decent commentary and be able to measure and analyze the puts & takes on the company, and if it was tracking towards M-LT targets. We'd just usually size positions according to "visibility + conviction".
At MM I was forced to have a game plan prior to results for each ticker. I'd have to pre-populate in to our system how I'd want to be positioned prior, intra-day and after depending on different outcomes - regardless if earnings was a non-event or not. My pre-close work very detailed and clearly defined. Earnings season = Super Bowl! I can hold names for shorter and longer periods, but I'd always need to have a view on where #s will come out for each name.
When I transitioned to MM I found myself feeling like "everyone gets the LT secular story that's easy" so incremental for me was around timing of various initiatives, and trying to grasp when it hits the PNL. If a company under coverage would miss vs. expectations I'd be like "is this guy overpromising and blaming macro as usual, and is it enough for him guide down next Q?".
Each of my positions/pairs were time tagged and needed to produce $ within a set timing framework relative to its position size. At a SM, if the position made money I wasn't worried about it, and I'd usually let it gather dust. "It's compounding" I told myself and focus on something else.
At a MM I had to constantly re-evaluate each position regardless if they're in the green or red. Even IF they are in the green and haven't hit target returns, I'd still had to think hard about if there was better alpha in other names from here relative to the ones I had put on.
Learnings & Conclusion:
I had fun at a SM. I felt smart and like a true investor. I never knew what I'd get paid even if I did have a good sense on how much we've made in a given year. But I'm ngl.... I learned more in 1-2 qtrs at a MM then I did in years of SM where I just didn't have any material exposure to risk management, position and portfolio construction, trading. I can't speak for other SMs, but from what my friends at other SMs told me at the time their experience was similar.
At MM I could see my PNL in real-time, and if I fkd up it'd be because of me, not someone's perception of me. More importantly, I came to learn that I hadn't appreciated all the different ways of generating and measuring alpha. There's more to do then just ideation. I was amazed by institutional tech infrastructure at my disposal, and vividly remember thinking during my first week at a MM "how tf did I even compete without all of this stuff?".
I honed my research muscles at a SM, did fk loads of proprietary indepth research... It's was an excellent school and I'd do it all over again... BUT... for me the change of the landscape has happened for a valid reason.
A lot of rambling from me whilst I'm home sick... Over and out!
Beautiful explanation. thank you
Could you give a brief summary of your background ?
Conventional / "boring" background... IBD → PE → SM L/S → MM L/S
Very helpful. What Sharpe have you realized at the MM? Annual return relative to MDD?
Is there a Sharpe that you would advise staying at an SM? I.e. anything X? (1.0?)
Not gonna give specific track figs here, but thankfully it's been ranging from okay years to good years thus far. More importantly, had the benefit of working for top PMs before branching out on my own, so I had the benefit of learning & applying best practises from individuals much smarter than I.
Can't speak for others, but for me individual risk sizing is driven by MCTR, not Sharpe (it's an output rather then input). I'll form a view from the risk lense based on available risk budget in that specific sleeve. The goal is maximizing expected return per unit of risk capacity used, not targeting a specific Sharpe (again for me).
The Sharpe focus comes in at the book and sub-book level - specifically how uncorrelated my different sub-sector alpha streams are. If I'm running five different sub-sectors each generating Sharpe of 1 individually, the overall portfolio Sharpe ends up materially higher if my alpha streams are adequately uncorrelated bets. So I'm pressing my Analysts to stay in their lanes.
I work at a pod - I have more ideas that fit your SM style ideas than I do pod ideas, maybe 70/30 split. Feel like it’s the same for my peers and in my sector (TMT/c)
Fair enough. Poor writing from me here... Not so much change in the 'fundamental thesis construction' in isolation, but alot more emphasis around various trading, risk & positioning metrics when that drives decision making vis-à-vis the SM seat.
End of the day, different pods put on different type of trades.
super helpful
Amazing post. I noticed you didn’t talk about quantification of either the sm or pod theses into eps beats. How would you translate those to your constantly updated model? Like revenue growth is expected to be 8% but I think its 9% (but maybe 10% beats buyside and the difference between 1-2 pts of growth is within margin of error for a lot of factors beyond the specific thesis). In what I wrote I just made up 9% based on being “a little higher” than consensus but as you can see there was no actual direct quantification
At SM, you're right - I was more focused on directional calls and if Street was materially missing something structural. Like "consensus at 8% but my deep dive on product cycle suggests 12-15% is realistic given XYZ penetration assumptions."
At the pod, the process is much more granular. I maintain a live model that tracks every driver - units, pricing, mix shifts, channel inventory - and constantly triangulate between my bottoms-up math, real-time data points (distributor checks, app download data, etc.), what's actually in Street models.
The key is understanding sensitivities. If I think revenue is 9% vs Street's 8%, that's probably not enough edge on its own (at least for my strategy). But if I can show that mix is shifting 200bps better than modeled, or channel inventory is 2 weeks leaner than assumed, now we're talking about high conviction deltas that Street is missing.
It's less about having a magic number and more about identifying specific drivers where my work suggests Street models are wrong by a quantifiable amount.
Could you talk a bit about the institutional tech that blew you away?
I didn't grow up in MM land, so I was positively surprised by the real-time analytics across every position, information aggregation tools, army of data scientists at my disposal to help build bespoke dashboards with alt data feeds on top of the existing enterprise layer. Also enjoyed using all the trade optimization tools that could scenario plan position sizing across the entire book while respecting all book and risk constraints (self imposed and firm imposed). Helps time management on the day when you got 5 names releasing numbers pre-market and you wanna adjust sizing pre-open whilst you're listening to an earnings call. Basically a lot of automation in to my workflow.
Thank you so much for this. What does materially more hours than in SM mean? Could you help frame it with your daily schedule?
Just referring to general intensity really. Hours vary significantly by PM style, strategy, and individual time management. Don't wanna generalize too much as some SMs run intense daily tracking like MMs, while some MM PMs are more research-focused. But for me - personally - it looked something like this:
SM Analyst Life:
MM Analyst Life:
Key learnings: Initially struggled with time management at MM - too much P&L watching and obsessing over every tick. Eventually learned to time-block research periods and setup targeted Bloomberg alerts (volume spikes, significant price moves) rather than watching constantly.
Interesting observation: Often saw best P&L days during conferences or road shows when I couldn't be as active with trading (🤫 don't tell the LP's).
Weekend Contrast: SM Sundays spent synthesizing research insights for Monday Sector/CIO meetings. MM Sundays more tactically focused - drafting email on next week catalyst prep, position planning, performance attribution, etc. Less back and forth with PM on differentiated views, but more framed as (believe this will make $ based on XYZ views) & overall book tilt.
Key nuance is the constant decision-making intensity for a MM Analyst, rather than just comparable raw hours. At SM you can go hours without checking positions during research deep-dives. That luxury doesn't exist at MM.
Worth really considering if this intensity aligns with your style before jumping to MM just because it happens to be hot right now.
have you cracked 8 figures running this strategy yet?
Let’s put it this way; my vesting schedule has more lockups than a SPAC. I'm basically a structured note at this point.
Thanks for this. Every time I read your posts I learn so much.
I’m trying to learn how to pitch in a MM L/S kinda style, that is, thinking more about incremental edge and event paths/catalysts and alpha isolation. Any free resources or examples you can recommend I look at? Any books, blog posts, or courses? Thanks a ton!
I'm generally a promoter of studying "real materials", i.e. going straight to the source, dissecting filings and transcripts of companies, on repeat, until it becomes second nature. In a world full of AI summaries and Fintwits reading filings without other people's subjective interpretation is an edge.
(1) Pick a sector, read releases & transcripts, and subsequently you'll notice that a "pattern" emerges, you get a sense for underlying drivers (secular, cyclical, commonalities & ability quickly parse what matters).
(2) Go back and study old transcripts & releases (say LTM) of a peer set of companies that are somewhat inter-related, make short notes of what management have said, street questions, puts/takes on guidance, plot down catalysts, and how you'd think about validating thesis proof points leading up to the catalyst (earnings, product releases, shift in biz momentum, etc.), and then link it to price action between releases (absolute and relative).
(3) Think about implied street feedback/reactions. How would you have invested after the Q4 2023 release if you didn't know the price development? Did it play out the way you thought? Why/why not? Roll forward to Q1 2024 and do it again up until present day. Learn what works and what doesn't - straight from the source with ability to back-test what actually works.
After a while you get past the a critical tipping point of the "learning curve", and you develop a feel for how Street reacts to various signals & market feedback loops, whilst connecting the dots across a sector. Those factors lends itself well to the elementary / fundamental parts of the MM L/S investment process - as it's less about finding the odd one-off mispriced security on an abs basis, but more repeatable & scalable sector-based relative approach to alpha generation.
→ IMO this beats any "framework" which by definition are stale, when the market operates like a constantly evolving organism of what it likes/dislikes. You'll be wrong a lot. Key is to be wrong quick, and let winners run and play the law of probabilities. Additionally, you develop real critical thinking abilities with a good sense of commercial acumen of what makes $$... Not in theory from a book/blog... but trial-and-tested by you, straight from the source. You've now built domain expertise & can debate with a solid foundation. You'll find yourself saying "yeah but in these names you need to see deleveraging AND organic beats in X segments for the stock to actually move as looming concerns of refi maturity walls in a higher-for-longer environment will depress economics in the entire space... so next Q we should see this play out more favourably, esp in ticker X relative to ticker Y based on relative rev attribution, and X short thesis will see SI unwinding", etc., and not "uhm yeah X looks oversold here, there's 20% upside on a DCF... I'd go long". When someone debates a stock in sector X you can suddenly draw conclusions from similarities in sector Y as reference points of hurdles & key success factors which helps with evidence-building and knowing what to look for. Your sectors theses becomes scalable across a bunch of names.
Like most things, it becomes fun when it's second nature, and you ease through case studies as this is "what you fkn do"... After a while WSJ/FT headlines relating to your sector are suddenly thought of in context of actionable trading opportunities by spotting disconnects between expectations/reality.
I know it sounds basic, but I genuinely believe it offers the best return on invested time to emulate real-life investing as much as possible as opposed to reading books/blogs were you'd need to rely on others judgement of things.
Needless to say, sometimes book & blogs can help with inspiration. If you're targeting practical litterature on "expectations investing" specifics I'd skim through posts by Brett (FundamentEdge on X), Investing in Financial Research by Cheryl Einhorn (some research & thesis examples), Thinking in Bets by Annie Duke (probabilistic thinking), Expectations Investing by Michael Mauboussin (I don't apply his methods, but explains the theory behind it). For alpha isolation & risk management in MM setting, read Advanced Portfolio Management by Gappy Paleologo (don't worry about the title, it's not that advanced).
Helpful
While I do believe this was written with sincerity from a real analyst, the risk of these reports is that they are highly anecdotal and always sound like a highly sophisticated, former analyst turned business development Citadel talent analyst wrote them. Let me just highlight the below excerpt... it basically sounds like a bunch of sophisticated fluff. There is no such thing as a "sharpe adjusted return" or "alpha slope" -- yes I understand you are trying to communicate "low volatility high return etc etc" -- but, really, anything you cannot explain in simple terms is just made up to sound sophisticated. A SM could just talk about hitting the 3rd derivative S-inflection to a massive triple TAM unlock but it is really just the same guidance and EPS best & misses. Who cares if you work 15 hour days compared to 12 hours at a SM.... it doesn't matter. The koolaid can be drunk in both ends of the pendulum.
The only two key questions are 1) can you actually causally generate P&L this way and 2) can this ever scale into your portfolio instead of being a half execution trader mining headlines and doing napkin math / half hired gun sell side analyst for a PM. That's what I'd like to know. Do you think you can generate more P&L at MM compared to SM and if so / if not, why?
"I'm bordering on "systematic" approach to relative performance tracking between names, their correlations, which pairs offers best sharpe adjusted returns. I just don't focus on catching abs returns anymore. I was forced to train myself to a laser-like focus on building conviction around the "slope" of the alpha curve between two names and think hard about position constructions that would yield M-HSD returns and LSD vol."
I smiled reading this... Your confusion is literally my business model. Somehow you managed to both miss the point (by focusing on terminology), and prove how your lack of comprehension keep markets inefficient... Which makes me bullish on my job security.
Newsflash: this is not a report. Just my personal experience & ramblings on OPs question on SM -> MM transition. But since big words seems scary to you, allow me to translate from 'sophisticated fluff' to English adjusted for the neuro-diverse:
'Sharpe Adjusted return': Sharpe = return divided by vol. Mind-blowing, I know... When you pair trades, you actually lower vol (crazy stuff! Think of it as magic...). And get this - the more uncorrelated bets you add, the better your risk-adjusted returns get. It's almost like there's a reason platforms run multiple pods!
Ahh yes... 'Alpha slope' is alien to you - For me it's realizing when a stock is running out of marginal buyers & steam, even though your thesis is still playing out. For you it's when you look at your Robinhood account and punch the air as it's deep in the red but you don't know why. 'Stonks go up' right?
Oh yeah, and that 'borderline systematic' approach you mocked? It's just having an actual process instead of YOLO'ing on vibes. Wild concept, I know...
But please, tell me more about how platforms don't use these concepts. I'd die to hear your insights on what I've been doing wrong for the past 10 years & teach me what 'real' investing is.
Trust me when I say, if there only were more people like you, I wouldn't need a process. All I would need to do would be "napkin math and mine headlines" for a living. Would make my life much, much easier :)
Incredible. Thanks for sharing.
Super helpful. thanks for the writeup with examples.
dang i missed the reply before you deleted it.
please repost
I'm asking again lol. Please repost haha
Great write up BayesianBets! The biggest change for me (emerging manager, running an RV strategy at a mid-net SM) was in moving from a single leg trade (“buy Apple”) to a multi-legged/spread perspective (“Samsung / micron spread at extreme levels”), trading a mix of relative change in ex ante estimate revisions and earnings outcomes. I prefer this game a lot but do find that it is not what your traditional investor / allocator likes to hear unless they’re familiar with MM.
best sincere granular post on working at MM vs. SM i've seen!
now all we need is a MM-->SM post of the same level of sincerity / granularity
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