Is there a future for non-quant hedge funds?

I'm a banking analyst and I did an internship in PE and I liked it but I think there's more opportunity in the public markets and I want to have autonomy (and high earning potential) earlier in my career than post-MBA PE. From what I've read on VIC I also slightly prefer the hedge fund stock picking process to the PE business planning process.

So I'm in the very early stages of trying to have conversations and learn the HF industry and how to pick stocks. Luckily banking and PE does prepare you well for this. But I see that Tiger Management founder Julian Robertson said this:

“As you have heard me say on many occasions, the key to Tiger’s success over the years has been a steady commitment to buying the best stocks and shorting the worst,” Robertson wrote. “In a rational environment, this strategy functions well. But in an irrational market, where earnings and price considerations take a back seat to mouse clicks and momentum, such logic, as we have learned, does not count for much.”

So is there a future for non-quant hedge funds? I've seen people on here talking about how with HFT and quant market making at shops like Citadel, or the firm that Getco became traders can "pick up pennies" and make money with probability almost one.

 

Seems difficult to me. At least on the hedge fund model. Capital is too flighty and the product may not be worth the fee level.

PE has a few large advantages over the hedge fund model. 1). Not judged on a quarterly basis. So can take a multi-year value opinion 2). Not judged on factor investing which can very much distort the model 3). PE seems to be getting away with overcharging. What is pe really? A lot of it is leveraging the small cap premium. And they still get to charge higher fees. Truth is a lot of institutional money loves not being on the screens. They don’t see the volatility that is coming from public markets. Another example are Reits almost everything is superior for them being in public markets but the non-traded Reit industry exists and while their fees have come down I believe they still charge double public Reits.

I think something like what Bill Miller is doing is very interesting in the mutual fund space. He thinks it’s a lot easier to make money now than in the past but much more difficult in the short term space. He likes to say a lot of mutual funds are just closer indexers. My guess is he’s correct. Which also means there’s not a lot of money doing real multi-year risks reward investing in the public space. It’s dominated by quant funds, passive, closet indexers, hedge funds with redemption risks, quarterly traders.

But where traditional long-short etc in the hedge fund space could do well a decade ago by basically outhustling mutual fund guys I’m not sure works anymore. Since you don’t have the mutual fund guys to outhustle and in the time frame they worked best in they are now competing with algos and passive distortions.

 

It would be incorrect to say "No, there isn't" though the general market trend is favoring algorithmic/quantitative trading mechanisms over stock-picking family funds. The main reason being data extrapolation and diversified risk.

There are still many firms that are founded on fundamental analysis though these firms are wildly differentiated in their theses from the rest of funds. There are few players in the game that can genuinely generate alpha with a fundamental point-of-view.

If you are seriously considering going into the world of HFs or Trading, you should understand why firms are moving to more quantitative models and why that is an important pre-req for the market. Also brush up on your skills (financial mathematics, statistics, programming) and learn about being an active market participant. HFs differ widely in the fact that they (for the most part) don't care about your prior experiences in banking or PE since those skills don't necessarily translate to understanding value in capital markets. The best you could use your skills would be in risk arbitrage cases and still there are better ways to trade it.

 

Most models in PE/IB are based on static financial statements not necessarily any strategic work (at least at the base level). Maybe if you're at a firm where there's a lot of strategic work (Centerview?) to understand the market/industry then there maybe some beneficial skills.

In HF work, you have to be able to understand and create a general thesis that is both quantitative in nature and also fundamentally rich in an industry. If you think about it, most bankers don't necessarily have the background/knowledge in equities to make these determinations.

 
dick_fluid:
ou should understand why firms are moving to more quantitative models and why that is an important pre-req for the mark One word: backtesting while over-fitting params. it's a LOT of B/S.

Have you learnt ways to backtest and NOT over fit?

 

Banking doesn't prepare you to pick stocks even a little bit. Banking provides the ability to model and have a general sense of the research sources you'd use (10k, Factset, etc.). It isn't a job where you're trying to understand the fundamentals of the business, just one where you're grabbing SS projections and copying & pasting.

That being said, there is opportunity in in public equity HFs, but not for very many. HF openings last year were half of what they were a year before, and I wager that this trend will continue. With all the HF closures & firings, unless you end up at a shop in the top quintile, you're probably screwed.

 

How did you get good at understanding what businesses are good and what price you would assign their stocks? Broad question I know but having trouble organizing all the different ways of thinking about a business into a price target

 

I started almost right after graduation and have a fantastic sr. analyst mentor who's helped me with this stuff. Books can help, but after the 4th or so investment book, there's huge diminishing returns, and as much as they teach you theory, they don't actually dig into the analysis portion.

My advice is to network and find a few mentors who are willing to point you in the right direction.

 

Why is everyone so defeatist? There are a lot of fundamental investors out there that don't earn their fees. I do not think that means the world will move entirely to passive/quantitative investing. I think its a pendulum that's swinging away from HFs after they were able to rake in the cash post financial crisis. People chase yields until they eradicate them, then course correct.

As for a long term future, I think there's always going to be room for disciplined, fundamental investors willing to take a risk averse approach to investing. If you have to take an extrapolation of all L/S and value guys being run out of the business, and all money being plugged into quant/passive/extremely diverse mutual funds, then who is doing the deep fundamental work on companies to correctly price the market? The idea that AI or quants or quantimental will be able to fully replicate security analysis is far fetched in my opinion. That being said there's plenty of dinosaurs in the business and HFs with AUM built off survivor bias rather than differentiated strategies.

 
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kppw1517:
Why is everyone so defeatist? There are a lot of fundamental investors out there that don't earn their fees. I do not think that means the world will move entirely to passive/quantitative investing. I think its a pendulum that's swinging away from HFs after they were able to rake in the cash post financial crisis. People chase yields until they eradicate them, then course correct.

As for a long term future, I think there's always going to be room for disciplined, fundamental investors willing to take a risk averse approach to investing. If you have to take an extrapolation of all L/S and value guys being run out of the business, and all money being plugged into quant/passive/extremely diverse mutual funds, then who is doing the deep fundamental work on companies to correctly price the market? The idea that AI or quants or quantimental will be able to fully replicate security analysis is far fetched in my opinion. That being said there's plenty of dinosaurs in the business and HFs with AUM built off survivor bias rather than differentiated strategies.

Agree 100% with everything you said. Specifically on passive, in a world where all money is passively managed, there is no price discovery. In that dystopian future, companies would have unlimited access to free capital, they could raise equity anytime they want with no repercussions. Dilute all the shareholders down to 0, why not? No one is going to sell the stock all-else equal if all money is passive. Only flows would have an effect on valuations. If anyone thinks that is realistic, they're mistaken. Passive investing only works if there are active investors out there to force price discovery.

Secondly, the markets work best when the crowd is diverse. There's definitely diversity in quant strategies, but not as much as you would think. I think quant will develop more and become more sophisticated as AI and machine learning get better incorporated, but I don't think it will ever replace disciplined fundamental completely. If anything, it will enhance fundamental's ability to compete as better tools get integrated into their more traditional processes.

On poor returns, I've come to realize that there is a ton of money out there being managed by absolute morons. Everyone has a strategy that sounds great in the slide deck, but few actually invest with any real discipline. Herding is real on both the retail and institutional side. Furthermore, a lot of guys have ridden one solid/lucky call into some AUM, and then proceeded to underperform for years. The average lifespan of a shitty hedge fund is a bell curve AUM flow wise, and you have to understand that with more AUM comes more limits on a fund's agility and what trades they can actually put on without arbitraging away their perceived price inefficiency through the simple act of entering the position! It's why a lot of disciplined guys will refuse new money past a certain point.

That said, really what are the expectations here? Over the past few years you see more and more articles making claims like "the majority of active managers underperform the market, most people would be better off investing passively". Ya, no shit, when you are collectively "the market", there will be winners and losers. It isn't possible for every fund to outperform the market. It's like saying the majority of NFL teams don't beat the average winning percentage of the league. There is room for everyone, quant, passive, HF, good managers, bad managers....markets are healthiest when the crowd is diverse. Markets rarely function in a perfect equilibrium in regards to that diversity, and hence, different strategies win and lose in a cyclical fashion. As one strategy becomes more followed, the returns get arbitraged away, and it opens the door to a different strategy to step in. No one gets it right all of the time.

 

So I'm a RE guy. Bored to the core currently. When that's the case I like to come to the HF forum. Really interesting stuff here. Anyways, now that you're all buttered up, I have a comment (likely stupid) to make.

Won't algorithmic / quantitative strategies dilute themselves by virtue of their continued growth? My base understanding is that quant funds make their margins via fractional mispriced securities identified by their models and act upon these mispricings through quickly entering and exiting positions. Eventually, won't the margins become too thin simply due to too much participation within oft similar strategy segments? As an outsider looking in, it feels like life cycle whereas fundamental investors will be favored again in the next 5-10 years and then quants will trend up in the next decade, and boom, a new cycle within the cycle is born...

Is this opinion idiotic?

 

short answer - no

long answer - no, that won't happen because finding true mis-priced securities is more art than science, and very difficult. Very rare for multiple firms to have the exact same models, because when you find a model that works, you don't tell ANYBODY how it works. There are infinite ways to model stuff in the markets, and people are all using different time-frames..so what looks cheap to one fund on a 1 minute time frame might look expensive to another fund in a 30min time-frame. Thats why we have markets...everybody gets to express their opinion, and we do not have perfect information (and never will).

just google it...you're welcome
 

short answer - yes

Long answer- yes.

Reality is that whatever edge you find in the markets gets reduced over time. the speed of that reduction depends on many factors. The other poster is correct that finding mispricings is more art than science and itis unlikely that investors have the same model. But this is not relevant- investors could have different models and still come to consensus ideas. all banks have different equity valuations - but they're usually 90% in favour of buying apple/latest hot trend. The trend now seems to be in favour of quant funds but it will change over time. Many quant managers have under performed especially in 2018. if you look at the industry as a whole, for every Rentech, there are 100s of quant firms that struggle. My advice is to follow which route suits you better rather than trying to predict which route has the longest probability of success

 

The answer lies in the data that the industry can manage to collect. Right now quant funds are limited in some of the trades they can do by what questions they can ask and answer from the available data sets. The gaps in these data sets is where humans will exist, the less of a gap there is, the less of a need for people. This is the raw truth.

 

I don't think Julian Robertson was referring to quant in that quote - seems like he is referring to stocks like TSLA and SQ. That price action is not due to quant funds.

I was also interested in Hedge Funds over PE for the exact same reasons you mentioned. The benefits PE is currently enjoying has been well-explained by others in this thread so I'll stay away from that.

I have wrestled with this question as well but mainly because I'm worried about AI... that said, those concerns seem overblown for the time being. My answer for now is yes but not everyone has the capability to succeed.

I do think that it is harder to make money in the short-term space but that is probably more due to the large platform funds competing for that alpha. Even there though - yes, there is turnover (sometimes large amounts) but there are still teams at those places that are consistently making money every year even as the platforms increase their AUM by billions and billions every year. So clearly they are doing something right.

On the longer-term side, the prevalence of money focused on shorter-term opportunities naturally means that there is an opportunity to make money on the longer-term side. The difficulty here is building a business model where LP's are willing to stick with you through rough periods. But it works - Baupost is probably the premiere example but there are others out there and people seem to not be mentioning that Coatue, Tiger Global, and Viking (except for the occasional tough year) have been performing well and largely retaining AUM.

Even on the long-only side, you have funds like Cantillon that stay under the radar and run large AUM with small teams.

I think there are three points that are generally missed.

1) media reports continually talk about the average hedge fund doing poorly but a) the average hedge fund (like the average pe fund) probably won't be very good or big and there are much higher barriers to starting a pe fund and b) those media reports don't take into account the vast number of teams at the platforms, which I would argue that due to the market neutral mandate and turnover self-select for more capable portfolio managers, and therefore the "average" hedge fund is probably sub-average

2) media reports focus on once high-flying hedge funds that start doing poorly but strategies go in and out of favor and the markets are not always kind, this is where having a patient LP base or the wisdom to know that your strategy won't work helps, and

3) the path to becoming top dog at a hedge fund can be achieved quicker but that comes with a lot more responsibility and pressure. At PE funds yeah you can work hard but you aren't driving investments decisions until you are higher up on the food chain. I would put a PE MD as the equivalent of HF PM and both of those jobs are very perform or GTFO with the caveat that barrier to entry is much higher in the former and obviously the structural advantages PE enjoys as mentioned. But my point is, you have to be good. And that's by definition uncommon.

That said - the good quants obviously make things harder through picking up factor returns. Things like low vol, value, growth, and quality were probably being unconsciously exploited by fundamental investors back in the day. But that's the nature of the industry, it is constantly evolving as strategies that work get widely disseminated. Understanding and being a basic value investor decades ago gave you a large competitive advantage to exploit but now you have to find value that may not be easily identifiable using knowledge from decades ago as that opportunity is much more quickly acted upon today. That brings the counterpoint though that, other than the premier funds like Renaissance, there is much more crowding in quant strategies which creates opportunities in itself.

 

A couple of themes keep recurring,

1/ concern about AI: I think this is vastly overblown. First, AI means anything from linear regression to exotic deep learning architectures that deepmind/brain/fair (top 3 industrial AI labs) are using. If we restrict AI to deep learning related methods then I'm yet to be convinced any quant fund has implemented it as part of their process.

2/ Every argument for quant funds keeps invoking Renaissance, and I think specifically people mean Medallion. They did extremely well for the years with returns known to the public. But since 2005 no one has seen any of their returns. How have they done since then? Also, there were other funds that were pioneers in the quant space that had similar return profiles to Medallion but never became goliaths like Renaissance.

3/ As already mentioned, most quant funds actually have not performed well, if at all, over the last 5 years. Reversion to the mean is a powerful principle.

 

Late to the thread but I discussed this a year or so ago with some people from a large Fund of Hedge Funds. Generally it just seems that a lot of investors are more willing to invest in a person with a strategy they can understand than with an algorithm that they can't understand. Plus a lot of quant funds make alpha through trend following or other signals etc and investors may not want that kind of alpha ~ they might want a portfolio of 50% quant-driven alpha and 50% stock picking alpha

 

this is essentially the argument for the multi-manager funds like millennium. 200 pods...each with a different strategy....some algo, some fundamental, each with similar risk restraints (lose 5% and your capital gets cut in half...lose another 5% and you are fired). By having 200 investment pods under the umbrella fund, each with different strategies...you get diversification (not only of markets, but of strategies).

You could start with just 2 pods (one fundamental, one algo)....but the more pods you get under the umbrella, the more stable should be your returns (which has been the experience at the pod firms like millennium...and explains why they have grown so large...~35bln last i checked...most investors seem to prefer stable returns)

just google it...you're welcome
 

Markets can only be efficient with respect to certain pieces of information when participants make that the case through their buying and selling decisions.

Computers lack signal processing to be informed of certain pieces of information. For example, computers cannot talk to company currents or formers to understand basic information about industry trends. The reason is simply because computers can’t have live conversations and so they can’t reflect this information in their models. How can an algorithm create an market efficient with respect to this information?

Moreover, they may not understand good and bad conceptual fact patterns and apply to rare cases. For example, they may not walk through a mall and see that Balenciaga and celebrity XYZ had a promo with Crocs and that these factors are sufficient to beat consensus. While an algo may be able to process some articles it can at best make a statistical bet on this information - they can’t reach the same level of conviction as a human.

Computers cannot find smoking gun frauds. There will never be a algorithmic version of a muddy waters report. Computers can screen companies and suggest that some companies are more likely to be frauds, but they can’t fly to China and see that a corn farm in China is nothing but an empty field. They can’t watch the cars going in and out of a building to realize that there’s nothing inside and that a company is a sham.

Computers will only look where you tell them to look. In some cases the right data is hard to find and might require you to call someone on the phone to get an XLS file with the data. The computer can’t pick up the phone and do this. For any given company, the data might be slightly different, and so unfortunately there’s no way to automate this.

Last but not least, it’s inportant to understand what machine learning is: it’s just statistics. To do proper statistics you need many data points. Like 100s. If a company reports numbers quarterly and has existed for 2 years, you then have 8 data points. This isn’t much to draw a statistical relationship from. In other words; any company specific model information cannot be factored into an algorithm. Algorithms can only handle very broad generalizations about companies. Humans in other words add value if they understand company specific information.

 

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