Multi Manager Hedge Funds

According to academic research, 40% of positive earnings results make the stock price go down. So, even if you correctly call if a stock will beat earnings than there is still a high chance that you lose money. With this level of uncertainty how exactly are the LS equity pods at multi manager hedge funds making money?

 

60% when you correctly predict the beat or miss. I thought that portfolio managers enter trades very close to the expected earnings announcement and exit right when the beat is prices in. If this is not the case then when do they determine entry/exit on trade?

 

No I am talking about the individual fundamental pods, not the whole fund combined

 

Pod shops don't make money on company's net income. Also earnings are very tricky - if you beat your EPS guide by 100% but then you explain that you shipped your entire revenue for the next year already, your stock will go down - so I'm not certain I understand what you mean by "earnings beat" and what study you're quoting, there are a lot of variables that come into play when a company reports earnings. So yes you could make a trade right before EPS hits but that's not the point really of a net-neutral pod shop. The easiest description I could give you is the classic Coke & Pepsi example - a pod shop that thinks Coke has gained share on pepsi over the past Q and will do better over the near term will go long coke and short pepsi - then they will lever that up a bunch (through the main fund usually) and then the spread they make on the trade is how they make their money (if for example they only cover consumer companies). However, each pod PM is different but usually you're looking at near term performance 

 

if you are a Pod you wouldnt cover sprint and coke at the same time. and again it all depends on the PM at that pod shop and what his tolerance is, there's no exact guidance but as people called out already, near-term means less than a year, usually a lot less - because if you get a drawdown of certain amount of $, you just get fired so it's fairly near term oriented

 

Do you mean that they train them to lower position size when there is an earnings beat and vice versa or to use the strategy to buy if you think there will be an earnings beat and sell after it is reflected in the price

 

There are a lot of different approaches. However, an easy one is to look at industries starting to perform and buying companies expecting earnings beats and guidance raises. This creates momentum through PEAD which can last for another quarter (and sequentially add). If the company beats AND raises, you jump in very quickly. If the company misses and lowers guidance, you drop the stock or go short immediately. Note, these general rules are the instinctive reaction of managers, but there is usually some type of analytical process to gauge whether the odds of a beat/raise or miss/lower is in the cards. Read-throughs from other recent earnings is helpful, as are alternative data points or independent surveys. 

 

So a typical strategy is buying if you think a company will beat or guidance will be raised and shorting for the opposite. How do they know when to exit the trade? Also, do they enter the day before the announcement in order to not deal with any other market fluctuations?

 

It depends on the manager. I ran an L/S pod that was quite successful and brought me to my current gig... If I was watching industry Y and identified companies that were well positioned (this is qualitive research -- digging into business model, supply chain reviews, channel checks, talking to brokers/ER, talking to other buyside PMs), we would scale into a position starting 2-3 weeks before earnings/catalyst. I would typically sell the stock 2-3 days after earnings unless there was a change in the thesis due to guidance (happened about 25% of the time). 

I had a beta view, so my Ls and Ss were cross sector typically. For example, "long best idea in aerospace (positive outlook), short best idea in auto part mfgs (negative outlook)". 

 

Consensus beat or miss isn’t always what matters (as your referenced research suggests). MM pods want to predict what the stock will do, earnings vs consensus are one part of that. 
 

The simplest example is if actual buyside expectations going into the quarter are different than BBG consensus. What the whisper number or ‘bogey’ is could matter more and is hard to quantify for research.

another common ‘what matters’ item is guidance, which usually matters more than best/miss vs consensus. If a miss is expected due to data, pre-announcement, input pricing moves between street ests and the print, or any other reason but the guidance is way better, cons will be revised up and often the stock will react. You’re predicting what the stock will do, beat and miss vs. consensus is important context but other things matter more and less at dif times 

 

In other words, apart from earnjngs plays how exactly do PM’s come to the conclusion that a price will go up

 
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The topic question is sort of based on a misunderstanding.

1. "Beat on earnings," has two meanings. One is literal, that the stock's EPS was reported to be above Bloomberg consensus. The second is colloquial, but more accurate: the stock outperformed the market's weighted expectation of results on a broad number of KPIs. The academic study will look at reported consensus for EPS, but that's the wrong measure for a few reasons

a) Companies guide EPS conservatively, and sell-side models out company guidance. Investors know this, so the true market expectation is consistently higher than "consensus EPS" as reported by Bloomberg or some other source. Thus, "beating consensus EPS" is relatively meaningless. 

b) Sometimes EPS just isn't that important a metric. Many companies have KPIs that are more relevant than EPS (bookings, billings, backlog, new users adds, etc.), and beats vs. consensus on those measures matter more. 

2. Multi-manager analysts and PMs know this, and thus try to predict outperformance vs. market consensus (as opposed to reported sell-side consensus) on the KPIs that matter. In broad outlines, the way they try to figure out what they need to predict is:

a)  Talk to sell-siders who are "in the information flow" and go to hedge fund idea dinners and such, asking what the "bar" is for various KPIs. In short, try to get a better sense of what people really expect.

b)  Measure how the stock goes up and down in response to different KPI levels of outperformance vs. reported consensus or other measures of expectation. See which KPI correlates best with stock outperformance. Then try to predict that KPI.

That's the basics of it. Obviously in practice it's tricky and ugly. But it's not just "mechanically out-predict reported consensus EPS." 

 

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