Hypothetical No-tinker P/F with Saul's Jan 2

I have now back-tested the proposed portfolio management procedure on a mock equal-weight portfolio of 12 growth stocks supposed to have been created on January 6, 2015.

alpha - it sounds like you might be manually back-testing the data. Just thought I’d share for those who like to back-test - you may want to try PastStat.com.

It searches back for the last 4 years of market data and reports how the back-test did. I have no experience with it as it wants a login after 5 uses, but thought it might be useful to others.

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A long time back, I investigated a “Boiling Frog Syndrome” rule as way to avoid getting stuck in lousy stocks. My thesis at the time was that much of the time a bad stock will slowly decline in price without being noticed, and then all of a sudden that comfortable warm water is too hot.

This doesn’t work in all cases. The question was (and I guess is), given a set of stocks that meet certain criteria in terms of financials and growth expectations, would it work enough of the time to be a winning strategy? Can we alert the frog to jump out with second degree burns before he’s a culinary delicacy?

We all know that one of the key’s to Saul’s success is that he continuously evaluates the long term expectations for his stocks, and isn’t afraid to reduce his allocation or get out completely if he feels the long term case is broken. Strikes me that what is going on here is trying to algorithm-itize that to dump you out of a stock before it gets even worse.

Back testing is probably the best way to see if this kind of logic has merit. The obvious problem is that if you set the limit too close, you’ll sell out of stocks that are taking a breather before their next (big) rise. Look at NVIDIA’s action late last year, for instance. But, not close enough and it’s too late anyway.

I ended up getting distracted by other things and so never really followed through. I also couldn’t find an easy way to back-test various theories of mine far enough back. So data and equation flexibility are needed.

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We all know that one of the key’s to Saul’s success is that he continuously evaluates the long term expectations for his stocks, and isn’t afraid to reduce his allocation or get out completely if he feels the long term case is broken. Strikes me that what is going on here is trying to algorithm-itize that to dump you out of a stock before it gets even worse.

Smorg,

As another who is greatly interested in Saul’s secret sauce, I have thought about the various determinants of his success a lot too. I think he’s very good at selling before the bottom, but I think that’s probably the least important of his many skills as an investor when it comes to actually driving returns.

I don’t think what’s going on here is any “algorithm-itizing” of selling before the bottom. As you said, when Saul closes a position it’s usually based on a change he sees (often before others) in the long term thesis, not due to any reaction to price drop alone. In fact, price drops of the exact same magnitude can cause him to in some instances sell, and in others, buy more.

Rather, the main benefit of selling is that he can then use the proceeds toward a winning investment. These winners are the real secret sauce. Selling is just a bump along the way, and Saul’s redirections are usually small. I’m sure Saul doesn’t sweat selling out of MITK, TEAM, CYBR, PYPL, LOGM or any of his other tiny to small positions for one second. That’s just part of finding good companies. Now, he can correct me if I’m wrong, if he cares to, but my guess would be that selling out of INFN or SWKS or SKX over a longer period of time actually feels like more of a defeat, because:

  1. He had so much invested that could have been put to better use

  2. He lost a lot with any drop because he had a lot invested

  3. His confidence was high in these positions, so it was all the more frustrating when the theses changed

Obviously I’m not Saul, so I’m not really trying to speak for him. I’m just trying, as I said, to discover the real secret sauce that has worked so well for him. In the year or so that I’ve been examining my portfolio like he does, my experience is that selling is no big deal. Sure if Saul gets out earlier than most and saves a few bucks that’s great. But that’s not what supercharges his returns. If selling were the key, Saul would have had a crackerjack 2016, because he got out of many things that fell much further later (INFN and RUBI esp come to mind). No, the secret sauce is that over the years he’s found excellent places to put his money. AND, then he allocates the most money to the stuff which he identifies as likely to win the most, and/or is likely to lose the least, etc. That should not be glossed over. An equal weight portfolio (as some have discussed) cannot compete with Saul’s approach. This is why he can crush the indexes in “market up years” and still beat them (or even make money outright) in “market down years.” My favorite days are not when the Russell is up 1% and I’m up 2%. They’re when the Russell is down 1% and I’m up 1%. That’s when you know you’re doing something right.

In summary, it’s not when you sell, but how you allocate your money moving forward that matters.

Bear

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Bear,

We’re just going to have to disagree on almost everything, sorry.

For starters, this thread is about an algorithm for selling. See the post to which I responded, postulating a 5% or 10% threshold.

For enders, when you sell does matter, as it determines how much you have to redeploy.

And there’s a whole bunch of other stuff in the middle as well, but I don’t want to sidetrack this thread any more.

As another who is greatly interested in Saul’s secret sauce, I have thought about the various determinants of his success a lot too. I think he’s very good at selling before the bottom, but I think that’s probably the least important of his many skills as an investor when it comes to actually driving returns…

Thanks Bear, excellent analysis. I can’t say that I strongly disagree with anything you wrote about what I do.

Best,

Saul

Alpha,

As a new member to the board I can say thanks for stimulating such a knowledge filled interesting thread.

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Thank you Eyelise.

alpha