On Wong's "Random Walk Part 4"

This is a note I jotted down after reading

Random Walk Part 4 – Can We Beat a Radically Random Stock Market?
by Theodore Wong, 10/9/17, Advisor Perspectives

This series of 'papers' on markets and vol and risk is pretty good.  It takes a fresh empirically-oriented look at how risk and return work in practice and throws in a decent dose of probability thinking for good measure.  That's always a good thing, right? This last paper ties his thoughts together.  It was pretty interesting as far as it goes but I had a tiny bit of ambivalence about it at the end and I wasn't sure why so I decided to introspect and see what was holding me back.  Here is what I think I was thinking as I hesitated to embrace it fully. Most of this is pretty minor:

• He used the phrase "Unlock a little-known market beating secret." Even if that is in fun or in good faith, and I have no doubt that it is, it feels a little like a red flag, like something that is in clickbait or infomercial territory. Beating the market or "secret" are words and phrases I usually don't see in peer level papers.  So, it's no big deal but I started to doubt which, when that happens, means my eyes are often drawn to the bio.  There I see "consulting firm offering clients investment research services" so maybe it's just a little harmless marketing and I guess I'm ok with that.

• The names for a couple of his models are probably fine but labels such as "holy grail" and "super macro" make me pause and think too hard about what is being sold.

• I was left wondering if he has maybe never seen the Omega ratio or is maybe claiming one of his  techniques is new by ignoring Omega.  In effect his risk ratio looks like a special case of the Omega ratio where the threshold is set to 0.  Omega is the ratio of different parts of an integrated pdf, one part from a threshold to infinity is the numerator and then that over the other part, an integration of the pdf from -infinity to the threshold.  The threshold could just as easily be the risk free rate or an arbitrary hurdle rate (rather than zero) in order to define the frontier between something that is "bad" vs "good." There are tradeoffs in choosing the threshold, though, in terms of the meaning of the results.  I like this approach because it considers all of the moments of the distribution rather than one or two, and it does in fact address some of his concerns about the weird return distributions seen in finance, but this idea in general and Omega in particular has been around for awhile and is known to be easily misused or misunderstood.  I wish he had acknowledged some of this.

• He doesn't say the word timing, though he has in past articles where I think he claims he is not really timing. Instead, here he talks about getting market health checkups by triangulating amongst several models (don't get me wrong, triangulating is good practice) with the implication that there is tactical allocation going on by way of a posture of capital preservation in an unhealthy environment and expansiveness of spirit when things are "healthy." Call it what you wish but that is timing.  That's not necessarily "bad" because timing can be ok even though it gets discredited pretty often because it's hard and sometimes elusive.  But momentum is a type of timing and that has been a particularly successful factor for a while. The same can be said for certain tactical allocation programs. The difference is that these are (or should be) rules-based and systematic. And that's where I stop. Anything beyond that, anything subjective, invites the various furies of behavioral finance. And I feel like that subjectiveness is the core proposition in the article but I might be wrong.  

So, I think the paper is worth a read and is additive but those were a few of the things that gave me some (superficial) pause while I went through it. Thought I'd pass it along in case anyone was interested.