Welcome to the new era of Robo Investing.

OK. Now what?

How do you usually react when you, as an investor, are pitched the next big thing, when the likes of Schwab, Vanguard, and Fidelity are all over it, when startups raise eye-catching amounts of money to jump into it, when the media is all over it (Google the phrase, you’ll see)? Usually, my gut reaction is to cringe: “Uh oh, here we go again.”

It’s good to be skeptical. After all, it’s your money the robos want to manage. And they’re coming at you with some serious marketing including diligent-sounding questionnaires, attractive web sites, and, of course, some nice advertisements. So yes, there is definitely a healthy supply of sizzle.

There are also “white papers” and methodology descriptions you can access if you find and click on the appropriate links. In some cases, there is some serious name dropping here such as Burton Malkiel, Harry Markowitz, Fischer Black, Robert Litterman and William Sharpe and references to such things as expected return, variance, covariance, standard deviation, correlation, capital asset pricing model, mean-variance optimization, efficient frontiers, Black Litterman optimization, and full-scale optimization, constraints, alpha, beta, skewness (a term well known to statisticians and those at Microsoft who program Excel but apparently unknown to those who handle the Word spell checker), and kurtosis.

So the answer to the Substance or Sizzle question is: Both of the above.

Yes, there is a lot here. It really is a very big thing

WAIT! Don’t let your well-justified skepticism cause you to click away to a different article.

Guidance With a Difference

Consider who it is that’s now telling you about this next big thing. (This is where it gets awkward, the place where I explain why you should follow me in this new blog about all things robo. I’m not used to writing about myself this way, but I’m doing this the morning after the first debate among candidates for the Republican presidential nomination, so perhaps my display of ego can blend in with the overall landscape.) 

I do not have a degree in marketing. I’m strictly a finance guy, and not just any sort of finance guy. I worked for nearly 20 years analyzing stocks at Value Line and was, in fact, the first analyst anywhere to bring Berkshire Hathaway into regular coverage – with the support and cooperation of Warren Buffett. And since the 1990s at Value Line and later at Market Guide, Multex, Reuters (it was a series of acquisitions, not job hopping) and now Portfolio123, I’ve been creating, writing about, teaching, and investing real money on the basis of models created using screening and multi-factor ranking. And although I’m not a quant per se, I have enough understanding and respect for the filed to have written a mid-1980s Value Line Selection & Opinion primer walking subscribers through the process of calculating Timeliness™ ranks article through an article that was reviewed and approved by Sam Eisenstadt, who developed the model, and to have been invited about 20 years later to host a panel discussion on real-estate derivatives at the insistence of Robert Schiller because he was impressed with the way I understood and effectively described on Reuters.com the guts of the then-new S&P/Case Schiller Home Price Indices.

So I can name drop as well as any of the Robos. But that doesn’t mean I’m on board with everything being hyped. I know what works and what doesn’t work. And as we go on, I’ll explain it to you in plain English.

There really is a lot here that’s terrific and that can benefit you more than you may realize. I’ve been robo-investing long before the phrase was invented so my reaction to the current hoopla isn’t “Golly gee, how can I get a piece of that action,” but “What took y’all so long? Where have you been for the last 20 years?”

There’s also a lot here that’s junk, and having managed a junk bond mutual fund during the heyday of Drexel Burnham/Michael Milken, I know junk when I see it. Way back in 1979, I wrote my MBA thesis bashing the Nobel-Prize winning great-on-paper-garbage-in-practice Markowitz mean-variance optimization model (yeah, the one being touted by some big contemporary robos) a little more than a decade before Fischer Black and Robert Litterman introduced their now well known (and used by some robos) corrective alternative to what had by then come to be described as error maximization aspects of the original model. (And as I’ll explain in a future post, the Black Litterman isn’t as much a solution as it purports to be.)

Mean-variance optimization isn’t the only big-time quant contribution that’s a mess. On 4/10/15, I publicly took issue with a lot of the most widely used risk measures including Beta and Standard Deviation. (You can also get to the article via Twitter through the hash-tag #QuantsBlewIt).

An Exciting and Hopefully Profitable Journey

It’s important that you know what’s what in this area. It’s important if you use a full-blown robo-advisor. It’s important if your human advisor is using robo models in whole or in part. It’s even important if you use robo stocks models such as can be found in a variety of places including the Ready-to-Go offering of my company, Portfolio123. I’ll discuss this, and others, as we go along. And yes, I have skin in the game. Why not? I’ve been in the business for 35 years and, as noted, I’ve been in robo for 20 years and writing about it and investing with it.

I’ll be offering here three categories of content.

• Education: The more you know, the better off you’ll be. It’s just that simple. I know there’s a danger that content along these lines can be dull. But I’m with you. I get bored as easily as anyone, so I try as best I can to make how-to material as readable and as engaging as possible. If you want a recent sample, check a four-part series I published explaining why stocks are priced as they are.  
• Commentary: The world marches on and what happens is relevant to all things robo and all things investing. So I’ll be explaining how significant developments out there (“significant;” not each and every headline) impact what we’re doing.
• Models: Naturally, the sweet stuff, dessert, comes last. I’ll be offering plenty of specific actionable ideas as we go along. If you want something quick and simple to look at right now, go to Portfolio123 and look at my free Ready-to-Go Cherrypicking the Blue Chips offering (you’ll need to sign on for a no-cost membership to see the 10 stocks in the portfolio as well as the weekly updates). I’ll discuss this in more detail, and offer other models, later, after I cover some very important preliminaries. But I did at least want to provide a head start right now. (I invest real money based on this model through my account at FolioInvestoing.com.) Stocks have been my main area of focus but I’ll also be discussing ETFs, and addressing fixed income.

In my next post, I’ll going to address some important preliminaries, Alpha and Beta. That will be followed by another post on Smart Alpha and Smart Beta. Except for smart alpha (a fairly new phrase), these may already be familiar. But it’s crucial that you understand what they tell you. These ideas are what help you recognize whether you are being well served by your current investments, and the answers are not as obvious as many expect.

After we nail down those concepts, I’ll introduce some models, including a full-fledged explanation of the Cherrypicking approach. And then, we’ll be off and running with coverage or all three of the broad topics introduced above.

Oh, one more thing. If you look at the Cherrypicking model and decide to use is as a basis to invest, please own all 10 stocks and update as needed along with the model. Owning a full portfolio gives you a huge advantage over picking and choosing among individual stocks (I know, I know, but I chose the phrase cherrypicking in a different context).