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How investors make investment decisions

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I had a really interesting conversation today with a really smart entrepreneur (more on him in a later post) and it just got me thinking how retail investors make investment decisions. I guess if you had to break down the process of decision making in pulling the buy/sell trigger, we make our investment decisions in the following ways:

  • Simple screening: Like Yahoo Finance’s stock screener, these tools allow us to search for both basic and more advanced parameters/criteria to filter out candidates completely from the investment universe (in fact, they’re banished, never to be heard from again, until we conduct another screen). Some quantitative investors rely solely upon the output of these filters (see Joel Greenblatt’s Magic Formula). Charting falls under this umbrella, too.
    • Pros: Allows investors to sort through mounds of data to extract value
    • Cons: Once screened out, stocks that don’t fit the criteria are forgotten about and stocks that make the grade are never compared to these by-products.
  • Lateral recommendations: Like Amazon’s “people who bought X also bought Y”, here investors are using research tools like Morningstar to pivot around a particular investment of choice to broaden their research to find something similar, but maybe better performing/less risky. I see this a lot in the interpersonal interaction on message boards where one know-it-all tells everyone “If you like this stock, why don’t you check out this stock.” The point here is that there is a frame of reference and new research takes off from there.
    • Pros: Unlike buying a new phone, where a customer can describe accurately what he wants (“I want the iPhone”), many investors lack the language to describe what it is they are actually seeking in an investment and what tradeoffs they may incur in making such a decision (risk/return). Lateral recs allow investors to make decisions by saying something to the effect: I want something like that.
    • Cons: Lateral recommendations are frequently compiled by using website activity and purchasing data and then working backwards to create a personalized rec. The truth is, though, there is nothing personal about this suggestion. It’s just data. In fact, it can stray pretty far away from what a user really wants.
  • Piggyback investing: Investors buy things based on weighted opinions from others. These recommendations can come from an article in Forbes to actually hard-core piggybacking hedge fund picks like the guys at AlphaClone are helping investors do.
    • Pros: Taken as individual suggestions, many of these picks do fine in terms of future performance. In fact, building an entire portfolio of ideas like this and creating a portfolio of them grounded in historical performance can act as an investment strategy that’s as good as any out there. This takes much of the decision making out of the hands of the investor — he merely needs to decide which guru to follow.
    • Cons: Piggyback output lacks any personalized context. Because John Paulson is buying gold doesn’t mean that Ida and Murry should be buying it for their retirement portfolios.

I’m sure there are many other ways I’ve missed but these seem to be the way most investors I’ve been in contact make decisions to invest or pass on opportunities. In fact, decisions aren’t made via only one route like I’ve listed above — it’s probably a hodgepodge of ways. Each one of these directions has problems associated with them and when technology is used to help solve these problems, new issues arise that have to do with the structure of the software thrown at the problem.

Please join me in asking WHY YAHOO FINANCE HASN”T REALLY CHANGED IN 10 YEARS?! C’mon — with all the smart people we’ve got in the industry, investors deserve more.

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