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3 Psychological Stumbling Blocks That Kill Investor Profits

Individual investors underperform the market . Here's why

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A lot of studies suggest this is the case, but none is as interesting as that by Philip Z. Maymin, an assistant professor of finance and risk engineering at Polytechnic Institute of New York University.

Maymin scrutinized records kept by the investment firm Gerstein Fisher from 1993 to mid-2010. Professor Maymin’s work included analysis on more than 1.5 million interactions between the firm and its clients and made a staggering finding. The value of investment advisers is not so much in picking stocks, but in keeping clients from impulsively trading at the wrong time. Maymin found that aggressive orders cost clients about 4% a year.

In other words, investors act against their own best economic interests with alarming regularity and cost themselves huge amounts of wealth in the process.

Dr. Casti says this is because society tends to form social groups based on affinity rather than simply becoming a collection of isolated individuals. That’s why investors tend to magnify the importance of information you see in the herd around you rather than breaking from it before it goes over the cliff.

When it comes to money, we see this in a phenomenon known as “chasing returns” or following the hot money. This is why annual performance issues like those published in Forbes, Money Magazine or Kiplinger’s, for example, are so irresistible. And so dangerous.

That brings me to fear.

The Only Thing We Have to Fear …

Right now millions of investors are sitting on the sidelines completely paralyzed by plain old-fashioned fear.

Yet, I would argue that fear actually contributes to both recency and herding because it causes people to sit on cash that should be invested or keep money in the game when it should be taken to the sidelines.

Studies show that this comes down to pain. Losses hurt. They hurt financially and they hurt emotionally. Nobody likes them.

That’s why people are more likely to let a losing position go against them than take profits — because they can’t take the “pain” of being wrong. The fact that they are unprofitable becomes almost irrelevant.

I can attest to that, having helped hundreds of thousands of investors over the years through my columns, presentations and seminars worldwide. That’s why I do everything I can to enforce the discipline of taking profits and minimizing losses in careful concert with an overall plan.

By breaking the recency factor and eliminating the herding mentality that went with it, I find that many times fear is no longer an issue. So how do you break the habits that you didn’t know you had?

Here are three simple options:

  1. Have a plan. Use the proprietary 50-40-10 structure allocation model I pioneered. That way you can sleep well at night knowing that even if the markets pitch a hissy fit, your money is properly concentrated in a safety-first structure that’s high on income, stability and growth.
  2. Take a measured approach. Dollar cost average into positions over time by splitting your money into chunks instead of investing it all at once. That way you’re investing a little at a time and can overcome the recency bias associated with big down days or bad news that rocks the markets. People usually look for patterns they can bet on, and averaging in removes this self-defeating tendency very deliberately and effectively.
  3. Use trailing stops. Conventional wisdom tells you to sell your losers and let your winners run. I think that’s backwards. Nobody ever made money by selling losers. You have to periodically sell your winners without interference and trailing stops let you do that. Of course, you’ve got to trim your losses, too, so don’t get me wrong here. Most brokerage firms have online trading platforms that can do this automatically. If yours doesn’t, consider a simple, inexpensive service like

In closing, there’s no denying that what happens tomorrow is a function of what happened to us yesterday. The question is how we harvest what we learn in the meantime.


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