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Alpha is finance-geek speak for an investor\u2019s skill that allows her to outperform an index<\/a>, like the S&P 500, on a risk adjusted basis. At a recent behavioral finance conference<\/a>, I sat on a panel<\/a> that addressed the idea of behavioral<\/em> alpha. Our moderator asked, \u201cWhat is it and how do we get more of it?\u201d<\/p>\n\n\n\n

I offered the observation that, in a sense, all alpha is behavioral. Whether you follow an algorithm (set of automatic rules) to select investments, decision rules, gut feeling or all three. It is a human who is making the trading decisions. (Even an algorithm is programmed by humans, with all their biases and skills.)<\/p>\n\n\n\n

We know that most individual investors create negative <\/em>alpha. Their returns lag indexes. Indeed, a notorious study by Fidelity<\/a> found that the best performing individual accounts were those that the owner forgot about. Indeed, the average retail investor lags major indexes by several percentage points.<\/p>\n\n\n\n

\"Investor
Data: Quantitative Analysis of Investor Behavior, 2016,” Dalbar, Inc. http:\/\/www.dalbar.com<\/a>. Graphic: Brett Whysel.<\/figcaption><\/figure>\n\n\n\n

Investor returns in stocks and bonds have lagged indexes.<\/p>\n\n\n\n

At the behavioral finance panel, I argued that the now-classic behavioral economic concepts of cognitive biases and noise can help us understand why negative alpha happens and how to reduce it. We discussed how individual investors and professional traders alike have been known to hurt their results by:<\/p>\n\n\n\n