No, he didn't beat the S&P, but holding some investment in the S&P and some in his fund beat the S&P in risk-adjusted returns (Sortino ratio, Shapre ratio, etc.).
As I mentioned, look up portfolio optimization in Post-Modern Portfolio Theory or Modern Portfolio Theory for details, but the gist is that
His fund was essentially uncorrelated with the S&P, so Cov(X,Y) was approximately zero. MPT uses Var(aX + bY + ... )^0.5 as its risk measure, and PMPT uses downside_variance^0.5.
My wife is a financial advisor at a name you've heard of. Maybe I can translate a bit ;)
The idea with an advisor is that you create wealth targets, and use the market to optimize your saving to hit those targets. Then other stuff like college savings accounts, taxes, what happens when you die, various financial vehicles to optimize your saving while limiting your downside.
You don't really care to beat the market, because all you need is, for example, 8.5% returns to hit your wealth goals.
It's really complicated, and hard to do alone. Just by the sheer knowledge required in so many different areas.
Right. I shouldn't have assumed it was obvious why many people would prefer to maximize risk-adjusted returns over maximizing expected returns.
One reason, as you mention, is that most people have some goals in life. The amount of happiness gained by having $500,000 more than enough to put the kids through college, pay off the house, and retire at age 60 is less than the unhappiness of being $500,000 short of these goals. Most people's happiness isn't a linear function of their money, and it's perfectly rational to maximize happiness instead of maximizing money.
But, even if you're just trying to maximize money, the amount of leverage (loans, etc.) you can get should be related to your probability of being able to pay the loan back, so better risk-adjusted returns should allow you to get more leverage, leading to better expected returns if you're the type to maximize leverage.
