The theory behind smart investing
If you want to invest wisely, you need to know what "investing wisely" even means. There have been incredible breakthroughs in the science of investing over the past century, with academic research that has put together a solid framework for designing investment portfolios...a framework that, by and large, is unknown to the investing public. The underpinnings may be complex, but the basic ideas are pretty straightforward. Even if you delegate your investment management to a financial advisor, it's worth understanding the basics of the theory, so you can ask good questions!
There's no such thing as a free lunch
Wouldn't it be nice if you could park your money in an investment that doubles your money every few years and never loses value? (Without it being a Ponzi scheme, that is.) Sadly, you can't. And the reason is logical: if you could, everyone would invest in that thing, which would drive the price up -- and the returns down. So in order for returns to be high, there generally has to be a reason for people not to invest in it.
The financial phrase is "being paid a premium". Maybe it's a liquidity premium -- for example, you can lock your money up in a CD rather than a more-flexible savings account in order to earn extra interest. Often it's a volatility premium, such as when you invest in stocks rather than bonds, taking on more price fluctuation but also having a high (but not 100%!) chance seeing higher returns over time. Whatever the premium is, there's almost always some sort of risk attached.
Now, these days liquidity is generally a given. Whether it's a bond fund, a tradeable real estate investment trust, or a collateralized commodities futures fund, you can buy or sell access to a wide swath of investment assets on extremely short notice -- and given the importance of flexibility in life, it's generally worthwhile to stick to these kinds of assets. Because of this, modern portfolio design generally revolves around the risk-reward tradeoff of volatility vs. returns.
The efficient frontier
This leads to the concept of the efficient frontier. Let's take a look at a graph of returns v. volatility, and put short-term bonds (the green dot) and emerging markets (the orange dot) on that graph:
As you might imagine, short-term bonds have low volatility, but low returns. Emerging markets -- developing countries like China and Brazil -- have high volatility, but high returns.
Now, that's not to say that every investment rewards volatility. For example, let's add commodities in yellow:
Commodities -- investments in physical materials like gold or timber -- have neither low volatility nor high returns, which is why I generally recommend against them. They're "inefficient", not producing returns in line with their volatility.
Let's add a few more asset classes -- intermediate-term bonds, long-term bonds, real estate, small US stocks, large US stocks, hedge funds, etc. I won't label each of them, because for now I want us to focus on the big picture.
There are a couple important observations to draw from this graph:
"Up and to the left" is unilaterally better -- that means more return for less risk. "Down and to the right" is worse -- less return for more risk.
"Up and to the right" or "down and to the left" are a tradeoff -- less return but less risk, or more return v. more risk. Which one is better? That's entirely up to your risk tolerance and risk capacity.
Given these two observations, the ideal would be to create a diversified portfolio that occupies a space on the graph that that is as "up and to the left" as you can go and still meet your required return or risk. These ideal spaces form a line known as the "efficient frontier":
Expanding the efficient frontier: uncorrelated asset classes
Now, you may have noticed that the frontier is "up and to the left" of most of the asset classes I've plotted. What is this sorcery, and how is it possible? The answer is one of the "secret sauces" of portfolio design: uncorrelated asset classes.
Correlation between asset classes is simply the likelihood that when the price of one moves, the price of the other moves in the same direction. A correlation of 1.0 means that the two assets move in lockstep; -1.0 means that when one goes up, the other always goes down, and vice-versa. 0.0 means that the two are completely independent.
As it turns out, mixing uncorrelated asset classes makes your portfolio more efficient. A brief (and only slightly over-simplified) thought exercise can explain why this is: if there are two assets that are identical in terms of returns and volatility, but non-correlated, the volatility of the two will cancel each other out but leave the returns intact!
Moreover, systematic rebalancing can increase returns on top of that. As two uncorrelated assets move in relationship to each other, when you rebalance between the two, you effectively "buy low and sell high".
Simple...but not so simple
Those of you with analytical mindset are already designing the optimization algorithm. It might look something like this:
Determine the standard deviation and returns of all asset classes, as well as the correlation between them.
Use these to model the efficiency of every possible combination of asset classes.
Construct an efficient frontier of the most efficient portfolios.
It's a great idea in theory...but it's not so simple in practice. For one thing, "garbage in/garbage out" is always a danger. How do you determine the data in step #1? Depending on the period of history you use, you can end up with wildly varying outcomes. For example, analysis of the decade before the tech bubble burst might have indicated that your most efficient investment would be 100% large growth stocks -- not a great idea!
Also, the sad truth is that correlation doesn't remain constant over time. For example, the Great Recession saw many asset classes across the board suddenly become highly correlated -- precisely when investors needed risk protection the most!
This is why many investment managers rightly come to the conclusion that portfolio design is as much an art as a science. It's a very iterative, as we pair the output of optimization with our understanding of investing in general -- which is constantly changing over time as more academic research comes out!
The object of the game
The upshot of all this is that the end goal of portfolio design is twofold:
Create a set of portfolios containing uncorrelated asset classes, each of which are as efficient as you can make them in terms of returns v. volatility.
Of those portfolios, choose the one that best fits your risk tolerance and risk capacity.
And now that you know, you can either use this information to do research into creating your own investment portfolio, or ask good questions of your financial advisor!