When it comes to investing, there's a reward-to-risk trade-off, which essentially means that if you want higher returns you have to assume more risk.
If you have good data, you can measure and compare levels of risk in terms of the dispersion of the data in relation to its mean (or average). This is known as standard deviation. The more disperse the data, the more volatile that item is. The less disperse (or more concentrated) it is, the more predictable the outcomes are likely to be. So, risk (variance, uncertainty or volatility), is the opposite of predictability.
Let's investigate the concept of dispersion around a mean (or average). Here are 5 sets of test scores from students in a class. In this exercise, you will learn how to calculate the mean, the median, the mode, and the standard deviation. To access the exercise please click on this link.
Some risks are worthwhile, while some aren't. Good investors really get to know the reward and risk characteristics of what they're investing in before they jump in. When it comes to investing, it's not that we should avoid risky assets altogether, but rather we should be getting paid more for each additional ounce of risk that we take. If we aren't getting paid for sticking out our neck, that particular investment should be avoided.
Consequently, we should invest the most to those securities or strategies that are giving us the highest pay-out per ounce of risk - even if those risk levels are much higher than the riskless investment (CDs, Treasury bills, e.g.)
In this exercise, we will learn how to measure reward and risk, and then explore the reward-to-risk characteristics of major asset classes.
To begin the exercise, please click on this link.
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