Suppose you had 2 scenarios:
Scenario A: 1 investment, $100,000, probability of being profitable is 68%, will have a 30% profit.
Scenario B: 100 investments, total $100,000, average probability of being profitable is 68%, will have an average 30% profit.
Now you have 2 choices: you either can choose Scenario A or Scenario B to invest in. Which one would you choose?
I’d choose Scenario B. By divserfiying among 100 investments that have the same (on average) probability & profitability as that of 1 investment (mentioned in Scenario A), you’re:
Letting the Data Cancel Out Outlying, Random Events
This post is very much of a statistical lesson. In statistics, we know that there is a general trend (as obvious in the graph on the right), but like all sets of data, there are OUTLYING data that do not fit within the general trend. These are what we consider as random data, data that cannot be predicted, and thus, cannot be assigned a probability (of happening). For most of the points on the graph (the trend), we can assign a probability e.g. the probability of this point happening is X%. However, for the random outlying events we cannot assign a probability because the event cannot be predicted. Thus….
Probabilities Are Only Useful When Considering Multiple Investments (More Data)
Let’s assume you chose Scenario A. On paper, the probability of that investment becoming profitable is 68%. In reality, whether or not that investment will be profitable is 50-50, because whether or not this investment is profitable is SHEER LUCK. This is because you might get unlucky and accidently get stuck with an investment that’s an OUTLYING data, meaning it might be way off the normal trend. In other words, that fact that the profitability is 68% is useless, because I’m ONLY TESTING THIS PROBABILITY (68%) ON ONE INVESTMENT.
Now look at Scenario B. With a 100 different investments, the random, OUTLYING data will cancel each other out and revert back to the normal trend. Thus, the probability that I calculated, 68%, is ACTUALLY USEFUL because I’m also guaranteed that all the OUTLYING data will cancel each other out and the data IN GENERAL will conform to the probability (68%) that I calculated.
Regarding What Warren Buffett Said…
Rule #1: Don’t lose money.
Rule #2: Follow rule #1.
By this, Buffett is saying that once you lose money, you’ll have to make a much better return to make that money back. For example: if you lose 50%, you’ll need to make 100% just to get back to your starting point.
Scenario A is really a 50-50 bet even though on paper it sounds like a 68% chance of profitability. Thus, if you invest all you have into this investment and the investment becomes unprofitably, you’ll have to make much better returns to make that money back.
Because the probability (68%) of Scenario B becoming profitable is spread out over 100 investments, you avoid the sticky situation that Scenario A can get you in.
