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This chapter is from the book

What It Means and Why It Works: A Nontechnical Overview

At this point, why this works may not be obvious. But assuming that it does, it gives a nice interpretation of option pricing. It is just the weighted average of option payoffs, assuming that stock returns are normally distributed.

But why is it logical to assume that stock returns are normally distributed? Normal distributions occur naturally in science and statistics, with some of the earliest work on these distributions linked to observations about purely random events. In fact, normal distributions describe the frequencies of random events. So are stock prices random?

The Efficient Market Hypothesis, one of the best-known and most controversial ideas in investing, says they are. The EMH has been tested over decades and against massive amounts of data, and it seems to be just as predictive and controversial today as when it was first introduced. The conclusion of the EMH is that neither technical nor fundamental analysis of stocks helps to predict stock prices in the future.

The reason for this is the efficiency of large, liquid markets to absorb and digest new information almost immediately as it becomes known, with stock prices moving to their new price points before investors can take advantage of the information. That is, stock prices reflect all currently known information. The next move in price depends only on information that is not known yet and, therefore, is random.

If the EMH is true, stock prices should follow the mathematics of random movements such as Brownian motion, random walks, and stochastic processes. And if you can describe stock prices, the option payoffs and option values that depend on them can be described as well. What this means is that only one simple idea is behind the mechanics of option pricing: the unpredictability of stock prices.

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