Financial modelling terms explained

Expected Value

Expected value is the mean value of a random variable calculated by multiplying the probability of each possible outcome by the expected value of such outcome. Expected value is a key concept in finance and probability theory.

What Is Expected Value?

The expected value (EV) of an investment or gamble is a measure of the average value of all possible outcomes. In the context of a financial model, the EV is used to calculate the expected return of an investment.

The EV can be calculated by multiplying the probability of each outcome by the associated payoff (or loss). The sum of these products is the EV.

For example, imagine that you are considering investing in a new company. There is a 50% chance that the company will go bankrupt and you will lose your investment, a 25% chance that the company will be moderately successful and you will earn a 10% return on your investment, and a 25% chance that the company will be very successful and you will earn a 20% return on your investment.

The EV of this investment is calculated as follows:

0.50 x (-100) = -500.25 x (10) = 2.500.25 x (20) = 5.00

The EV of this investment is -50.

How Do You Calculate Expected Value?

Expected value (EV) is a measure of the average value of a given outcome. To calculate expected value, you multiply the probability of the outcome by the value of the outcome. This gives you the expected value for that particular outcome.

To calculate the expected value of a financial investment, you need to know the probability of each possible return and the value of each return. You then multiply the probability of each return by the value of that return to get the expected value for that investment.

What Do You Have to Watch out for When You're Calculating Expected Value?

When calculating expected value, it's important to watch for the following:

-Bias: Bias can distort expected values, so it's important to be aware of potential biases and to correct for them where possible.

-Variance: Variance can also distort expected values, so it's important to be aware of the variance of the data you're using and to correct for it where possible.

-Sampling Error: Sampling error can lead to inaccurate estimates of expected value, so it's important to take into account the size of the sample when calculating expected value.

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