## Does correlation affect expected return of a portfolio?

If two assets have an expected return correlation of 1.0, that means they are perfectly correlated. If one gains 5%, the other gains 5%. If one drops 10%, so does the other. A perfectly negative correlation (-1.0) implies that one asset’s gain is proportionally matched by the other asset’s loss.

**How do you know if its correlation or causation?**

Causation explicitly applies to cases where action A causes outcome B. On the other hand, correlation is simply a relationship. Action A relates to Action B—but one event doesn’t necessarily cause the other event to happen.

### What is the best correlation for a portfolio?

1.00

A correlation of 1.00 indicates perfect correlation, while lower numbers indicate that the asset classes are not correlated and generally do not move in tandem with each other—or, when the market moves down, these asset classes may not fall as much as the market in general, which could mitigate risk in your portfolio.

**What is the difference between correlation and causation examples?**

Correlation is a relationship between two variables; when one variable changes, the other variable also changes. Causation is when there is a real-world explanation for why this is logically happening; it implies a cause and effect. So: causation is correlation with a reason.

#### How is portfolio return different from portfolio risk?

Portfolio theory originally developed by Harry Markowitz states that portfolio risk, unlike portfolio return, is more than a simple aggregation of the risk, unlike portfolio return, is more than a simple aggregation of the risks of individual assets.

**What is the difference between expected return and required return?**

The required rate of return represents the minimum return that must be received for an investment option to be considered. Expected return, on the other hand, is the return that the investor thinks they can generate if the investment is made.

## Why is correlation not the same as causation?

For observational data, correlations can’t confirm causation… Correlations between variables show us that there is a pattern in the data: that the variables we have tend to move together. However, correlations alone don’t show us whether or not the data are moving together because one variable causes the other.

**What are the important differences between correlation and causality?**

Correlation suggests an association between two variables. Causality shows that one variable directly effects a change in the other.

### Is beta same as correlation?

From the statistical definition above, an alternative definition of beta is that it equals the correlation between the stock’s returns and the market’s returns multiplied by the standard deviation of the stock’s returns and divided by the standard deviation of the market’s returns.

**Why is it important to understand the difference between correlation and causation?**

When changes in one variable cause another variable to change, this is described as a causal relationship. The most important thing to understand is that correlation is not the same as causation – sometimes two things can share a relationship without one causing the other.

#### What is portfolio expected return also known as?

Expected return and standard deviation are two statistical measures that can be used to analyze a portfolio. The expected return of a portfolio is the anticipated amount of returns that a portfolio may generate, whereas the standard deviation of a portfolio measures the amount that the returns deviate from its mean.