# Investment Risks: Metrics Used to Quantify Risks The financial markets carry significant risks. And in order to beat these risks and come out profitable, you need to know how there are quantified and measured to better understand them and their impact. Read on to learn more about investment risks and the metrics used to quantify them.

## Alpha and Beta

When it comes to quantifying risks and value, the statistical metrics called alpha and beta are very much useful for investors.

Both of these risk ratios are used in the modern portfolio theory and they help  to determine the risk-reward profile of investment assets

### Alpha

The alpha measures the performance of an investment portfolio and compares it against the benchmark index, like the S&P 500. The difference between the returns of the portfolio and the benchmark is called the alpha.

When the alpha is positive one, the portfolio has beaten the benchmark by one percent in terms of performance. Meanwhile, if the alpha is negative one, the portfolio slumped against the benchmark by one percent.

### Beta

Meanwhile, the beta measures the volatility of the portfolio compared to a benchmark index. The statistical measure beta is utilized in the capital asset pricing model, which aims to price an asset by using risk and return.

Beta takes into account the movements and swings in asset prices. A beta that is higher than one indicates higher volatility while a beta lower than one means that the security is more stable.

## R-Squared

R-squared is a statistical measure that represents notable component of regression analysis. The coefficient R represents the correlation between two variables. When it comes to investments, R-squared measures the explained movement of a fund or security in relation to a benchmark.

The higher the r-squared, the more in-sync the performance of the portfolio with the index. Analysts use the r-squared with the beta to paint a better picture of the asset’s performance.

## Standard Deviation

In the world of finance, standard deviation uses the return of an investment to measure the investment’s volatility. This metric is different from the beta in that it compares volatility to the historical returns of the security instead of a benchmark index.

## Sharpe Ratio

The Sharpe ratio measures the expected excess return of an investment relative to its return volatility. This financial metric tries to determine how much additional return you can receive with the added volatility of holding risker assets.

A ratio equal to or higher than one is generally considered as a better ratio with better risk-reward tradeoff.

## Efficient Frontier

The efficient frontier is derived from the mean variance analysis, which tries to create more efficient investment choices.

The usual investor gravitates toward high expected returns that have low variance. The efficient frontier is constructed accordingly by using a set of optimal portfolios that provide the highest expected return for a specific risk level.

## Capital Asset Pricing Model (CAPM)

The CAPM is an equilibrium theory that is built on the relationship between risk and expected return. The theory helps investors measure risks and expected return of an investment to appropriately price the asset.

Specifically, investors need to be compensated for the time value of money and risk. The risk-free rate represents the money’s time value for being placed in the investment.

In other words, the mean return of a security should be linearly related to its beta coefficient, showing that riskier investments earn a premium over the benchmark rate.