What is a linear relationship?
There is a linear relationship when a change in one or more independent variables that have a single or zero power affects a dependent variable. Linear relations are represented on land as line. In statistics, linear regression is used to adapt the linear equation through a set of data points that are linearly connected. An example of financial theory is the safety characteristic line that describes the linear relationship between excessive revenues from the asset and market.
Linear relations are usually described by linear equations written in the form of guaranteeing the inclination y = MX + b. The independent variable x is plotted on the horizontal axis and the dependent variable Y is plotted on the vertical axis. Constant m is a slope or steepness of a line. The constant B is called y-intercept and it is the value of y when the line passes through the vertical axis.
If the set of data points has a perfectly linear relationship, their conspiracy will be and will be and. Rarely occurs in data from the real world, although between twoThere may be a strong linear relationship with variables. Other times, the data is weakly linear, but the linear equation is still interesting because it is easy to work with and model. In both cases, linear regression techniques, such as the smallest squares method, can be used to describe the relationship.
studying a linear relationship between two variables can be useful in predicting future behavior. For example, linear regression could be used for wage data over the past ten years, taking into account the wage as a time function. The expected wage rates in a particular year can be calculated using a linear equation and this information can be used for budget for savings and retirement.
In the price of the price of capital assets, the security characteristics line is derived from linear regression to one activumhistorical data and describes a linear relationship between systematic and unsystematic risk. The independent variable is excessThe market return and the dependent variable are an excessive return of asset. The intercept y called Alpha measures the income of investment due to its risk. If Alpha is positive, the investment has exaggerated, if it is negative, it is insufficiently powerful and if its revenues are reasonable due to the risks of the investment.
The slope of the characteristic line is called beta and describes the sensitivity of the asset to market changes. Positive beta means that the price of the asset is moving with the market. If the beta is between zero and once, the price of the asset will fluctuate just like the market and can reduce portfolio volatility. If beta beta is greater than one, then the asset will overcome the market if the market increases, but if the market decreases, underestimates the market, allowing higher earnings or losses.