30 years: Financial markets trader
In the earlier video on the overview of linear regression, Abdulla explained the process of how to construct the regression line. In this video, Abdulla will discuss the related jargon used in financial markets and calculate the numbers for the regression line using Microsoft Excel functions.
In the earlier video on the overview of linear regression, Abdulla explained the process of how to construct the regression line. In this video, Abdulla will discuss the related jargon used in financial markets and calculate the numbers for the regression line using Microsoft Excel functions.
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5 mins 38 secs
Beta is the relationship between an asset and the general return of the market. A positive beta means the asset’s value moves positively with the market and vice versa for assets with negative betas.
Key learning objectives:
Define beta
Understand how to calculate beta from a linear regression
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Beta can be any positive or negative number. Positive means if one goes up, you expect the other one to generally go up as well. The convention is to assign a beta of plus one to the market itself. So, a stock with a beta of plus one should track the market. A negative beta suggests that if one goes up, you expect the other one to generally go down. A beta of 0 implies that the stock or portfolio is insensitive to market movements.
Take another example. If the beta of the stock or portfolio is 1.20 and the market goes up by 1%, we expect the stock to go up by 1.20% and to fall by 1.20%, if the market fell by 1%. In effect we’re saying that it is 20% more volatile than the market. Clearly then, beta can also be seen as a measure of a stocks’ relative volatility compared to the market.
Beta can be calculated as the slope of the regression line. Linear regression provides the line of best fit that defines the relationship between two variables in the form of a simple formula:
y = bx+ c
The result for y is an estimate or expected result. In financial markets, x and y are usually measures of return, and the slope of the regression line is referred to as beta. Beta is used in estimating the return for y given a return for x as well as an indicator of the relative volatility of the stock or portfolio compared to the market.
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