Beta in Finance
In finance, beta measures the volatility or systematic risk of a stock or portfolio in relation to the overall market. A beta of 1 indicates that the stock's price tends to move in line with the market, while a beta greater than 1 suggests higher volatility and lower than 1 indicates lower volatility. It is a key metric used in portfolio management and investment analysis.
6 Key excerpts on "Beta in Finance"
eBook - ePubSTOCK MARKET INVESTING FOR BEGINNERS (New Version)
A Simplified Beginner's Guide To Starting Investing In The Stock Market And Achieve Your Financial Freedom
- Nathan Bell(Author)
- 2022(Publication Date)
- Youcanprint(Publisher)
...In terms of grading different types of possession classes, the two are connected, and both the risk and volatility of government stock. Volatility nevertheless determines just how much rates rise or fall over a set time for each investment sector, or share, and this is exceptionally beneficial when building portfolios, evaluating margin requirements and position sizing. What is beta? Beta is another procedure of volatility, and while completely different from underlying variance, it, however, provides another angle in portfolio or trade building. Standard deviation identifies the volatility of a fund, sector, market, or stock according to the variation of its returns over some time, whereas beta figures out the volatility in contrast to an index or other benchmark. This suggests that the list should typically match the underlying movement in that standard over time if a financier has a portfolio of shares with a beta of 1. It doesn't imply that it will naturally be better or even worse on a specific stock basis. Every single stock has a beta, which is essential for CFD traders, and a beta of more than 1 suggests higher volatility than the benchmark, with a beta of less than one recommending a low volatility. A beta two stock would be expected to move two times more than the standard, or double the hidden index relocation. If a trader has the option of going shorts and longs, the average beta on each side needs to be examined in terms of the total risk of significant market moves in one direction. Usually, not always, the highest beta stocks are those with the most significant volatility as measured by the standard discrepancy, but also how much they are affected by the business cycle and rate of interest...
eBook - ePubBusiness
The Ultimate Resource
- Bloomsbury Publishing(Author)
- 2011(Publication Date)
...Calculating the Alpha and Beta Values of a Security WHAT THEY MEASURE A security’s performance, adjusted to risk, compared to overall market behavior. WHY THEY ARE IMPORTANT Just as coaches would expect their most accomplished athletes to perform at a higher level than others, investors expect more from higher-risk investments. Alpha and beta give investors a quick indication of just how risky a stock or fund is. Alpha is defined as “the return a security or a portfolio would be expected to earn if the market’s rate of return were zero.” Beta is a means of measuring the volatility (or risk) of a stock or fund in comparison with the market as a whole. The beta of a stock or fund can be of any value, positive or negative, but usually is between +0.25 and +1.75. Alpha expresses the difference between the return expected from a stock or mutual fund, given its beta rating, and the return actually produced. A stock or fund that returns more than its beta would predict has a positive alpha, while one that returns less than the amount predicted by beta has a negative alpha. A large positive alpha indicates a strong performance, while a large negative alpha indicates a dismal performance. HOW THEY WORK IN PRACTICE To begin with, the market itself is assigned a beta of 1.0. If a stock or fund has a beta of 1.2, this means its price is likely to rise or fall by 12 percent when the overall market rises or falls by 10 percent; a beta of 0.7 means the stock or fund price is likely to move up or down at 70 percent of the level of the market change. In practice, an alpha of 0.4 means the stock or fund in question outperformed the market-based return estimate by 0.4 percent. An alpha of –0.6 means the return was 0.6 percent less than would have been predicted from the change in the market alone. Both alpha and beta should be readily available on request from investment firms, because the figures appear in standard performance reports...
eBook - ePub- Robert Irons(Author)
- 2019(Publication Date)
- Routledge(Publisher)
...This occurs because, with sufficient diversification, the firm-specific risk in the portfolio can be eliminated, leaving only systematic risk in the portfolio. That is why the only relevant risk for a stock is the risk it adds to a diversified portfolio. While the metric for total risk is the standard deviation of returns, the metric for systematic risk is beta. Beta Beta measures the sensitivity of a stock’s returns relative to the returns to the stock market. Researchers typically use the returns to the S&P 500 index fund as a proxy for the returns to the market; the S&P 500 includes the 500 largest stocks in the US and contains approximately 85% of the value of the stocks that make up the total stock market. Therefore, beta can be calculated by comparing the returns to a stock to the returns to the S&P 500. Beta is a relative measure of risk—that is, relative to the risks involved in investing in the stock market. That makes it particularly useful for understanding the risks associated with a stock’s returns. The beta of the market is always 1.0, making it a benchmark to which other stock’s betas can be compared. This is where the relative nature of beta is apparent: a stock with a beta of 2.0 is twice as risky as the market, whereas a stock with a beta of 0.5 is half as risky as the market. Or, more to the point, its returns are half as risky as the market’s returns. One simple way to measure beta is to divide the covariance between the stock and the market by the variance of the market returns. These figures can be calculated using Excel’s COVARIANCE.P and VAR.P functions. For example, for 2013, the covariance between Amazon’s daily returns and the daily returns to the S&P 500 is 0.000068, and the variance of the daily returns to the market for that year is 0.000056...
eBook - ePubMastering Corporate Finance Essentials
The Critical Quantitative Methods and Tools in Finance
- Stuart A. McCrary(Author)
- 2010(Publication Date)
- Wiley(Publisher)
...Investors who want to avoid all risk should invest all of their money in risk-free assets. Investors who tolerate risk well might invest all of their money in the market portfolio. Investors with a modest tolerance for risk could invest some of their money in risk-free assets and some in the market portfolio. Figure 3.2 depicts the Security Market Line. Investors can achieve any point on the line connecting the risk-free rate and the expected market return by changing the portion of their assets invested in risk-free assets and the market portfolio. If investors can borrow money at the risk-free rate, they can increase their returns along the same line by leveraging the market portfolio. The measure of risk on the horizontal axis is beta. Beta is defined as the covariance of a particular stock divided by the variance of expected market return. (3.2) The expected return of a particular stock (r i) depends on the risk-free rate (labeled r f in Equation 3.3), the expected return for the market portfolio (labeled r m in Equation 3.3), and beta (β i). The risk premium for a particular stock is calculated as shown in Equation 3.3. (3.3) This beta is the same statistic found in the regression section of a statistical textbook. In fact, one way to calculate the beta of a stock would be to run a regression using the return on the individual stock as the dependent variable and the return on the market as the independent variable. When viewed as a regression statistic, the meaning of beta is clear. If an individual stock has a beta equal to 2, the expected return in excess of the risk-free rate—the risk premium for the individual stock—would be double the risk premium for the market. Stocks that have a beta equal to 1 have no more or less systematic risk than the market portfolio. Stocks that have a beta larger than 1 have a concentrated portion of systematic risk and contribute more than proportionately to the risk in a diversified portfolio...
eBook - ePub- Alan J. Baker(Author)
- 2018(Publication Date)
- Routledge(Publisher)
...We shall find version (b) of equation (xv) extremely useful in discussing the implications of the CAPM for capital budgeting by firms; but first we must explore the meaning and measurement of a security’s beta coefficient, i.e. β i in equation (xv), version (b). By a further small manipulation we can express β i as the crucial linkage between the excess return on the market portfolio, (R M − r f), and the excess return on security i, (r i * — r f): (r ¯ i * − r f) = β i (R ¯ M − r f) (xvi) Given that our model relates to a holding period of short duration, the expected return on a security or a portfolio is inevitably dominated by expected price movements within the period. It follows that β i can be seen as a measure of the extent to which the expected price movement of the security in question exceeds, matches or falls short of the expected change in the price of the market portfolio. Thus, for example, a beta coefficient that is positive but less than unity implies that on the average the price of the security in question is expected to fluctuate in the same direction but less widely than the price of the market portfolio. Exactly analogous interpretations apply to beta coefficients in other ranges. In principle the value of β i can be estimated by regression analysis, if historical data on actual rates of return over a number of previous periods are accepted as representative of the probabilistic relationship between r i and R M likely to apply in the near future. Equation (xvi) suggests a regression of the following form: (r i − r f) = α i + β i (R M − r f) + v i (xvii) in which (r i — r f) and (R M — r f) are the actual excess returns on security i and the market portfolio, respectively — one pair of observations for each period covered by the regression; α i is the constant term in the regression equation; β i is the regression coefficient; and v i represents the variation in...
eBook - ePubBen Graham Was a Quant
Raising the IQ of the Intelligent Investor
- Steven P. Greiner(Author)
- 2011(Publication Date)
- Wiley(Publisher)
...The interpretation of the standard beta, however, is hazardous because it relies on covariances between returns that are usually and mostly non-normal. Herein lies the rub: bivariate distributions can have zero covariance and yet still maintain linear dependency. 10 I will digress to explain the importance of this, but understand that beta is an attempt to calculate in a single parameter both the volatility of a portfolio relative to a benchmark and, simultaneously, the portfolio’s correlation or association more generally with its benchmark. Now, why the interpretation of beta is hazardous has to do with the covariance being in the numerator of its definition, because if two variables are linearly independent, then their covariance is always zero, which means they would have a zero beta. This is always true; however, the converse is not true. To say that a portfolio has a zero covariance or very low beta does not tell you whether the portfolio is truly independent of the benchmark. To understand linear dependence in simple investment returns, we are interested in whether a portfolio is a simple multiplier of the benchmark return. That is, if the benchmark moves X, will the portfolio move 0.92*X? Has it done so consistently? If so, they are linearly dependent. Or are the two unrelated, in which case they are linearly independent. Mathematically, this means we can express the return of the portfolio as a simple multiple of the benchmark if they are dependent, giving beta some validity. We determine this by calculating beta, but what if their covariance is zero (or very low), resulting in a zero or near zero beta? This would mean we cannot discern if they are dependent, rendering beta essentially meaningless. When markets are turbulent, exhibiting high volatility, as in the tech bubble or credit crises of late 2008 and early 2009, asset returns went negative...
