 Personal Finance PowerPoint Presentation, Beta Calculation. Prepare to get financially fit by practicing personal finance. Most of this information can be found at Investopedia Beta, which you can find online. Take a look at the references, resources, continue your research from there. This by Will Kenton, updated June 30th, 2022. In prior presentations, we've been looking at investment goals, investment strategies, investment tools keeping in mind the two major categories of investments. That being fixed income, typically bonds and equities, typically common stock. Also keep in mind the investment tools that you're using. If you're saving for retirement, for example, you might be using mutual funds or ETFs to kind of pool your resources together and be able to diversify with those tools. And you might be using different strategies to measure the market and get your diversification. Then if you were using, say, individual stocks or purchasing individual stocks, in which case you would probably be looking more at the financial statements themselves during the ratio analysis and trend analysis on the individual stocks. Keep in that in mind. What is Beta? Beta is a measure of the volatility or systematic risk of a security or portfolio compared to the market as a whole, usually the S&P 500. So we're trying to look at the risk. Remember when we're investing, we want to think about the risk we're going to get and the return we are going to get. One way we can get a grasp of the concept of risk is to look at the volatility. Volatility, basically the change, we could think about the fluctuation of the prices and you would expect that if there's a more volatile price, you might have more capacity for an upside, but you also could have more risk for the downside to get some idea of where we stand with the volatility in relation to the market. We can compare it to like a market fund such as an S&P 500, which is a standard kind of benchmarking type of index fund that we can compare to. Stocks with Beta's higher than one can be interpreted as more volatile than the S&P 500. So we might do some examples on this, but the general idea is once you do the calculation, if you get numbers higher than one, then you've got more volatility. Doesn't necessarily mean it's a bad investment, but then you've got to take into consideration the volatility versus the return and how possibly that investment fits into your overall portfolio and strategy. So more than one can be interpreted as more volatile. Okay, so Beta is used in the capital asset pricing model, so that's the CAPM, which describes the relationship between systematic risk and expected return for assets, usually stocks. So clearly, this is the kind of idea we want to get in mind because we're kind of balancing out the returns that we could be getting and the capital that we're putting involved in the risk related to the investment that we have. So CAPM is widely used as a method for pricing risky securities and for generating estimates of the expected returns of assets considering both the risk of those assets and the cost of capital. How Beta works, a Beta coefficient can measure the volatility of an individual stock compared to the systematic risk of the entire market. In statistical terms, Beta represents the slope of the line through a regression of data points. In finance, each of these data points represents an individual stock return against those of the market as a whole. So we can plot the data points and then we can put the line through the data points. So once again, in statistical terms, Beta represents the slope of the line through a regression of data points. We've got the data points, we put the line through the data points in finance. Each of these data points represents an individual stock's returns against those of the market as a whole. We might dive into this a little bit more in practice problems as well to get a little bit deeper into the technicalities of it. So Beta effectively describes the activity of a securities returns as it represents two swings in the market. A securities beta is calculated by dividing the product of the covariance of the securities returns and the market's returns by the variance of the market's returns over a specified period. So the calculation for Beta, Beta coefficient, we've got the covariance, RE, RM, divided by the variance, RM, where RE represents the return on an individual stock, RM, the return on the overall stock, covariance, how changes in a stock returns are related to changes in the market's return variance, how far the market's data points spread out from their average value. So we're using kind of statistical analysis to paint a picture here. And again, we might dive into the technicalities a little bit more in the future. The Beta calculation is used to help investors understand whether a stock moves in the same direction as the rest of the market. It also provides insights into how volatile or how risky a stock is related to the rest of the market. So it's important to understand if the stock is kind of moving along with the rest of the market, because then you can get an idea if it's kind of linked to the same driving forces that are causing the rest of the market to move around, or if it's not, and that can help you to think about how to use it in terms of diversification. Are you using it in such a way that it's going to go up when everything else goes up, or if you have a kind of stock that's going against what everything else is doing, you might be able to use that kind of like as a hedge. And then, of course, you want to think about the riskiness of a particular investment as well, so you can take that into consideration both in terms of that individual stock as well as your overall portfolio plan. Remember that if you're investing in, say, mutual funds or something like that, then you might take a kind of a different approach instead of the individual stocks. You might be thinking about, you know, sectors of the stock or indexes of the stock or different areas within the market. So for any case, for beta to provide any useful insight, the market that used as a benchmark should be related to the stock. So they've got to be related in some way in order for the analysis to make sense or give some useful data. For example, calculating the bond's ETS beta using the S&P 500 as the benchmark would not provide much useful insight for an investor because bonds and stocks are too dissimilar. Understanding beta, ultimately an investor is using beta to try to gauge how much risk a stock is adding to a portfolio. Well, a stock that deviates very little from the market doesn't add a lot of risk to a portfolio. It also doesn't increase the potential for greater returns. In order to make sure that a specific stock is being compared to the right benchmark, it should have a high R squared value in relation to the benchmark. R squared is a statistical measure that shows the percentage of a securities historical price movements that can be explained by movements in the benchmark index. When using beta to determine the degree of systematic risk, a security with a high R squared value in relation to its benchmark could indicate a more relevant benchmark. For example, a Gold Exchange Traded Fund that's an ETF such as the SPDR GoldShares GLD is tied to the performance of Gold Boolean. Consequency, Gold ETF would have a low beta and R squared relationship with the S&P 500. One way for a stock investor to think about risk is to split it into two categories. The first category is called systematic risk, which is the risk that the entire market declining. So you might think, well, what would happen if you're investing and the whole market declines like there's a recession or something like that? Well, that's going to have, you're not going to be able to diversify using the same strategies as you might if only a sector of the market was to go down, which would happen kind of in normal times. The financial crisis of 2008 is an example of a systematic risk event. No amount of diversification could have prevented investors from losing value in their stock portfolios. So if you had money in the stock market, even if it was well diversified when you're in a recession and you got money in stocks, well, the stock's going to go down because it doesn't matter where your money is because the whole thing went down. Unsystematic risk is also known as undiversifiable risk. Unsystematic risk, also known as diversifiable risk, is the uncertainty associated with an individual stock or industry. So now you're within the market and you're saying within the market, even during normal times, some sectors and some companies are going to go up, some are going to go down. That's when diversification can really help you out and hedge the bets against a downturn in any particular area. So for example, the surprise announcement that a company, Lumber Liquidatures, LL, have been selling hardwood flooring with dangerous levels of formaldehyde and formaldehyde. That's what it is. In 2015 is an example of unsystematic risk. So now you've got this one company that tanked. If you had all your money in that company, that wouldn't be good. But if you're diversified, it might not hit you so hard. It was risk that was specific to that company. Unsystematic risk can be particularly mitigated through diversification. Types of beta values, beta value equal to one. So if a stock has a beta of one, it indicates that its price activity is strongly correlated with the market. So they're going to move in alignment in other words. A stock with a beta of one has systematic risk. However, the beta calculation can't detect any unsystematic risk. So obviously if it's in the market, you've got the systematic risk. We don't know about the unsystematic risk here. Adding a stock to a portfolio with a beta of one doesn't add any risk to the portfolio, but it also doesn't increase the likelihood that the portfolio will provide an excess return. Beta value less than one. A beta value that is less than one means that the security is theoretically less volatile than the market. So less volatile, you would think would be less risky than the market. Including this stock in the portfolio makes it less risky than the same portfolio without the stock. For example, utility stocks often have low betas because they tend to move more slowly than market averages. So again, if you put that in there, your portfolio will be lower, but you would also expect with less risk, they might not have the same potential for the returns as other risky stocks. So beta value greater than one. So beta that is greater than one indicates that the securities price is theoretically more volatile than the market. For example, if a stock beta is 1.2, it assumed to be 20% more volatile than the market. Technology stocks and small cap stocks tend to have higher betas than the market benchmark. This indicates that adding the stock to a portfolio will increase the portfolio's risk, but may also increase its expected return. So now you've got more risk taken on, and when you take on more risk, sometimes you might get a potential for a greater return. So these are the pros and cons typically. So negative beta value, a negative beta value, some stocks have negative betas. A beta of one means the stock is inversely correlated to the market benchmark on a one-for-one basis. This stock could be thought of as an opposite mirror image of the benchmark's trends. Put options and inverse ETS are designed to have negative betas. There are also a few industry groups like gold miners where a negative beta is also common. Beta in theory versus beta in practice, the beta coefficient theory assumes that stock's returns are normally distributed from a statistical perspective. So now we've got this kind of concept of this normal distribution concept, which has come up under a lot of scrutiny. You've got to know when you need to deviate from that assumption. You've got to kind of know what the assumptions are when you're using a statistical kind of analysis thing. And one of the assumptions that comes into play oftentimes is like this idea of a normal distribution. So however, financial markets are prone to large surprises. In reality, returns aren't always normally distributed. Therefore, what stocks beta might predict about a stock's future movement isn't always true. So what you kind of want to know the theories on these kind of things, and if you want to dive into it in a little bit more detail and then talk to people that are breaking out of the box of the theory a bit. For example, that guy Tilesh or the guy that did the black swan is one that gets on this topic of these assumptions about the normal distributions being problematic in many cases. So first you've got to know the normal distributions. Why whenever we make a model, we have to make assumptions about the model. We simplify the model and then look for those areas where that simplification doesn't hold and then choose your investments accordingly. So a stock with a very low beta could have smaller price swings, yet it could still be a long-term downtrend. So adding a downtrending stock with a low beta decreases risk in a portfolio, only if investor defines risk strictly in terms of volatility rather than as the potential for losses. From a practical perspective, a low beta stock that's experiencing a downtrend isn't likely to improve a portfolio's performance. Similarly, a high beta stock that is volatile in a mostly upward direction will increase the risk of portfolio, but it may add gains as well. It's recommended that investors using beta to evaluate a stock also evaluate it from other perspectives, such as fundamental or technical factors being assumed it will add or remove risk from a portfolio. So note, and oftentimes when we start to get critical, when you hear people like debate about these different techniques, they also do it, they often do it kind of harshly because they're basically saying, well that technique has these flaws and it led to this flaw and that flaw, and so this is another technique that you can use, but clearly what we want to do whenever we're using statistical analysis, whenever we're trying to predict like the future, is look at it from multiple different angles, recognizing the assumptions that we're making and trying to account for when there's errors in those assumptions and then adjusting our theories accordingly. So statistics is not going to be about one thing, we're trying to paint a picture and the more kind of angles we get, the better that picture might be, the better our decision-making might be. So drawbacks of beta, while beta can offer some useful information when evaluating a stock, it does have some limitations, beta is useful in determining a security short-term risk and for analyzing volatility to arrive at equity costs when using the CAPM. However, since beta is calculated using historical data points, it becomes less meaningful for investors looking to predict a stock's future movements. So clearly we have to at least start at the prior data points, historical data because it's hard data, we know what it is, but clearly there's limitations to taking past data to figure what's going to happen in the future. Beta is also less useful for long-term investors since a stock's volatility can change significantly from year to year depending upon the company's growth stage and other factors. So when you're doing the long-term investing, then oftentimes you've got to take different approaches to look at the long-time horizon versus the medium-time horizon versus basically the shorter-time horizons. Furthermore, the beta measure on a particular stock tends to jump around over time, which makes it unreliable as a stable measure. So what is a good beta for a stock? Beta is used as a proxy for a stock's riskiness or volatility related to the broader market. A good beta will, therefore, rely on your risk tolerance and goals. So obviously the answer, once again, as you might expect, is it depends. It depends. It always depends for crying out loud. If you wish to replace the broader market in your portfolio, for instance, via an index ETF, a beta of one would be ideal. If you are a conservative investor looking to preserve principle, a lower beta may be more appropriate. In a bull market, betas greater than one will tend to provide above-average returns, but will also produce larger losses in a down market. So obviously you would be thinking that the more risk, the more volatile stuff are represented by the beta above one. So if you're in a bull market, meaning the market's going up in general, you would be in the more risky areas, you would typically do good. That's when you get 100 people coming out saying, I'm a day trader and I'm a genius because everybody's a genius because the stock's been on fire no matter what you put your money into for the last 10 years. But then when it goes down, then you'd be better off having your stock market, your stock in the conservative side of things, and that's the beta possibly less than one or at one with the market. And then all the conservative guys are coming out and saying, see these hot shots put all their money and now they're tanking for crying out loud and the story goes on and on as the market goes up and down between the two. So is beta a good measure of risk? Many experts agree that while beta provides some information about risk, it is not an effective measure of risk on its own. Beta only looks at a stock's past performance relative to the S&P 500 and does not provide any forward guidance. So you're totally dependent on past data. So if you had a more sophisticated model, you might try to take into consideration changes in the future that you can put into your model. It also does not consider the fundamentals of a company or its earnings and growth potential. So again, you're looking at kind of a trends kind of thing and a lot of fundamental analysis say, hey, the way to get the most value is actually to drill down on the fundamentals, look at the financial statements, do your ratio analysis and look for value that way. And so obviously you might want to take some different approaches to build a model that feeds in from these different approaches, but some people are going to lean towards more what they favor in terms of their view of the market. So how do you interpret a stock's beta? A beta of one for a stock means that it has been just as volatile as the broader market, i.e. the S&P 500 index. If the index moves up or down 1%, so too would the stock on average. Beta is larger than one to indicate greater volatility. So if the beta were 1.5 and the index moved up or down 1%, the stock would have moved 1.5 on average. Beta also less than one indicates less volatility. If the stock had a beta of 0.5, it would have risen or fallen just a half percent as the index moved 1%.