May 30th, 2023
Estimated Reading Time: 12 minutes

What is Volatility?

Volatility is both a risk and, for those prepared, an opportunity.

This edition of Investment Insights is all about volatility, one of the foundational concepts of finance. Volatility is often used synonymously with the term ‘risk’ in such contexts, though this is only sometimes correct. When incorrect, those seeking to protect and build wealth may miss out on the opportunities volatility provides. Understanding this distinction is important to efforts toward that objective.

This column, the first in a three-part series, will define volatility, describe what causes it, explain why it is both good and bad and differentiate between when volatility represents a risk and when it presents opportunities. The series will continue with a discussion about compounding, another foundational concept of finance, before concluding with an entry on asset allocation that will introduce something called “the stack” to integrate each concept.

As with the Investment Insights detailing investing, this column will also begin with a dictionary definition.

This is a very general definition, widely applicable within any number of disciplines – behavior, weather, chemistry, sports, etc. Within finance, volatility is commonly used to mean fluctuation in either the price of an asset or in the underlying cash flows of an asset. For current purposes, volatility will be used to denote fluctuations in the price of an asset. 1

Continuing with this narrow definition, financial asset price volatility is commonly measured using a statistic called standard deviation. To demonstrate how this is done, let’s look at Berkshire Hathaway’s stock over the past year (a in the table below) and measure the volatility of its monthly percentage price change (b) using the standard deviation.

The first step is to calculate the average monthly percentage price change (c). Then, subtract the average (c) from each data point and square the result (d). Total the squares (e) and divide by the number of observations to calculate the variance (f). Finally, standard deviation (g) is the square root of the variance.

As shown, the volatility of Berkshire Hathaway’s stock over the past year (as measured by the standard deviation of monthly returns) has been 7%. For comparison, Tesla has been a much more volatile stock over the past year, with a standard deviation of nearly 22%. 2

The neat thing about using standard deviation as a proxy for volatility is that it can be used to estimate the rough likelihood of a specific outcome. If the range of possible outcomes is normally distributed 3, then 68.3% of outcomes will be within one standard deviation of the average, 95.5% will be within two standard deviations and 99.7% will be within three standard deviations.

For example, if the average height of an adult male in the U.S. is 70 inches and the standard deviation is three inches, then roughly two-thirds of men will be between 67 and 73 inches tall (5’7” to 6’1”) and roughly 95% will be between 63 and 76 inches tall (5’4” to 6’4”). Clocking in at 6’5½”, I am two-and-a-half standard deviations above the average height and taller than 99.4% of American men. Put differently, only about six out of every 1,000 American males would be taller than me. 4

Returning to the stock price example above, we would expect Berkshire Hathaway’s stock price to go up or down by about 7% or less in any given month and rarely by more than 14%. Tesla’s monthly stock price performance on the other hand would typically fall between a decline of 24% and an increase of 19% in any given month but rarely fall by more than 46% or rise by more than 41%. 5

Beta is another statistic used to measure the volatility of financial asset prices. 6 Whereas standard deviation measures the absolute volatility of an asset, beta measures volatility relative to another asset, often the S&P 500 Index for stocks. A higher beta means greater volatility, while a lower beta means less volatility. For example, a stock with a beta of 1.0 would move in lockstep with the market, going up 10% if the market is up 10% and down 10% if the market is down 10%, while a stock with a beta of 2.0 would move twice as much and a stock with a beta of 0.5 would move half as much. Continuing with the comparison above, Berkshire Hathaway has had a beta of 1.0 over the past year while Tesla has had a beta of 1.5.

One critique of standard deviation and beta is that they are both backward looking measures of historical volatility and future volatility could look quite different from the past. While actual future volatility is unknowable, there are ways to estimate it. Options contracts 7, for example, reveal market expectations of future volatility based on the price of the contract. 8 Concluding our running comparison, Berkshire Hathaway call options striking at $320 and expiring June 21st of next year have an implied volatility of approximately 21%, while Tesla call options striking at $170 and expiring on the same day have an implied volatility of approximately 54%.

There are many different things that cause volatility, but they largely fall into three broad categories, all of which are interrelated to some degree: changes in fundamentals, changes in sentiment and exogenous factors.

Changes in fundamentals, or the underlying cash flows of the asset, are the prime cause of price volatility. Businesses viewed as having more stable and certain cash flows, like a consumer staple such as Proctor & Gamble, tend to have less volatile stocks than do businesses viewed as having more volatile and uncertain cash flows, like a commodity producer such as Exxon Mobil. 9

Changes in sentiment, or investor behavior, can also cause volatility. As investor preferences and expectations for future underlying cash flows ebb and flow over time, asset price volatility can be magnified beyond that justified solely by changes to fundamentals. A good example here would be pandemic darlings such as Zoom and Peloton. 10 As the economy began to reopen, expectations for future underlying cash flows declined, investor sentiment toward stay-at-home stocks soured and volatility increased.

Sometimes exogenous factors, things that have nothing to do with fundamentals or sentiment, can cause volatility. This is usually driven by the tangible flow of funds into, around and out of the market affecting the balance between supply and demand. An example here would be the Archegos trading scandal of 2021. Archegos used derivatives to secretly purchase large amounts of a few stocks, boosting those share prices to unnaturally high levels. When the scheme collapsed, those share prices swiftly fell back to natural levels, resulting in significant volatility. 11

Though not necessarily causal, many other factors can influence volatility. Different asset classes have different levels of volatility based on the seniority of their claims on the underlying asset’s cash flows. A bond, with a higher claim on cash flow, has less volatility than does the equity of the very same business. Different security types have different levels of volatility based on their structure. Stock options, for example, provide exposure to equities for a fraction of the cost of purchasing the shares outright. This built-in leverage, however, amplifies volatility in the price of the option.

Volatility is also influenced by market structure and liquidity. Private markets, where there is no functional market to price the asset, can mask volatility. Private equity firms, for instance, typically value their investments just once a quarter, combining valuation models with market inputs to price the asset. There is significant discretion involved in this process, which has the effect of muting price volatility relative to similar, freely traded assets. The volatility is there, it is just hidden.

A lack of liquidity in the marketplace can amplify volatility. If an asset needs to be sold immediately but there are very few buyers, the price of the asset will likely fall significantly before the transaction occurs. Imagine if you were forced to sell your home for cash today. You would likely have to sell it for far less than you would like. The situation works in reverse as well, pushing prices higher when there are many potential buyers and only very few sellers.

Volatility is conventionally thought of as a negative. This is correct, for a few reasons. Investors tend to prefer certainty and predictability over the opposite and uncertain and unpredictable cash flow streams typically receive a lower valuation. Returning to an earlier contrasting pair, Proctor & Gamble, with a more stable and predictable cash flow stream, trades at roughly 27x estimated 2023 free cash flow while Exxon Mobil, with a more volatile and less predictable cash flow stream, trades at roughly 11x that same metric.

Investors also tend to avoid volatility because it can increase the likelihood of losses. Volatile assets typically have a much wider range of potential future outcomes, many of which will be negative and some of which could be catastrophic. The negative outcomes are much more acute if investing for only a short period, when there may not be enough time for asset prices to bounce higher if they were to fall. If the money is needed soon, it might not all be there when the asset must be sold. Regardless of timeframe, volatility combined with leverage is particularly bad. If you buy an asset for $100 and the price drops by 5% you have lost 5% of your money. If you borrow $90 of the $100, however, and the price drops by 5% you have lost 50% of your money.

Volatility is not all bad, however. For those prepared to take advantage, volatility can create opportunities to acquire assets at discounted prices. This could be due to the other party being forced to sell due to leverage, due to the general ups and downs of the market or due to something else altogether. Volatility can also be managed lower via portfolio diversification. By combining volatile assets that zig with volatile assets that zag, the effect of the volatility on the overall portfolio is reduced without impacting the expected return. 12 More generally, volatility tends to promote strength and robustness. Economist Hyman Minsky popularized a theory that “stability breeds instability” in financial systems, though the concept applies to a multitude of seemingly unrelated disciplines. 13 Acknowledging that a wider range of outcomes is possible discourages risky behavior and encourages planning and preparation, to the benefit of almost any type of system.

Just as volatility has both drawbacks and benefits, volatility can be both a risk and not a risk. In fact, the same instance of volatility can be both at the same time, but for different people. One of the core principles of protecting and building wealth is to structure your financial affairs to transform volatility from a potential risk into a possible opportunity.

Volatility creates risk in at least three types of situations. Volatility creates risk during short time periods, over which price fluctuations up and down do not have enough time to cancel each other out. If you invested money that you may need soon in a volatile asset, you could be forced to sell at a low price and turn a temporary, otherwise avoidable price fluctuation into a permanent, realized loss. This is made worse if the asset to be sold is illiquid, as the price may need to fall abnormally low to attract a buyer.

Even over longer periods of time, volatility creates risk when combined with leverage. Buying stocks using a margin loan is the best example of this. Though you may have every intention of holding onto your shares for the long term, through all the ups and downs along the way, if share prices decline far enough, you could be forced against your will to sell shares at a permanent loss to repay your loan. This same dynamic applies to any business funded with debt. If cash flows are volatile and decline far enough, the business could be at the mercy of its lenders if it is unable to satisfy its obligations.

Even with no leverage, volatility creates risk through psychological pressure. When asset prices fall, uncertainty that they will ever recover arises. The farther that asset prices fall and the longer they remain low, the greater this uncertainty grows. As this uncertainty grows, the psychological pressure to sell the asset to avoid further losses intensifies. Those who succumb to the pressure and sell their assets before prices fully recover will have done nothing but lock in their losses.

In each instance of risk above, there is opportunity for those better prepared to either avoid losses or even capitalize on volatility. Those who invest in less volatile assets for the short-term eliminate the potential for losses upon need of the money, while there may also be opportunities to purchase assets at discounted prices from those having no choice but to sell to raise the necessary funds. Those who avoided leverage, or kept their borrowing to appropriate levels, similarly have the opportunity to act as a liquidity provider for those unable to satisfy their obligations and forced to sell, usually acquiring assets at fire sale prices. 14 Those who understand the cash flows underlying their assets may feel less psychological pressure to sell and/or be able to resist it more successfully, preventing temporary declines from becoming permanent losses and perhaps even allowing for incremental purchases at increasingly attractive prices.

Volatility is one of the foundational concepts of finance, with statistically measurable price fluctuations caused and influenced by a variety of factors. Conventional wisdom has it that volatility is bad and a risk, which is true but incomplete. For those with the right plan, the risks created by volatility can be managed and mitigated to protect wealth. For those prepared, volatility presents opportunities to build wealth. Understanding this difference and applying that knowledge in a disciplined and consistent manner over decades is one of the key determinants between eventual success and failure.

The next column in this three-part series will cover a seemingly unrelated topic, compounding, in a similar fashion, finishing the groundwork for a final column on asset allocation that integrates volatility and compounding with a concept I like to call “the stack.”

Thoughts? I would love to hear them. Email me at

Written By Keith R. Schicker, CFA

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  1. Though such volatility is often, but not always, ultimately caused by fluctuations in the underlying cash flows of the asset, we will set aside this interrelationship for the sake of simplicity. Two examples of assets without this interrelationship are assets without cash flows, like gold or cryptocurrency, but that still exhibit price volatility and assets where the underlying cash flows may be stable but variances between actual and expected cash flows still cause volatility. I am sure there are other examples as well. Please write to me if you know of any that I missed.

  2. Don’t read too much into these figures. This is a very small sample size and the results are not statistically significant.

  3. A normal distribution is the symmetrical bell curve shape that you are likely familiar with. Many things in life are normally distributed. Percentage changes in stock prices, however, are not, but I used the normal distribution here anyway for the sake of simplicity.

  4. Six out of every 1,000 seems too high to me based on personal experience, but the math is the math.

  5. Same as before. Don’t read too much into these figures. This is a very small sample size and the results are not statistically significant.

  6. Having reached the limit of how much math I can ask my readers to wade through in a single column, I won’t walk through the calculation of beta.

  7. An options contract gives the holder the right to buy (call option) or sell (put option) a stock at a predetermined price (the strike price) up until the expiration date of the contract.

  8. This is definitely too much math.

  9. Case in point, over the last five years Proctor & Gamble has had a standard deviation of 21%, while Exxon Mobil has had a standard deviation of 34%.

  10. Over the last three years, Zoom has had a standard deviation of 62% and Peloton has had a standard deviation of 86%.

  11. As before, I am sure there are other examples as well. Please write to me if you know of any that I missed.

  12. I will explain this dynamic in greater detail in a future column.

  13. Those curious can read Minsky’s working paper here.

  14. J.P. Morgan’s acquisition of the assets of First Republic Bank out of Federal Deposit Insurance Corporation (“FDIC”) receivership is a timely example of this dynamic at work. Warren Buffett is also quite skilled at this.