Digital Dives
Our relationship with risk is complicated. Threats can force action, or they can paralyze. Sometimes we overreact to a perceived danger and other times we underestimate a hazard, resulting in loss.
Capital markets are a realm of uncertainty. As such, operators use a variety of benchmarks to analyse historical events, make sense of what’s going on, and inform estimates about the future. Conducting this kind of assessment can be helpful, but it must be accompanied by a healthy and consistent dose of humility. Given the popularity of investing in the media, there are countless figures thrown around to describe various investments. These metrics can be used to provide confidence in a risky environment. However, it’s always important to dig a bit deeper because too much reliance on reported barometers can lead to a false sense of security.
Some common statistics that get used in financial vernacular include averages, correlations, and variance. If I told you that four datasets all share the same values for those figures (to the decimal), would you think they’d look similar?
The charts above comprise Anscombe’s Quartet. The four datasets appear to be identical from the perspective of summary statistics but they’re actually quite different. This finding emphasizes the importance of outliers and other influential observations. Understanding distributions is essential to modern society and statistics is the language we use to explain them, but it still pays to look under the hood and examine the data visually.
Modern portfolio theory defines risk as an asset’s volatility. Additionally, there is supposed to be a proportional relationship between volatility and expected returns. Riskier assets have the potential to generate higher returns, but they also have a greater propensity for loss. An investor must accept uncertainty if they are to generate returns above the “risk-free rate”. Building off this idea, a Nobel Laureat, William Sharpe, developed a ratio that looks to standardize an asset’s excess return as follows:
The Sharpe Ratio seeks to characterize the extent to which an asset’s return compensates the investor for the risk taken. In the asset management business, one of the first questions prospective capital providers will ask is, “What’s your Sharpe?” It can be used to evaluate the performance of an investment portfolio or that of an individual holding. Anecdotally, I’ve seen the metric applied more commonly in a historical context, but expected returns and volatilities can also be used to generate an ex-ante Sharpe Ratio to inform asset allocation decisions.
When comparing two investment opportunities, choosing the one with the higher reward-to-variability ratio is generally preferred because the investor receives more return for the risk assumed. However, there are some important nuances at play that can ambiguate an assessment using this metric alone.
First, the frequency of data measurement matters. A ratio calculated using daily price swings will capture more variability than one which only uses monthly figures because significant intra-month reversals will be missed. Further, there is no distinction between up or down price moves and it’s difficult to interpret a negative reading. Finally, non-volatile assets can still be quite risky. Private equity investments are marked-to-market quarterly (at best) and even still, the assessment of value carries some element of subjectivity, which can dampen volatility compared to a market-based assessment. As the world has been made acutely aware these past few weeks, securities booked as held-to-maturity are carried at cost on a bank’s balance sheet, but their underlying value changes with macro inputs like benchmark interest rates.
To illustrate why relying on key benchmarks is not a substitute for comprehensive due diligence, let’s consider the various elements of the Sharpe Ratio for Silicon Valley Bank (SIVB) versus the S&P 500 Bank Index. We’ll begin with the 15-year total returns.
The Silicon Valley Bank stock chart looks like something you’d expect to see from one of their high-flying tech clients and even after a 66% decline last year, they still outpaced their peers’ returns by more than 2x. It’s worth pointing out that, when calculating the Sharpe Ratio, the numerator isn’t simple total return like we’ve shown above. We’re concerned with the excess return above the risk-free rate, which has been incorporated into the analysis that follows.
Turning to the denominator of the reward-to-variability ratio, we can see that SIVB’s excess returns have demonstrated considerably more variance than the weighted average S&P 500 bank. This can be expected since the individual name doesn’t benefit from the diversification of the index. However, the average volatility of the now defunct financial institution was almost twice as high on an annual basis over the period observed.
Now let’s synthesize the excess returns and volatility to compare the historical Sharpe Ratios of Silicon Valley Bank versus its benchmark to see if investors were being adequately compensated for the bumpier ride:
Up until very recently, the case for owning SIVB based on risk-adjusted returns was quite compelling – they outperformed on a Sharpe basis more often than not. Frankly, the fundamental thesis justified the higher returns as well. From the Great Financial Crisis to the end of 2022, SIVB compounded its Earnings Per Share at 10.5% and grew Book Value Per Share at 16.6% annually, which compares to the Index at 8.9% and 2.0% respectively.
Here’s the thing... Often, risky investments will demonstrate more variable returns, but identifying risk solely by price volatility is overly simplistic. Perils fester out of sight while we’re distracted by other narratives. It’s easy, almost obvious, to explain what happened at Silicon Valley Bank in hindsight, but few were sounding the alarm until right before the bank run and ensuing crash. Sure, the stock underperformed in 2022, but historically, investors had been rewarded for accepting this higher volatility. Looking back, it’s clear that shareholders had not been adequately compensated for the true risk of their holdings in the firm.
Taking a digital assets perspective… Bitcoin has provided many holders of its native tokens with outstanding profits. Over the past five years, adding a 10% allocation of BTC to a traditional portfolio of 60% equities and 40% bonds would have generated a 49% return compared to only 11% for the 60/40 alone. On a “risk-adjusted” basis, the digital asset has outclassed traditional investments, too. The BTC & Balanced portfolio had a Sharpe Ratio of 1.5 compared to a balanced proxy at -0.67. So far, volatility has proven to be more of a feature than a bug of the digital asset ecosystem given the wealth creation afforded to those who managed to hold-on through the turbulence.
However, the digital asset ecosystem recently experienced a significant bout of volatility where it’s unwanted – stablecoins. While regional banks were failing in America, USDC depegged meaningfully from $1 as the ecosystem feared that some of the reserves backing the stable stalwart had been lost.
Animal spirits have since calmed, but has risk subsided or is it festering behind the scenes somewhere? If you listen to this interview with Circle’s Jeremy Allaire (USDC’s parent), then you might come away thinking that the bout of volatility has resulted in an outcome where a fundamental piece of infrastructure has been reinforced. Like our bones, which grow stronger under stress, surviving the chaos may have buttressed USDC. As I said at the beginning, our relationship with risk is complicated. It might be tempting to distill it down to a simple metric or two, but this is a misguided substitute for diligent and humble analysis. Frankly, a little paranoia can be helpful too.
So, what are you worried about right now?
