# The Man behind the Sharpe Ratio

Before it was an investment ratio, it was this guy’s last name. Hearing William Sharpe talk about his namesake ratio that now reigns as one of the most quoted risk-adjusted ratios feels a little weird – like meeting Gordon Moore of Moore’s Semiconductor Law or Pythagoras of triangle fame. But thanks to Barry Ritholtz’s Master’s in Business podcast, we all have the privilege of listening to a little more than an hour of conversation between the two discussing his early work, Sharpe’s current thoughts on the ratio, and stories from his time in the business. Here’s what we found interesting:

## Naming the Sharpe Ratio

There’s no doubt the name came from his last name, but as he tells it he didn’t name it after himself and didn’t expect for it to become what we think is the industry standard for risk-adjusted ratios. When he first developed the ratio, he called it the Reward to Variability Ratio (For those who haven’t the slightest idea what the Sharpe ratio is, we talk about it here). But soon after the ratio was noticed, people quickly adopted the term after his name. Sharpe recalls that his wife screamed when the Sharpe ratio made its way into the dialogue of the hit Showtime TV Show Billions.

## Computer Algorithms and His Dissertation

William Sharpe worked on getting his dissertation while also working at RAND Corporation and teaching, what seems to be an unthinkable task nowadays. What’s more, Sharpe was the first dissertation at UCLA that used computer models. Computer models in the 1960s? Seems like words that didn’t belong together back then. This was in the 1960’s before the days of Google, Yahoo, and even excel spreadsheets to offer answers to complex statistical analysis. The title was, “A Simplified Model of Portfolio Analysis.” The simple idea of was to take historical data of a group of securities and plug it into an algorithm that could take advantage of the models – and find efficient portfolios. With the help of investment advisor Fred Weston – they worked to make probabilistic forecasts – running efficient portfolio theories them through algorithms to see what it implied. Step back a second and think about how long that might have taken? Here’s a snippet of Sharpe talking about how he executed these tests:

I did a test in my dissertation of 30 mutual funds – that was my database. And I had to write them down on index cards and write down all the numbers and use a desk calculator.

So how does Sharpe describe what his dissertation was about?

I did what my training was as a micro economist. What if everyone did this? What would be the equilibrium between expected securities and some measure of risk. The conclusion was that the common factor that would mater would be the market portfolio. That’s when the term Beta came to be. That expected return would only be related to Beta – in a linear matter.

## Not All Good Ideas Are Embraced

Despite the modern portfolio analysis being accepted across the board in the investment portfolio world today, his findings were not originally embraced. Sharpe says after a hiccup of his academic advisor not embracing work, he sought out Harry Markowitz, a co-worker of his, who “filled in the role of dissertation advisor” to help get it off the ground.  Just goes to show not everyone thinks something is a good idea.

## What is Risk To You?

Despite the creation of the Sharpe Ratio decades ago, Sharpe seems to have a good understanding of the way people think about risk. Sharpe says there’s no truth definition of risk because it’s all relative not only to what you’re comparing it to but also people’s own definitions and expectations of risk. When asked the appropriate way investors should think about risk, this is what he had to say:

For most human beings – risk is losing a lot of money in a short period of time – unexpectedly. If you think about risk in something that’s more likely to go up then down – risk is a probability distribution; the wider it is, the more risk there is. You can start using measures like variance and standard deviation and simplify it. We don’t worry about upside risk but they seem to go together.

When it comes to the expectations of risk, Sharpe tells a story of a conversation he had with a friend who is an investment advisor:

He said well you want to know how I know what the true risk tolerance of a rich client is? After the markets had a really bad day and I got a call from a client at 2am and they’re yelling, “I can’t take it – I can’t take it.” From a guy who said ‘oh’ I can take risk.”

## Putting The Risk in the Sharpe Ratio

As we’ve talked about before, the Sharpe Ratio isn’t perfect. It treats all rapid or quick movement  (what we are all referring to as risk) as bad and penalizes investments that have good volatility (large quick upward movement) and bad volatility (large quick downward movement). This is what Sharpe had to say about the Sharpe Ratio’s criticism.

Maybe we should worry about semi-variance – which is a measurement of the downside. It takes all the possible downsides and weights them and squares them. Frank Sortino came up with a ratio that uses downside – and yes there’s not doubt about that people weight downside much more than they weight upside. That all is very appealing and attractive but is very difficult to build equilibrium models – that math gets really squirrely. In many cases the distribution is systematic enough – you get similar numbers. Although we’d talked about it, because the math is difficult for securities portfolios – we keep the Sharpe.

Rich investors have a lot more voters – do a lot more research – they presumably can be more intelligent about trying to estimate risk – no one can really estimate risk – I would prefer to think of the markets of setting pricing – taking into account best as one can info about the uncertain future.

## Are We Applying the Sharpe Ratio Wrong?

This might come to a shock to most people, but Sharpe comes right out and says that most people are incorrectly using the Sharpe Ratio. How does he mean? Well, for the Hedge Fund, Managed Futures, And Global Macro types, many include the Sharpe Ratio as a statistic for each of the individual quants or programs. Sharpe says, in his interpretation, the Sharpe Ratio should only really be applied to find a full portfolio’s risk-adjusted return, to compare to other portfolios.

Moreover, Sharpe goes on to say that for the average investor that’s broadly investing in multiple index funds, that Sharpe doesn’t really mean much.

## His Life – His Work

Now in his 80’s, Sharpe continues to work, stating he doesn’t care much for fishing or what you’re supposed to do in retirement. He’s worked with the GM pension fund, the Stanford Endowment Fund, and even had clients that had money invested in the infamous Long Term Capital Management. When Ritholtz asked him about LTCM, he stated, Long Term Capital Management gave his clients back their money before it all came crashing down. One of the few.

Sharpe has spent a great deal of his life educating, and says it’s rewarding, frustrating, and sometimes boring. When asked what he would tell millennials about their interest in getting involved in investment portfolio work, he says to get a very broad education, because we don’t know what the job market will look like in 20 years as some jobs might be taken away by automation.

From his dissertation work, to having his work mentioned in a Showtime TV show, to his days in the classroom, the Master’s in Business interview was a delight. We’d recommend the listen.

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