Financial Opportunities Uncovered: A Keeler & Nadler Family Wealth Podcast

From Spice Routes to Sharpe Ratios:  Building Smarter Portfolios with a History Lesson

• Andy Keeler

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Think your returns tell the whole story? We challenge that belief by walking through the real engine of smarter investing: the relationship between risk, return, and correlation—and how those forces shape a portfolio you can actually live with.  Andy, and Mark Beaver, the head of our investment team, revisit the elegant logic behind modern portfolio theory, map assets onto the efficient frontier, and show where many investors unknowingly take more risk than they need to.

We keep the math human. Risk isn’t just “losing money”—it’s volatility, the swings that test your resolve and erode compounding. We unpack geometric return, standard deviation, and beta in plain English, then put them to work comparing U.S. equities, international stocks, and bonds in the real world. You’ll also hear why diversification is more than owning many funds, why bonds don’t always save the day, and how a portfolio can be tuned to sit on the frontier rather than drift below it.

We also spotlight the Sharpe ratio—subtracting the risk‑free rate and scaling by volatility—to judge whether a “great” 10% decade actually earned its keep. Expect practical examples and historical context going back to tea-and-spice trading days. 

If this conversation sparks an audit of your own allocation, tap follow, and share it with a friend who tracks the S&P like a heartbeat.   Plus, leave a review with the one question you want us to tackle next.

The opinions expressed in this program are for general informational purposes only and are not intended to provide specific advice or recommendations.

It is only intended to provide education about finance, tax, retirement and related planning topics. To determine which investments or strategies may be appropriate for you, consult your financial, tax or legal advisor prior to implementing. Any past performance discussed during this program is no guarantee of future results.

Any indices referenced for comparison are unmanaged and cannot be invested into directly. As always please remember investing involves risk and possible loss of principal capital; please seek advice from a licensed professional.

Keeler & Nadler Family Wealth is a registered investment adviser. Advisory services are only offered to clients or prospective clients where Keeler & Nadler Family Wealth and its representatives are properly licensed or exempt from licensure. No advice may be rendered by Keeler & Nadler Family Wealth unless a client service agreement is in place.


SPEAKER_00:

Do you consider yourself a savvy investor but haven't heard of the efficient frontier? We will explain how tea and spice trading in the 1600s helped to inform our portfolio construction framework today. I welcome Mark Beaver, head of our investment team, to take a deep dive into the underpinnings of portfolio construction. Mark? Good to be here. So back in the day when Captain Jack, yes, that's a Pirates of the Caribbean reference, was walking the plank and tying scurvy dogs to the yard arm, ships crossed the high seas carrying all sorts of goods from the Far East to developing nations. Tracking the flow of imports and exports, let alone the performance of any organized trade, was pretty sketchy up until the 20th century. We didn't have telephones until the end of the 19th century. Slowly, data became available that was used to develop a picture of the global economy, which again was highly disorganized and disjointed back in the day. Fast forward to 1952, where an academic named Harry Markowitz published a concept called modern portfolio theory. He surmised that creating a portfolio by diversifying among asset classes that had low correlations or no correlation would reduce portfolio risk, thereby increasing the geometric return. Okay, so I've thrown a couple of fancy terms out there: correlation and geometric return. Mark, can you start by kind of defining that stuff for us?

SPEAKER_01:

Try not to uh get everybody to stop listening too fast to this one. But um yeah, you the the theory, uh modern portfolio theory from Markowitz, this was from an essay, like you said, in 1952. And at the time it was kind of a revolutionary idea. I think thinking about it now, it doesn't seem that revolutionary, but he he did win a Nobel Prize for this theory. So at the time they thought it was pretty important. Their main consideration, or his main consideration with this theory, is taking an investment portfolio and analyzing it uh based on really two things, risk and return. We hear those two terms all the time, but back then the risk component wasn't often part of a portfolio construction idea. So he really pioneered that concept. Um so really what you're looking at is taking a portfolio's um return profile, expected returns based on and their expected volatility and and trying to figure out is it worth taking that taking on that volatility or not?

SPEAKER_00:

Aaron Ross Powell I use the term correlation. So it would seem to me that the correlation is sort of built into the return and risk. So you have the return, which I use the term geometric return. And and really all that is is the return over a period of time, including sort of the volatility. So it's a compounded return. Morningstar and other data sources use geometric return, and that's really the most accurate method because it it factors in the volatility factor. Volatility is measured by standard deviation, and the simple way of putting that is just how much is a particular investment deviating from the average from one year to the next. And so if you take just those two things alone, the return and what the return was by year and the standard deviation, all by itself, it doesn't mean a whole lot. But when you compare it with something else, you can kind of get a picture as to what these two things are doing in tandem. Are they doing opposite things, the same thing? And then if you multiply that by 10 different asset classes and you have some zigging when others are zagging, that's what I think what he was more or less trying to do is put all those things together in an effort to smooth the rate of return.

SPEAKER_01:

Is that fair? Yeah, I would say back to risk for a second. A lot of people when they think of risk, if you say the word risk as related to investing, most people I think just think the chances of me losing my money. And that's what they define risk as. And that I mean, that's obviously is a risk. Uh, but when you think about investment theories like this one, risk is really volatility or variance of the returns that you're experiencing. So it's not really the same same thing. Because you could have volatility to to the positive, too. You know, if things go up, that's also part of the variance of its return, just as much as it going down. Uh but that's the one everyone's obviously trying to alleviate. So as you're describing with modern portfolio theory, he was looking at these factors to say something about asset allocation. So to throw another term out there. So asset allocation meaning investing in different things. You have investment A, investment B. Investment B has an expected rate of return of five, and investment B has an expected rate of return of 10. That's all great. Sounds like B is the winner, but what if B has a volatility that's four times the amount of A? You know, so now we have a different factor. There's a risk factor that might sway us one way or the other. And then he developed something that's called the efficient frontier, where you plot out uh combinations of these different investments and you see what combination of those two things produce the most quote, you know, efficient portfolio, meaning you're taking you're getting the best return for the least amount of volatility, which is the name of the game. Yep. So that's in an ideal world. You you you know pin that exactly where you want it. We're not taking on any excess risk that's not being rewarded because we're really efficient in how we position our portfolio.

SPEAKER_00:

I'm gonna say everything Mark just said, but I'm gonna say it a different way. So this is remember 70 years ago, so not so modern now, but anyway. So he found that every asset class exhibited different return and risk characteristics. Risk, again, is volatility. You have the obvious one with cash, which is low risk, low return. And on the other end, you have the small caps, which are high risk and supposedly high return. Um, that's a joke for another day, I guess. But uh so the capital markets are based on this idea that you get rewarded with high returns for taking higher risk. So no one would invest in small unknown companies if they offered a lower return than big established ones with AAA credit. So uh GE and Amazon, Home Depot versus say high-max technologies or paysafe unlimited. Um basically plotted the risk and return of each asset class on a graph with return measured on the y-axis. That's the vertical access for those 30 years out of college, and risk on the X asset axis, which is the horizontal one. Again, with cash being low risk and low return, that asset class sits down in the lower right-hand corner. Bonds have a little bit more risk, but more return, so they sit above cash to the right. Large cap US stocks yet more risk and return, so they sit up further and to the right, and so on. Small caps would be far right and up given the higher risk and higher return. When plotting these, the line actually appears concave, like sort of a normal yield curve.

SPEAKER_01:

Yeah, it's almost like a tilted C that's stretched out a little bit. I don't know how else to describe that verbally. But um, in a perfect world that doesn't exist, you know, in that those axis you just described, your investment would be all the way up to the left. No, no risk or no volatility, but all of the return. But not on the line. It's not on the line because it can't happen. There's no such thing. Um, so you have to try to actually get into the real world, and that's where you're plotting around this bending frontier to see where are we taking effective amounts of risk.

SPEAKER_00:

And so a sub-optimal portfolio could be optimized or made more efficient by either a increasing the expected return for the current level of risk, which is again standard deviation, or so yeah, you have two choices. You either do that or you reduce risk, but achieve the same expected return. And so, you know, and it's it's hard for listeners maybe to envision this, but as Mark said, it's sort of this inverted C. You know, you could kind of just draw a line from lower left to upper right, but put a little curve on it. We find in practice is that a lot of the prospective clients we talk to, their portfolio, if we if we make like a dot plot, and based on all of the different things they have in their portfolio, 10 different investments or 12 different investments, a large cap growth, a large cap value, a foreign, whatever, their dot is below that line, which is the efficient frontier, which means that their portfolio is inefficient and it's exposing them to unnecessary risk. As Mark said, you know, everybody wants to be above the line. Well, that's out of bounds. It's not possible. Um, but you'd at least want to be on the line, and you can do that by basically just tweaking the portfolio allocation. So can you talk a little bit more about how that's done and correlations, maybe give some examples of you know, we use we use the the S ⁇ P 500 as kind of ground zero. It's sort of the baseline, and then all these other asset classes, which you can talk about some, maybe the more common ones and maybe some obscure ones, uh, and and what how they relate in return to the S P 500.

SPEAKER_01:

Yeah, the the efficient frontier stuff really only starts to work when you have less or non-correlated investments. If they're all doing the same thing, the the line's not really going to bend in any sort of efficient way. So correlation just meaning how connected are those returns from one investment to the other? If one is going up, is the other one going up just as much? And if and vice versa, if it's going down, it's going down just as much, then you're just really duplicating your results. You're not changing it at all, you're not softening the losses, you're not, you know, smoothing out the experience at all. So that's what we mean by monitoring correlation, how connected is one investment's experience to the other. And so when we look at that, we can look back, you know, the last 10 years, roughly, uh, on a number of different investment uh asset classes, just meaning different kinds of investments. So the US stock market, the SP 500, like you mentioned, compared to international stocks, for example. So that used to be one avenue, I would say historically, where there were lower correlations. And so people would think of that as a really nice diversifier. More recent times in the last 10 years, they've been fairly correlated. So the correlation is around 90%, meaning, you know, the market, the stock, US stock markets going up, international markets are going to go up about the same, you know, roughly, uh, and vice versa. So not that different. If we look at uh really the big category that we see, especially when you're doing these efficient frontiers, is stocks versus bonds, you know, how much you want to have there, because that was always seen as the big diversifier. Uh low.

SPEAKER_00:

They do the opposite. The theory is they do the opposite of stocks.

SPEAKER_01:

Yeah, lower or sometimes negative correlation. Like you said, 2008 stocks dropped, you know, a massive amount, you know, depending on the time period, I think, you know, 35 to 50 percent uh during the whole situation, and bonds went up five percent, I think, in 2008.

SPEAKER_00:

So they went the opposite direction, which is which is a negative correlation, a correlation of less than zero. Okay.

SPEAKER_01:

So that's perfect. That's what you want from a diversifier. Now, in the last 10 years, bonds have had about a third correlation, so 0.3 or so. So a lot different than negative. It's a lot lower than international stocks, but it's still moving in the same general direction. Somewhat correlated. So you can kind of look at that across the board at these different asset classes and see is one more or less correlated to each other. But that's not the whole story either, because these asset classes all have different volatility to them, too. So bonds are a little bit correlated, they also have a pretty low amount of volatility. Uh international stocks more correlated, more volatility. So that's giving you less diversification benefits. So if you take all these different things and you do the dot plot, like you said, you plot this all over the chart, it's gonna look pretty scattered. It doesn't really look like a frontier, it's just all over the place. But then you start making combinations of these things and drawing that efficient frontier sort of along the the outside of the dots and see, okay, this combination of this, this, and this gives me my best combination for risk in return.

SPEAKER_00:

I come back to the reality that many portfolios out there are inefficient. And the uh inspiration for this nerdly episode, and and I I'm imagining anybody that has gotten this far in the episode, they're they're nerds. They're into it, and we're gonna go even deeper. But uh for those that just want to get an optimal portfolio with the minimum amount of risk you need for a specified amount of return, we find that it's not uncommon. It's I would say more the um rule, not the exception, for portfolios to be inefficient to some degree, some more than others. And so the moral of the story here is that by tweaking the allocation of your portfolio, you may be able to either increase the return for the same amount of risk, or if you're comfortable achieving the same amount of return, lower the risk. It's one or the other, but you should do you should pick one.

SPEAKER_01:

It's been very instructive to the investment community ever since. But at the same time, it's not a perfect theory. It is a theory. Uh and interestingly, there's a a quote from Markowitz himself when someone was asking about it, and um, I think this is in Jeremy Zweig's book uh about investor psychology. And he said, you know, for his own personal portfolio, I should have computed the historical variants of asset classes, drawn the efficient frontier. You know, that's what he made up. He said, instead, I visualized my grief in the stock market if went if it went up and I wasn't in it, or the grief if I it went down and I was completely in it, so I just did a 50-50 portfolio. This is the guy who made this whole thing up, and he's saying, I don't know, I just do 50-50 because so I don't get mad if it goes up or mad if it goes down. I'm doing you know pretty well in both situations.

SPEAKER_00:

That was Jason Zwag?

SPEAKER_01:

That's the author of that book, but he's quoting Markowitz saying this. You know, so um even the person that found the you know this whole connection uh when it comes down to it is a human being, and so you have to kind of do what you can do.

SPEAKER_00:

You know, I think there would be folks out there that say, okay, I have this these menus of investments and correlations and all this stuff. And if, for example, the SP 500 has I use geometric return, but basically it if it has the highest compounded rate of return, who cares what the risk or correlation is than anything else? At the end of the day, I have achieved a higher compounded rate of return in this particular asset class than any others. So why do I need to really bother with all this other stuff?

SPEAKER_01:

And the best return that you get is the one that you actually get, not the one that you got on paper looking back the last 20 years. You know, so all of these theories and and measurements are useful, and we certainly use things that we've we talked about here, but they're looking backwards to see what the returns were, what the volatility was. That doesn't mean that's what it's going to be going to the future. You know, so we'll use things to throw more terms out, like the capital asset pricing model to say, you know, this is the expected rates of return for these asset classes, the expected uh volatility. So therefore we can try to build the best portfolio on that. Those are educated guesses because you know, we don't know the future uh and what it what it brings. So, you know, there is limitations on that because we are, you know, driving the car looking in the rearview mirror, you know, with some of those things, which we know can cause some problems. So I think there's always the the academic side that we're going to continue to have influence over our portfolios. And then there's the human element in the psychology element of you can only really invest in something that you can stay invested in, because some of these efficient portfolios might look good on paper, and there's no way someone's going to stay invested in those things because there's kind of wonky looking portfolios actually, and you might be disconnected from what the market's doing for a decade or so before that you know uncorrelatedness actually starts to actually show value. And people don't tend to do very well with scenarios like that where they are so far away from what's going on in the market that they just ride it out for seven or eight years. Probably not. They probably bailed in year five or six and lost all of those actual benefits.

SPEAKER_00:

So yeah, you know, I started with uh Pirates of the Caribbean uh analogy, and to kind of come back to that and and connect it to what you just said about us looking in the review mirror, most of what we use is based on history. We generally look at longer-term history. We're not so concerned about what happened last month or last year, but what what happened the last 10 years or 20 years? Markowitz was looking at the history that I gave, which was really uh unchartered waters until at a minimum the end of the 1800s, and then really data became available at the beginning of the 1900s, so he's looking at correlations and returns and risk of asset classes for that period of time from say 1900 to 1952. Times change. We are not the same world today, 70 years later that we were then. We are a global economy, and with technology, um, communication, uh, the speed at which we can get goods from one coast to another, all of those things have made those correlations increase. Well, I guess now is a good time to talk about, okay, the capital asset price at pricing model and capital market expectations. You know, now we're saying let's sort of discount what happened through 2024 and try to predict what's going to happen in 2025 and the next 10 years. And it would seem to me, my gut would say, and you know, I'm not a noble laureate here, but my gut would tell me that correlations, at least to foreign assets, would likely start decreasing because those some of those countries are trying to become a little less reliant on trade with the United States. And so I don't know what the correlations were to foreign, but say 80% or 80 to 90 percent correlated. Um so meaning if you invested in a foreign stock fund, um your returns were about 80 to 90 percent correlated to the S P 500. So not a great diversifier, but you know, back 60, 70 years ago, much better diversifier and and maybe a little bit better diversifier going forward. It's hard to say.

SPEAKER_01:

Yeah. And it's all this stuff is so dynamic because you could look at one decade to the next on all of these asset classes and all of the correlations change just in those different periods. So that's where you know, trying to guess what they could be over the next decade is is a a really big challenge. Uh, you know, so there has to be some assumptions that are made. But yeah, it's not even just looking historically and saying this is what they were, because even through whatever period you're looking at, they've probably changed multiple times through that. You know, so we saw international stocks uh in the turn of the millennium, you know, during the 2000 to 2010, international stocks did very well compared to US stocks. So there was that one decade there that they did good, the following decade not so good. So if we just looked and said over the last 50 years, that's not even telling us the whole story of correlation or volatility because they can fluctuate.

SPEAKER_00:

And you know, talking about those swings, let's let's talk about a specific asset class, a specific category that does have a dry spell and the returns are really paltry, either zero or you know, one to two percent over a 10-year period. And it just so happens that it's got a low correlation to the S P 500. Is that asset class adding any value to the portfolio?

SPEAKER_01:

I would say whenever we're looking at asset classes to add or not into a portfolio, there's a couple of things we want to make sure of. One, we're hoping that there's a real expected rate of return. And when I say real, it's not like imaginary or not. It's is it above inflation over that expected period of time? So a zero or a one or a two is probably negative real rate of return going forward. So from a that I don't really see that as an investment. It might be some kind of store of value, like you know, having it in a savings account or something, but or commodity. Yeah, but it's not really adding something beneficial from a return perspective. So we we like the low correlation aspect, but we also want real rates of return over time. So if you don't get both of those, then it's less ideal. It's harder and harder to find things with low or no correlation, though. Like you said, most things have some amount of correlation these days. Probably is because information's everywhere. Um, it has to be something to do with that, I would imagine. And um, interesting you brought up the globalization and maybe bringing correlations together. And you know, in the last year or probably more than a year, maybe there's some cracks in that where people are sort of isolating themselves country to country, and maybe that brings back a little bit more opportunity from a correlation perspective.

SPEAKER_00:

So I said for the the nerds that are still tuned in and listening, we would get deeper into the weeds. So I want to introduce another concept. Um, you know, we have we have uh Markowitz, we've talked a little bit about him. Um there's also another gentleman named William Sharp, and he created this thing called a sharp ratio. And I'll have Mark explain what that is in a second. But I want to ex I want to start by really laying the groundwork as to why it's helpful to know the sharp ratio of a portfolio. So it's not uncommon to meet with a prospective client and they say, you know, I'm really pleased with the performance of my portfolio. Okay, so what what was your rate of return over the last, say, 10 years? It was 10%. I'm really pleased with that. And you know, the first question that I would ask is, well, you know, is that really good for the amount of risk that you were taking? Could you have earned 11 or 12 with the same amount of risk or less? But before we get into that, um I think it's important to be to compare risk and return. And I'll kind of start with a baseline portfolio that has a return, uh let's say it's a 10-year return of 10% and a standard deviation of 15. So that's kind of your your benchmark. If you had a an investment or a portfolio that had a return of five and a standard deviation of seven and a half, you'd say, okay, it would seem like they're comparable. It's half the return, but it's also half the risk. If you had a portfolio that had a nine percent return instead of ten, but had a standard deviation of sixteen instead of fifteen, you'd say, yeah, that's probably not as good. Because I'm getting really 10% less return, 1% out of 10%, 10 to 9. But I have a standard deviation that's one point higher. So that that's an unfavorable trade-off. But when you start, first of all, I would say most people don't really know where they stand with respect to these numbers. They just know, okay, I earned 9%, I'm happy with that. Did you know that you could have earned 10 with less with less risk? But where the sharp ratio comes in is where you have more tricky numbers. Let's say that your return is nine, not 10, but the standard deviation is 14. So they both went down by one point. Kind of quick math would say that the standard deviation went down less by a lower percentage than the return went down. So, Mark, explain what the Sharp ratio is and how it works.

SPEAKER_01:

Yeah, and I think William Sharp was actually a student of Markovitz's, if I'm not mistaken. Um, so I think in some of his you know, education along the way, he came up with um a number of different things. Some of them we've already mentioned. You know, he was the person that introduced beta. You know, it's another comparative uh thing that we look at. We're just throwing out all these functi measurement fun terms today. Um so you know, beta is comparing volatility of one investment to something else. So it's not just saying standard deviation is sort of on its own. You know, you have a standard deviation of this number, that's the measure. Beta is comparing it to something else. So if you have a beta of 0.5 to the S P 500, it's saying you've half of that volatility relationship to the SP. So he added all these kind of comparative ratios and things. So the Sharp ratio is kind of similar, where technically taking the excess return, so you take the return minus a risk-free rate. So say it's like 3% for treasuries or something like that. So you have the excess return divided by the volatility, like you said. So now I can compare that ratio to something else and see how effective or how efficient is that return. So kind of back to what we were saying earlier of would we want to add this low return, low volatility investment or not? Well, if you're subtracting the risk-free rate, that's gonna make it look even worse. So if you had a 3% return, 3% volatility, but the risk-free rate's three, it's everything's zero. You know, so you have zero sharp ratio versus something that might be, you know, six percent return, six percent volatility, but at least you have a sharp ratio of 0.5, you know, in that scenario. So it's saying still worth it because you're getting excess return over the risk-free rate. So um it's a it's a a much better ratio than uh a lot of other ones for that me, that reason. That it's not just comparing return, it's not just comparing the volatility, it's comparing the combination of those things. So it's kind of taking Markowitz's efficient frontier concept and saying, here's a quick ratio to compare one to the other uh and and look at that that relationship.

SPEAKER_00:

Well, thanks, Mark, for making my brain hurt. And as always, we thank our listeners. I'm Andy Keeler, and this is Financial Opportunities Uncovered, brought to you by Keeler and Nether Family Wealth. If you have questions on anything you heard in this episode or you have an idea for a future episode, connect with us on LinkedIn or shoot me an email at andy.keeler at knwealth.com.

SPEAKER_01:

The opinions expressed in this program are for general information purposes only and are not intended to provide specific advice or recommendations. It is only intended to provide education about finance, tax, retirement, and related planning topics. To determine which investment strategies are appropriate for you, consult your finance, tax, or legal advisor prior to implementing. Any past performance discussed during this program is no guarantee of future results. Any indices referenced for comparison are unmanaged and cannot be invested into directly. As always, please remember investing involves risk and possible loss of principal. Please seek advice from a licensed professional. Keeler and Nadler Family Wealth is a registered investment advisor. Advisory services are only offered to clients or prospective clients where Keeler and Nadler Family Wealth and its representatives are properly licensed or No advice may be rendered by Keeler and Nadler Family Wealth unless a client service agreement is in place.