In
the new economic paradigm of higher interest rates and higher inflation, allocators
are considering different ways to rebalance to meet their targets. In this discussion,
Christine Giordano, editor of Markets Group’s Institutional Allocator,
interviews Donald Pierce, the Chief Investment Officer of the $14 billion San
Bernardino County Employees Retirement Association in California, and Arun
Muralidhar, who has a Ph.D. in managerial economics and finance from MIT and is
co-founder of M-cube Investment Technologies LLC, (developer and licenser of AlphaEngine® software) and the asset
management company, AlphaEngine.
When
Pierce joined the fund in 2001, he wanted to find a way to enhance the range-based
rebalancing that had been in place. Since 2005,
he and Muralidhar have been working together to improve SBCERA’s
rebalancing methodology, and Pierce has gained about 100 basis points per year.
Throughout this interview, the two will elaborate on how exactly they have done
it and explore how their process responds to market volatility, from the Great
Recession of 2008 to the high interest post-pandemic environment.
Christine
Giordano: Donald,
you’ve been at the fund since 2001 and you’ve initiated the software since
2005. Can we talk about what convinced you to put this in place and what it
took for you to get there?
Donald
Pierce: Thank you very
much. When I first joined the system back in August 2001, the peak of the
market that year was in March. So we didn’t really start getting a sell off
until later in 2002 and continued into 2003. The range-based rebalancing we had
at the time didn’t feel adequate for what we were dealing with. Unlike what was
popular at the time, which was the idea of perfectly implementing your policy
portfolio as the ideal, ranges were an acknowledgement of the frictions in
implementing the perfect policy. But that rebalancing was not viewed as
potentially additive, but as a risk mitigant. In general, they were right in
the way they were doing it by just using range-based rebalancing and letting
the market tell you when to move based on price movement. And so in 2003, I had
proposed a feasibility study to review our rebalancing method and while the
concept was strong, the proposed execution was lacking.
That
is when around 2004, by happenstance, I met with Arun when he was showcasing
AlphaEngine and I was floored because he was dealing with things I was only
just scratching around at. I had a problem wherein the back of an Excel
spreadsheet wasn’t entirely convincing to the board. Instead, a model and
software application that was pulling live data down to make better decisions
was something we took back to the board in July 2005 when we went live. But in
order to explore this, what we really wanted to do was make sure we’re not
transacting more than we would if we were just doing range-based rebalancing. So
the board was engaged at least because we kept telling them that we have this
concept and this idea, and I think that they were open to it to the degree that
we didn’t transact more than we would have otherwise. From there, we went live
in in July of 2005. And then we brought on an overlay manager to help us as
Russell Investments to help us in 2006. And it’s been working that way ever
since. The genesis was a two year incubation period, but with the accelerant of
a software program that really dealt with the issues. I’m sure Arun can go over
what prompted him to do it because at that point it was outside the viewpoints
of asset allocation and asset management for pensions.
Giordano: Arun, can you tell us what led to this
new idea?
Arun
Muralidhar: Sometimes
it’s wonderful to make big mistakes. And I tell a story which I tell to all my
students that in 1998, I worked for the World Bank’s pension plan, and I put an
asset allocation in place where the expected return on equities, for example,
was 10% and that had been pulled from all the major banks and asset managers.
Then I left to go to JP Morgan (in 1999). And when the tech bubble burst, we
put very tight ranges on the assumption that it was actually good risk
management.
To
Don’s point, why not have perfect policy implementation – when you get into a
secular bear market, the tight ranges make you buy, then you lose again, then
you buy again, and you lose, and they can actually be a risk-increasing
activity. At the same time, I was in charge of the research on 20 billion of
currencies at JP Morgan, which was being done on Excel spreadsheets. Enter the
World Wide Web and it just struck me that finance is nothing more than taking
data and converting it into decisions. Today, they call that Big Data AI, but
all I wanted every morning when I woke up was to have a simple GPS that every
asset owner could have had to apply on the one decision that affects 100% of
the portfolio. But then I saw all the clients at JP Morgan getting smashed because
their asset allocation took a beating in the tech bubble. Forgetting about the
alpha, the question that came up was how we could help pension funds and
endowments manage the single biggest risk in the portfolio, which is asset
allocation, in a slightly more intelligent and informed manner? And so
essentially, what we were trying to do with the software was allow intelligent
folks like Don to take their ideas, put it in software, and then allow it
(AlphaEngine) to process (regularly). That way, clients would have exactly the
same process (on 100% of their portfolio) as a JP Morgan or a Blackrock would
have in managing 2% of their portfolio. It was very idealistic because we
really, genuinely thought we could transform the industry since nobody was
providing the service at the level we were offering it at. And that allowed the
CIOs who would be interested to do this in a much more efficient manner.
Giordano: Looking into the data, and sorry if
I’m kind of digging into your secret sauce, what exactly do you look for that
makes the difference here?
Muralidhar: For us, data typically comes from
vendors. So, you could have economic data coming from the Federal Reserve, the
OECD, or the IMF, which is a lot of data that’s being thrown at people. And
then you have price data on things like securities, the price of oil, and the
price of copper, along with credit spreads and volatilities. So, there’s a lot
of data that’s sitting out in disparate places. Our idea was to centralize the
data in one place, where somebody like Don wouldn’t have to go hunting for it.
And with a couple of clicks on our website, he could find it and make sure that
it was cleaned up before he acted on it. That is a service we’re providing with
a team in Bangalore which still does that every day. They’re gathering that
data, scrubbing it, and making sure that it’s clean. And then he can write
whatever rules he wants to say that as the price of oil goes up, for example,
he can reduce his stocks accordingly. Or if interest rates go up, to throw a
lot of stocks into bonds. That’s essentially all we were doing with data, with enabling
technology to empower CIOs to make much better decisions.
Pierce: And so, if I could, the things that are
our model methodology tend to rely more on valuation methods. We tend to have
very yield focused analytics, so if the yield on bonds is higher than a certain
amount of the dividend yield or earnings yield, or favor bonds over equity, we
then use sentiment indicators like credit spreads, VIX spreads and things like
that. And so are our data use tends to be valuation and sentiment driven as
opposed to economic, but that doesn’t mean that people can’t do it, which is the
real benefit of Arun’s AlphaEngine. His thought process was that he could
provide a menu of options for people. And whether or not you elect to to use it
or not would be entirely up to you. But I think that was certainly our
experience within the confines of a turnover limit. That’s what we ended up
with.
Muralidhar: We went one step further, Christine, because
we didn’t want to have people dependent on us for data, as Don is finding out
data vendors can be difficult to deal with. So we even allow clients to upload
their own data into the system. Let’s say your asset manager’s willing to send
you a certain data series that you want to make decisions with. The platform is
meant to be data agnostic, so that if you wanted the data from us, we would
collect it from you, but if you have the data from your own source, no point to
paying for it twice. Because the data was just one part of the whole process, on
how do we get you to better decisions, once the data is in the system and scrubbed
and clean and ready for you.
Giordano: So many people are strapped, in which
they cannot hire that extra analyst, access public pension funds, or don’t have
the permission to hire that full timer here and there. Does this actually take
the place of an analyst? How does this work to kind of perhaps pay itself off?
Pierce: The value-add proposition here was entirely
an improvement on the rebalancing methodology, as opposed to more of a cost
savings for employees. We certainly made the argument that that range based
rebalancing that we had in place, had a track record of reducing risk, but not
really adding a lot of value. And then on any particular day, it might have
added a particular amount of basis points to the plan, but if you were to fast
forward six or seven months it might not have. As Arun made that particular
point of saying, in a bear a secular bear market, taken in totality, range based
rebalancing would be a risk reducer, but it didn’t add value. One of the things
that we had established is that in using market data to make better decisions,
we hypothesized that we could use we could make 35 basis points on the total
plan, and for every CIO out there listening, they’re going to realize that is a
staggering amount of added value. If you gave a money manager 350 basis points
of outperformance, they would need to have a 10% allocation to get that sort of
the same kind of buying value. And as Arun has shared and suggested, this is
one of the areas that is just not fully engaged in. We spend a lot of time evaluating
our asset allocation and managers. But we don’t spend nearly as much time
evaluating the shifts of the portfolio within the ranges that have been
established. And so, for us, it was really a value-add argument, as opposed to
just saving on some employee costs and things like that.
Muralidhar: I just came from the Netherlands where
I met my first ever client, Roland van den Brink and Patrick Groenendijk from
PME Pensioenfonds. Patrick was the equivalent of Don and Roland was the CIO. When
I showed him the software, he told me, “Arun, don’t fall in love with your
software. For me, the most valuable thing, even if it doesn’t make me a single
euro, is you now told me I can delegate to my staff and the decisions will be
transparent. This is exciting governance where you’ve pre-tested the idea before
pulling the trigger, because that type of discipline and governance is worth a
lot of money to me.” I’ll never forget that. In fact, it was one of my
most enjoyable afternoons with him still; because he taught me how critical it
was for a CIO to be able to trust a staff member, and how important transparency
and this ability to say when he’s pulling the trigger, there’s a 50/50 chance
that he’ll get the direction correct. But if he’s done all the hard work
before, and the analysis is good, then he could defend that position very
easily. And that was a very, very insightful comment.
Giordano: It comes from the top down as far as
the thesis is plugged in. But it’s malleable; you can shape it to your own
thesis within the Investment Office. Are there certain theses that you’ve seen
for this new economy that are impressive that you can share?
Pierce: We don’t have an economic motive to
change our model because I don’t have a month-to-month track record that I have
to necessarily sell. But I am incredibly encouraged by the robustness of the
rules. The reason I say that is because it has served us in long stead and the
most recent circumstances where we had a sudden shift from a very frothy market
in 2021 with a recognition that the inflation was not transitory and that rates
needed to rise to combat it. The value of using an overlay program to help you
with rebalancing is that you’re a lot closer to the market and I’m happy to go
into that. As an information or knowledge management improvement, I cannot
stress that just getting one step closer to the market makes you a much better
investor, it really does. There are knock on effects to being a more engaged
investor, on top of the 35 basis points of expected return, or in our case 100
basis points since inception of the program! We’re going on 16 years, 17 years
and what I’m proud of is a model that was developed out of research in the late
90s, early 2000s, has held its ground and has been very robust during our time
period. Now, it has not worked in every period, but when it has, it pays off
immensely.
Muralidhar: I would add that the central bank’s
intervening in markets has been a complete paradigm shift. It encouraged an
enormous amount of risk-taking behavior, low interest rates, and basically
bailing out the slightest stumble in markets. So, capturing sentiment became
very critical and we still we run an investment business using exactly the same
software license with very different objectives from what Don’s doing. Using
sentiment indicators becomes very critical because the market can shift on a
dime. Because Don doesn’t have to worry about managing assets for third
parties, he has the ability to be more patient, which I’m very envious of.
Because there are some rules that are so easy to look at, if you could just
have the patience to wait it out. So for somebody who’s faster moving, you have
to worry about technical analysis and sentiment indicators. Somebody like Don,
who can be a patient investor, can consider overweight equity positions for a
number of years, and whether it is good or not.
Giordano: And of course, everyone is talking
about inflation and a potential recession. With both of you actually having
lived through the Great Recession financial crisis with this software in hand,
how do you expect it? What would you have expected to do with it if we didn’t
hit a recession?
Pierce: Our model is based on relative value expectation.
So in other words, we’re not making forecasts as to whether or not stocks are going
to go up eight or ten or twelve. What we’re simply doing is saying stocks might
be better than bonds, or in some cases, like now, we think bonds will be better
than stocks. And that sort of differentiation of where you think those payoffs are
is less a forecast and more an evaluation of the things that we’ve talked
about, which is valuation and sentiment. This includes things like VIX levels, credit
spreads, and things like that. And so we have a number of the rules that we’ve
developed, based on the research from the 1990s and early 2000s. That gives us
confidence that the portfolio on any particular month could be offside, like
for the last six months, where it’s been overweight bonds and underweight
equity, which has not felt like a particularly smart thing. Watching the stock
market rally in the face of interest rate hikes is not one of the most fun
things to watch. But at the same time, we and the board have confidence that the
program will work over time, and it does need that time. Earlier on, we
probably had the same issues, whereas when we first started the program back in
2005, had we had a bigger misstep and we were running into issues, we probably
might not have survived. But the longer you go, hopefully the more your clients
will stay around.
Muralidhar: We had a really good 2008. We nailed
it and I asked how we could make it even bigger. We got lucky because we had David Deutsch at
San Diego County who started as a software client (in 2006) just like Don. But
the board was putting so much pressure on him saying you can’t be this smart.
He was making money, so he called us up one day and asked us to manage it
because we knew how to do this and it was easier for him to hire us. He came to
us with one (additional) request, which is don’t just make the money, but make money
when things go really bad because at that point, I’ve got no outlet. And so we
ended up putting together these rules like Don was talking about that had a
particular tendency to do well when the markets blew up. So we had a very good
2008, we had a very good 2018, which again was where people were struggling.
And I hate to say this, but this smells and feels like 2008 on steroids. We’ve
got a lot of allocation to illiquid assets and Central Banks have huge balance sheets., Raising
rates is only focused on inflation and nothing else. Silicon Valley Bank and
Credit Suisse both folded. There’s a lot of damage in commercial real estate.
Not to sound depressing, but when this breaks, it’s not going to be pretty
because one of the things that happened was when it broke in 2008, is the fact that people had so much allocated
to illiquid back then – the Ivy League’s particularly – the cash illiquidity
forced them to sell more equities. And now every pension fund in the world, not
just in the US, are so heavily allocated to illiquid assets, I think it’s going
to be catastrophic if you don’t have a process in place to manage the risk of
your illiquid assets. I think that will be the killer this time around.
Giordano: And we mentioned having rules in place
that served in 2008. Can you share one or two of these rules?
Muralidhar: We have one rule, which is a very
common one in the academic literature, called the Baltic Dry Index, which
measures global economic activity. And when that slows, it’s typically a bad
sign for the economy, which is a bad sign for stocks. We also look at the ratio
of price of oil or the price of copper, which industrial prices indicate. So,
we see trends in those indicators within the economy. As Don says, we look at
credit spreads and how different risky assets behave. And then investors start
to shed risk that can move very quickly. So we want some slow indicators that
take you into position and sometimes they’re early. And you want some
indicators that are fast, which are a little bit late. The goal is supposed to
be never too early, nor too late. So in Don’s case, six months is perfect. In
the case of me, as an asset manager, six months is hell, so I’ve got to shrink that
window down dramatically. Because as an asset manager, people won’t be
comfortable with the six months. That’s why we’ve got slightly faster signals.
Giordano: You mentioned the Baltic Dry Index and
the impact of these global indicators. What specifically does that mean for the
economy?
Muralidhar: As the Baltic Dry Index is going down
that means global economic activity is still declining. If the price of copper
is going down that means the economic activity is declining. Typically, the
price of oil is going down, that means oil demand is down. So they are very
simple indicators and all of this is in the public domain. I don’t think
there’s any idea and Don’s model or in ours which doesn’t have some economic or
academic backing, too. Don, in your case, didn’t your board require you to have
academic backing?
Pierce: Yes, 100% of all our rules are backed
by academic literature, because for some reason, they didn’t want some 31 year
old to make large decisions on the portfolio because he thought moving averages
was a good idea. Most of the literature really focuses on the top and bottom
deciles. So in effect, the top 10% of experience and the bottom 10% of
experience have information and the rest of the 80% really doesn’t have much
information. That’s our methodology. For all of our statistical friends out
there who might say by definition you have the sample size because each day you
get new samples, it’s not as robust because the thing that might have been in
the top 10% ten years ago is no longer there. That’s why we don’t use a 95%
confidence interval or something like that because we don’t have to prove
beyond a reasonable doubt something works, we can simply use a preponderance of
evidence. And so for us, it’s the top 10% and bottom 10% of experience that is
instructive. And then the rest of the 80% is largely not as actionable.
Giordano: What is the overlay process you use?
Pierce: When you use an overlay manager and
using futures and derivatives to implement the rebalancing, you’re now one step
closer to the marketplace. I can safely say that as an improvement of your
overall engagement with the market and your engagement with managers, is it is
night and day. As a market participant, you are hearing and listening to what’s
going on in the marketplace much closer and getting more knowledge transfer. From
my standpoint, it’s been a very engaging part of the work and it’s something
we’ve embraced, frankly, because when we talk about allocating, we ask about
the assets. You might have an awesome management team but fundamentally, what
are the assets that they hold and how are they extracting the value, as opposed
to being one step removed and simply relying on a more antiseptic view of the
process. At the end of the day, it’s the assets that are going to drive your
performance. The management team is there to select them and manage the process
but at the end of the day, it is the cash flows that you receive, or the sale
of the asset that you’ve purchased, hopefully at a lower price, and you sell it
at a higher price, or the income you’ve received from an asset and then finally
paid back – that is what drives this. By getting that much closer to the market
allows you to have that kind of level of conversation with the managers to
understand what assets they are purchasing and how they’re how they’re trying
to make money for you, as opposed to looking at your performance. It’s just a
night and day difference between being an investor in that way.
Muralidhar: May I just add, I got lucky that I
started my career on a derivatives desk before I went to the pension fund. I
then implemented a currency overlay then I went to another derivatives vendor. But
because asset allocation was my passion, it was trivial for me to expect that futures.
Forwards, and options and homers[AM2] would be used by sophisticated
institutions to manage their portfolios. And it’s surprisingly underutilized. For
example, even though people might use futures, there are many simple strategies
that are just begging to be implemented by the use of options. Because of the
lack of familiarity among boards and CIOs and even consultants about these
strategies, I think the industry is underserved and it behooves some of these
CIOs to get the familiarity that Don learned over time. Don, you did this on
your own right? You didn’t have somebody sit you down, you just basically learned
by virtue of having to do it?
Pierce: Yes and the first thing that you will
experience is that you engage in an overlay manager and they’re using futures. They
might come to you, or maybe the Street comes to you and effectively say, “We
noticed that you have this allocation, maybe you would prefer a swap on it. So
instead of now rolling your position every day, month, or quarter, you might
put this on for a year. And we can give you a string of a fixed rate against
that.” So your roll yield might be volatile but I can lock in a rate right
now on the S&P 500 and maybe you can get an S&P flat or perhaps minus
five basis points. We use the Russell 2000 futures that way. There was an
inherent short in the marketplace for a long time where you were able to accrue
the Russell 2000 return and you would get a roll yield benefit of between 40
and 120 basis points. When we would look at small cap equity managers, it
wasn’t the small cap equity index that you had to beat. You had to beat the
Russell 2000 index plus the roll yield that I would be getting, and we have
zero of those. The first entree will be US swaps. So, you know, the decision
that whether or not you want to continue to do roll yield is
I
just want to say with all sincerity that Arun changed the trajectory of my
career, to go from allocating to investing. And that’s something I can never
say thank you enough for, so thank you.
Giordano: Don, I’m sure other CIOs would love to
learn exactly your philosophy, your movements, and how you’re making it work?
Pierce: In talking about the progression from
using futures and forwards to using swaps, there’s a sort of put-call parity,
so a future is equal to long a call and short a put. But once you introduced
the concept that futures have an option equivalent, suddenly it becomes a very
powerful tool to incorporate options because from time to time options also
have interesting payoffs. The information growth and learning in adopting those
tools just makes for a much more enriching career.
Giordano: Where did it save you? Is there a case example
in which you had if you hadn’t, you would have suffered?
Pierce: One of the first large foot positions
that we put on was selling puts during the European debt crisis. The insurance
industry offers financial products that have embedded protections into them. So,
if you buy a principally protected investment for some time period, three or
five years or seven years, the insurance company goes out and buys that
insurance. During 2010, the long dated implied volatility for the S&P 500,
the Russell, 2000, the Nikkei 225, and Euro Stoxx 50 were all trading at
staggering levels. We sold puts at a strike price where, if you included the
premium that you received, you were buying the stock market below March 2009
levels. For us, that was a demarcation to say there’s something broken that
somebody’s willing to pay insurance for something that would be worse than what
then worse than what happened. That doesn’t mean it couldn’t have happened, but
we were taking a calculated risk. As it turned out, that worked incredibly
well. So well that that we got taken out of it within two years that we made
close to 85% of the premium that we would have received. So, we closed that
position out three years early and moved on. That was an upside participation.
More recently, we purchased one year puts on the S&P 500 back in September
of 2021 and also June of 2021. Having that kind of protection on into the teeth
of 2022 was incredibly helpful. But you don’t just jump into buying puts and
calls and using some of these strategies without first getting the underlying
knowledge from your derivatives experience, which starts with an overlay
program.
Giordano: What should you be sure to have in
place if you’re going to go ahead to do this strategy?
Pierce: You could certainly implement an
informed rebalancing on a physicals basis and that was what we did in the first
year. I wouldn’t recommend it, but to each their own.
Giordano: So, you wouldn’t recommend an informed
rebalance?
Pierce: I would recommend an informed
rebalancing program, but a rebalancing method that uses futures is so much
better. It’s hard for me to imagine if we were simply stuck with physicals, but
I suppose it’s possible. And our estimate of 35 basis points on the forward
estimate was implementation agnostic. But it’s hard for me to imagine not
having it because the tools are so valuable, and the learning has been so edifying
and helpful as an investor that I can’t, it’s hard for me to extract that out,
but I suppose it’s possible.
Giordano: Last advice to other CIOs things that
been working?
Pierce: When you have a model in place, it’s
not always going to be right and certainly the last six months has not been a
lot of fun. The model has definitely preferred bonds over equity and that
started increasing duration as rates went up. We started at the end of 2021 at
a duration of less than a year; we were a quarter of the year, 0.25 that has
now since moved up to about 3 or 3.5, so it’s been steadily increasing
duration. But watching the stock market rally in front of very aggressive rate
hike sequences always challenges you.
Giordano: I think we all kind of feel your pain a
little bit.
Pierce: Thank you. I appreciate the solidarity.
Giordano: I want to thank you so much for your
time for your words of wisdom here and really drilling into something that’s
been working for you and helpful for other people to hear about.