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In 1978, so the story goes,
the world’s first investment product reflecting a quantitative model was
launched in the US by the
former Wells Fargo
investment division. It was a simple strategy which tilted the portfolio
towards stocks that paid higher dividends. Since then quantitative investment strategies
have come a long way, with both the number of quantitative managers and other
institutions mushrooming along with the number and variety of strategies employed.
In fact, recent criticism of the likely future effectiveness of quantitative
strategies tends to centre on their popularity. Some commentators believe that
the weight of money making similar bets when the world first felt the tremor of
financial crisis in August 2007 contributed to the underperformance of
quantitative managers. Recovered ground by those managers since has dampened
the debate and the search for new and better strategies has intensified, as has
the development of better risk management techniques. This is an edited transcript
from a roundtable in Melbourne,
sponsored by BNY Mellon Asset Management and its affiliate Ankura Capital,
which looked at quantitative investments from the point of view of
institutional investors and their advisers.

Participants at the roundtable were: • Ross Blakers, associate director, Access Capital Investors • Kristian Fok, deputy managing director, Frontier Investment Consulting • Matthew Ross, head of quantitative research, Goldman Sachs JB Were • Greg Vaughan, chief investment officer, Ankura Capital • Richard Dalidowicz, senior investment manager, AustralianSuper • Dennis sams, head of public markets, UniSuper Management • Peter Laity, general manager, investments, ESS Super • James Gruver, managing director, BNY Mellon Asset Management Australia • Greg Bright, publisher, Investment &
Technology Greg Vaughan: When the storm first hit in August 2007, it was
easy to say that the situation in the US was an extreme circumstance,
leverage was a big part of what had happened and there was some contamination
from the sub-prime crisis.

At that point there had been not a lot of disruption
to Australian quantitative returns. If you wind the clock forward those 18
months, as a general statement the quantitative managers have been about a
quartile behind the balance of other managers. Even in Australia there has been a
differential that has emerged over that period and there are a number of
nuances of that. When you look at how firms have performed over those 18
months, there’s a suggestion that US-aligned processes have struggled more than
locally-derived processes.

The pool that has been drawn on by quantitative
investors over the last five years has some fairly simple common denominators
in it, as well as some more nuanced and specific tools. Those common
denominators are also drawn on by hedge funds and we’re all aware of the hedge
fund explosion. So there’s more of a risk of contagion in that common
denominator of quants, and that has probably fairly copped some scrutiny in
light of what’s happened over the past two years.

Greg Bright: Looking at the performance numbers for the group of quant managers
in Aussie equities (see table) it is interesting that there are only two out of
nine which have outperformed the median of all managers and they are both Australian
managers: Ankura and AMP Capital. Matthew Ross: Most
managers have managed to outperform the benchmark in the past 18 months – the
vast majority of active funds have outperformed the benchmark. The quant
managers, by and large, have outperformed the benchmark with the exception of
maybe two or three.

Greg Vaughan: I think capacity is an important issue. We’ve
come up with the broad guideline of half a per cent of market cap (as a maximum
size for a fund) which is a common-sense kind of number that floats around. But
we have managers that are well in excess of that. There’s also a great focus on
the importance of research with quantitative investing. There’s all sorts of
research but the research where I believe there is some critical competitive
advantage is more market-oriented research – the nitty gritty stuff rather than
conceptual research. If you’re given the challenge of designing a process just
for one market, just for the Australian market, you’re going to be focused on a
lot of that nitty gritty research.

If you’re given a task of overseeing a
quantitative research across a number of markets and potentially multiple
products, I think your research has a slightly different, more conceptual flavour
to it. That’s not to dismiss the broader conceptual sorts of research but in
this particular environment, where the terrain has become much more awkward,
the more market-oriented research has come into its own. Matthew Ross: The spread between the best and worst quant manager over this
credit crisis period has been about 11 per cent.

The spread between the best
and worst value, growth or styleneutral managers have been roughly the same
sort of levels, maybe a bit higher. The quants, generally speaking, run lower
tracking errors, so you’d expect to see a lower spread between the best and worst
quant managers just by the fact that they’re not taking as much active risk as
the fundamental managers are. Quantitative investing, also, is not as much of a
black box as what some people think it to be. I think there is a lot more
judgement, a lot more qualitative oversight. I look at quant funds primarily as
the best information processors in the market. They have very strong
operational efficiency.

They communicate with us in a very seamless fashion in
terms of the information they collect, whereas a fundamental manager might need
to take six or seven phone calls to capture the same amount of information that
a quant manager gets through a well-organised data file. Greg Vaughan: One of the things that feeds into that is the fact that the Australian
market is so narrow. You can’t really run a quantitative process in the
Australian market on auto pilot as you might attempt to do in the US or in Japan where you have the benefit of
vast diversification.

Richard Dalidowicz: Why have Ankura and AMP done better than the
cohort? Is it because you apply a bit more of a judgemental overlay to the quant
process? Greg Vaughan: It’s obviously awkward for me to speculate on
criticisms of other managers but I think there is a dangerous philosophical
edge to some quants where they really have a religiosity about their models and
they believe them to be robust and valid eternally and they’re very reticent to
say: “Hey, this is about to run over a pothole here unless I just guide it
around.” Or, “Things have changed such that the way I thought this part would
be rewarded is no longer going to be rewarded as reliably in this environment.” So I think that it comes down to an ethos of selfexamination or honesty about
knowing what you don’t know versus having absolute confidence. You have to have
a bit of experience to delineate between when you’re becoming part of the
behavioural bias problem and when you’re exploiting behavioural bias. That’s
the essence of what quantitative investment is about – trying to exploit
behavioural bias.

Kristian Fok: Quant managers are probably among the most
transparent in terms of seeing the impact of their funds under management. Any
quant manager that you’d want to have in a portfolio has an appropriate way of judging
costs for trades and integrating that judgement into how you construct the
portfolio at the time. And because quants have a whole range of options, if one
option’s too costly they can go down the curve. But what that means is the information
ratio does deteriorate over time. When quant managers talk about capping their
funds it’s not because they suddenly can’t (use the process), it’s because they’ve
decided that they’re willing to accept an information ratio of a certain amount
and then estimate what size of fund is suitable.

In relation to assessing a
quant manager, although it’s true to say that a number of them have very
similar approaches, the way that they go about putting the pieces of
information together can be quite different. Some look at all the factors and
put them together concurrently, others look at them independently and put
baskets of portfolios together. To my mind, a big differentiator is not just
what factors are used but what access to information they have. And we can see
that there are differences over time between those that are relying on information
that comes out (publicly) versus those that have built up proprietary databases.
You tend to find that the bigger firms do that.

So it’s a positive for them but
obviously they have more funds under management, which is a negative. We would
normally expect human judgement in a number of places. First thing is in
looking at the data and making sure that it makes sense. That’s just a given.
Secondly, where we do see a little bit of difference between managers is where
they recognise that there may be something going on in the market which means
that that model is less reliable, so they exercise judgement to change the
weighting to those components of the model.

If you think about what’s gone on and
what’s been driving the markets and you look at the way that most quant
managers operate with their risk controls, you can explain why at this point in
time the returns haven’t been as strong for the risk taking compared to the
fundamental managers who got it right. But now these things work in cycles.
This is a very extreme environment with quite significant themes at play. And I
think to say that this is the beginning of the end for quants, I think, is
probably a little bit premature.

Ross Blakers: In
terms of the market conditions, it has been nothing short of extraordinary and
a lot of investment styles have been affected. It’s been a very difficult time
for active management generally across the board. I think one thing from the
market conditions and particularly affecting quants is the cross-sectional
volatility, which is at extraordinarily high levels. This is a twin-edged
sword. Normally when you have higher cross-sectional volatility or greater
dispersion between the best performer and the poorest performing stocks, that
ideally sets a nice platform for active management to generate outperformance.

However, it’s been so extreme and so volatile that it hasn’t really been picked
up yet at all. In very recent times, we’ve seen that come down a little bit.
Looking forward to the other side of this event – and who knows when that is
and what it looks like when we get there – but as that cross-sectional
volatility stabilises, I think you’ve got a very conducive environment for
active management and particularly quants to generate solid outperformance. I
think last year has been, as Kristian touched on, a sector picker’s market.

With the banks, the resources, and others there were some really nice themes
that rolled through there. To the extent that fundamental managers picked those
up, that’s where a lot of outperformance came from. In terms of the
cross-sectional volatility, that’s at the stock level and that’s where it has
been random so I think it’s been probably a bit easier at the sector level and
incredibly difficult at the stock level. In terms of manager selection,
research is certainly one of the key themes for us.

That’s looking at what the
managers have done through time and what they’re looking at at the moment, not just
in terms of ideas, but how they’ve actually been implemented and the final outcomes.
There are quite extraordinary differences. We’re seeing some managers, say with
a value signal, that have generated very strong outperformance from that, while
others have been hit very hard. So even though everyone’s got value, how they
actually construct it, how they implement it is very, very different and we’re
starting to see that come through.

Everyone hopes to find that proprietary data
source or that new signal which lasts for as long a timeframe as possible. Some
have been more successful in that space. Dennis Sams: Some of
the concern about industry data models though is that you may fall into the
trap of just fitting history and it becomes too specific. And the second thing
is that some of the big proprietary databases, which may look new and original
and no-one else has touched them before, but when you think about what signal you
actually can extract from that, do you actually get a different signal to the one
that you’ve already got from some other indicator?

Peter Laity: Talking about unique ideas, I was speaking to a fund manager in London who said: “Oh we
reckon we’ve got about a quarter of our ideas that are unique and we’d like to
get that to 50 per cent.” And I just looked at him and I went, “Pffft!” That’s
a pretty big challenge given that there are just the three major factors. I was
wondering Greg (Vaughan)
what sort of uniqueness you think you have in your process compared to others?

Greg Vaughan: I think a lot about this concept of knowing what you don’t know,
knowing where to restrict yourself and when to play, if you like. And in this
market that is a very nuanced thing. When we look across the market and think
about the problems for a quant process, I think we come to quite different
conclusions than other managers. Differences between the quants are probably
underestimated. There are those whose processes have a comfortably broad
application, without too much differentiation, and those that really start to
segment it up. The Australian market is very peculiar. The text book industrial
company, that people tend to think of when they can see quantitative processes,
represents about a third of our market, when you take off financials and
resources and asset players. But in the US it’s about two-thirds of the
market. So, it encourages a more general view of process in the US.

Rixhard Dalidowicz: Is there an environment where quant investing
works better than fundamental? For example, is quant a lot better in an
environment in a full market, with markets going up, or merely the trend? When
the market’s very volatile, when leadership is changing dramatically between
sectors and stocks, quants can’t pick up on a theme, because by the time they
get the information into their models, they’ve missed it.

Ross Blakers: They tend to get hurt at points of inflection. Kristian Fok: A lot of quants have processes in place to identify how reliable a
signal is likely to be and they can either dial it up or down relative to
others in an certain environment. That’s quite acceptable. But if they have a
stated philosophy and then suddenly say “Ah, it’s not working …” and change it,
that’s quite a different situation. Ross Blakers: Since I
have been covering quant managers, I’ve never seen an instance where someone
has really thrown out the core philosophy and adopted a new one.

Greg Bright: Richard, does AustralianSuper have a different way of looking at
risk now, post crisis? Is risk different now than it was two years ago? Rcihard Dalidowicz: Risk is in today’s terms, the risk of losing
your money, risk of losing capital more than anything. And in terms of
diversification in our portfolio at the balanced plan level, there is plenty of
diversification there. The key thing that we’re thinking about at the moment is
the economic environment that we’re in and those managers that would do best in
that environment. If we’re entering, for example, a recovery stage, we would
expect a manager with a stronger earnings focus to do better than a value
manager.

And perhaps a manager with a stronger bent to emerging markets. The
biggest risk is ultimately losing our members’ money, earning negative returns
overall. We don’t really measure risk, like tracking error or Sharp ratios or
information ratios, I think because in the current market dislocation, those sorts
of things have almost become out of date. Greg Bright: The typical quant manager tends to have a lower tracking
error. Does that not matter right now?

Richard Dalidowicz: Most quant managers are quite sector neutral, most of their active
stock bets are perhaps within one per cent of benchmark, or only one half a per
cent, but some have delivered such bad returns that measuring tracking error is
not perhaps a useful measure to look at. Matthew Ross: I think
processes that are very heavily risk dependent will be very whippy in this
environment, because the volatility and the correlation shifts are extreme.

Take the correlation between the resource and the banking sectors. For 10
years, those two sectors moved in lock step and then we hit a period, with a
negative correlation between them. And that’s really caught a lot of portfolio
managers short. As a general comment about active investment management, in
favour of the quants, is they actually do have a focus on tracking error. Most
of the other active managers in Australia
don’t really take a view on correlations. They tend to look at single names
because most active managers are largely stock pickers.

Peter Laity: You don’t want managers to be changing their processes and their
styles, but you’d want them to continually question their processes. If
something isn’t working, you’d hope that they’d say: “It’s not working at the moment,
let’s talk to our clients and ask them if we can take some risk off the table”.
Richard Dalidowicz: I think it’s important, as Ross said, to be
flexible, to be able to change your process to the market environment. For
example, many managers were long resources in particular and suddenly during
the September and December quarters, they all blew up. So there’s nothing wrong
in being flexible and changing the process.

James Gruver: It all
comes back to skill. If people have skill then flexibility is more tolerated.
It would be interesting if we could track the number of research enhancements
over the last five years, by firm, and then compare that to performance. We
might see that there’s actually an inverse correlation between performance and
the number of ideas. There seems to be an insatiable appetite in the investment
community for new ideas, especially in the quant space. We (BNY Mellon)
represent both fundamental managers as well as quantitative managers and there
is clearly a bigger appetite for enhancements with the quantitative managers.

Greg Vaughan: The hang up on process reinvention is peculiarly an obsession with
quants. Researchers are content with a more gradual process evolution with conventional
managers. Kristian Fok: To my mind, the quant managers – the ones that
we use anyway – have always had some fundamental basis for the way that they put
things together. This environment is fairly unique in terms of the dynamic of having
to reduce leverage, compounded with asset prices falling. The normal view of
risk is a little bit different, because we’re talking about the risk of total
loss now.

Dennis Sams: At both manager selection and the fund
structure levels, you really are trying to set up longer-term structures that
are going to work over time. And that’s part of the perspective for quant
managers. Just because of August 2007 it would have probably been a very bad
mistake to react very negatively or very quickly at that point time. So you
have to watch that short-termism. That’s a real risk for superannuation funds. Greg Bright: It seems like member choice has brought that short-termism to the
fore.

Dennis Sams: That’s a danger we face with members. But how
we actually control them and stop them making bad choices, is very difficult. Greg Bright: There’s a philosophical issue of whether we’ve gone too far
with choice. Kristian Fok: It is a potential big issue for planning.
Anyone who has to deal with liquidity and cash flows has to plan for things
that may not happen. Which does reduce your capacity to take on things that may
be hard to reverse in the short term. Greg Bright: Getting back to the risk processes of managers, Greg, you make
distinctions between embedding risk controls within a process and kind of
bolting them on.

What do you mean by that? Greg Vaughan: There’s
a difference in how people build risk models. At the one end it’s a classical
multi-factor fundamental-type risk model in the spirit of BARRA. Cutting
through that we conceive of other common elements of risk that just aren’t
vivid enough statistically or historically to really be picked up in that way.
They may be topical, they may be transient, but they’re important and they can
be implemented in a structured way but not necessarily statistically estimated
in the same way that you can with other things.

Richard Dalidowicz: Greg, should clients have full access, full transparency? For
example, Kristian would you want full transparency through their proprietary
risk model? Kristian Fok: The responses we get are different for
different managers. A lot of these things are very complex, so for us
consultants to understand properly it’s very hard. So we ask for a bit of time
and patience. Sometimes you actually go into a bit more of the detail when you
finally say, “well you’ve got to bring us along a little bit here. But
transparency is about information that’s useful to you. There’s no point in me
looking at the code in the system, because I couldn’t understand what it is,
but being able to understand how it’s put together is important. Everyone does
the big headline factors and then you have to go through about 12 sub-factors
and how they interact with each other.

And how portfolios finally get put
together because that’s a big differentiator. Firms have to be willing to do
that but then likewise we have to be prepared to spend a lot of time with them.
I have gone to a manager and spent two days with them which is hardly
scratching the surface. Dennis Sams: We have to have that transparency of the
explanation. Take Madoff, for example. Madoff, wouldn’t get legs in Australia
because none of us will deal with anyone who doesn’t prove to us what they’re
actually.

Greg
Bright: But you could
have invested in a fund of funds which did? Dennis Sams: No, we
wouldn’t have. If there was a barrier between us we won’t invest. We’re not
likely to go into funds of funds for that very reason. Matthew Ross: We haven’t heard much about the people side of funds management.
Maybe it’s because quant managers talk about their processes a lot. But the one
thing I’d say, dealing with the full spectrum investment managers, is that my
quant clients have been the most stable.

Greg Vaughan: One
advantage in having a stable team is what we were talking about earlier, mixing
judgement with process. That delineation between what is objective and what is
subjective, is hard to make when people first start out. The longer they’re
with a process they all start to sing off the same hymn sheet in terms of those
issues. Greg
Bright: I’d like to
turn the conversation briefly to fees. Matthew, do you have an observation on
fee levels between the types of managers?

Matthew Ross: I think
the 130:30 funds have offered pretty good value for money if you look at it on
a fee-adjusted basis. I’m a big fan of performancebased fees. I think that
traditional managers charging 40 basis points for what was, in the bear market,
less than 200 basis points tracking error in a lot of funds, is a pretty big
number. I prefer to see performance-based compensation. I don’t think there’s
enough of it in investment management. I think that’s one of the main reasons
why the quant funds have had a large market share of Australia’s traditional money.

On
an after-fee information ratio basis, they’ve probably offered the best value for
money. I’d say the quant managers are 10 to 15 basis points cheaper than a traditional
long-only manager and have generated an equal or higher information ratio over
the long term. Kristian Fok: The fees issue is a big issue, because what’s
happened is that as new things get put in, everyone promises better and better
returns, the fees are being incrementally increased but the reality is the
delivery is probably less than expected.

Investors snow scrutinise the
proposals a lot more. We’re quite mindful that the environment for certain
investments will be quite attractive, but what we don’t want is another round
of hedge fund-type of fees for things that are more straight forward. Quant
managers have done it a lot – coming up with their own special extra super
you-beaut product which they want to charge twice as much for, rather than
enhancing the existing product. Greg Bright: Ross, your clients have on average a lot of unlisted assets, a
lot of performance-related fees. Are fees now more important and would that
actually impact on your asset allocation?

Ross Blakers: We are
mindful of fees, we always have been. We do like quant because it is much
cheaper than other forms of active management. We do have a preference for base
plus performance fee. One important thing here is that it’s not just the
after-fees return that matters, but also the after-tax return. A key focus of
ours is to make sure that the manager’s interests are aligned with the super
fund members’ and that is the after-tax after-fees return which is credited in
their account.

The quant managers are at varying levels of sophistication in
tax management. We work very actively with the quant managers that we utilise
to make sure that not only things like franking credits but also capital gains
tax considerations are taken into account in their investment process. So that
they’re getting the best outcomes for the members. Greg Bright: What about trading off lock ups to give the manager, say, a
three year contract in return for lower fees?

Kristian Fok: There’s
a problem there because things change with people and personnel. James Gruver: But we have seen clients requesting annual fee caps with any
excess fees earned rolling over to the next year too… If you’re willing to back
yourself with a performance fee you are likely to seek additional reward for the
additional risk however the reward probably should not be unlimited.

market.

 

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