Wells Fargo Asset Management’s Wai Lee discusses the considerations that go into implementing an allocation to trend following strategies in a multi-asset portfolio and finds that small changes can have big consequences.
In the current turbulent market conditions, triggered by the COVID-19 virus, the question of how best to protect portfolios against equity market downturns is on every investor’s mind.
Undoubtedly, the best form of protection is buying a put option. Puts are effective and responsive in protecting the downside, but here is the catch: they are very expensive to run on a continuous basis.
That’s why investors have looked for other ways to build protection into their portfolios and historically have relied on government bonds for cushioning any equity drawdown.
But with bonds at minimal yields, investors have started to look for additional ways to diversify equity risk, and, with the experience of the Global Financial Crisis fresh in mind, found potential in trend following strategies.
With the current crisis at hand, this has been the first live test for an approach that leans heavily on trend following.
The results, it turns out, are mixed.
Some trend following strategies have been able to identify the regime shift in time and mitigated the fall in equity markets. But others have only added to the free fall.
Good implementation is the key here, but some investment strategies have inherent biases that are not always easy to detect and can lead to unexpected behaviours in strategies, Wai Lee, Global Head of Research – Multi-asset Solutions, at Wells Fargo Asset Management says.
Lee illustrates his point at the hand of the Black-Litterman model, an asset allocation framework that helps institutional investors decide how to allocate their investments across different asset classes and countries, taking into account the investor’s views.
“When I was researching the Black-Litterman approach myself more than 20 years ago, I noticed something very interesting,” Lee says in an interview with [i3] Insights.
“By now, the Black-Litterman approach has become a pretty standard methodology out there, but 20 years ago there was not much literature about the practical implications of applying it.
“And when I used it, I noticed that if I followed the Black-Litterman approach strictly, I almost always overweighted risky assets.
“Black-Litterman is a very powerful framework, but those investors who use it blindly might not realise that the so-called equilibrium returns in the Black-Litterman approach already reflect the fact that riskier assets have higher returns than less risky assets.
“So even before investors have put in any active investment views, the framework itself will tell you that risky assets are expected to outperform as if it were parts of your active investment views, and you may just go ahead and buy more risky assets,” he says.
Such inherent biases can exist in some other investment strategies too, Lee says. In a recent working paper, he looked at inherent biases in some generic trend following strategies and the derived characteristics suggested that these strategies have a fair amount of beta embedded in them.
My paper is not saying that trend following strategies are entirely beta. But it does have embedded betas in there and let’s just come forward with that
The paper, titled ‘The Friend of your Trend’, found that throughout the cycles these strategies tend to have a beta of around 0.3, given reasonable parameters of how the underlying asset behaves.
“My paper is not saying that trend following strategies are entirely beta. But it does have embedded betas in there and let’s just come forward with that,” Lee says.
This has implications for allocations, because investors need to be careful not to double up on their beta exposure when implementing trend following strategies in their portfolio. It also has an implication for the level of fees you want to pay for them.
“In normal days, the clients probably ‘overpaid’ a bit, because part of the trend strategy return is cheap beta,” Lee says. “But of course, the catch is you can’t predict when the normal days stop, so you pay to stay in the game for the moments when the strategy becomes most helpful.”
Another complicating factor in trend following strategies is that in down markets, volatility tends to spike and this influences the return profile of a strategy, resulting in a sometimes more flattering picture of a manager’s skill to outperform in all markets than is strictly true.
“It is not easy to uncover (which part is beta and which part is alpha), because in a down market, the volatility jumps up. And when your volatility jumps and your trend strategy delivers more ‘alpha’ because of this jump in downside volatility, it creates the impression that you are very symmetric in your ‘alphas’ – that whether you are in an up market or down market, you add ‘alphas’.”
“There is some asymmetry in the market which makes empirical evidence difficult,” Lee says.
But overall he is positive about the ability of trend following to provide a cushion against market drawdowns and Wells Fargo applies these strategies in its own framework for building resilient portfolios.
“Sometimes you need to extrapolate what a client wants,” he says. “When a client says they want protection, they want a resilient portfolio, it means more than protecting a portfolio. They mean: ‘When I don’t need your protection, can you make some money for me as well?’.
“So a good resilient portfolio does not only have to protect on the downside, but in a normal market it should also expose our clients to the upside.”
“With that in mind, we think trend is a viable strategy, because, yes, in the normal market it does have some degree of beta and in my paper I say that in a full cycle trend following might have a beta of about 0.3. That is part of the upside potential that you can bring into a resilient portfolio,” he says.
“Government bonds can be less reliable for protection than trend following, because you are relying entirely on its negative correlation with the underlying risky asset you try to protect. That is not always the case. Like around mid-March we heard people question government bond as a diversifier again when it struggled with equity at the same time.
“But government bonds remain another viable dimension in building a resilient portfolio, as the break in correlation with equity had been temporary” he says.
When your volatility jumps and your trend strategy delivers more ‘alpha’ because of this jump in downside volatility, it creates the impression that you are very symmetric in your 'alphas' – that whether you are in an up market or down market, you add 'alphas'
It is not just inherent biases that investors have to look out for in implementing a trend following strategy. One of the most important decisions is to calibrate how quickly a strategy should react to market changes.
“That is the tricky part,” Lee says. “First of all, a trend following strategy is not designed to predict the turning points, but to respond to and follow the turns. We have to be clear on that.”
“But I thought about this question a lot: what is the right time horizon? And there is no clear answer in my view, because if you calibrate your trend strategy to be too responsive then you react to noise. Daily movements are noisy and at the end you will pay some price of reacting to noise.
“On the other hand, if you calibrate your trend following strategy to be too slow and you wait longer to confirm the turning point, then you will miss some protection from the strategy.”
Equally important is the decision when to slow down following a downwards trend. Are you going to follow the trend all the way to the bottom and wait for a signal that markets are improving, or do you build in some form of brake?
Lee is an advocate for the latter.
“After you de-risk to a certain degree and you believe that the market will eventually bounce back, you have to make the decision of when to slow down your principal protection selling?
“We are not trying to actively predict the turning point, but we do have a built-in parameter there so that we don’t just derisk forever.
“Of course, we can’t predict whether our parameter is the best all the time, but at some point you have to give your portfolio a chance to rebound,” he says.
A trend following strategy is not designed to predict the turning points, but to respond to and follow the turns. We have to be clear on that
There is also the matter of sizing a trend following allocation. If it is too small, then the impact on the overall returns of the fund are likely to be minimal. It has to be sizeable enough to move the needle.
But if your allocation is too large, then your portfolios will experience high tracking errors, something that not every board can stomach.
“If you really have a view that a trend following strategy is not very correlated with your underlying assets and you throw it into an optimiser, then it is no surprise that it will tell you to allocate more to trend,” Lee says.
“But here is the trick: I’ve been working with Australian clients for a long time and they really care about peer group risk. If you allocate too much to these alternative strategies, the tracking error, not only to your benchmark or target return, but also to your peers will make you stand out.
“So I always bring in the peer group risk into my considerations,” he says. “At the end of the day, optimal allocation is the result of balancing a number of considerations.”
Wai Lee is Global Head of Research for Multi-assets at Wells Fargo Asset Management. His paper – ‘The Friend of Your Trend’ – can be found here. For more information on this topic, please contact: [email protected]
This article is paid for by Wells Fargo Asset Management. As such, the sponsor may suggest topics for consideration, but the Investment Innovation Institute [i3] will have final control over the content.
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