Investing in emerging markets (EMs) is by definition a global endeavor, but as the old joke goes, it’s a small world but you wouldn’t want to have to paint it. In a fast-moving investment universe where opportunities ebb and flow on a daily basis, an optimized strategy for tapping into the potential of emerging markets can be elusive. But what if you could cover the world every day? If you could look at detailed analysis of EM equities every day – and seize the advantage when it’s there and before it’s too late? II spoke with Arup Datta, Head of Global Quantitative Equity at Mackenzie Investments, about how quantitative strategies can help draw a bead on the elusive optimization of EM strategies.
You like to say that emerging markets in particular are a sweet spot for quant strategies. Why is that?
Arup Datta: First, it’s a less efficient market than the rest of the world, and there’s also less competition than there is in U.S. large cap. Both of those facts should lead to more alpha for either fundamental investors or quants. However, we believe it’s the breadth of names in emerging markets that plays into the strengths of quantitative strategies.
For example, in our investible emerging market universe we cover about 6,000 stocks that we rank on a daily basis. It’s very hard for a fundamental manager to do that – I don’t know of any fundamental manager that can. Breadth is your friend, and you can leverage computing power and your models to cover more stocks pretty easily. I believe that’s why, historically speaking, quants have delivered good alpha in emerging markets.
Do fundamental managers really struggle to match that breadth?
Datta: Even the most seasoned fundamental equity analyst can only cover 30 or 40 stocks. If you do the math, if you have to cover 6,000 emerging markets stocks regularly, and let’s say that 40 stocks are the most one analyst can cover, you need 150 fundamental analysts to cover that many stocks. Does any firm have that many fundamental analysts covering emerging markets?
Is risk management part of that EMs sweet spot for quants, too?
Datta: Everyone knows that emerging markets are more volatile stocks than, say, U.S. large cap. Risk models are relevant everywhere, but become even more relevant in an area like EMs where the stocks you trade move around more than in other areas. A good quant manager builds its own proprietary risk model – we don’t just rely on standard providers. We build our own risk model that is attuned to our process and can better determine the risk in our portfolios. It’s much more finely honed in terms of how we position size a name. Once we like a name, we use our algorithm to determine how much we can buy of that name.
For example, we have simple rules such as if you’re a biotech name, we target half the weight of any single name as elsewhere because biotechs are much more volatile, and it’s an all-or-nothing story when it comes to trial phases. So, in an area like that we diversify our bets by buying more names.
Similarly, on riskier names – typically small cap names – and high beta or more volatile names, we take smaller positions than we do on Alibaba or Tencent, for example, because for various reasons there’s less liquidity in those names. So, the focus in our risk model is essentially that for every name our position-sizing algorithm determines how much we should buy. That’s critical in emerging markets, where names are riskier than in developed markets.
You don’t meet with company management as part of your strategy. Is that a strength compared to a fundamental manager?
Datta: It’s just a different approach and philosophy. Quants are disciplined, and we try to quantify everything. To us, you can tell the quality of management story by looking at financial statements – is return on equity improving? Is return on invested capital improving? We’re not interested in a judgmental, subjective lens.
The quantitative process is about ranking everything from highest to lowest in every sector, and then trying to buy the highest names and sell names that are going down in our rankings. It’s a very disciplined process that we do every day. Fundamental analysts can sometimes struggle with when to sell, because they don’t have a disciplined number telling them when to sell. Now, selling a winner is often easier – they’ve made the money, they sell it. But fundamental analysts and portfolio managers can struggle on when to sell losers – and sometimes that is because they are biased toward management. In that sense, not meeting management can make you more objective in your decision-making.
In many ways it sounds as if your strategy is optimized to seize the moment when it presents itself.
Datta: That goes back to breadth and speed. We can cover the whole globe on a daily basis, and because we look at 10 to 20 criteria per stock, such as how are you ranked on price to cash flow versus your peers, for example, we can act and trade on a daily basis. Not many active managers do that – either fundamental or quant. Our strategies are capacity constrained – we don’t want to be too greedy about assets under management – so that we are able to get in and out of names faster than other managers, and our robust infrastructure enables us to do that. That’s an advantage for us, especially in liquidity challenged areas with high transaction costs. If you can get into a name early on the upside, you can ride it up more compared to a manager getting in on a weekly rebalancing cycle or a monthly rebalancing cycle. That’s the advantage of speed we gain from daily analysis and trading.
