As fast as the Covid-19 crisis is unfolding, leaders of private equity firms have to move faster.
While it is impossible to gauge the outbreak’s ultimate impact, efforts to contain the virus have already ground broad swaths of economic activity to a halt, generating widespread ripple effects across global financial and consumer markets.
By now, most firms have set up an emergency response team, have implemented measures to take care of their people and are communicating with investors. They are paying more and more attention to determining the outbreak’s potential impact on portfolio companies and developing a clear, decisive action plan to mitigate the damage.
By definition, there is no universal playbook. The outbreak affects every portfolio company uniquely, requiring a tailored plan for each. Tactics like drawing down credit lines or aggressively managing working capital might work across the portfolio. But those are table stakes, not strategies.
The real question is what to do next. Given limited time and resources, it is essential to triage portfolio companies by identifying the most pressing threats and drawing clear priorities. Fund managers need a rapid and logical way to:
Assess specific risks to individual portfolio companies;
Prioritize companies with the greatest potential to affect fund performance; and
Develop a customized action plan for each priority company.
Assessing portfolio company risk
To navigate the swirling uncertainty presented by the coronavirus outbreak, PE firms should start by modeling the most likely impact scenarios and determining the signposts that will signal new developments. Firms then can make a rapid risk assessment of each portfolio company in light of those evolving scenarios. Conditions will differ based on everything from geography to government response. What’s critical is to identify the most pressing challenges first, allowing the firm to direct its limited time and resources toward the companies with the most immediate and consequential issues.
We’ve developed an interactive survey tool that serves as a useful triage mechanism. It helps fund managers quickly gauge each portfolio company’s vulnerability based on four areas of potential exposure: reduced demand, supply chain or operational interruptions, workforce issues and financial stability. Is revenue set to fall off a cliff, or is the company’s position more resilient? Is your supply chain secure, or has the global run on toilet paper suddenly disrupted your deliveries of pulp-based packaging? Do you need to raise new debt in the short term, or has the turmoil in the bond markets foreclosed that? Can you operate in a way that ensures the safety of staff and customers? If not, do you have the flexibility to adjust?
A uniform assessment process makes developing a response as straightforward as possible. Using the findings, firms can plot portfolio companies on a matrix based on how much risk each faces, whether that risk is addressable and how much value is at stake for the fund. By aligning companies this way, firms can build an action plan that shifts more effort and resources to portfolio companies with the highest vulnerability and the highest controllable value (see Figure 1).
Firms can triage their response based on individual portfolio company risk and “controllable value at stake” for the fund
Building a customized agenda
A strong, customized plan identifies a tactical set of initiatives the company can launch immediately. For each prioritized portfolio company, it lays out a phased execution roadmap that mobilizes the resources―opex/capex injections, project staff and outside expertise―these critical initiatives require. The most effective firms also establish a structure for learning, continuously following up on initiatives and sharing best practices across the portfolio.
While different companies may share similar risks, no two plans will look alike. Consider a hypothetical chain of retail health clinics focused on primary care. Having spent the previous two years implementing a strategy to roll up smaller provider groups, it currently has 50 clinics in three European countries and is still integrating several of those acquisitions. Its balance sheet is leveraged but in relatively good shape. From a commercial standpoint, it has developed a strong franchise and growing “same-store” sales.
A full government lockdown in its core markets, however, has put heavy strain on the company’s short-term outlook. Although health clinics are allowed to remain open, this company faces issues across all areas assessed: demand, supply chain, workforce and financial. On the demand side, fear of contracting the virus could drive down retail traffic for a period of time, raising the real risk of a cash crunch. Staying open at all will depend on maintaining staff safety and coping with a dwindling inventory of clinical supplies across the company and its geographies.
These risk factors pose immediate danger and require a rapid response. The first priority is to identify the clinical supplies critical to staying open safely and searching for alternative sources. Second, the company must implement specific protocols to protect clinical workers from Covid-19 infection, while drawing up a dynamic plan to reallocate workers as necessary to cope with gaps in coverage. If demand drops far enough, the company might also need to generate cash by trimming part-time or nonessential workers and adjusting salaries.
Supporting revenue calls for an immediate campaign to tell customers when clinics are open and communicate the steps the company has taken to ensure their safety. It will also involve implementing a plan to switch over to telehealth, using videoconferencing tools to screen patients and give nonemergency medical advice from a safe distance. The company will want to explore what Covid-19-specific offerings it might be able to develop, including testing support. And while all of that is in motion, the finance team will have to develop clear plans for improving cash generation while maintaining a close eye on debt obligations.
Now contrast that scenario with the situation faced by a hypothetical US-based software company. This firm builds solutions for retail customers and is well on its way to transitioning to a SaaS subscription model. While a total clampdown in many states is no less alarming for the leadership of this company, it has more time to form a response. That’s because its products are mission-critical for customers and generate a recurring stream of predictable revenue. It is also lucky that not all of its retail clients are in markets that have been shut down. Like any company in this environment, this one has to scramble to make sure its employees are safe. But even that is made easier by the fact that many of them work remotely already.
The software company’s big issue is what happens as the virus-related economic disruption spreads and deepens. While a SaaS model creates revenue resilience, retailers struggling to stay open will eventually ask for relief or simply stop paying. The top priority, then, is to devise a plan to help these customers weather the storm while deepening the company’s relationship with them.
That effort should start with an assessment of the company’s own financial situation. How much financial leeway does it have to offer customers relief? The next step is to assess the impact of the Covid-19 crisis on key customers, from those that are severely distressed and unlikely to recover to those that are actually experiencing a bump in demand (or better). By layering on an analysis of the company’s engagement with those customers (deal in the pipeline, just sold something, renewal upcoming, no current activity), sales leadership can map out a customer-by-customer path forward and offer tailored win-win solutions. One example: Offer a holiday from subscription payments in return for an early renewal or longer-term contract.
As our dedicated coronavirus page demonstrates, the outbreak poses myriad different issues for each industry, company and CEO across the global economy. What makes the private equity challenge uniquely difficult is the range of risks presented by a complex portfolio of companies spanning a number of industries and geographies. Generalized playbooks don’t add much value at a time when a global crisis affects each portfolio company differently. What’s critical is developing a practical plan to assess risk, prioritize action and execute quickly.
Do All Investors Predict Doom? Not Quite.
New research from Greenwich Associates shows a disparity in investor confidence for 2020 performance.
Amid increasing market volatility related to the coronavirus pandemic, investors are split in terms of confidence that they’ll be able to meet their portfolio objectives over the next year, new research from Greenwich Associates shows.
The research firm surveyed institutional investors on how confident they are about achieving their portfolio objectives and what they need from investment managers right now.
As of March 25, investors’ confidence that they would achieve their portfolio objectives for 2020 was, on average, a 4.9 out of 10, with 10 being the most confident, according to Greenwich. The range of investors’ answers was large: some answered 1, while others answered 9.
“Some are still kind of trying to be optimistic and think about this as much more of a short-term blip,” said Sara Sikes, principal at Greenwich Associates, by phone Friday. “The people at the bottom presumably think that this is going to have a dire effect. Our interpretation is that it demonstrates the uncertainty that exists right now.”
Where investors converge, though, is in their view of the long term.
On average, investors said that for the next three-to-five years, their confidence in their ability to achieve desired portfolio outcomes is 8.1 out of 10, the data from Greenwich showed. The range of responses in this category was much smaller, with the lowest being 6 and the highest being 10.
“What we saw as the good outcome is despite that wide range of uncertainty, on a long-term perspective, investors are maintaining the course that they should,” Sikes said.
Greenwich also polled investors on what they thought the most useful information they could be receiving from managers right now would be. Investors could choose more than one response to the question.
According to Greenwich, 69 percent of respondents said that specific commentary on how the market downturn is impacting their own portfolios is among the most useful information to be receiving from managers right now.
This, according to Sikes, is in line with the typical response from institutional investors. But what was surprising was the second-most popular response: Fifty percent of survey respondents said that among the most useful information they could receive from managers is on the actions being taken internally to protect the manager’s business.
“They want to make sure managers are doing the right thing,” Sikes said. She added that investors specifically want details on how managers are handling cybersecurity and business continuity planning, among other operational details.
“It has risen up the list because it matters more in a crisis,” Sikes said.
Special Report: Emerging Markets: Adding Value Through a Disciplined Strategy
According to a recent Bloomberg report, emerging markets are anticipated to heat up in a big way this year, building on the $14 trillion they’ve made for investors over the past 10 years. The report was based on a survey of global investors, strategists, and traders, who conveyed their expectation that emerging markets will outperform developed markets, with Asia in particular looking promising. The total wealth in emerging-market stocks and bonds now exceeds $27 trillion, bigger than the economies of the U.S. and Germany combined.
Emerging market equities are always on the radar of alpha seekers – but they represent a highly nuanced area for allocators, with countless variables including sometimes less than pristine data to inform decisions. Are quantitative strategies especially effective at tackling the challenge of emerging markets? That may very well be the case, as this report reveals.
- 1. How Quant Can Nail the EM Sweet Spot
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?
You like to say that emerging markets in particular are a sweet spot for quant strategies. Why is that?
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?
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?
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?
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.
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.
- 2. The Small Cap Opportunity in EM
Most investors agree that there is more inefficiency in small caps – no matter where in the world you find them – and thus more potential for alpha. In EMs, however, where small caps may be especially inefficient, there’s an opportunity that is often overlooked, and not typically part of an allocation plan by any but the largest funds.
A fairly common asset allocation plan for a U.S.-based fund would incorporate a U.S. allocation, an international allocation, and an emerging markets allocation. Historically, a reach for increased alpha in U.S. or international small caps has been more difficult because they don’t move hand-in-hand together with their large cap brethren. In both U.S. and international equities, large and small caps tend to have more independent and less correlated performance relative to large and small caps in EMs. In other words, when large caps are on an extended roll as they have been for many years now, the small caps aren’t necessarily along for the ride. In emerging markets, large caps and small caps have moved much more closely together. Further, the annualized volatility of EM large and small caps has been more similar relative to large and small caps in both U.S. and global equities.
So why does this matter? If allocations to large caps are all about beta, and allocations to small caps are about alpha, then in EMs we believe you have a better chance of getting both at the same time, rather than one or the other.
Human intelligence overlay
The emerging markets investment capacity at Mackenzie is, at a high level, constrained, so that the team can be in and out of stock ahead of managers encumbered by much larger AUM. Leveraging its computing power, the team is as nimble as they come, ranking and trading stocks daily, tapping into highly ranked names it doesn’t currently own and getting out of names that have fallen down the ranking.
Daily trading and daily rebalancing require a strong infrastructure, especially with a 24/6 clock (Middle East markets are open on Sunday). Mackenzie’s EM team spends a lot of time making sure that its models can run several times over the course of a day – as Asia opens and closes, then Europe, and finally the U.S.
“The world never stops for anyone in terms of the rebalancing cycle, so when other managers say they rebalance monthly or weekly, that’s a lot of missed opportunity, and it’s why we scrape data daily and rank stocks daily. There is always new information out there, and a name might still look cheap in a week or two, but I’d rather buy today than five days later when the stock has run up a lot already,” says Datta.
A common knock against quant strategies is that they are “black box,” meaning they lack transparency and turn over all decisions to computers. Embedded in the process at Mackenzie Investments, however, is a feature that not many other quantitative shops offer – serious and detailed human review. If there is one thing Datta makes clear he abhors it’s the “garbage in, garbage out” results of unchecked data dumping.
“It’s even more an issue in emerging markets because the data is dirtier there,” says Datta. “Most quants claim they do some statistical checks, but every trade we do is vetted or checked by either myself or my colleagues in the portfolio management and research teams at Mackenzie. And we do find names that we pull on an almost daily basis. We don’t trade them because we found that some variable the model was looking at was not correct, or that various data sources didn’t agree. Why are we selling a name? Why did we buy this for the first time? We dig deeper. If the data is bad you’re making a wrong investment decision, so we do spend time making sure the data is clean on a name-by-name basis in our buys and sells. Pulling trades is something we do almost every day, and certainly more prevalent in our emerging markets strategies than it is in our developed market strategies.”
All of this requires top-level talent, and Datta builds his team based on their programming excellence, and with an eye consistently on the future. “One trait of our quant business is that we mix the experienced people like me with the tech-savvy youth, not all of whom need to be PhDs. There are plenty of smart people with undergrad and masters’ degrees out there. The importance of mixing experience and bright, new thinking is that technology changes at a very fast pace, and it will change even faster going forward. Today, everyone uses [the programming language] Python. That was not the case five years ago, and I don’t know what the new Python will be five years from now, but I can tell you it won’t be Python. It will be something else.”
The human factor extends to EM trade execution as well, where varied exchanges, trade settlement processes, and so forth come into play.
“We have as much sophistication and discipline in our execution as we do in our stock picking and risk management – it’s all integrated into a single process,” says Datta.
The firm has proprietary market impact/trade cost models for every trade, with key drivers such as the level of liquidity demanded and stock volatility. According to Datta, its actual EM transaction costs have always come in slightly below what has been anticipated – a clear sign that trade execution is solid. “We deal with many brokers, and we are upfront in telling them that we trade a lot of names every day and we try to get the lowest commission possible because of the volume business we do,” says Datta. “And we let them know they’ll be measured versus yesterday’s closing price and VWAP [volume-weighted average price]. We monitor them closely, and if a broker is not doing well, we cut them off or lower the trading with them. It’s a very efficient process.”
Strong execution is particularly relevant when shorting an emerging markets’ stock, which is something that sophisticated investors sometimes avoid. It can be done through swaps, but execution is crucial when shorting in different regions of the world. “For example, there are plenty of hedge funds out there that appear to be shorting in Asia and China, but if you dig deep most of them have a long bias and all they’re shorting is the benchmark,” says Datta. “With the market-neutral type product such as we have in emerging markets, we actually short single stocks in almost all emerging markets.”