How can quants find value in volatile markets?

Smart investment decisions have been difficult in the last 10 years with the market easily categorised with low interest rates, low volatility levels, and the occasional spikes in the latter. This year at QuantMinds Americas, a panel of experts came together to explore solutions and new techniques to find value in volatile markets.

Moderator:

Aymeric Kalife, Associate Professor, Paris Dauphine University and Founding Partner, iDigital Partners

Panellists:

Chris Kelliher, Quantitative Researcher, Global Assets Allocation team, Fidelity Investments

George Mylnikov, Portfolio Manager, Head of Quantitative Research, Windhaven Investment Management

Greg Gurevich, Portfolio Manager and Founding Partner, Maritime Capital LLC

The current climate: low rates, low volatility, and spikes

If we step back and assess what has been happening in the financial markets over the past decade, one of the central issues is that we have been living in an age of low or even zero interest rates. This has made alpha extraction very difficult for many asset managers, particularly at a time when there is also heavy pressure on fees – we are essentially being asked to do much more for much less.

At the same time, there has been a dramatic change in volatility, which peaked during the great financial crisis, and has generally been low since then, with occasional wild spikes. Some triggers have been fairly obvious: e.g., the European Sovereign debt crisis, Chinese growth in 2015, and Brexit in 2016, but the vol spikes are hard to anticipate and have had varying durations. The selloff in Chinese equities in 2015 lasted a few days, although it followed several months of less intense selling. In February 2018, there was a one-day spike in vol, but it subsided very quickly. And finally, in Q4 2018, the selloff in the US market began in late October and continued to the end of the year. But no matter how short or long in duration and how intense the effects, prediction and mitigation can be quite challenging for investors.

Adaptation and education for clients

So the question is: “Faced with this low rate, low vol, yet hazardous environment what should we do?” One answer lies in staying the course. If you believe in your investment process, then follow that process. You can also adjust the range of back-testing scenarios to include both low vol and spiky vol environments. Some may be tempted to capture some gains in the high vol environment, although it can be difficult to monetise and complicated to sell the idea to clients. Other approaches include finding vol neutral strategies or have a long convexity component to a portfolio.

In attempting to capture volatility premia, we know that vol is generally seen as being persistent and mean reverting – this has been true before and after the financial crisis. However, the persistence lasted longer and the speed of mean reversion (MR) was slower prior to the GFC. Now, with less persistence and much faster MR, the risk decisions are more complex. Some guidance on risk may come from observation of feedback effects. By discerning between technical and fundamental elements, one can work to gauge whether a spike is indicative of a systemic risk event. If it is a technical but not a structural problem, it may be best not to react too soon.

The new volatility regime also creates opportunities for new value propositions. Many clients are focused on how to mitigate the spikes, for example, so there can be a benefit in efforts to customise portfolios even more and rebalancing with a closer eye on risk preferences. In this context, it is useful to engage more deeply with the clients and extract information and preferences from them, while providing education and advice. One area where an asset manager can truly make a difference is in educating the client not to chase the market – too often we see that they will buy on the rallies and sell on the drops. Other clients are more sophisticated and want to understand factors, benchmarks, and when and how you will make and lose money over time. Client education and transparency are key during liquidity and volatility events; the more that is known about the investors, the more insight we will have on when to let things ride and when to work on de-risking due to changing market conditions.

The liquidity conundrum

As markets have shown, liquidity is very important, but we still don’t know how to handle it very well. It is unpredictable and when we need it the most, that is when it tends to disappear. In addition, there are two types of bad liquidity – the first, more dramatic version comes from assets selling off and investor panic; the second arises simply when there is not much trading taking place. One way to address the liquidity question is to select and invest in ETFs carefully – they serve as effective diversifiers. Further, they may have some illiquid constituents, but those are often offset by liquid counterparts.

Another consideration is that there are two sides to the illiquidity coin – what might be bad for one counterparty (CP) could be good for the other one. The impacts depend on your size and the types of instruments you trade. In some instances, there may be opportunities to make markets and extract liquidity premia. This is an area where quants can navigate well and add value for clients.

The last words: data science

One of the main areas of innovation in recent years is the extensive use of large and growing data sets. Yet, as much data as there is, the dependent variables have not really changed, but the explanatory variables have exploded. Here, data mining can be a significant danger for the inexperienced. The keys in wrestling with such issues are ensuring the quality of datasets and carefully vetting the methodologies used on them. Look for data sets that are as complete and clean as possible and that have less survivorship and look-ahead biases.

The new generation of machine learning tools is enabling more rapid development of models, but it is important to have employees with financial expertise involved. If the team is only composed of computer and data scientists with no portfolio management experience, there may well be problems and even blow ups.

In conclusion, there are many risks and opportunities out there, as always, in the ever-changing financial landscape. As analytical tools and technologies have evolved, there is a significant role for quants in helping their firms and clients adapt and survive in this new world.