Lumyna – Sandbar Global Equity Market Neutral UCITS

Discretionary large cap single stock alpha

Hamlin Lovell
Originally published in the February | March 2020 issue

The last two years have been challenging for many market neutral strategies. Several have been exposed to underperforming factors such as value, and/or have been whipsawed by the violent reversals in and rotations around outperforming factors like momentum, growth and quality. In contrast, Sandbar, which has no structural bias to being long or short of any styles or factors and has limited exposure to them, has generated performance close to the manager’s long run average. Since 2007, Sandbar CIO, Michael Cowley, who featured in The Hedge Fund Journal’s 2019 “Tomorrow’s Titans” report, has averaged returns of around nine percent with volatility around five and a half percent over the last decade. At Citadel he worked for another portfolio manager who has featured in the Titans report, Anchor Bolt founder, Robert Polak. 

Given average gross exposure of circa 300%, the strategy has, on average, delivered gross annual alpha of around three percent per turn of leverage. Net performance of seven and a half percent in 2019 was a shade shy of the long run average, whereas in 2018 the strategy returned 11.80% which was above the long-term annualised returns. As opposed to many long-biased managers, Sandbar naturally did not participate in the 20-30% surge in global equities, which was powered mainly by valuation multiple expansion. Cowley asserts that, “we have a structurally lower risk profile than most hedge funds, because we focus on single stock risk and minimise directional, country, sector and other factor risks”. Though a snapshot of portfolio exposures at any point in time may indicate some minor residual, factor risks, this is partly a function of how they are defined. In any case over a full year these exposures tend to prove ephemeral and their aggregate contribution to returns is minimal, based on third party analytics (from providers such as Axioma or Morgan Stanley Fund Services using MSCI Barra models). 

Generally, portfolio managers’ processes chop and change, and they blame firm constraints or management structures. We don’t deviate from my process or universe.

Michael Cowley, CIO, Sandbar

Cowley argues that, “the consistency of process and investment universe are what most distinguish our track record from other fund managers. It is unusual to get a consistent process and track record in the hedge fund world. Generally, portfolio managers’ processes chop and change, and they blame firm constraints or management structures. We don’t deviate from my process or universe.”

Sector selection

His returns have endured multiple market environments: bull and bear runs including the GFC; several business cycles for various industries and sectors; booms and recessions, periods of high and low volatility, and – most importantly for the strategy – episodes of high and low stock dispersion. “My style of intra-sector pair trading relies on idiosyncratic dispersion, which might be caused by some companies winning market share from others,” he says. “If correlations spike towards one, the odds are stacked against stock-pickers generating enough alpha to cover stock borrow, financing, trading, and commission costs.” Somewhat subdued single stock dispersion helps to explain why 2019 was less profitable than 2018 for Sandbar. Therefore, Sandbar avoids trading stocks in several industries – such as finance, REITS and utilities – where there is not enough attractive idiosyncratic dispersion. (Financials display plenty of dispersion but it is substantially driven by the sorts of macro and systematic factors that Sandbar eschews forecasting.) 

“The best idiosyncratic, intra-sector, dispersion has historically been found in industrial and cyclical sectors: aerospace & defence; airlines; autos; building materials; business services; capital goods; chemicals and transports,” he continues. “The investment universe has been mainly stable with very little attrition or turnover. We are not looking for new sectors. Regressions are reasonably consistent and when they do change it is pretty clear why.” The universe of c 500 to 700 companies in 40 sub-sectors is global: mainly listed in North America and Western Europe but can include more liquid emerging market stocks mainly in Asia. 


Since 2007, Cowley has averaged returns of around nine percent, with volatility around five and a half percent over the last decade.

Large caps

Some hedge fund managers set great store by obtaining an information edge from there being little or no high-quality sell-side analyst coverage of small and mid-cap stocks – particularly in Europe, emerging markets or Japan. They use their own research to populate information gaps in such companies’ patchy disclosures. Yet Sandbar’s process thrives on the extensive transparency and visibility afforded by large and mega cap companies, seen in their more regular and granular guidance and in more detailed forecasts from banks and brokers. “This makes it easier for us to gauge consensus expectations, and identify where a differentiated view can add value for our market neutral approach,” says Cowley, who recognises that the greater transparency of large caps might not be so helpful for a thematic approach that may seek to anticipate which factors and sectors will move into vogue amongst investors. But Sandbar is focused far more on predicting short to medium term earnings surprises, than on valuation multiple changes, which are of course partly based on which factors are fashionable. Cowley is well aware that some valuation measures have recently ranked “value” stocks at their deepest ever discount to “growth” stocks but reiterates that he is not in the business of making calls on factors.

“A classic pairs trade, long of cheap stocks and short of expensive ones, would be a massive value versus quality skew,” he says. “We have no interest in running such a factor skew as it has been the graveyard of many investors. We are more interested in relative value versus industry peers. But valuation alone is only half of an investment thesis, and often valuation divergences can widen out further – the question is how you crystallise the value.” To do so, Sandbar also requires a catalyst, though not in the sense meant by many event-driven funds. “We need to anchor the position with a data-driven thesis and justification to invest based on why the market is wrong short term.” Typical catalysts include earnings releases, or guidance thereof at conferences or capital markets days. Though nearly all discretionary managers would say the same thing, Cowley declares with sincerity that, “the strategy outperforms when fundamentals are driving the markets”.

Dimensions of diversification 

Whereas traditional long/short equity funds or activist funds may have 10, 20 or 30 positions and many quantitative funds have several thousand, Sandbar sits between these extremes and typically has 150 plus stocks, covering both long and short books. Performance attribution is broad based amongst countries, sectors and stocks, and can generate as much alpha from shorts as longs. “This diversification ensures that no stock or pair makes or breaks the month, quarter or year. We cap positions at a maximum 10% of NAV and two to three per cent of GAV but rarely get that high. There are too many pieces of fundamental information or datapoints that cannot be controlled or forecast. Even with the best research team, too many external factors can trip you up,” says Cowley. These diversification criteria also mean that the strategy fits easily into a UCITS pari passu (and managed accounts can also be offered pari passu with different volatility targets). And the liquidity of the portfolio is a good match for UCITS. Large caps, with market caps of five billion dollars upwards, averaging above $15bn are traded and allow Cowley to estimate strategy capacity of around three billion dollars of net assets (which implies c $9-12bn of gross assets). In fact, it is liquidity rather than market cap alone that decides the investment universe: average daily volumes are at least $50m for each name and Sandbar expects to be able to liquidate at least 75% of the book within five days, trading no more than 20% of daily volumes. 

This portfolio also allows Sandbar to maintain a high degree of factor neutrality, which Cowley reckons would be more difficult with a concentrated book. As well as classic factors, proprietary factors, such as crowdedness, are controlled. “We are generally not going to be in stocks where hedge funds are massively long or short,” he says. “At the same time, we do not want to run an aggressively contrarian stance. But neither of these are hard and fast rules. We may sometimes be short of highly shorted names, and sometimes own consensus longs. It is all about balance: if we are short of a heavily shorted name, we may balance it out by being short of others that are much less widely shorted.” 

Medium term tactical trading

Sandbar does not expect to make money every month. “We do not have perfect timing, and we will sometimes lose money short term as the market takes time to latch on to datapoints we have identified earlier. We absorb some short-term losers as they grow into becoming immature long-term winners. A diversified book allows us to tolerate losing positions for longer than more concentrated strategies.” That said, there are some position level stop losses and fund level drawdowns that could require risk reduction.

Sandbar might profit on fewer than half of trades entered, but one flaw of metrics such as hit ratios, win loss ratios, and slugging ratios is that the calculations equally weight positions, which might closely approximate some strategies but is not a good fit for Sandbar. Cowley states that, “we have a notable sizing alpha. Position sizes are not equal weighted, and upsizing positions at times of highest conviction has added value to returns. Our investment thesis includes when to add to and when to cut the position.” Sandbar trades around positions, within an average holding period of six to twelve months per name. This is clearly much longer than another sub-strategy within equity market neutral: the “statistical arbitrage” pairs trading strategy, which typically has intraday or multiday holding periods.

I used to be an engineer and would rather break problems down to first principles.

Michael Cowley, CIO, Sandbar

Proprietary fundamental data analysis

If Sandbar needs to be put into a strategy bucket, it is discretionary equity market neutral, but the process has a higher quantitative content than do some fundamental stock-pickers. It is grounded in a firm foundation of proprietary quantitative analytics. Cowley declares that Sandbar and many quant funds share a common goal of wanting to create a process anchored in data, “to remove emotional connectivity, confirmation bias and other behavioural biases from the process”. What distinguishes Sandbar from some purely or substantially quantitative or systematic strategies is the analytical framework and starting point for the approach. While some quants take a top down, macro view, seeking correlations between stocks, factors and macro variables, Sandbar is more micro-driven: starting from the bottom up. “We have a deep fundamental analysis understanding of companies and sectors. Fundamentals are driving the data, and not the reverse. We are dealing with sizeable datasets but are wary of data scientists identifying correlation patterns that could be spurious or statistical anomalies,” says Cowley. “And our process is not heavily reliant on corporate access. We regularly interview company management but this is only one part of our investment process.” Cowley began his career in corporate finance before moving to the buy-side.

“All of Sandbar’s data is publicly available and is mainly conventional fundamental data. No expert networks are used. Independent research providers in the form of classic boutiques could be used, but not for esoteric data. Though the firm does venture into what might be dubbed ‘alternative data’ with some web scraping, the edge does not come purely from bespoke datasets. We are not data snobs. We are smart when it makes sense but stay simple when that is adequate. We do not want to outsmart ourselves and get into an intellectual rathole when bang for the buck can be so small. I used to be an engineer and would rather break problems down to first principles. We only want to be more complex if it is scalable,” says Cowley.

Sandbar’s competitive advantage comes from more timely access to information, and how it is interpreted and prioritised. In terms of speed, Sandbar subscribes to live feeds including commodity and chemical prices. In terms of finding signals amid abundant noise, the manager distils a small number of salient datapoints that are the key drivers of profitability for large cap companies. “For instance,” he explains, “plane engine makers make most of their profit from servicing, so we focus our edge on data capture for the aftermarket business; the rest is noise somewhat. We are humble enough to accept that we cannot capture all idiosyncratic drivers.”

“We maintain our own intellectual property in house, building sector and company models, based on hard quantifiable data and fair value inputs and outputs,” he continues. Absolute and relative valuation is then assessed using a variety of metrics, lookback periods, and peer groups.

Sell-side analysts also pride themselves on their model building prowess. How can Sandbar’s team of six or seven buy-side analysts (several of whom overlapped with Cowley at his former firms) covering hundreds of companies maintain a repeatable and statistically robust competitive edge over sell-side analysts, who might have spent 20 or 30 years specialising in a smaller number of companies? In contrast to some managers who claim to be allergic to any sell-side contact, Sandbar has a good dialogue with the sell-side, which informs their understanding of earnings expectations. But Sandbar cannot be perfectly compared with sell-side brokers anyway, as their end goals differ. “We are not constructing a ten-year DCF model to value a company, based on forecasts of economies, industries, exchange rates etc that must be subjective,” he asserts. “Long term DCFs are so sensitive to small changes in inputs that I could reverse engineer a DCF to arrive at almost any price target. We are building shorter term models based on hard data.” Sandbar is looking for inconsistencies and anomalies around expectations on a 12 to 24-month basis. These can be found by cross referencing companies’ projections to identify some with share prices that are over-optimistic and others that could be too cautious, based on the key datapoints. This process of triangulation homes in on disconnects between share prices, Sandbar’s forecasts and consensus forecasts, without making bold predictions of macro or industry trajectories. “We are very light on qualitative information or forecasting economies or industries, such as China growth or housing starts,” he says.

ESG feeds into the train of thought but is not currently a key differentiator. Sandbar has not excluded any companies based simply on ESG criteria except when specified by investors, is not engaging with companies nor voting proxies, and is in the process of creating its own ESG scores while currently using external data providers for scoring of their universe. But ESG is integrated into the investment process. An ESG ratings agency informs analysis of ESG factors, and although Cowley is cognisant that scores vary between agencies, some criteria are unequivocal. “We are generally more likely to be short companies that have bad corporate governance or are not totally transparent,” he says. “Governance is pretty fundamental.” Additionally, heeding the environmental aspect of ESG, “we are more likely to be long of companies that win market share by making more energy-efficient products, and short of those that are losing customers due to making less efficient ones. There is likely to be a very high correlation between fundamental longs and ESG scores.”

Best ideas portfolio 

An open plan office mentality fosters cross fertilisation of ideas – and crucially data – between industry sectors along and across supply chains. “We scale the data over verticals and horizontals. As well as competitors in the same sectors, Sandbar looks at suppliers and customers, globally. “One analyst may look at firms with raw material outputs that are inputs for another company, such as a white goods maker. Airlines buying fleets of planes drive the aftermarket for engine makers,” says Cowley. 

Sandbar avoids siloed structures like those in which Cowley has worked at several of his former employers. Some of their offices are reputedly as silent as libraries; staff engrossed in analytics wear headphones and avoid interaction with colleagues. While Sandbar analysts do specialise in sectors, they do not “eat what they kill” in the sense of being remunerated on personal P&L. The objective is to generate the best ideas for the whole portfolio. “If each analyst ran their own book, what would be optimal for a very narrow universe might not be at broader portfolio firm level. We do not want to be the sum of inefficiently constructed portfolios,” says Cowley. He is thus rather critical of the business model that is used to manage the great majority of assets in what is one of the smallest hedge fund strategies by assets: fundamental equity market neutral. A differentiated perspective in the context of an unfashionable hedge fund strategy sets the stage for Cowley continuing to generate uncorrelated returns.