Nick Rees has over 15 years of investment banking & investment management experience. He started his career in 1998 at Goldman Sachs, beginning in Equity Operations before moving to the Equity Capital Markets division of Goldman in 2001 where his primary responsibilities included the management of financial and operational risk in connection with IPOs.

In February 2004 Nick joined Absolute Return Partners as its first employee and Business Manager. In October 2005 Nick became a Partner with primary responsibility for business development. Today Nick is the Managing Partner of the business and manages some of the Firms’ key client and strategic relationships. He sits on the Firm’s Investment and Management Committees.

LUXHEDGE :  First of all, can you describe a bit your company?

NICK REES: The Nemesis Global Equity Alpha Fund (GEA) is a joint venture between Absolute Return Partners and StockRate Asset Management in Denmark. Absolute Return Partners has two primary business lines. In our advisory division we are an allocator of capital to third party hedge funds. Here we specialise in genuinely low beta (niche) alternatives such as lending, leasing, royalties and niche trading strategies. In our fund management division we manage the Global Equity Alpha Fund which is a joint venture between Absolute Return Partners and StockRate Asset Management in Denmark.

The company is 13 years old and we managed a little over $500M in total.

Niels C. Jensen	Tricia Ward	Steven Bartel

LH: And among those $500M, we have your Nemesis – Global Equity Alpha fund.

NR: Indeed. We currently have assets under management of US$39M in this specific fund, and the pure long only strategy is a further US$450M and growing. That’s managed directly by StockRate Asset Management in Denmark.

We launched GEA in February 2011. The main philosophy behind the fund is a simple one – we cannot control whether equity markets will go up or down but we can focus on identifying highly rated, stable companies who have a track record of delivering value to investors. By ‘value’ I mean return on equity as evidenced in company audited accounts, not stock price. We are completely agnostic to the price of a stock and do not use it in any part of our process.

The main idea behind the fund is based on a well-known empirical observation: many fund managers underperform their benchmark because of the risks associated with discretionary management. Those fund managers might have inherent biases because of where they sit (London, Luxembourg, Paris…) or get emotionally attached to specific stocks when building the portfolio. The aim of our process is to eliminate this risk.

In addition to the stock picking process another important feature of our fund is the risk overlay strategy we implemented in June 2013. This overlay was created by AlphaSimplex, a Boston based company managing US$4.5B. It’s not a hedge per se, but is used to smooth the volatility of equity beta in the portfolio. Via index futures the system adjusts the fund beta in line with how it sees the volatility environment. Since you can experience high volatility during periods of sharp market correction as well as in equity bull markets, it is extremely important to distinguish between these environments.

This graph shows the performance of the fund starting June 2013, when we implemented the risk overlay.

LH: How does AlphaSimplex differentiate the downside risk and upside potential?

NR: That’s actually the selling point of the system. To keep it as simple as possible, global equity prices are used as an input. From the daily movements AlphaSimplex extracts return, volatility, correlation and covariance estimates and uses those factors to assess the volatility environment we are currently operating in. The risk system does not look at fundamentals or macroeconomic forecasts: it is truly a quantitative price-driven model.

LH: What is the net exposure of your portfolio?

NR: We are always going to be long biased. During the most bullish scenario, we can be long 90% equities and long 35% stock index futures, resulting in a total net exposure of +125%. On the opposite end of the scale, the most bearish scenario leads to a net exposure of +50%. Today our gross exposure is very close to 100%. We have not been significantly below this since introducing the system in June 2013, as markets generally been on the rise over this period, and hence our signals have been bullish on the whole.

LH: What are your views for 2015?

NR: Well, truth be told, we believe that the environment we have seen for the last 2+ years, where risk assets have risen across the board, is coming to an end. This is the result of the withdrawal of quantitative easing (in the US at least). In actual fact this is good news for our strategy as people will have to refocus on corporate fundamentals. As they do we believe high quality stocks (our focus) will outperform lower quality stocks rather than all stocks going up in value due to central bank intervention or policy.

LH: Now, looking at the performance since you introduced the risk overlay in June 2013, you had a return of 23.33%. Could you comment on that?

NR: We are obviously pleased with this performance as we have outperformed the MSCI All Countries World Index by over 5% over this period, and our LuxHedge UCITS peer group by over 13%. As I alluded to before, that is despite the environment not being optimal for our strategy as QE has created a bull market for all risk assets. That can’t continue forever and when it ends it is my firm belief that high quality blue chip corporates will outperform.

LH: You experienced two volatile months in January and February 2014 with -5.6% and 7.25% respectively. What happened?

NR: We made one change in our risk overlay since we launched it in June ’13. Up to April 2014 our maximum gross exposure could be 150%, not 125% as it is today (i.e. we could be 60% long index futures in addition to being 90% long stocks). As a result when the market was down in January we were long and lost money. In February when the market bounced back we gained on the upside as well. The reason we changed our limits was to ensure that the overlay was skewed to the downside. It’s not there to be aggressively long in rising markets, rather it’s there to reduce beta in falling markets. We feel we have the right balance as a result today.

LH: Can you detail your systematic process of picking stock?

NR: Our process uses three main variables: earnings strength, financial strength and stability. The universe of stocks that could potentially be included in our portfolio is 35,000. The first step is to narrow down this universe using a liquidity filter since we only invest in stocks that are listed on a recognised exchange, with a market capitalisation of around a billion dollars and that have traded at least 2.5million dollars per day over the preceding 3 months. This first filter leads to a universe of around 7,000 stocks. Then, we rate all of those stocks according to earning strength using return on equity, return on cash, and other similar metrics, relative to the rest of the universe. We also assess the financial stress by analysing the quality of the balance sheet. We end up with a ranking of the 50 best stocks. Our process penalises specific features such as excess leverage on the balance sheet, or good will. We only use audited data with a 5 year look-back window. We tend not to react to corporate announcements.

The image above shows a typical stock ranking that our system would provide. We tend to focus on stocks that appear on the top right corner, which indicates high earning strength as well as high financial strength. Usually we colour code each ticker to give an indication of the stability of both these ratings, but in the attached we have used the colour coding to indicate stock P/E ratios. This is NOT a factor in our investment process but we do monitor it and as can be seen in the chart, there are plenty of examples of cheap (green) highly rated stocks, as well as expensive, lowly rated ones. So a high rating does not necessarily translate into an ‘expensive’ stock.

In essence, what we are looking for is repetitive behaviour in a company’s ratings. As human behaviour is repetitive it follows that we are really looking to identify high quality management teams as evidenced by consistency in our rating of the company. We think that a company that delivers returns to shareholders is a better predictor of future performance than stock prices. As to how the company is going to perform going forward. Whether a stock has a PE of 15 or 5 makes no difference for us and this is another key differentiator in our process versus our competitors.

LH: Do you compare a stock relative to all other stocks, or do you have some subgroups, using for example sector differentiation? Does the model compare IT companies with, say, healthcare companies?

NR: We don’t care much about being overweight or underweight to any specific sector. We see ourselves as sector agnostic with our portfolio being driven by our stock selection process not our sector weightings relative to an index. That said, the financial sector is a special case. As banks naturally leverage their balance sheets to make loans, and our process penalises leverage on corporate balance sheets, it is hard to compare banks with industrial companies. We therefore rate them separately (using the same process) and invest in the best in class. As you might expect the financial stocks we do own tend not to be banks, but rather highly cash generative asset management companies with stable revenues and little or no leverage on their balance sheets.

Obviously as a result of our process we will have a bias to some sectors over others. Energy stocks, for example, tend to have a high beta and are less stable than companies in other sectors. That’s the main reason why we have less exposure here.

The only discretionary element in the stock selection process is where we have very large sector concentrations in our top 50 names. This rarely happens but if it does, to ensure diversification and for good portfolio management, we might switch out some of the stocks in the top 50 and choose a few stocks from less concentrated sectors. So, to put it another way, we might not invest in the top 50 stocks, but rather in 50 from the top 60.

Regarding the weighting itself, when we invest in a portfolio, we do not take a discretionary view on whether stock number 1 is better than stock number 50. Both stocks will be included in the same proportion in the portfolio. This initial equally-weighted portfolio evolves since we hold the stock and allow the performance to accumulate through the year. We have a low turnover and only rebalance the portfolio in May, mostly because all the audited data we need is available around that time. In the annual rebalancing process around 10-15% of the stocks exit the portfolio (so 7-8 stocks) and those remaining stocks are rebased to an equal weighting again.

Our rule is to be invested in 50 stocks at least, but we can invest in more. One development we are considering for our portfolio is to go up to 100 stocks. Our research suggests that performance should not be significantly different if we were to do this.

LH: Geographically speaking, you have a clear overweight, nearly 60%, to the US. Is it something you’re looking at?

NR: No we do not really mind since most of the stocks we invest in are global businesses. A US-listed company might very well derive its revenue stream from Asia mostly, and the seemingly huge exposure to US might simply be misleading. In this regard, that’s not much of a concern.

In terms of currency hedging, we don’t hedge our non-US dollar currency risk at the stock level. We do hedge our non USD shares classes (euro and sterling) back to USD so investors in these classes are only exposed to the return of the strategy, not large swings in the FX markets. The way we do this is via 3 months currency futures; typically rolling our exposures every quarter.

LH: Is there a way one of your stocks might leave the portfolio aside from the usual rebalancing in May?

NR: There are indeed a few instances when we would sell a stock we hold in the portfolio. One obvious example would be as a result of M&A activity – particularly in a highly leveraged transaction where the new parent company would be penalised in our process as a result of the new debt on its balance sheet. A change of management may also be another reason. As I mentioned before, human behaviour is repetitive so we like to see stable, successful management teams in place.

LH: Thank you very much!