Journal

It is with great pride that I look back on the first year of the LF Havelock Global Select Fund’s life. In this time there have been two distinct phases of performance. Firstly, a wave of negative sentiment sent a chill through equity markets in the autumn of 2018, with falling prices leading to negative performance. These concerns melted away during 2019, with a buoyant mood driving equity prices higher and helping the fund recover its losses and make new highs.

The fund was well placed to weather the storms at the end of last year, owing to the amount of dry powder it held in the form of cash and government bonds. This was determined by us having conservatively set the “volume control” which drives how capital is invested into company shares. We made this decision because market valuations were high relative to history, and in the belief that our opportunities for investment were likely to improve. The combination of prices generally falling, and us completing further new investment research, led us to increase the volume control, which increased the fund’s holdings of equities in time to benefit from the general uplift in markets.

The US economy has experienced its longest period of economic expansion on record. A widespread belief that central banks will support markets if the world’s major economies contract, has led many investors to be complacent about the risk of financial loss and helped push stock markets to new highs. This rising tide lifted all ships, and so contributed to the fund’s positive performance in the first half of 2019.

The chart below shows the Shiller PE ratio, which is the ratio of prices to average earnings in the last 10 years for companies in the S&P 500 index. This metric has been widely touted as evidence for why valuations are at worryingly high levels, with current low interest rates forming the major defence of why such high valuations can be sustained.

Our own analysis suggests that valuations have become even more stretched for the most expensive stocks. To rank as one of the ten percent of most expensive US companies it currently requires a price earnings ratio above 60. At no point during our 60-year study, including during the dot-com boom, was this higher. It follows that many market participants are willing to pay a hefty premium for high quality or high revenue “growth” companies, in the belief that future profits will give them “jam tomorrow”. This bears some resemblance to the so-called Nifty-Fifty stock market boom of the late 1960s and early 1970s, where a bubble emerged amongst a small and concentrated group of large companies.

The narratives used to justify current high valuations both generally and with respect to high growth and high-quality companies have hallmarks of “this time it is different” about them. The risk to asset owners is that the world cannot sustain a low-interest rate, low-inflation and high profit growth environment, and that something must “give”. Furthermore, the Nifty-Fifty stock market boom provides some cautionary lessons on the risk of investors’ believing that valuations cease to matter for the “best” companies.

In the short-term the fund’s performance will be impacted by the sentiment of others in the markets, but in the longer term we believe that it will be driven by the performance of the businesses that we choose to buy. Our twin lines of defence against the current risks we see is to continue to hold some dry-powder, and only own stakes in sound businesses where undue optimism is not required to justify their purchase price. With hindsight an all-out bet on high-growth companies would have been more profitable than our own cautious stance so far in 2019, but our resolve to maintain our approach is, nonetheless, unchanged.

We believe that the current high tide is unlikely to never recede, but we cannot predict when it might turn or how far out it might travel. We move forward into the remainder of the year in the belief that our investment approach will leave our ship well placed to weather future storms.

Footnotes

[1] Data courtesy of Prof Robert Shiller (http://www.econ.yale.edu/~shiller)

Important information

Please ensure you have read this important information. The value of investments in LF Havelock Global Select may fall as well as rise. Investors may not get back the amount they originally invested. Investments will also be affected by currency fluctuations if made from a currency other than the fund’s base currency. Past performance is not a reliable indicator of future results. Potential investors should not use this website as the basis of an investment decision. Decisions to invest in LF Havelock Global Select should be informed only by the fund’s Key Investor Information Document (KIID) and prospectus. Potential investors should carefully consider the risks described in those documents and, if required, consult a financial adviser before deciding to invest. LF Havelock Global Select can invest more than 35% of its value in securities issued or guaranteed by an EEA state listed in the prospectus. The KIID and prospectus are available in English from this website and from Link Fund Solutions.

This website is not intended for any person in the United States. None of Havelock London’s services or related funds is registered under the US Investment Company Act of 1940 or the US Securities Act of 1933. This material is not an offer to sell or solicitation of offers to buy securities or investment services to or from any US person.

As the name implies, when you own a share you own a slice of a business. The market price of your share should depend on the existing value in the business and the future value it is likely to create. In his Nobel prize winning work on the empirical analysis of asset prices, Professor Robert Shiller demonstrated that over the long-term, market prices do indeed track earnings.

However, in the same work Shiller showed that prices fluctuate more than they should if market participants were always responding rationally to new information. This means there are periods when prices and fundamentals dislocate. How you spot such a dislocation is an important, valuable, and difficult question to answer. In Figure 1 we see that the price-to-earnings ratio of the S&P 500 is high with respect to history[1], having only peaked above 30 twice before in the 150 years of data we have. Whether this does or does not represent a dislocation partly comes down to whether these stocks are set to experience a very high level of growth in their future earnings, among other factors.

Much has been written about the relative performance of value and growth stocks during this long-in-the-tooth bull market. In Figure 2 we show the historic performance of a value and a growth portfolio since 1926[2]. In the last ten years (to Dec 2018), the value portfolio has returned 11.0% annualised, and the growth portfolio 15.1%. Such relative performance appears to be remarkable; across history value has rarely underperformed growth in any ten-year period.

But what exactly do the terms ‘value’ and ‘growth’ mean? A very specific methodology is used to define the portfolios shown in Figure 2[3], and many other methodologies exist using different fundamental metrics, metric combinations, datasets, selection criteria, and weightings. All applied to different universes of stocks.

Are the terms ‘value’ and ‘growth’ understood? And are they useful for making investment decisions?

Any metric based on recent realised fundamentals provides only a crude view of what you need to know to make good long-term investment decisions. You need to understand the future fundamentals of a company in order to know what price you should be paying for its shares. At Havelock London we do in-depth data-driven research into companies to understand their potential future earnings, and uncertainties. We are “valuation” investors rather than value investors. A stock doesn’t have to have a low price-to-earnings multiple for us to like it. But it does have to be trading at an attractive price, relative to realistic expectations of its earnings.

By using data to identify companies that we believe are good quality and are trading at attractive prices we are not simply ‘value’ or ‘growth’; we are both.

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Footnotes

[1] Data courtesy of Prof Robert Shiller (http://www.econ.yale.edu/~shiller)

[2] Data courtesy of Prof Kenneth French (https://mba.tuck.dartmouth.edu/pages/faculty/ken.french/)

[3] The methodology follows that of the Fama-French “HML” factor; US stocks are ranked by price-to-book each year with the top and bottom 30% assigned to ‘growth’ and ‘value’ portfolios respectively. Equal weight is given to small and large stocks within each portfolio, to separate a value effect from a size effect.

As professional investors, managing the risk of losing money is a responsibility we take very seriously. The traditional approach when managing a portfolio is to allocate money to different opportunities as if it were a pie being sliced, with each slice being measured by the amount of money invested. Limiting how big a slice of pie you eat is a good way of managing the risk of over-eating, but when it comes to investing, judging risk based on the size of an investment works less well.

The same amount of money invested in two different companies does not result in the same risk of loss. For example, the amount of debt a company uses will alter the chances of it exposing investors to future losses. It is for this reason that we spend time looking inside the pie (company!) to understand the threats to a company’s on-going health.

Our investment approach does not require us to be fully invested in stocks at all times, and the analysis below demonstrates how this helps us manage risk. We show the performance of a naïve value strategy, which each year selected the cheapest 10% of US companies based on their price/earnings ratio. This is compared to the performance of having invested equally in all US companies[1]. These results support the established academic result that a valuation-driven strategy can deliver superior long-term returns. As a simple measure of risk, we show the average return in down months[2], and on this basis the simple value strategy exposed investors to a greater risk of short-term loss than investing in all companies.

The value strategy also had long periods of time when it was subject to above-average levels of volatility as measured with the “beta” statistic (which quantifies the volatility of a stock, or group of stocks, relative to the average).  If we relax the need to invest entirely in stocks, we can attempt to make this risk more consistent through time. The “risk-controlled value” series in the charts takes the simple value strategy and attempts to control its relative volatility (or beta) to be 90% of the average. It did this by varying its allocation to the “value” stocks and investing the spare cash in US government bills. This combined approach of a value strategy coupled with risk control delivered simulated returns that were above average, whilst reducing the typical monthly losses.

This exercise is just an illustration and does not represent the actual way in which we select and weight companies in our portfolio. Instead, we wish to demonstrate that forcing yourself to be fully-invested in equities is like tying one hand behind your back when it comes to managing the risk of financial loss. It means that your risk of losing money is entirely determined by your choice of stocks, without any other way to make this risk stable through time. Being able to hold some money in the safe harbour of government debt can provide greater freedom to actively control this risk, whilst seeking the best long-term investment opportunities.

Using this flexibility to pursue more consistent risk management is part of our creed of “modern investment management”.

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[1] Datasets are courtesy of Kenneth French and details of calculation methodologies are available on his website.

[2] We define down months as being those months where our all-companies portfolio experienced a loss.

Successful active management comes from two components; investment selection and portfolio construction. Very crudely, the former is about maximising long-term returns and the latter is about ensuring there are no surprises on the way. Effective diversification requires identifying feasible scenarios that could impact a portfolio and determining portfolio weights that make it as resilient as possible.

The minimum number of securities required to achieve adequate diversification is a recurring question among investors and academics. It depends on an investor’s risk tolerance, and the scenarios most relevant to the securities in the portfolio. But one scenario that all portfolios are exposed to is that of idiosyncratic shocks in individual securities. Concern for exposure to single-name events drives investors to prefer larger portfolios to smaller ones, however the relevant risk is not usually well quantified, and the distribution of weights is as important as the portfolio size.

To explore this, we develop a metric that quantifies the single-name risk of a portfolio by establishing its effective size. While several metrics exist that quantify portfolio concentration, they generally lack interpretability in terms of risk[1]. Our metric is based on the chance of experiencing losses from single-name shocks, thus it goes straight to the heart of the matter[2].

We review some well-known indices in the table below and find their effective sizes to be much smaller than the headline number of assets[3]. This is a result of weight being unevenly distributed and concentrated in a relatively small number of holdings. In these examples, the effective size is well approximated by 2 x the number of assets covering 50% of the portfolio, which drives home the fact that it is the size of the largest positions that determines the exposure to single-name risk and not the number of assets in the portfolio.

Index	Number of assets	Effective size	Largest weight	Sum (number) of weights > 5%	Number covering 50%	Gini coefficient
FTSE100	100	25	11.3%	24.7% (3)	11	0.59
NASDAQ	100	22	9.7%	36.9% (4)	9	0.61
S&P500	500	99	3.6%	0% (0)	50	0.60

Rather than working with simulations, heuristics often form the basis of practical approaches to managing diversification. One well established rule is the 5/10/40 restriction placed on most UCITS funds which says that no single weight can be greater than 10%, and weights greater than 5% must total less than 40%. This equates to a minimum effective size of ~15-18[4]. It is interesting to note that these rules are relaxed specifically for UCITS schemes that replicate indices, and the FTSE100 and the NASDAQ are frequently at odds with them[5]. Therefore, products that track these indices can, and do, take positions that are prohibited for an active manager.

We conclude that it is important to look past the number of assets in a portfolio in order to assess risk. Equity funds that contain ~25 stocks will generally be referred to as ‘concentrated’ by the industry, but as we have seen here these portfolios may have lower risk levels than those with a much larger number of assets. Working with metrics that meaningfully quantify the risk you are concerned with is key to effective risk management.

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[1] For example, the Gini coefficient compares portfolio weights to those of an equally-weighted portfolio of the same size. This does not help to understand the risk associated with portfolios of different sizes, as seen in the table.

[2] We simulate 10⁶ 10y futures in which each asset in a portfolio has a 1% chance of experiencing complete loss in a single year. We quantify exposure to large losses with a weighted-count of 10y losses >15%. Effective size is defined as the size of an equally weighted portfolio with the same exposure to large losses, using the same methodology. Using like-for-like analysis makes the effective size metric robust to the underlying assumptions of the simulations.

[3] Index weights are as of 31/12/18, 15/02/19, and 14/02/19 for FTSE100, NASDAQ and S&P500 respectively. Multiple share classes for the same issuing body are combined.

[4] The higher of these considers that it is not practical to maintain weights exactly at the boundaries of what is permissible.

[5] For example, the FTSE100 largest position is currently 11.3%. Further, as of 16/11/2018, the NASDAQ had 41.0% of its weight in just 4 positions with the largest at 11.9%.

Nearly one year on, Jake Moeller returns to Havelock London to chat once again to CEO Matthew Beddall about the company’s progress and recently-launched fund, LF Havelock Global Select.

Listen below, or visit https://tmsnrt.rs/2Un9llU.