Foresight Capital Partners

Last week, we detailed how a dividend investing strategy provides a generous “margin of safety”. Here we detail a worked example of ‘dividend investing’ using the example of an investment in BT Group I recently exited.

Dividend investing candidates within the FTSE 100, display some or all of the following characteristics:

1. Dividend yield is at least 150 per cent of the average.
2. PE ratio at least 20 per cent less, than the average.
3. Dividend payout ratio less than 50 per cent of earnings.
4. Investment grade debt, with cash growth on the balance sheet.
5. Stable dividends going forward, backed by a predictable and sustainable business.

By systematically sifting through the FTSE 100 using, the objective criteria (1-3), will provide a manageable list. The more subjective criteria of (4) will require further detailed study of the companies through their annual reports, announcements and investor presentations. Criteria 5 demands research into not only the company but also the business environment.

In spring 2005, such analysis identified BT Group with a PE under 10, and yielding 5 per cent. Though the headline growth figures where not inspiring from 2000 to 2005, the firm had undergone a transformation at the balance sheet, valuation and shop-floor level. In 2000, BT traded on a PE of over 40, had no dividend to speak of and had debts of £30 billion. By 2005, the debt had been reduced to £10 billion, the speculative growth stock valuation requiring many “ifs” to justify had be replaced with a utility like valuation, and the firm took the bold move to turn itself into a ‘platform business’.

In 2002, the firm re-organized itself around the belief that revenue from calls where going to zero and future growth would come from services (media, broadband, corporate data service) offered over its platform. Resulting in BT building its 21st Century Network platform.

Such developments though enhancing BT’s position where not reflected in its share price until they started to feed through to the bottom line. On 26 April 2006, when this feed through was imminent I purchasing BT at 220.62p (including costs/tax), under 10 times historical earnings and 9 times my estimate of future earnings.

This position went against the consensus with City firms Bear Stearns (14 Nov 05), and Goldman Sachs (13 July 05) both subsequently downgrading BT. As Ben Graham would say, “it is the quality of your analysis that makes you right as a stock picker, not whether the market happens to agree with you”. On 8 May 2007, I sold BT at a price of 318.75p, at which point the earnings had moved forward 20 per cent, paid 6 per cent in dividends and the rating had moved forward to 13 times earnings, provided a return over the year of over 50 per cent.

John McGuinness who holds the current TT lap record at an average speed of over 129mph, reported to the BBC. “On Bray Hill, you go from 0-180mph down a straight. On a normal road elsewhere, you would immediately go to jail or kill yourself. It looks ridiculously fast and mental and insane, 200mph on a road looks like absolute madness. But I leave a little bit, my safety buffer.”

Investing though certainly not implying any of the physical risks of the TT does by its very nature carry financial risk. Actively managing the downside risk against various return expectations is vital. Just as John McGuinness leaves a “safety buffer” when riding in the TT, in the words of Benjamin Graham the founder of value investing, an investor should build in a “margin of safety” when seeking investment opportunities.

A “margin of safety” in the context of value investing refers to the difference between the price a security can be purchased and its intrinsic value. Where the intrinsic value is a value assigned to a security in accordance with your analysis. Value based investors will use a variety of indicators such as the PE ratio, price-to-book, replacement value or dividend yield, in order to ascertain a securities intrinsic value. However, the application of these metrics is only a reliable approach if the metrics you base your model are at worst stable, where ideally the move in your direction.

Dividends offer such a metric and as a source of return are historically much more predictable than capital growth. Capital growth depends on the behavior of other market participants, but dividends depend solely on cash flow and company policy. Executives will generally lean on the side of caution when deciding on the dividend level to ensure that they can be reliably paid and reliably increased. The most likely reason for this is that any dividend cut generally results in senior management being relieved of their posts.

In the main dividends are reliable and consistently increased but even in the most difficult operating environments the exhibit exceptional defensive qualities. For example, in the 2000-2003 bear market when earnings collapsed, the FTSE All-Share index dropped around 50 per cent the aggregate dividend yield only dropped 7 per cent.

For these reasons, the valuation metric of dividend yield and the associated dividend investing strategy where one buys into stocks with a high and sustainable dividend yield is an approach offers a generous “margin of safety”.

Just as John McGuinness’s “safety buffer” does not prevent him from setting lap records, dividend investing with its “margin of safety” does not exclude the possibility of obtaining exceptional returns. Which leads us to next weeks column where I will detail a ‘dividend investment’ I have just exited which provided a return over the one year holding period of almost exactly 50 per cent.

John McGuinness quote originally appeared on the BBC News site at:

http://news.bbc.co.uk/1/hi/magazine/6670313.stm

Ben Graham’s principle of “margin of safety” is detail within his text ‘The Intelligent Investor’ originally published in the 1950s, and is still in print today. The full text of ‘The Intelligent Investor’ is available online at:

http://www.investinvalue.com/0/value.php#intelligentinvestor

The Wikipedia page:

http://en.wikipedia.org/wiki/Margin_of_safety_%28financial%29

also offers further explanation of the investment principle of “margin of safety” and its application.

Here we detail our Investment Process which roughly speaking consists of an ongoing investment research effort, with all known investment ideas working within a competitive flux for capital. The research process consists of the following three consecutive stages which form an investment complex:

Investment Research Process

• High Level Ideas: Select Top-down Investment Themes with a likely duration of ideally 2-5 years.
• Medium Level Research: Systematic research of all LSE listed assets which allow the expression of the ‘High Level’ Theme, and the selection of the assets (or basket of assets) which allow the most efficient expression of the ‘High Level’ Theme.
• Low Level Quantitative and Trading Techniques: Once the asset(s) have been selected suitable structures and trading approaches will be developed in order to gain exposure to the required assets.

Flux of Investment Complexes

The competitive flux for capital is created when there are more known investment complexes than sufficient capital to cover these complexes. By continuously under-taking fundamental research in order to select ‘High Level’ Investment ideas, construct asset(s) to represent these ideas and investigate the technical and trading aspects of entering such investments. At all times all such discovered investment complexes (invested and un-invested) are in a competitive flux and the fund will switch between investment complexes if and when a un-investment complex is deemed to provide a sufficiently strong argument over an invested complex.

We aim to be fully invested at all times.

Detailed description of the Investment Research Process

The investment process consists of the following three consecutive stages:

1) Generation of High Level Ideas: Macro, stylistic/sector specific or thematic Investment Ideas

The key driver of the out performance of the investment process is the identification of top-down, stylistic/sector specific or thematic investment ideas. The managers are seeking to identify investment ideas which will play themselves out within financial markets over a 2-5 year time frame. The mangers believe that through continuous systematic research and lateral thinking, they will be able to identify on average 2-4, such ‘High Level’ investment ideas per year. The managers also strongly support the view that it is not the number of such ideas which will determine the over-all performance of the fund but the quality of these ideas. For this reason the managers are highly selective in there acceptance of any such ‘High Level’ investment idea and numerous investment conjectures will be considered during any one year. Note that a ‘High Level’ investment idea will generally be formed from multiple underlying investment conjectures.

2) Medium Level Research: Value Oriented Fundamentally based, contrarian Research approach to select particular securities which efficiently express the ‘High Level’ investment ideas.

Once the ‘High level’ investment ideas have been identified by the managers, the managers will systematically undertake a search for securities which first allow these ideas to be expressed, and secondly offer the best risk/reward profile within the context of how the managers believe the high level idea will play out within financial markets. Though the fund managers would broadly agree and apply much of the traditional value investment methodology as detailed within the writings of Benjamin Graham and Warren Buffet, in particular the works:

• The Intelligent Investor, by Benjamin Graham.
• The Essays of Warren Buffett, edited by Lawrence A Cunningham, 2000.

The managers have developed a certain variant of this approach which is compatible with their own mental frameworks which they have applied within the various investment activities and markets in which they operate.

The managers have often found that the most efficient means in which to express a given ‘High Level’ investment ideas is by taking positions within under researched small cap (or even fledging) securities. The managers believe that the rationale for such findings is that these sectors are often the least covered by the research community, and in many cases are just to illiquid to be considered by institutional investors, and as a result the greatest inefficiencies often occur in such sectors. It is anticipated by the managers that investment companies and associated assets (many of which are fledging) will form a significant portion of the investment portfolio. Though such securities themselves are often small-cap the underlying securities which they hold are generally a well diversified collection of blue chip securities, and hence such investment companies do not pose a high level of risk to the investor. It should also be noted that due to the fact that over the past 10 years the managers have often found the greatest opportunities within this sector the managers have build up an expertise within the investment company and associated sectors.

Note: The investment process is not in any way either a small-cap or fund-of-funds approach. Any selection of either small-cap or investment company investments is taken purely because it is believed to be the most efficient means (i.e. best risk/reward profile) in which the express a given ‘High Level’ investment idea.

3) Low Level Techniques: Scalping/market making/technical trading, relative value quantitative techniques and the leveraging of the technology foundation of the fund managers.

This portion of the investment process will generally supplement and run in conjunction within the fundamental research (item 2 detailed above) which is undertaken. The portion of the investment process results from the particular technical skill set which the fund managers bring to the investment process. The technical skills can be divided into two sections: trading (scalping, MM strategies, TA), and quantitative/software. Below we provide further details:

• Trading: Overlay the application of short term trading techniques such as scalping, various market making strategies and acting as a provider of liquidity. In addition, analysis of market internals and trading considerations from a technical analysis stand-point will be considered. The aim of this process is to provide more opportune entry and exit points within our fundamentally selected investment opportunities. In should also be noted that these techniques may also be applied during the period when a given investment idea is being expressed within financial markets. Where we envisage taking a general stance with appropriate holdings over an extended period, however within this period we either switch between associated assets on a relative value or market internals motivated based, and/or scale in/out of the position in order to increase the risk adjusted return profile.
• Quantitative Techniques and Software Platform: Since 1999, we have undertaken firstly the research of quantitative finance, and secondly the development of financial and mathematical software components (see http://www.webcabcomponents.com). These components offer a wealth of financial and mathematical functionality which is leveraged within our internal research systems. In addition, we have developed a proprietary data archive and quantitative financial research platform. This system can apply a variety traditional and state-of-the-art statistical and quantitative finance techniques including regression and time series analysis; pricing and risk (Greeks/global VaR methodology) analysis (for virtually all equity and equity derivative contracts in accordance with a number of price/volatility/interest rate model assumptions).

Two Yale academics have formally justified what I expected all along. That is, on average real stock pickers who have high conviction (most likely concentrate) index independent portfolios who ideally have smaller sums under management, not only outperform the “cookie cutter” closet index trackers and the sector/theme rotator funds but also the index before and after expenses. The degree of this out performance after expenses is a highly significant 3%, and this out performance is persistent. In particular, the authors show that the funds with the highest Active Share (see below) continue to outperform there indexes (after expenses) by 2.29%-3.69%.

The key introduced notion (known as the Active Share) within the research is to view the level of active management by the level to which the managed portfolio weighting deviates for the underlying indexes stock weightings. Rather than the portfolio’s deviation in term of performance.

For further details, we refer the reader to the following web page of one of the authors:

http://www.som.yale.edu/Faculty/petajisto/research.html

where you will find the main article “How Active Is Your Fund Manager? A New Measure That Predicts Performance”, but also a number of other interesting related articles included some popular summaries of the research.

As I have mentioned a number of times I just feel the Hedge Fund product class offers the typical investor a rather bad deal. With the 2% annual and 20% of return, fee structure it is difficult to see the average investor doing better in hedge funds than putting his money into an index tracking fund. Saying this, if anyone out there has $1B USD (even $50M is OK) and wants to pay me 2/20 fee structure and all I have to do is out-perform the 9.55% YTD hedge fund index (see CS/T Hedge Fund Index) then I will be more than happy to oblige

Now following on from the work of Andrew Low at MIT on the ability of passive computer driven investment strategies to mimic hedge fund returns, Goldman Sachs has produce a product known as Goldman’s Absolute Return Tracker index (ART) which aims to do exactly this. The basic idea is that the computer is feed in the performance of all known hedge funds over the past month and through a variety of models of the trading strategies used works out and aggregate strategy weighting over the entire class. Then the following month it applies algorithms which mimic these strategies. Though the data is provided one month is arrears the tracking error does not seem to be unduly affected, or at least Goldman Sachs is prepared to take this risk on. This product has a fee structure of 1% per annual which means that the product is not only going to beat the hedge fund index but will do so with a product which is still open to new investors (unlike many of the most successful hedge funds) and one that scales in terms of assets under management.