Monthly Archives: August 2012

I will soon publish the initial composition of the first Obliquity Portfolio, but before that, here are the nine criteria I’m using to assess stocks. Each individual criterion is either a pass or fail, and a stock is considered for admission if it passes 7 (out of 9) or more.

The criteria aims at identifying “good companies” that are likely to be long term profitable, in order to build a diversified “index less crap” portfolios. The aim is to rebalance as little as possible — to “never sell” in a Warren Buffett kind of way.

The criteria are primarily qualitative, and to a large extent valuation-free: we’re trying to find good sustainable businesses; not, as such, cheap ones.

1) Useful business

A business passes if it produces a generally useful product, that people need or enjoy, and don’t need to be tricked to buy. For example a wine producer or a mattress manufacturer are good. A casino operator or a financial intermediary whose success relies on obfuscating their fees are not.

I include there soft ethical criteria, like excluding the makers of weaponry, and tobacco companies, as killing people generally destroys value; even merely stockpiling killing gadgets is a dead weight on the economy. I guess that it is a debatable point in pure investment terms, this could mean missing a missile manufacturing bubble, but then it’s not a bubble I particularly want to be part of.

At a company level, a particularly well run or keenly priced tank manufacturer could escape,  but given that there are thousands of investment options to choose from, random but limited restrictions on the investment universe shouldn’t hurt.

2) Long term

Basically here we’re trying to answer the question: is there a high chance that this business is still here in ten years time? I don’t want to have to trade all the time, and bankruptcies are bad for your returns.

3) Employees

This is based on the idea that people who enjoy themselves at work are more productive that those who don’t. For most people, including some who wouldn’t necessarily admit it, work is more than just a way to earn a living, it occupies a good chunk of one’s awake time, and forms part of who people are; so it is valuable for work to be rewarding for its own sake. Not all jobs are fun, but for any given task, companies can get in the way, or they can be helpful.

Assessing that for companies with thousands of employees is well nigh impossible. I’m attempting to guess from, on the one hand, management attitude, trying to read between the lines beyond the “our people are important to us” platitudes that are part of every annual report template, and on the other hand, whatever I can find on the web about employee testimonies, from company assessment sites like

4) Executives

Here we are trying to find out whether the executives are reasonably competent, and if not how easily they could destroy the company. Large companies are made of a lot of individual activities that essentially run themselves. Belgium recently ran without a government who could make strategic choices for almost two years, and so could most large conglomerates. Still, sufficiently bad strategy can destroy even businesses that could run themselves.

So the questions to answer are what leeway the executives have to destroy the business, and then do they appear to be sensible guys who care enough about the actual business, and are not outright crooks or simply dickheads. In their communication, they should talk about what the business does more than about accounting metrics or silliness about “shareholder value”.

5) Low volatility

Historically over the long term, a low volatility bias tends to return slightly more than the market, and markedly more in risk adjusted terms (slightly more returns over markedly less risk). This is known as the “low volatility anomaly”. The world hasn’t reached a consensus on an explanation, other than that it seems very widespread, across time, geography and asset classes. Like any anomaly that has been documented, it may not persist, but it seems a good bias to have anyway, and the risk it reverses to become a negative risk factor seems low.

As luck would have it, most of the other oblique criteria tend to imply low volatility. Still a highly leveraged or too fashionable company pops up on occasion.

This is assessed by looking at beta, volatility and particularly shaky charts.

6) Price action

The second and last criterion that uses price charts, through a quick glance at the chart (on long and short time scales) rather than any clever technical analysis, aims at capturing funny price action: a sudden drop, or spike, or a parabolic trend. The portfolio is for the long term and therefore excludes stocks which are currently hot, e.g. subject to takeover proceedings or rumours, or have just crashed, for whatever reason.

Short term small jumps, like a couple of percent, either way, after say an earnings announcement can be mostly ignored. This kind of noise disappears via time and diversification.

7) Balance sheet

While we’re not trying to do valuation, a few accounting checks can be useful. This is a cursory look at whether the balance sheet of the company seems reasonably solid: not too much debt, a sizeable amount of equity, no excess amount of “goodwill”.

The usual metrics like Price to Earnings are also looked at, but just to check they’re within reason. We’re trying to exclude basket cases, not to find fine grained value in the accounts. Basically we assume that most of the things that can be read in standardised accounting numbers, on a medium term horizon, are more often than not priced in by the market, given the many people who crunch and worship such numbers.

8) Free float

When someone owns the majority, or close to, the majority of the shares of a company, there’s no market for governance: if the controlling owner, through malice or incompetence, runs the company into the ground, and they won’t sell at any price, there’s nothing the market can do about it. When a company has sufficient free float, the price collapses and someone takes it over. This has grown into quite a competitive activity so that the odds that the entity taking a failing company over is better than existing management — and not mere asset strippers — are reasonable.

Besides, even if the company is well run and valued, someone may still wish to buy it, e.g. to combine it with their existing business, or for empire building, and usually have to pay a premium for this, and sometimes overpay, which is like a free call option for existing shareholders. This possibility does not exist in the same form when there’s a sticky controlling interest.

So a free float or 80% plus is usually desirable. The free float numbers published on financial websites are not always meaningfully reliable, so the regulatory disclosures are also checked.

9) Diversified

I don’t plan to buy hundreds of stocks just to get enough diversification, so the stocks selected need to be sufficiently diversified, both in what they’re doing — commensurate with the size and sector of the business — and geographically, e.g. have a scope similar to that of the portfolio, e.g. world presence for a world equity portfolio.

Most sizeable companies who are a leader in their domain do, and this is usually a refreshingly easy one to assess.

As part of the construction of the Obliquity portfolios, as previously introduced, I’ve had to come up with a way to weight selection criteria and the stocks themselves.

A binary choice

The selection criteria is composed of nine individual factors, which will be introduced in a later post, that are combined to make a pass or fail outcome for each company being considered for inclusion in the portfolio.

I’ve considered three possible scoring schemes:

  • Binary pass/fail
  • Ternary pass/fail/neutral
  • A “star” grading system from 1 to 5 (poor to good)

The star-like system seems to be popular in many contexts and appears to be a sweet spot in granularity to judge, and read about judgements, of qualitative criteria. It’s granular enough to express a variety of opinions, yet doesn’t fall into the excess precision of say a percentage scale. Most people could judge say a hotel on a scale of 1 to 5 but few could make a difference  between 52% and 53% good.

For the purpose of the Obliquity Portfolio, it though introduces the problem that for quite a few criteria, given the resources available to me, the judgement I make is really a vaguely, sometimes very vaguely, educated guess. There is often not enough information to make a 1-5 judgement, while there is often a sense whether the stock passes or not the criterion.

Ultimately, given the issue of trading costs and manageability, the portfolio cannot be the full universe of available stocks weighted according to an average score, so we may as well apply the fact that a stock is either in or out at the level of the individual criterion.

The ternary solution was mildly appealing, but in the end it seems simpler to opt for binary criteria. This wasn’t a strong decision and maybe I will change to a ternary version in the future. Having a middle option would help when the situation is not clear cut either way, or when no or not enough information is available. But then there’s the question that “middling” and “don’t know” are really different things. The finer grained the choices, the more the computation to aggregate the individual scores becomes complicated.

So, despite the imperfections, binary criteria it is. There is some scope for a small amount of cheating, or shall we say flexibility: when two criteria that are hard to decide overlap, it’s possible to consider them in aggregate which reintroduces a ternary choice (fail+fail, pass+fail, pass+pass) through the back door.

As for combining the criteria into the final choice, I use a threshold of seven: the stock must pass 7/9 of the selection criteria to be admitted. This is a practical choice: allowing only one fail would be too tight with too few stocks passing, and 5 passes definitely too weak, so it was 6 or 7, and in the end 7 seems, empirically, a better choice.

Weighting stocks and rebalancing

The weighting scheme for the portfolio is a hybrid of market cap and equal weights: the portfolio buys fixed size allocations, similar to equal weighted, but does not rebalance them so as to behave like a cap weighted portfolio as time passes. This minimises transactions and simplifies record keeping.

The rebalancing scheme is not an issue I need to fix in stone just yet — I don’t expect to have to sell anything any time soon — but the basic idea is that when a position becomes too big — perhaps when it doubles — damaging the diversification of the portfolio, it will be trimmed back to the corresponding lot size, as if it were a new position, if it still matches the selection criteria. The entire holding of a stock that convincingly stops matching the selection criteria will be sold.

In a similar vein, dividends and the proceeds of corporate action will be contributed to the free cash and and when there’s enough spare cash and the market is auspicious, used to buy new holdings that match the criteria. Total return performance contributions can be computed separately.

To account for the greater intrinsic diversification of large caps, I have settled for three sizes: 1 base unit for small cap or special situations with unusual risk, 2 base units for mid-caps and 3 base units for large caps. The allocation to each category is done qualitatively depending on how diversified and risky I think the company is, so say a large-ish but narrow company could end up in the mid-cap section. Although in general there are few surprises: size 2 is for companies that are usually classified as mid-caps and 3 large caps. I’ve not as yet selected any size 1 candidates.

Hilarious post at FT Alphaville: a bunch of market participants are outraged at today’s ECB meeting not announcing a blank cheque after Mario Draghi’s declaration last week that the ECB would do whatever it takes to save the Euro.

Super Mario picture from

Mario Draghi on his way out of an ECB board meeting (credit: Oscar Mota on Flickr)

The misunderstanding is simple: he didn’t say they would do whatever it takes within a week, and as the “markets”, or at least the short term traders or bloggers component of it, have a time horizon of about five days and can’t imagine that anyone could have a time horizon of a few months or years, there was inevitable disappointment. The Euro is not collapsing this week, and whatever it takes can be carefully done if and when it’s needed, and a hurried up bond buying programme was unlikely to be it.

Between people who don’t get the timeframe and people who don’t get European politics, the markets are becoming very pleasantly inefficient.