Look beyond the numbers.

I’d like to thank Mike for commenting on this post on ROE. By focusing on the actual calculations, Mike made me realise that I failed to explain the main idea behind the post. ROE is an excellent ratio, it’s one of the first financial ratios you should put in your tool-belt. The next step is to understand the three business levers that underpin ROE; profitability, asset turnover and leverage. The product of those levers is ROE, they are the three main tools management have to enhance the return to owners.

Watching management control those levers is a glimpse into the quality of management.

It’s best to analyse both through time and across similar companies. Take a look at Westfarmers’ ratios. Data from ApsectHuntley. Click Image to enlarge.

Were Westfarmers managing for ROE when they bought Coles? Comparatively, Woolworths have doubled their profit margin, improved their inventory turnover and reduced their leverage to keep their ROE in a healthy mid twenty and up band, over the same timeframe. Woolworths is currently managed better, and according to MyClime selling at a good margin of safety.

Until now we’ve been looking in the rear view mirror, it’s time to look forward to consider what is coming. Westfarmers have the opportunity to improve, unfortunately the current price seems to assume they’re going to. Can WES improve their net margins, or at least stop the slide. I’ll leave you considering the future.

In this article on the five financial ratios you need, the author picks five decent ratios, yet combined they don’t even allow you to construct the basic accounting equation of assets, liabilities and equity. They chose; gross profit margin, net profit margin, current ratio, inventory turnover, return on owner’s equity. By replacing ROE by financial leverage (Assets/Equity), you can easily calculate ROE and determine liabilities. Drop gross profit as well, you’ve already got COGS and Sales in the other metrics. It’s a good list, yet fails to consider the importance of cash flow.

If you want to learn more about financial analysis then I recommend Analysis for Financial Management by Robert Higgins. Amazon has 92 used copied from $0.01. 

Disclosure: No position in WES or WOW. Amazon link; I wonder what my cut of $0.01 would be?

Bill Miller from Legg Mason provides an excellent summary about investing in this video. His outlook is also interesting, even if it is a few months old.

Investing is about expectations. Look for companies where the expectations are too low. This is usually caused by pessimism, controversy, complexity or fear. This belief has been echoed over the ages and expressed in many ways by Ben Graham, Warren Buffett and other value investing luminaries. The idea is very simple, yet surprisingly hard for most investors to implement. Buy fear and sell greed!

The video is well worth seven minutes of your time.

BP is an excellent recent company specific example. Late 2008 early 2009 is a great macro example. Many people are currently arguing that Microsoft is a great example of expectations being too low. MSFT certainly is shrouded with pessimism and deserves a very close look at the least.

Telstra is a blue chip Australian company that almost fits the bill. With a current reasonably safe fully franked dividend of $0.28 and price of $2.65 TLS.AX is sitting on a yield to SMSFs of over 12%, that implies a lot of pessimism. I’m certainly a considerably more comfortable holding Telstra than any if the Australian banks. Telstra should do more than simply talk about floating Sensis, they should flog that cash cow, before it is fully milked and only fit for dog food.

DAVID Thodey has given his first indication that Telstra may be open to spinning off its directories business, Sensis.
The Telstra chief declined to rule out a possible sale of the subsidiary in an interview with BusinessDaily.

Disclosure: Long Telstra, considering Long position in MSFT

Discussion on Skewness

What is Skewness

Skewness is a measure of the asymmetry of probability distributions. Negative skew or left skew has fewer low values and a longer left tail, while positive skew has fewer right values and a longer right tail.

Image 1: Skewed Distributions.
Image source http://en.wikipedia.org/wiki/File:Skewness_Statistics.svg reprinted here under creative commons attribution CC-BY-SA-3.0

Why skewness in returns is important in asset pricing

Modern finance is heavily based on the unrealistic assumption of normal distribution. This discussion aims to highlight the importance of skewness in asset pricing. The primary reason skew is important is that analysis based on normal distributions incorrectly estimates expected returns and risk.

Harvey (2000) and Bekaert and Harvey (2002) respectively found that skewness is an important factor of risk in both developed and emerging markets. Harvey (2000) concluded “Risk measures implied by asset pricing theory, in particular world beta and coskewness work reasonably well in capturing the cross-section of average returns in world markets.”

Nassim Nicholas Taleb in Fooled by Randomness provides an excellent example of the importance of skewness.

In an analyst meeting Taleb predicted the market had a 70% of going up the following week. Fellow employees were confused as Taleb had a very large short position on SP500 futures and was betting the market would go down. To which Taleb replied, “my opinion was that the market was more likely to go up…, but that it was preferable to short it…, because, in the event of its going down, it could go down a lot.” Taleb (2007 p101).

Knowing that the market has a 70% probability of going up and a 30% probability of going down may appear helpful if you rely on normal distributions. However, if you were told that if the market goes up, it will go up 2% and if it goes down, it will go down 10%, then you could see the skewed returns and make a better informed decision.

E(r) = 0.7*0.02 + 0.3*-0.1 = -0.014

Investors must look beyond simple probabilities, mean and standard deviation and think in terms of uncertainty, expectation and magnitude of the outcome. Taleb (2007 p103) states “rare events are not fairly valued, and that the rarer the event, the more undervalued it will be in price”.

Research on Skewness

There is a large body of literature on skewness across various markets and asset classes. Evidence of skewness in assets has existed for more than three decades (Beedles, 1979; Alles and Kling, 1994; Chen, Hong and Stein, 1999) to name a few. More recently, Harvey and Siddique (2000) suggested that investors require payment for negative skew and expected return increases with negative skewness. Their results showed skewness exists in asset prices and that a pricing model incorporating skewness helps explain expected returns in assets beyond beta, size and book to market. They concluded, “systematic skewness is economically important and commands a risk premium, on average, of 3.60 percent per year.” As mentioned above Harvey (2000) found that the majority of developed markets have negative skew.

Damodaran (1985) was the first to highlight that negative skewness can result from the distribution of good and bad news from companies. Companies’ release more good news than bad news and bad news tends to be released in clumps.

Hong and Stein (1999) proposed another reason for skewness. Analysing the implications of short sale constraints they developed the following intuition. As the price of a share falls more information is unveiled; specifically the price at which market participants with differing valuations see value. Their differing views were not previously available to the market due to short sale constraints. This led to Chen, Hong and Stein (1999), to test whether shares which investors disagree more about as shown by increases in turnover, have higher skewness. Montier (2002)

Chen, Hong and Stein (1999) documented three major conclusions in their study into conditional skewness in stock prices.

In the cross-section, negative skewness is greater in stocks that: 1) have experienced an increase in trading volume relative to trend over the prior six months; 2) have had positive returns over the prior thirty-six months; and 3) are larger in terms of market capitalization.

Behavioural Finance Explanations of Skewness

While the existence of skewness is well documented the reasons for the skewness are less certain. Alles (2004) using simulated data concluded a combination of Alles and Kling (1994) hypothesis derived from Kahneman and Tversky’s (1979) prospect theory in conjunction with Brown, Harlow, and Tinic’s (1988) “uncertain information hypothesis” (UIH)  can explain negative skewness. Importantly their finding also showed a simple version of the geometric random walk model could not generate negative skewness.

Alles also provided two explanations for the tendency of skewness to be less negative than normal during market downturns and more negative during upturns, as observed by Alles and Kling (1994). As per prospect theory, investors’ perspectives are subjectively based on their reference point. They become less risk lovers when losing and risk averse when winning. According to UIH investors categorise uncertain news as either good or bad. It can be assumed investors’ categorisation is subjective based on their reference point. So in bad times, bad news is viewed less negatively while positive news is viewed skeptically.

Investors’ preference for positive skewness and aversion to negative skewness

Financial theory says that rational investors should prefer positive skew; however, evidence exists showing that investors also prefer negative skew.

The longshot bias illustrated by the popularity of lotteries, gaming machines and researched in horse racing is used to show investors’ preference for positive skew. Hodges, Tompkins and Ziemba (working paper), show that the longshot bias does exist in some options markets, but I have found no evidence that a broad cross-section of investors ‘suffer’ from this bias. The bias may be no more than the behaviour of risk lovers.

Harvey and Siddique (2000) found negative skew receives higher returns. They assumed that investors require payment for negative skew; however they did not prove that investors both correctly assessed and required payment for that skew. The excess returns could be market inefficiency at pricing improbable events.

There is evidence that highlights the inability of individuals to correctly assess probabilities. As Taleb (2004) points out “agents underestimate the extreme values of a distribution in a surprising manner; violations are far more excessive than one would expect: events that are estimated to occur less than 2% of the time will take place up to 49%.”

Behavioural finance suggests investors have a preference for numerous small wins and a single large loss over numerous small losses and a large win. A negatively skewed distribution provides the necessary environment for many small wins, as the majority of incidences are to the right. The reasons for this can be explained by prospect theory, which hypothesises that investors receive decreasing reward for further gains.

Lakonishok, Lee, Pearson and Poteshman (2007) noted covered call writing is the most popular option strategy. Covered calls entail capping upside returns while taking on downside risk, a negatively skewed strategy. Shefrin and Statman (1993) and Hoffman and Fisher (2010), found framing and risk aversion can explain investors’ predilection for covered writes.

Kahneman and Tversky’s (1984) suggested one way to reconcile a co-preference for negative and positive skew. They argued that “black swans” are neglected whereas longshots are overweighted. I suggest risk lovers overweight the longshots while the majority of investors prefer negative skew, i.e. a preponderance of small wins while neglecting the risk of the skewed distribution.

Asset pricing factors such as firm size and book-to-market ratio may be acting as a proxy for skewness

Harvey and Siddique (2000) recognised that book to market (HML) and size (SMB) effects may act as a proxy for skewness in asset returns. They found partial evidence for that when adding skewness alone or in conjunction with HML and SMB to industry portfolios produced similar results. Ajili (2004) in a study on the French Stock Market found “co-skewness and co-kurtosis don’t subsume the SMB and HML factors.”

Chung, Johnson and Schill (2004) found “it is conceivable that the SMB and HML loadings are such good proxies for the higher-order co-moments that, given problems of estimating higher-order co-moments, the Fama-French factors could be superior in actual use.”

Distinction between skewness in returns and co-skewness in returns

Skewness refers to the distribution of returns of a single asset while co-skewness compares the returns of the asset to the market, i.e. is the asset’s returns more (positively) or less (negatively) skewed than the market’s returns. Finance theory suggests investors generally prefer both positive skewness and positive co-skewness.

Conclusion

Skewness exists in most financial markets and is an important measure of risk most likely not subsumed by HML or SMB. It is still unclear why skewness exists though several compelling arguments have been made; including, good/bad news asymmetry, price discovery, prospect theory and uncertainty of information. Negative skew had been shown to receive higher expected returns. It is generally believed that investors have a preference for positive skew, though evidence supporting a predilection for negative skew also exists.

References

• Ajili, Souad, Size and Book to Market Effects vs. Co-skewness and Co-kurtosis in Explaining Stock Returns (December 2004). Available at SSRN: http://ssrn.com/abstract=634684
• Alles, L,. “Time-Varying Skewness in Stock Returns: An Information-Based Explanation,” Quarterly Journal of Business and Economics, Thursday, January 1 2004, http://www.allbusiness.com/public-administration/administration-economic-programs/941260-1.html, Accessed 16 July 2010
• Alles, L., and J. Kling, “Regularities in the Variation of Skewness in Stock Index Returns,” Journal of Financial Research (Fall 1994), pp. 427-438.
• Beedles, W.L., “Return, Dispersion and Skewness: Synthesis and Investment Strategy,” Journal of Financial Research (Spring 1979), pp. 71-80
• Bekaert, Geert and Harvey, Campbell R., Research in Emerging Markets Finance: Looking to the Future (September 11, 2002). Available at SSRN: http://ssrn.com/abstract=795364
• Brown, K., W. Harlow, and S. Tinic, “Risk Aversion, Uncertain Information and Market Efficiency,” Journal of Financial Economics ( 1988), pp.355-385.
• Chen, Joseph S., Hong, Harrison G. and Stein, Jeremy C., Forecasting Crashes: Trading Volume, Past Returns and Conditional Skewness in Stock Prices (December 1999). Available at SSRN: http://ssrn.com/abstract=194948 or doi:10.2139/ssrn.194948
• Chung, Y. Peter Peter, Johnson, Herb E. and Schill, Michael J., Asset Pricing When Returns Are Nonnormal: Fama-French Factors vs. Higher-Order Systematic Co-Moments. Journal of Business, Forthcoming. Available at SSRN: http://ssrn.com/abstract=503122
• Damodaran, A., “Economic Events, Information Structure, and the Return-Generating Process,” Journal of Financial and Quantitative Analysis (December 1985), pp. 423-434.
• Harvey, Campbell R., The Drivers of Expected Returns in International Markets (July 25, 2000). Available at SSRN: http://ssrn.com/abstract=795385
• Harvey, C. and A. Siddique, (2000), ‘Conditional Skewness in Asset Pricing Tests’, Journal of Finance, Vol. 55, No. 3, June, pp. 1263 –1296.
• Hodges, Stewart D., Tompkins, Robert George and Ziemba, William T., The Favorite/Long-Shot Bias in S&P 500 and Ftse 100 Index Futures Options: The Return to Bets and the Cost of Insurance. EFA 2003 Annual Conference Paper No. 135; Sauder School of Business Working Paper. Available at SSRN: http://ssrn.com/abstract=424421 or doi:10.2139/ssrn.424421
• Hoffmann, A. O. I. and Fischer, Tobi , Behavioral Aspects of Covered Call Writing: An Empirical Investigation (May 25, 2010). Available at SSRN: http://ssrn.com/abstract=1615405
• Kahneman, D., and A. Tversky, “Prospect Theory: An Analysis of Decision Under Risk,” Econometrica, 47 (1979), pp.263-291.
• Kahneman, D., and A. Tversky,   “Choices,Values and Frames,” American Psychologist (1994), 39:4, p341-50 Accessed via http://www.poldracklab.org/teaching/neuroeconomics/kahneman-tversky_1984.pdf 14 July 2010
• Lakonishok, J., Lee,  I. Pearson, N. D. & Poteshman, A. M. (2007). Option Market Activity.
• The Review of Financial Studies, Vol. 20, No. 3, 813-857.
• Shefrin,  H.  &  Statman,  M.  (1993). “Behavioral  Aspects  of  the  Design  and  Marketing  of Financial Products. Financial Management”, Vol. 22, Issue 2 (Summer), 123-134.
• Statman, Mier, “How Many Stocks Make a Diversified Portfolio”, Journal of Financial and Quantitative Analysis, Vol.22 No.3 1987
• Taleb, Nassim N., ( 2007),”Fooled by randomness : the hidden role of chance in life and in the markets,” 2nd ed, Penguin Books

M2 Telecommunications (MTU.AX) delivered strong results across their businesses in 2009-2010. With underlying EPS up 72% to 16.7cents on the back of the People Telecom acquisition and organic growth. 2011 forecasts were strong with underlying EPS targeted in the 20.7-22c range.

With the current price of $1.80 you’re buying earnings growth of 28% for a P/E multiple of 8.4, which is an appropriate multiple for a no-growth company. In others words, current buyers are getting all M2′s growth for free. Alternatively the market believes M2 is not going to grow in the future despite their excellent management, strong history of growth and strong position in the changing telecommunications market. I think the market is wrong, YMMV.

The final dividend is 5c bringing the combined 2010 dividend to 10c, an 82% rise on 2009. That represents a fully franked yield of 5.6%. As M2 has a stated 70% payout ratio the forward dividend yield is 8.3%, based on their eps and payout guidance.

A Quick Look Behind the Numbers

Return on equity is increasing pushed by many financial commentators as “the number”. I don’t believe any single number adequately captures a companies value.  Even a justifiably good albeit problematic number like ROE is better viewed as the sum/product of its parts. While most of my readers probably know the constituents of ROE, I’ll go through it with M2′s numbers so everyone can get some benefit.

ROE is easily calculated by dividing profit by average equity, hence return on equity. However, that is not what I mean by constituent parts. ROE is more meaningfully viewed as the product of  profit margin times asset turnover time financial leverage. The first two items, profit margin and asset turnover give you return on assets (ROA).

Let’s run through the key numbers you need for M2, in thousands.

From those four figure we can calculate

The product of those constituent parts give an ROA of 10% and ROE of 21%. Once you’ve got those ratios you can look for trends over time and use them for comparison to similar companies. That’s when the numbers actually become useful. In M2′s case the profit margin and asset turnover increased while financial leverage decreased (2009 figures respectively 3.64%, 1.43 and 2.92 giving an ROA of 5% and ROE of 15%). From that we can hazard a guess that management are improving the business while simultaneously reducing the risk, which is what I like to see.

Interest coverage, current ratio and the acid test are three liquidity ratios worth keeping an eye on.

To calculate those we need a few more numbers

• EBIT 26,411
• Interest 2,244
• Current Assets 78,466
• Current Liabilities 66,473
• Inventory 338

To give us

• Interest coverage: EBIT/Interest is 11.8, which means M2 earns over 11 times the amount they need to cover interest.
• Current ratio: Current assets/current liabilities is 1.18, which means M2′s assets which should convert to cash within the next year can cover their liabilities due within the next year.
• Quick ratio:  (Current assets – liabilities)/current liabilities is not really required for a company like M2 with low inventories, as it is almost the same as the current ratio. The quick ratio is generally more useful for companies that sell stuff, as that stuff (inventory) is less further away from being converted to cash and in the event of distress is likely to be heavily reduced.

Click to Enlarge

Related Documents

• M2 2010 Investor Presentation
• M2 2010 Earnings Press Release
• M2 2010 Annual Report
• Vaughn Bowen discusses 2010 results on BRR

Disclosure: Long MTU

Theoretically, discounted cash flow (DCF) is the correct way of valuing an asset. However, as Yogi Berra noted, “In theory there is no difference between theory and practice. In practice there is.” The implementation of a DCF is riddled with problems. First off, we can’t forecast, which kind of puts the kibosh on the whole exercise. Even if we choose to ignore this inconvenient truth, problems with the discount rate still make a mockery of the whole idea of DCF. No wonder DCF has such a poor reputation. The good news is that several alternatives exist. We explore three that avoid forecasting altogether! via Simoleonsense PDF that is worth reading and re-reading.

One day I’ll post my reverse DCF spreadsheet. For those who haven’t read any of Montier’s books or musing I recommend you add his blog to your list and do a web search for more of his articles.

Montier now works at GMO, so the one link gets you Grantham and Montier. I’d pay to work with the GMO team!

No related posts.

This post on biggest investors mistakes by the usually brilliant Jeff Miller at A Dash of Insight pushed my buttons. Jeff normally takes great care with his assertions and goes to great lengths to back them up with credible evidence, but in this case he leads off with an apples to oranges example.

Many studies have shown that individual investors, managing their own accounts, do about 5% worse than they would if simply buying an index fund.  The top investment managers have regularly beaten the averages, so it is a big spread.

I commented

You’re comparing average investors with top managers. While I know that was merely an introduction and not central to your point, I found it incongruent from a guy who normally takes such care with his assertions. On top of which there is plenty of evidence to show that agency costs are a permanent feature of fund managers and as Patrick said that the average manager under-performs.

The average investor contains all investors. Do you know of any evidence that analyses experienced investors, say 10 years plus experience and accounts over say $300k, or any other figures?

Another commenter replied,

“CXO Advisory in March cited an SSRN paper that showed Chinese investors with large accounts (presumably more experienced) had higher returns than those with small accounts. The difference was quite significant, and apparently due to reasons that might be expected – buying value stocks and trading less frequently. They also have links to additional studies.”

I decided it was time to pull together some of the literature on individual investors.

Can Individual Investors Beat the Market?

We document strong persistence in the performance of trades of individual investors. The correlation of the risk-adjusted performance of an individual across sample periods is about 10 percent. Investors classified in the top performance decile in the first half of our sample subsequently outperform those in the bottom decile by about 8 percent per year. Strategies long in firms purchased by previously successful investors and short in firms purchased by previously unsuccessful investors earn abnormal returns of 5 basis points per day. These returns are not confined to small stocks nor to stocks in which the investors are likely to have inside information. Our results suggest that skillful individual investors exploit market inefficiencies to earn abnormal profits, above and beyond any profits available from well-known strategies based upon size, value, or momentum. read more

Wow! Not a bad starter, but let’s keep digging. If you know of any research highlighting how individual investors can outperform then please leave a comment.

In general individual investors tilt the scales in their favour by looking to exploit the excess returns offered by small caps, value stocks and momentum stocks. There is plethora of research on all three.

Momentum

Research into momentum in stocks shows stocks do exhibit positive momentum over 3 – 12 months. While over the longer term of multiple years a negative correlation is found, i.e. momentum stocks eventually fall back to the pack.

• Momentum studies like this, Momentum Strategies by Louis Chan, Narasimhan Jegadeesh and Josef Lakonishok, reveal how past earnings surprises predict large drifts in future returns as analysts and the market are slow to respond.
• Momentum Profits, Non-Normality Risks and the Business Cycle by Ana-Maria Fuertes, Joelle Miffre and Wooi Hou Tan. This paper show that momentum profits are not normally distributed and, relatedly, that the momentum profitability is partly a compensation for systematic negative skewness risk in line with market efficiency.
• For more on momentum.

I’ll post on value vs growth and small vs large caps in separate posts, but for anyone unfamiliar with the large body of evidence the basic story is both value and small caps have in the past outperformed growth and large caps by significant margins. I do mean to imply that all investors should manage their own investors. I actually believe the contrary, most investors should invest in index funds with long term perspectives, investing more when markets are historically undervalued and less when they are overvalued. Alternatively they should seek out small cap value focused fund managers with a record of outperformance. As with everything there are exceptions. Self directed investing takes a lot of time and skill and is an art that few truly master.

Advantages of Individual Investors over Institutions

The following is a quick incomplete list, primarily to get some thoughts down for further investigation.

• Jack be nimble jack be quick. Individual investors can react faster to opportunities and change their asset allocation much faster than institutions.
• Patience. Institutional imperatives force most funds into high turnover strategies. Individual investors can wait for fat pitches.
• Small caps outperform. Large institutions can’t take meaningful positions in small caps. Even small institutions find it hard to take meaningful positions in small caps without pushing the price up on entry and down on exit.
• Management costs. With active fund managers charging between 1-2.5% and sometime with an added 20% of excess returns, individual investors are given a head start.
• Agency costs.  On top of fees are agency costs. Institutions’ primary aim is to make themselves money, while they’d like to make their investors money too, conflicts can and do arise.
• Flexible guidelines. Most funds are constrained by their strategies, which for the most part are designed to fit in with particular themes, e.g. large cap growth. Plus many are mandated to be 100% invested all the time. Talk about a handicap. Individual investors can invest in the best opportunities regardless of style, market cap or any other arbitrary restriction and they can move to cash when markets are overvalued.
• Comparison.  Most funds ‘need’ to follow relative return investing styles. The smartest investors all say absolute returns should be focused on, with relative returns a mere point of interest. Individual investors can focus on their absolute returns without fear of being fired for underperforming.

In fairness, institutions have many advantages over individual investors, but as they also have large marketing departments I’m sure you;ve already heard their side of the story. Finally I in no way mean to slate Jeff Miller and encourage readers to add his blog, A Dash of Insight, to their regular reading list.

There’s an interesting thread on TMF, which discusses the following thought by Random Roger.

Using moderate weightings mitigates the consequence for conversations you cannot hear. As portfolio management is a series of correct and incorrect decisions, I have said many times putting 3% into a stock that ends up going to zero is not a portfolio deathblow it is merely a bad day. I believe the worst performer I’ve ever put into client accounts was Macquarie Infrastructure (MIC). For most clients who owned it it was targeted at a 2% weight. I under estimated the impact of it being so transaction oriented and thus reliant on capital markets to function. Despite it being (probably) the worst holding ever I have no recollection of a client even asking about it.

Whether you manage your own portfolio or manage money for others there is no avoiding bad holdings–from time to time you will be wrong. Being wrong is not the thing, the thing is the consequence for being wrong. A 2-3% holding blowing up is not a big deal but at some point a holding becomes large enough that it is a big deal.

To pick but one of the good comments so far in the thread.

What I’ve gotten in the HORRIBLE habit of doing before this year (I’m fixing things) is putting small wages in companies where you KNOW the business well and know that the valuation is cheap and the business is not hard to grasp. In those cases, using allocations like 1.5% or 2.5% is not only illogical it is plain old stupid. …when you have a truly great and OBVIOUS idea, you load up, and you don’t worry about penny differences or anchoring to the lowest price. The key is betting on the obvious ideas. …

For me obvious idea is 1) strong cash-heavy balance sheet, 2) big free cash flow, 3) easy business to instantly grasp, in 4) an area where you’ve had success, with 5) a clear change in business momentum, and 6) a valuation that takes 15 seconds to get happy about. PETS is the sorta stock that fits this definition except perhaps the last – on that one, you just wait for the valuation to get to the point where you want it, as analyzing the business takes about 30 minutes tops after the initial evaluation.

via TMF: Position sizing blurb / Deranged Monkey Criticism.

The thread also has some good insights on the airline industry.

I’m not a Buffett clone, I’m not even the wart on a Buffett’s clone arse, but I recognise he has said many great things. Filtered through other stuff I end up with:
Concentrate to accumulate. To concentrate use the 20 punch card concept and only swing at pitches you’re really comfortable with.

If you’re going for 3% positions then you’re doing the reverse. You’re diversifying to preserve capital. Perhaps that is the role of a portfolio manager, I certainly concede it is the role of a portfolio manager (PM) who wants to keep their job as not many people get fired by being closet index tackers.

As I’ve said before I swapped from my concentrated ways to a diversified approach and frankly, for me it sucks. It takes all the fun out of investing. It makes beating the indexes harder. It leaves me feeling inadequate as I can’t properly cover all my companies. It means a home-run stock doesn’t deliver index smashing returns by itself. So I’m slowly swapping back to my concentrated ways.

If you’re looking at the market everyday it hard not to take a few swings. So I limit those swings to small positions, let’s say 3%. When occasionally I see an opportunity that I find irresistible then I load up with at least 10%.  Some positions fall in between as I plan on going higher, but I still suffer from anchoring and hate chasing prices higher. I’ll work on that over the coming years.

Some numbers, nah let’s do it with a picture instead.

Does the graph make it clear?
Taking 3% bets on your best ideas gets you no where, whereas blowups on a 10% position don’t hit your portfolio much more than if it was a 3% position.

It all comes back to you concentrate to accumulate and diversify to preserve, that’s worth reiterating. May I boldly suggest many PMs are focused on preservation and I’m not talking about Buffett’s rule number one. If you layer on some Buffett then what the hell are you doing accumulating 3% positions anyway, you’d fill your lifetime punch card of 20 up in seven months. Let’s imagine turnover of .3, then you still gotta come up with 10 great ideas a year. Who can do that?

When you look at the market every day it’s hard not to swing at more pitches than you should. That’s what 1-3% positions are for. Though as soon as you start to think it’s only worth 1-3% maybe you shouldn’t bother swinging.

Personality and patience makes a good investor. Knowing your personality and matching an investment strategy to it and then exhibiting patience to follow your strategy.

I concede large portfolios may necessitate more positions as may certain investment strategies. I further concede I’ve never managed OPM and if I ever do then perhaps I’ll be wracked with more doubt than usual and so settle on 3% positions. Finally I may be totally wrong and if so I’d love to know why before I complete my return trip from diversified back to concentrated.

If you haven’t already I encourage you to read the whole thread linked above, there are lots of great thoughts on position sizing by smart people.

Further reading: If you enjoyed this or what to read more on position sizing then check out:

• Kelly Formula Meet Portfolio Management
• How to Size Individual Positions Using Kellyesk Formula