Financial Thinking

Mutual funds have an average MER of about 2.5% per year with no trading commission. For $100 / month, this comes to 2.5% of $1200 or $30 for the first year. You may have trouble finding a salesperson willing to work with you for so little (and will probably end up with a deferred sales charge).

ETFs have an MER of 0.2% – 0.5% or more, plus a trading commission. A discount brokerage, for a small account, will probably charge $25 per trade. For a $1200 investment over a year, the trading commission will be $25, plus an MER of 0.5% of $1200 or $6 for a total of $31.

Mutual funds and ETFs each have their place. Mutual funds come with advice (for whatever that’s worth to you) and they allow you to trade more frequently. If you require no advice and trade infrequently, ETFs are likely to cost you less.

Stocks have the advantage of having no MER at all. When you have a large enough account, the discount commission may be under $10. (In my case, I pay $6.88 per trade.) For a $500,000 portfolio, I can pay 363 trading commissions (363 x 6.88 = $2500) in a year before I pay the equivalent of a 0.5% MER. Even an extremely low MER of 0.2% is $1000 per year. For that much money, I can buy 145 different stocks (much like the diversity offered by an ETF, far more than the TSX 60) and after having owned them for a year, I am saving money compared to owning an ETF.

I have little patience for ETF evangelists. They tend to criticize the high MERs of mutual funds, but neglect to point out that individual stocks have no MER. They criticize owning individual stocks, but neglect to point out that it’s simple to have the same diversification, while cutting out the middle man, if your account is large enough. Just because you haven’t saved much yet, doesn’t mean that ETFs are best for everyone.

Here’s exactly how I do my comparative momentum calculation for my “asset rotation” portfolio. I’ll give a simple demonstration and then a comprehensive example. I’ve tried to base the calculation and assumption on research into what works in the market, mostly gleaned from CXOadvisory.com. Still, there’s a certain amount of data snooping that can’t be avoided. In plain English, that means the results could simply be a case of finding a pattern within random data points, and there’s no guarantee that it will continue to work.

Stock price movement is the result of human decisions, based partly in logic and partly in emotion. For that reason, I believe there’s a certain amount of our “herding” instinct that causes stocks to display characteristics of momentum. When stocks are going up, people want to invest, causing it to rise further. When stocks are falling, people want to sell, causing it to fall further. It’s difficult to pick the turning points, but the momentum seems to persist for a period of time (until it doesn’t).

There does tend to be some predictability around the timeframe for momentum. In periods under 12 months, momentum tends to persist. In periods of 2-5 years, performance tends to revert to the mean. That is to say, if a stock grew over the past 10 years, but fell out of favour, dropped in price and now looks cheap, chances are it will revert to its prior growth over the next 2-5 years. That’s the timeframe for value investors. On the other hand, it’s likely to keep falling for the coming few months, which is why momentum (or growth) investing tends to having higher turnover (number of trades).

Finally, capital is limited. A pension fund, an investment (mutual) fund or an individual investor only has so much money to work with. The manager (or individual) also has only so much time and attention to devote to investment decisions. For that reason, capital will tend to move between opportunities. If gold looks promising, an investment manager either has to raise funds or sell whatever else the fund holds in order to create cash to buy gold. When gold falls out of favour with the investment manager, it will be sold to buy something else (e.g. bonds or stocks). In the case of a balanced mutual fund, the weighting might be shifted gradually, reducing bonds to 30% and increasing stocks to 65%, before reducing bonds further to 25% and increasing stocks further to 70%. Those shifts of capital can be detected by fund flows (reported by IFIC), by volume information on the stock exchange or even by asset class performance (increased demand for stocks will push the price up).

Putting all of those ideas together, it’s possible to create a simple spreadsheet with past prices for stocks (XIU) and bonds (XBB). (In brackets are the index funds I chose; others might choose differently.) I also compare cash, in case stocks and bonds are falling simultaneously, which is rare.

Note: the cash “level” is calculated based on the high-yield savings account interest rate.

Working with these numbers, we can see that last week, stocks dropped from 16.55 to 16.26 (-1.75%), bonds rose from 31.48 to 31.82 (+1.08%) and cash rose slightly. If we look back further, 50 days (or 10 weeks) ago (to use the most popular moving average), stocks were at 17.94 and 200 days (or 40 weeks) ago (to use the other most popular moving average) stocks were at 17.14. Since they are lower today (-9.36% and -5.13% respectively), they obviously have negative momentum. Bonds, on the other hand, have positive momentum. 50 days ago, they were at 30.87 and 200 days ago they were at 31.15 (+3.08% and +2.15%).

In order to calculate the momentum for comparison, I find the average momentum over the period, overweighting the most recent data. In this example, for stocks, it would be (-9.36/10 weeks + -5.13/40 weeks) / 2 = average return per week of -0.532%. The same calculation for bonds results is (3.08/10 + 2.15/40) / 2 = 0.181%. Because the number for bonds is higher, I can say that bonds have more momentum and that stocks are unlikely to consistently grow in the coming few weeks.

In order to give some context to this particular example, bonds had greater momentum compared to stocks beginning January 4, 2008. Stocks came into favour April 18, 2008 until July 4, 2008. Bonds were (heavily) favoured until July 17, 2009 (except for 2 weeks from May 8 – May 22). As you can see, the model would have missed the top and bottom, but it would have saved investors a lot of loss and pain during the market crash of 2008. Not all signals are so clear, with momentum favouring bonds by less than 1% or 2% for a few weeks during the summer of 2010. The model turned negative of stocks again in June 2011, where it continues to suggest owning bonds.

For my more complex “asset rotation” model, I’ve modified the calculation slightly. I find the average return per month (not per week), and I average 1 month, 3 months, 6 months and 12 months. This heavily overweights the most recent performance, based on the herding characteristic I described earlier. The spreadsheet equation looks like this:

=((C2/C6-1)+(C2/C15-1)/3+(C2/C28-1)/6+(C2/C54-1)/12)/4

Over the past few months, I’ve been employing a momentum strategy to invest within my registered accounts. Outside of my registered accounts, I’m investing for income. I set up a model that I described previously, and so far it has worked extremely well. It doesn’t outperform the market each week, but it tends to help me get in front of the fast money, benefiting the rising prices caused by increased demand. My model included only ETFs traded on the TSX that represent bonds, gold, REITs, TSX 60 stocks, small cap stocks, and emerging market stocks. Being able to pick the asset class or sector most likely to outperform has translated into very good performance. For example, I owned gold from July to November of 2011. During that time, gold rose 15.4% and the TSX fell 13.5%. Since then, I’ve switched to real estate, then emerging markets, then back to real estate. Those further trades (up to June 1, 2012) earned me an additional 4.9%, whereas the market fell 4.2%. Although these results are extremely encouraging, I expect far more average performance, perhaps with increased volatility, during periods of rising stock markets.

Even though my strategy has been successful, I started to feel that it was somewhat restricted. It included gold, real estate, stocks and bonds as asset classes, and differentiated only between large cap, small cap and emerging market stocks. I felt there should be a place for the US market, the European market and certain other countries: Brazil, Japan and Hong Kong (as a proxy for China). Part of the source of that feeling came from reading economic news that showed Canada leading the pack out of the recession of early 2009, but then faltering in 2011. When our economy slowed and our market faltered in spring of last year, the US and, to a lesser extent, Hong Kong have outpaced the Canadian market. (Europe has done about the same, with Brazil performing far worse.)

For this reason, I added EWH, EWZ, SPY, IWM and XIN to my asset rotation model. The result was surprising. The model begins on May 24, 2002 (because that’s when enough data was available). Over the past 10 years, the stock market (represented by XIU) grew from $10,000 to $15,296 (as of May 25, 2012). The old model represented growth from $10,000 to a value of $46,366. The new model, by contrast, shows growth to $73,163. That makes sense to me, because with more assets to choose between, the model is able to select more profitable positions. The old model recommended 135 trades over the period, whereas the new model recommends 140 trades, which works out to around one switch each month. (Trading costs are ignored in the calculation; they can be significant in small accounts.) I notice that there are periods of uncertainty where the model switches every week over a period of 8-10 weeks, so I’d like to find a way to smooth the results and reduce trading frequency. I’ll share it if I find one.

These ideas are from Governance, Accountability and Sustainable Development, by Niel A. Shepherd. It’s like a textbook on governance. The main idea seems to be that governance, which has been practised for centuries, has worked, but must continue to evolve. The meaning of “good governance” hasn’t changed, but the context, the world around, is changing. There is a higher expectation than in the past decades, that governance be transparent, responsive and support sustainable development.

It is vital to identify the various stakeholder groups. In a corporation, this would include shareholders, employees, suppliers and partners and customers. In a government organization, it would include citizens, employees, government and partners and suppliers. It is necessary to determine what the needs of these stakeholder groups are, likely prioritizing them, and what their rights and protections are. A key issue is to what degree each stakeholder group will be involved in governance, in setting the principles and values of the organization and communicating its goals and objectives. The final piece is to decide how those responsible for execution will plan, perform and report on their accountability.

Normally, the board, in conjunction with shareholders and possibly the input of a client or advisory group, will determine the values and objectives of the organization. They will lay out the vision and mission, as well as setting medium to long-term goals and medium to short-term measurable objectives. They then pass the responsibility to management or the administration to set a strategy, put in place operational plans and take action.

In the economic view of a for-profit corporation, success has traditionally been measured by financial outcomes. That is shifting, as society expects companies to be more socially responsible and engaged in the communities where they exist. Even more than socially-minded corporations, government organizations need to find a way other than financially to guage their outcomes. A “balanced scorecard” might include categories such as: Financial View (traditional financials, process-based costing, balance sheets, income statements, earnings, etc.); Process View (process measures, quality, time, quantity, process capital, structural capital, innovation capital); Client/Customer View (known satisfiers, strength of relationship, partnership, customer capital); Human View (stability, capability, competencies, learning capacity, intellectual capital, innovation capital).

Good governance, in this view, can be summed up as deciding why the organization exists, who it is meant to serve and how it serves them, deciding which aspects of that mission are most important, finding management to put it into action and making sure that management is successful. Not a small task.