Tuesday, February 28, 2012

Would You Bet Your Retirement on a Repeat Performance?

Canadian investors have done well by staying close to home over the past 16 years. How much are you willing to bet that Canada will top the charts again over the coming decade?

Asset Class Returns in Canadian Dollars, 1995 - 2011
 Click image for ginormous version.

If your investments are Canada-centric, you're betting your retirement on an unlikely repeat performance...

By the way, Canadian bonds beat Canadian stocks, and U.S. Treasury bonds beat U.S. stocks over the period. Would you bet on that repeat performance?

Fortunately, you've got options.

Friday, February 24, 2012

ECRI's Indicators Confirm Recession 'In Short Order'

While we deride forecasting for the purpose of investing, we understand that many people are curious about the state and trajectory of the economy for other important reasons. Among the cacophony of bullish exuberance it is difficult to distinguish signal from noise, so in an effort to confound over-optimism with facts, we would point you in the direction of the Economic Cycle Research Institute. As forecasting goes, ECRI is the exception that proves the rule.


The Economic Cycle Research Institute is alone in its perfect record of forecasting recessions. The Economist magazine noted in 2005, “ECRI is perhaps the only organisation to give advance warning of each of the past three recessions; just as impressive, it has never issued a false alarm.” Since then they also successfully signaled the 2008 recession in advance, and perfectly timed the recovery.


From ECRI's website:
Most forecasters use models that reduce a complex economy to a rigid set of largely backward-looking relationships. Simply put, they try to predict the near future based on what has happened in the recent past. This can work for a while – until the critical moment when a turning point approaches, and such models reliably fail. This is because extrapolating from the recent past is a sure-fire recipe for being surprised by the next turn.
ECRI's cofounder, Geoffrey H. Moore created the standard suite of economic indices in 1950. These indices are still the standard indices issued monthly by the Bureau of Labour Statistics (BLS) in the United States. However, Moore abandoned the linear framework embraced by the BLS when he realized that these indices inevitably failed to identify the critical turns in economic activity.


ECRI's current framework monitors more than a dozen proprietary leading indices of inflation, home prices, foreign trade, manufacturing, services, and sector-specific activity. More from their website:


Source: ECRI
The durable sequences linking the indicators we monitor allow us to make sense of the consistent patterns at cyclical turning points. They let us objectively sort through data about the economy, while filtering out the “noise.” Unlike econometric models, ECRI's indexes are not based on data-fitting, and do not need to be tweaked or adjusted to account for new data or events.
This all sounds very fancy and technical, but what matters most is that they are among the very few who consistently get it right at the turns.


Lakshman Acuthan, ECRI's current Chief Operations Officer and public spokesman, re-iterated his recession call on CNBC yesterday, with strong conviction. Some take-aways:


  1. Since September when they first sounded the recession alarm, all important economic data points have been getting worse, despite consensus optimism.
  2. GDP, consumption, personal incomes, corporate sales, and manufacturing data have all deteriorated, and when combined to form the Coincident Index, are at 21 month lows.
  3. Over the past 50 years, every time the Coincident Index has declined to this extend, a recession has followed in short order.
  4. The consensus forecast is optimistic, and people are feeling better, because of the unprecedented and coordinated efforts of global central banks, which have printed mountains of money.
    • Similar to 2007 / 2008 where the recession began in December 2007 while oil went to $147 a barrel in June 2008 because central bank largesse was not being consumed for the purpose of commerce, but liquidity had to flow somewhere, so it went into commodities and emerging market stocks.
  5. The jobs picture has improved a little, but this is a lagging indicator. In fact, the jobs picture usually improves right into the jaws of a recession as we saw in 2001 and again in 2008.
  6. All of the leading indicators continue to confirm their recession call, which should materialize by mid-2012. It usually takes consensus economists about 6 months to realize they are in a recession, but stocks generally get it right sooner.


We would strongly encourage you to watch the full video below.




Links to other websites or references to products, services or publications other than those of Macquarie Private Wealth Inc. (MPW) on this website do not imply the endorsement or approval of such websites’ products, services or publications by MPW. MPW makes no representations or warranties with respect to, and is not responsible or liable for, these websites’ products, services or publications.

Wednesday, February 22, 2012

Volatility Harvesting and the Importance Of Rebalancing



We have now written about the importance of observing historical volatility when making rebalancing decisions (see here, here and here) and the importance of keeping portfolio volatility low (see here).  This post will discuss the benefits inherent in volatility itself through the concept of “harvesting” the volatility of individual positions within a portfolio.


We can simplify the idea of volatility harvesting through a thought-experiment developed in the 1940s by Claude Shannon, renowned genius and investor, averaging 28% annually in his lifetime! (Source: W. Poundstone, (2005) Fortune’s Formula). His experiment, known as Shannon’s Demon, showed how it was possible to profit even from markets that were characteristic of a random walk, as long as they were volatile.

The experiment is simple: Imagine a stock that is highly jittery and either doubled or halved in value every day. You then invest half of your portfolio in the stock, while the rest remains in cash. At noon each day you rebalance the portfolio back to a 50-50 even split. So, if you started with $1,000 and the stock got cut in half, the following day your portfolio would be $750 ($250 in the stock $500 in cash). After rebalancing, the portfolio would have $375 in stock and $375 in cash. As the chart below shows that after rebalancing only 72 times our $1,000 initial investment is now worth just under $100,000! That is not a bad chunk of change given that we didn’t have to do any stock forecasting to make this profit! In fact, had you bought and held this stock you would make zero profit.

 Source: Butler|Philbrick|Gordillo and Associates*
    
How can this be? Well, the key is to understand that as long as there’s volatility in at least one of your holdings you will benefit from the most basic of concepts in portfolio theory: Rebalancing.

In the fictitious case above we are looking at a stock that is volatile but has no return. What if we were to do the same experiment and this time use two stocks that have low correlation to each other but both lose money in the long-run? This is exactly what was examined in a recent study done by Dempster, Evstigneev and Schenk-Hoppe in “The Joy of Volatility”. Their experiment assumed that Stock A would either gain +40% or lose -30% at each period and Stock B would either lose -20% or gain +15% at each period (randomly). The results were impressive:

Source: Dempster, Evstigneev and Schenk-Hoppe


The author puts it best by saying that “poverty is the inevitable fate of the passive investor.” However, the active investor achieves certain success through rebalancing.

When applying this to the real world the problem we face is in finding stocks that are actually uncorrelated to one another to that degree. In today’s macro news driven environment we find that most risky assets have become too highly correlated.

So let’s apply this concept to the real world, but instead of stocks let’s use two asset classes we know to generally have low-to-negative correlation to one another: stocks and bonds. Let’s work with the Japanese stock market (Nikkei 225), which has lost -48% since 1995, and combine them with Japanese government bonds. We will rebalance this portfolio quarterly using the dynamic volatility weighting method[i] (click here for a detailed article on this simple concept).


Source: Butler|Philbrick|Gordillo and Associates*, data from Bloomberg
This chart shows how the use of an uncorrelated asset class along with simple rebalancing can make a big impact on anyone’s investment success. The portfolio went from losing -48% and having a peak-to-trough maximum loss of -79% in the Nikkei, to making a profit of +138% and keeping the worst peak-to-though loss at a manageable -13.97%.  Though the result of this two asset class portfolio is impressive, we would in no way espouse this model as an optimal framework not least of which because the stock / bond diversification ignores the myriad of opportunities available from other markets and asset classes (Click here for more detail on how we deal with this).  

The most important point behind these examples is that one doesn’t necessarily have to be right about which stocks, sectors or other asset classes will do well in the future, as long as they all experience bouts of uncertainty (i.e. volatility), they are significantly uncorrelated to each other and you employ an active portfolio approach designed to harvest that uncertainty. The math will take care of the rest.

If you are an avid risk junky and have always thought bonds were for losers, this exercise may be a good way of helping you talk yourself into introducing some cash and bonds into your otherwise risky portfolio. But make sure to always follow the number one rule … don’t forget to rebalance!



[i] This is important in order to keep the experiment in line with the Dempster study which requires us to keep the bet sizes the same in each rebalancing period. In the example of the two stock portfolio the odds are known in advance and the bet size is always constant. In the real world, bet sizes change with volatility. It is only by controlling the bet sizes through dynamic volatility sizing that we can come as close as possible to the results in the two stock study. Having said this, even if one decides to employ traditional equal dollar rebalancing quarterly we go from losing money in the Nikkei to making a profit of +41% and keeping the drawdown to only -33% (Click here for these results).

Friday, February 10, 2012

Sky-High Bullish Sentiment Suggests Caution is Warranted


We have not yet tested these sentiment indicators for significance, but with stock market sentiment reflecting such extreme bullish confidence, one has to wonder who is left on the sidelines with cash ready to push this market higher.

S&P500 Price (top) and Mutual Fund Cash as a Percent of Total Assets (bottom)
Source: SentimentTrader
Source: SentimentTrader via Evilspeculator.com 

Source: SentimentTrader via Evilspeculator.com 

Source: SentimentTrader via Evilspeculator.com 


Friday, February 3, 2012

Low Volatility as a Fiduciary Duty

Mike Moody, John Lewis and the Dorsey Wright team run a superb shop, and our views overlap about 80% of the time (systematic vs. clinical, anti-forecast, RS, etc.), but I feel compelled to address a recent post on their SystematicRelativeStrength blog (SRS).


The SRS blog took issue with a quote by investment legend and individual investor advocate David Swenson, who has led Yale's endowment fund successfully since 1985. We endorsed his statement yesterday in a post, but here it is again:
“A fiduciary would offer low-volatility funds and encourage investors to stay the course,” he said. “But the for-profit mutual fund industry benefits by offering high-volatility funds.”
SRS was troubled by the assertion that investors are more likely to stick with a low volatility strategy, and used Dalbar's study of investment behaviour to prove their point. Specifically, they noted that historically investors have been no more inclined to hold onto lower volatility bond funds than higher volatility stock funds. From SRS:
"I have a few issues with this. First, the data argues that low-volatility funds are not the answer. If low volatility were the answer, customers would hold their low-volatility bond funds longer than they hold their high-volatility stock funds—but they don’t."
I find this argument disingenuous and logically flawed. For evidence, I have drawn a chart using data from the 2011 Dalbar study (see full study here):
Source: Dalbar (2011)

Note that investors are indeed no more likely to hold onto bond funds than equity funds, with the average holding period for both around 3.2 years or so. However, what the SRS article did not mention (strangely, since they have several asset allocation funds), was that the investors tended to hold asset allocation funds for a full 33% more time than either stock or bond funds on their own. Huh.


The category of Asset Allocation funds is overwhelmingly dominated by balanced funds of stocks and bonds. Investors who allocated capital to asset allocation funds explicitly outsource the asset allocation decision to the fund manager, who they expect will bias the fund toward or away from stocks or bonds as opportunity knocks.


Dorsey Wright manages a Balanced Fund (Arrow DWA Balanced Fund) with annual turnover of 59%, which implies an average holding period of 1.69 years (1/0.59). The highest ranked fund in the U.S. Balanced Fund category, the Intrepid Capital Fund, had an annual turnover of 88%, implying that the fund turns over almost its entire portfolio about once per year (every 1.14 years to be exact).


Does this high turnover mean that these fund managers are trading their portfolio on intuition or emotion? Does it demonstrate a lack of expertise or conviction in their approach? I don't think so. Rather, the managers of these successful funds are moving capital around to take advantage of opportunities they identify, in DWA's case through their proven relative strength system.


Turnover is not a measure of investors' preferences; rather investors prefer the best returns for the lowest risk. Neither stocks nor bonds on their own can deliver this objective because they are much better together than either is on its own. Investors know intuitively that there are times to emphasize bonds and times to emphasize stocks. The less successful ones try to time these changes on their own, and make binary decisions to switch between them, while the successful ones leave the decision to experts who adapt portfolios incrementally over time.


Literature from the institutional space is beginning to identify the power of dynamic asset allocation (DAA). This approach advocates more frequent rebalancing based on changing expected return, volatility and correlation dynamics. This type of strategy often has higher turnover, but can be engineered for quite low volatility. Their objective is to capture a large proportion of upside returns from a diverse set of asset classes, but continuously optimized diversification protects portfolios from major losses. As a result, investors are more likely to stick with these strategies because they experience a steady return trajectory like bonds, but capture substantial equity returns as well.



Low volatility DAA strategies are also highly optimal for retirement outcomes because of the sensitivity of retirement plans to large sustained losses, especially in early years.


In summary, Swenson asserts that investment advisors with their clients' best interests at heart would guide clients toward low volatility strategies, mostly because these strategies are much easier to stick with through thick and thin. We have also shown, counterintuitively, that low volatility strategies may provide stronger absolute returns as a result of their smoother ride. This makes them especially compelling for investors nearing or in retirement, and who wish to maximize retirement spending while sleeping well at night.

We practice what we preach. Find our whitepaper here.

Thursday, February 2, 2012


David Swensen, the legendary manager of Yale University's endowment, arguing that acting as a fiduciary for other people's money and maximizing profits are incompatible activities. 

"A fiduciary would offer low-volatility funds and encourage investors to stay the course," he said. "But the for-profit mutual fund industry benefits by offering high-volatility funds."

Consulting Behemoth Russell Investments Advocates Volatility Sizing

We published a whitepaper in November that demonstrated the importance of sizing asset class exposures based on volatility that received a lot of attention. It turns out that global investment consultant Russell Investments also advocated for this approach in a recent study targeted at institutional asset allocators.

Their study includes some neat charts that further validate the mechanics of this approach. For example, the success of this approach is based on gambling theory which describes optimal bet sizing. If we assume expected return is either constant or unknowable, but positive, then it is optimal to always bet the same amount. However, markets force most investors to increase and decrease their bet sizes, sometimes dramatically, based on changing volatility. An investor's exposure to risk is much larger when the market's volatility is 30% than when it is 15%, but most investors fail to adjust portfolios for this higher risk.

The charts below illustrate how this plays out in markets. The charts at the top prove that returns in one month have little relationship to returns in the next month (left), but the volatility in the current month does a good job of forecasting the volatility in the subsequent month (right). So adjusting one's exposure based on the most recent month's volatility makes sense.

Source: Russell Investments

Some might argue that higher volatility should equate to higher expected returns, but the chart below invalidates that assumption. There is no relationship between volatility and expected return.

Source: Russell Investments

If higher volatility does not improve expected returns, then we should concern ourselves with optimal bet sizing. By doing so, we substantially improve investment results, especially after accounting for risk.

Source: Butler|Philbrick|Gordillo & Associates, 2012. Results are pro-forma and for illustrative purposes only.

See also: