In the previous article on surviving market crashes (“Surviving market crashes,” August 23, 2011) we looked at an innovative modification to Modern Portfolio Theory (MPT) that addresses one of its major drawbacks—that of keeping the investor fully invested during bad times as a well as good. We saw that MPT by itself can lead to substantial losses during severe market downturns, losses that can take years if not decades to recover.

To solve this problem, we applied an optimized market timing scheme to the MPT model. This not only resulted in superior returns, it did so at much lower risk. Since the results were so dramatic, there were many questions left in the minds of readers. This article is the result of those questions which will hopefully bring clarity to the issues that were raised.

Methodology
It was decided that the best way to show how a portfolio can survive market crashes using our model was to examine one in detail. The bursting of the dot-com bubble was chosen because it was the first severe market decline in recent history which most people remember (though many may not remember it fondly).

The mechanics of the market timing model are given in greater detail in the previous article which the new reader is strongly encouraged to read. For those of you who have read it or just want to skip it, a brief summary of our approach follows.

Nine of the most commonly used asset classes form the basis of the our investment portfolio: large-cap stocks, small-cap stocks, long-term investment grade corporate bonds, long-term government bonds, intermediate-term government bonds, real estate investment trusts (REITs), international stocks, international bonds, and T-bills (or some other risk-free asset class such as an insured money market). Gold and other precious metals are not included for reasons given in the previous article.

From these asset classes, a portfolio is determined per the required desired compounded annual return. The examples used in the previous article were based on a 10% required return and that 10% return will again be used here for sake of comparison.

Portfolios are determined according to the classic MPT model and also to our market timing model which we call Modified Modern Portfolio Theory, or MMPT for short. The MMPT approach uses an oscillator to determine when one should be in or out of a particular asset class. When the oscillator says to get out, the percentage that MPT would have allocated to that asset class is instead put into the risk-free asset class (Treasury bills or an insured money market). Further details on how the timing aspect of the MMPT model works are given at the end of this article.

Portfolios are rebalanced every month as soon as new asset class performance data is published. In this article as well as in the previous one, portfolio allocations for both the MPT and MMPT models are the output of our portfolio allocation tool, the SMC Analyzer.

The collapse of the dot-com bubble
Those with stock-heavy portfolios, especially in stocks of that newfangled invention called the internet, were thrilled to see their nest-eggs balloon during the dot-com bubble, but they were probably more distressed to see them deflate during the dot-com bust, those agonizingly turbulent months between September of 2000 and October of 2002. During that time, the S&P 500 (representing the Large Company Stock asset class) lost almost 50% of its value—not very pretty!

During the collapse, an MPT portfolio with a 10% required annual compounded return would have been heavily invested in the stocks of large companies (the S&P 500). (See Table 1.) But the MMPT equivalent model would have taken investors out of that asset class as early as the beginning of November of 2000 and reallocated those funds into the safety of Intermediate-Term Government Bonds and T-bills. (See Table 2.)

Because classic MPT does not consider trends but rather looks at all times as an average, the allocation recommendations kept the investor in Large Company Stocks through a period of sharp decline. In comparison, because MMPT can react quickly to changes in market direction it got the investor out of Large Company Stocks as soon as it was apparent the decline was not to be short lived.

Table 1. Classic MPT Historical Allocations During the Dot-Com Bubble Bust for a Target 10% Compounded Annual Return

Table 2. MMPT Historical Allocations During the Dot-Com Bubble Bust for a Target 10% Compounded Annual Return

You can see from the above tables that during this period MMPT placed the investor heavily in the safety of U.S. Treasury Bills and Intermediate-Term Government Bonds. But for some of the time there was a substantial allocation in Small Stocks. This can be understood when looking at their behavior (Figure 1). While the Large Stock asset class was collapsing (Figure 2), the Small Stocks actually hung in there despite fluctuations in value.

Figure 1. Total return: Small-cap stocks

Figure 2. Total return: Large-cap stocks

Table 3 below summarizes the performance of each asset class during this period. It’s interesting to note that Long-Term Corporate Bonds fared the best but MMPT did not allocate funds to it instead preferring the lower volatility and risk of Intermediate-Term Government Bonds. It’s important to note that in MMPT the oscillator strategy only applies to equity based asset classes and not bonds. Bonds are treated just as they are in classic MPT since they are by nature less volatile than stocks.

Table 3: Annualized total returns of all asset classes during the dot.com bust

Comparing models
During the months of the dot-com bust, the MMPT portfolio returned 8.3% compounded annually (green line) while the classic MPT portfolio lost money at an annual rate of -12.7% (magenta line). Further, the MMPT portfolio was much less volatile. It experienced a standard deviation of only 4.9% while the classic MPT investor was being whipsawed to the tune of 13.6%. Wouldn’t you have liked to make money during that time instead of losing it?

The reason that MMPT was unable to achieve the desired 10% return is because in the short term there is never a guarantee that asset classes will perform up to their historical norms. Also, figuring in the lower return of T-bills and the slightly negative return in Small Stocks explains why MMPT fell short of its goal during this two year time span.

Figure 3. Comparison of results
(green = MMPT)
(magenta = MPT)

Summary
We have shown that an MMPT investor during the dot-com bust was able to reap a decent return while the classic MPT investor, left heavily invested in large-cap stocks at the wrong time, suffered. The reason is that a judiciously and properly applied market timing approach injects an element of nimbleness and reactivity to a portfolio while still benefiting from historical experience. This is of tremendous value especially in today’s uncertain markets.

An even better reason to consider a market timing approach has to do with the increasingly positive correlation among asset classes. Historically, bonds have moved independently of stocks meaning that these asset classes were uncorrelated. Many commodities also moved contrary to stocks but lately all of this has changed.

The correlations among stocks, bonds, and commodities are becoming increasingly positive as national economies become more interdependent. Investors today are unsure as to where to place their nest egg. Every day the news concerning the deterioration of the global economy is increasing volatility across most of the traditional asset classes, and it’s for this reason that market timing approaches should be given their proper due. I believe we have shown with this case study that the MMPT approach combines the best of Modern Portfolio Theory with the desirability of a viable market timing strategy.

Appendix: The MMPT methodology using the SMC Analyzer
The SMC Analyzer uses an oscillator to identify when to stay in an asset class and when to stay out of it. Each component asset class has its own oscillator. Each oscillator is based on an averaging period, and it is this averaging period that is optimized every month according to new input data.

When the oscillator goes from positive to negative, that asset class is exited and the funds that would have been allocated to it are instead put into the risk-free asset class. Conversely, when the indicator turns positive, funds are placed back into the asset class according to the current allocation. Only equity-based asset classes (stocks) are subject to this treatment; bond classes are treated exactly alike in both the MMPT and MPT models since their values typically don’t fluctuate much if at all.

It is important to note that the time history of performance of an asset class in an MMPT allocated portfolio will differ from that of an MPT allocated one. This seems obvious but the point here is that you will not get even close to the same results by applying an oscillator externally to MPT-derived allocations alone. The reason is because MPT bases its current allocations on the entire time history of data for each asset class, and so to get the proper allocation you’ll need the MMPT modified time series that incorporates those periods of time where funds were not placed into a particular asset class.

For this article and in the previous article we used the CCI (Commodity Channel Index) with an optimized averaging period as our market timing oscillator. This is the indicator we use to generate our monthly subscriber email reports because we have found that this one works the best in general. That is, it produces the lowest levels of variability in portfolio value, i.e. lowest risk, while still achieving the targeted returns. Professional money managers, quants, and mathematically sophisticated investors will find two others in the professional software version of the SMC Analyzer along with many other useful features including the ability to add your own asset classes.

For further information on how you can save your nest egg from the devastation of market crashes such as the one we’re in right now, please visit our website.

Gold and silver have both broken key support levels today. The gold ETF (GLD) is down over 4%, breaking $165 support. Options trader might want to consider a 165/155 put debit spread as $155 is the next support level (and $145 below that).

Silver is suffering even more. The silver ETF (SLV) gapped below $32.50 support, falling over 9% as of this writing. Next support is $30 followed by $28, $26, and $24. You can play this one the same way as the GLD. I’m advocating option spread positions to mitigate the effect of heightened volatility.

The daily charts of the GLD and SLV are shown below.

Tags: Precious metals, GLD, SLV, gold, silver

In The Monopoly Method: An insider’s guide to navigating Wall Street and becoming a better investor, Wall Street veteran Greg McCall guides the reader through his value-investing approach to portfolio selection and management. Written in a straightforward easy to read style, McCall outlines his method of identifying and evaluating “monopoly” companies, i.e. those that have compelling “themes” and are sector dominators. Think Amazon and Apple.

The Monopoly Method approach
Selection of monopoly companies involves both in-depth fundamental analysis as well as some technical analysis. The author takes us on a tour of both.

Fundamental analysis includes balance sheet basics focusing on stats that give an indication of fiscal health and revenue growth. Technical analysis is limited to identifying when a stock may be breaking out or breaking down by looking at support and resistance levels, moving average cross-overs, and relative strength. Being a technician, I like his commentary on the first but feel that the discussions of the two others are inadequate and could confuse those with little or no technical training.

Sector by sector analysis
Monopoly companies are defined as those being in the right place at the right time. Sector by sector, the author identifies what he thinks are the monopoly companies of today, noting current themes as well as possible future ones. These companies can be used as a springboard for the beginning value investor.

McCall does a good job of explaining what sector-specific metrics are needed for proper evaluation. He also provides outside sources that he himself uses to determine fundamental values, sources that aren’t at the top of everyone’s lists. For example, www.greenmarkets.com is the place to go for pricing fertilizer, an essential metric in evaluating companies such as Agrium, Potash, and Mosaic. Who would have guessed?

Along the way, the author also explains how economic events affect price movement such as why commodities rise when the dollar falls. Those who have never taken an economics course might appreciate these observations.

[It’s interesting to note that although McCall addresses most of the major sectors, he does not mention the drug sector. I don’t know if the omission was intentional but it’s certainly a sector that is too important to ignore without comment.]

The scoring system
He puts it all together by walking the reader through three specific examples—Apple, Cisco, and Wal-Mart. But before he does that he runs us through his stock scoring system, a list of a dozen or so fundamental criteria plus a couple of technical ones. (You can view a stripped down version of the scoring method on www.monopolymethod.com.)

Guidelines on assigning parameter values are given in broad strokes. It’s left up to the experience and knowledge of the reader to provide the appropriate value.

All of this guesswork leads me to my main criticism of the Monopoly Method: it’s highly subjective. Given that, though, someone who does take the time (and that’s my other big complaint) to go through this process will gain an in-depth understanding of a company’s dynamics.

Other features
One takeaway that many investors might find useful is the risk/return formula. Calculation of this ratio requires determining the upside price target using fundamental data and the downside price target from chart analysis. The ratio tells you how rewarding your investment would be at current prices with the added benefit of providing you with your profit target (the upside price) and your stop/loss point (the downside price).

The book is a good primer for budding investment analysts and portfolio managers. Of particular note is the appendix chapter on interacting with company management where the “Flattery will get you everywhere” maxim seems to be the modus operandi.

If you really want to sink your teeth into this method, the book gives you guidelines on how to structure your day. As it turns out, to fully work the Monopoly Method requires an eleven hour work day (yes, you read that right), from 7am to 6pm (I’m assuming that’s Eastern time). That might work for highly paid Wall Street analysts and fund managers, but does that work for you?

Conclusion
All in all, The Monopoly Method is a straightforward manual for value investors and those wanting deeper explanations than what Jim Cramer provides. Two major downsides that were previously noted are that it is time consuming as well as being subjective. I suspect there’s a long learning curve involved in figuring out how to accurately rate stocks which would only appeal to the most motivated. By its very nature, this method also tends to overlook new companies with high-growth potential due to the inherent lack of fundamental data.

This book would make a good addition to the library of any value investor or those interested in learning more about it. You could, however, save yourself a lot of time and trouble by going out and buying some shares of a value fund or better yet, Berkshire-Hathaway. (Class B shares are $70.) At least here you know that your portfolio is in the hands of the definitive master of the Monopoly Method—Warren Buffett.

The escalation in the European debt crisis is forcing investors to find safe places to park their cash. The Swiss Franc (“Swissie”) and gold have been two of the more popular safe harbors causing a huge run-up in their prices. Worried about the effects of a hyperinflated franc, Switzerland decided to start pegging their currency to the euro which has caused the Swisse to tumble…and the dollar to rise.

The greenback, as measured by its exchange traded note the UUP, has rapidly risen 4% off its $21 base. (See weekly chart below.) Today the UUP broke recent resistance at $21.75 and is poised to go higher. The stock doesn’t move in large increments which means that you’ll get a lot more bang for your buck by using options, and the great thing about the UUP is that its near-the-money options are heavily traded (i.e., there’s a lot of open interest).

Options players can take advantage of a bullish move in the dollar with an at-the-money call debit spread. The October 22/23 call spread has the following advantages:

1. It’s low cost
2. You have nearly a month and a half for the trade to develop
3. The spread structure minimizes the effects of heightened volatility

Here’s the set-up:

Buy the Oct 22 Call for $0.37 (OI = 23K)
Sell the Oct 23 Call for $0.12 (OI = 7K)
Net debit = $0.25

On the return side, you’re risking 25 cents to make up to 75 cents which is a reward to risk ratio of 3:1—to get the comparable return with stock, the price would have to rise to $84! On the risk side, should the dollar take a dive, you can only lose the amount of your original investment which is 25 cents ($25 per contract).

One thing to note is that you won’t begin to make money until the stock rises above the breakeven point of $22.25 and your maximum return of $0.75 won’t be realized until the UUP rises up to or above $23 (on or before expiration which is October 21). The other thing to note is that the UUP is facing major support/resistance at $22. A more conservative player may want to wait until the stock breaks that level but if you do, realize that the options pricing will be less attractive thus lowering your reward/risk ratio.

Outside of trading the currency futures directly, I can’t think of a better way to make a buck off the buck.