Folks wishing to protect their long positions may wish to buy puts with strikes at support levels. If I owned Apple stock (unfortunately, I don’t), I’d look at a six month to one year $550/$500 put debit spread. (I prefer spreads which lower the cost of entry while also mitigating some of the effects of implied volatility.)

StockTouch is an app for the iPhone and iPad that provides an easily readable heatmap of the one hundred top stocks (ranked by market cap) in each of nine of the most popular asset classes. This is a nifty tool that shows you in an instant what is happening within each sector and how well the sectors are moving relative to each other.

If you watch CNBC, you’ll know what a heat map is. If you don’t, it’s a graphical display of what’s hot and what’s not: stocks trending up are displayed in increasingly brighter shades of green and those trending in the opposite direction are shown in increasingly brighter shades of red with color brightness defined by the magnitude of the gain or loss.

StockTouch is intuitive and users should have no problem implementing it. But if you can’t figure it out after a few minutes, there’s an online tutorial that can help.

Current features
Handy features include the following:

- Many display choices–by market cap, trade volume, percent price change, alphabetically (handy if you’ve forgotten the stock symbol or conversely, the company’s name), or price change versus the S&P 500.

- Charting time frames from 1 day to 5 years.

- Clickable headline views on any selected stock.

- A stock symbol search feature.

- An optional running ticker of the Dow Industrials, S&P 500, and Nasdaq.

- A “Favorite Stock” feature (touch the star button) that will cause selected stocks to stand out in macro views.

Desired additions
This application is in its infancy and the developer is promising to add more features. “Wants” that many current users hope will be incorporated into future releases include the following:

- An Android version that the company claims is coming soon.

- The addition of lower-cap stocks, ETFs, and commodities.

- A direct connection to online trading platforms.

- The ability to swipe to adjacent stocks in single view mode.

- More charting tools & indicators such as candlesticks, MACD, and RSI.

- The option of creating stock watchlists.

- Price alerts sent via email or text.

The bottom line
Users give this app a thumbs-up based on its graphic design and intuitive nature, but many feel that more bells and whistles are needed. I think the $4.99 nominal fee is well worth the price, and as more of the above changes are incorporated, it will become an even better value. If you’re an active trader and want to see at a glance how stocks, sectors, and markets are trending, then this is the app for you!

Disclosure: I was given the app to review and have no other affiliation with the company.

The weekly chart of the stock (shown below) is compelling because it finally broke out of its 10 month rangebound pattern to hit a new all-time high of $66. Judging just from the technicals, the stock has room to run to well over $100.

What is Modified Modern Portfolio Theory (MMPT)?
MMPT is the application of an optimized market timing strategy to MPT which not only produces superior returns but also does so at much lower risk than MPT. The reader is invited to read these articles* to become familiar with the basics of the approach which we call Modified Modern Portfolio Theory (MMPT).

In this article we will be considering the time of global instability arising from the debt crisis in the Eurozone in which we will show that the MMPT constructed portfolio would have significantly outperformed the classic MPT model portfolio.

Global Debt/Recession Fears
The movement of the market is heavily influenced by the uncertainty in the economic environment, and it is this uncertainty that is measured by the volatility index (VIX). Following a spike in volatility in March of 2011 resulting from the tsunami and nuclear plant meltdown in Japan, the volatility settled back down to stable levels below 20. But it began to rise again as both the domestic and Eurodebt crisis came to the forefront on the heels of sovereign debt downgrades heralded by some of the major ratings agencies.

It wasn’t until the end of July that the volatility began climbing to bearish levels (over 25). July 22nd was the last time the S&P 500 (SPX) hit a relative high of 1346 before the VIX took off, sending the S&P plunging 17% in a few short weeks. Following Standard & Poors downgrade of the US’s credit rating, the SPX hit a low of 1120 on August 8th as the VIX concommitantly hit a high of 48. After two months of extreme choppiness, the VIX hit another relative high on October 4th as the S&P put in an intraday low of 1075, representing an overall loss of 20% from its July high. (See charts below.)

Methodology
To compare how a modified portfolio would have done compared with a classic one, the reader should understand the underlying methodology. Both portfolios are made up of the same nine asset classes comprised of domestic and international stocks and bonds along with real estate (in the form of REITs). The model portfolios presented here are designed to return a 10% compounded annual return, the same that was used in the previous articles. The analysis rebalances the portfolios monthly as new total return asset class performance data is made available. The portfolio allocation tool used to conduct these studies for both the classic MPT model and the market timing MPT approach is the SMC Analyzer.

The allocations
During this turbulent time period, an MPT portfolio with a 10% required annual compounded return would have been heavily invested in the stocks of large and small companies both domestic and international (see Table 1). But the MMPT equivalent model (see Table 2) was already light in the large and small stock asset class having benefited from the recent experience of the dot-com bubble and subprime mortgage collapse. Despite some optimism for the alternative international stock and real-estate investment trust asset classes the allocations there were comparatively light, instead heavily favoring medium-term government bonds and the safety of Treasury Bills (or an insured money market equivalent).

Table 1. Classic MPT Historical Allocations During the Subject Period for a Target 10% Compounded Annual Return

Table 2. MMPT Historical Allocations During the Subject Period for a Target 10% Compounded Annual Return

Comparing models
During the months of this mostly fear-driven event, the MMPT portfolio lost at a rate of only 4.7% compounded annually (green line) while the classic MPT portfolio lost money at an annual rate of -40.4% (magenta line). Further, the MMPT portfolio was less volatile. It experienced a standard deviation of only 3.9% while the classic MPT investor experienced a standard deviation of 6.2%.

Figure 1. Comparison of results
(green = MMPT)
(magenta = MPT)

Summary
We have shown that an MMPT investor during the global debt crisis was able to hold onto almost all of his money while most other investors were getting hammered. The reason is that a considered and properly applied market timing approach injects an element of flexibility and responsiveness to a portfolio while still benefiting from historical experience. This is of tremendous value especially in today’s uncertain markets.

Every day the news concerning the uncertainty 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 once again with this case study that the MMPT approach combines the best of Modern Portfolio Theory with the desirability of a viable market timing strategy

For further information on how you can save your portfolio from the ravages of market crashes please visit our website.

*Previous articles on Surviving Market Crashes:
Part I: “Surviving Market Crashes”, August 23, 2011
Part II: “Surviving Market Crashes, Part 2: The dot-com bust”, September 29, 2011
Part III: “Surviving Market Crashes, Part 3: The subprime mortgage crisis”, November 19, 2011

This article is a continuation of the same theme, but here, we’ll be looking at something that wreaked more havoc on portfolio returns than did the dot-com bust—the subprime mortgage meltdown from 2007-2009. We shall show that MMPT-based portfolios again produce superior returns at much lower risk than their classic MPT-based counterparts.

Summary of the MMPT methodology
Since the MMPT methodology was explained in the first two articles, the reader is referred to those for the detailed explanation. Briefly, the approach applies a robust market-timing scheme to Modern Portfolio Theory to determine when one should allocate funds to a particular asset class and when one should take money out of that asset class and place it in the safety of the risk-free asset class (cash, insured money markets, or T-bills).

To illustrate fund performance, nine of the most commonly used asset classes form the basis of the our model 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). Gold and other precious metals are not included for reasons given previously (although we could add it if so desired since we have the gold database).

The devastation of the subprime mortgage crisis
The time frame we’ll be using in this analysis begins on October 11, 2007 when the S&P 500 hit an intraday high of 1576 and ends on March 6, 2009 when the S&P 500 reached its intraday low of 667. This represents a loss of over 57%, more than the 50% loss suffered during the dot-com bust. Figure 1 (which includes dividend income) illustrates just how steep this plunge was.

Figure 1. Total Return Derived from the S&P 500

Along with a steeper loss in the large-cap stocks, the mortgage crisis took a major toll on small-caps as well with similar losses. This was not the case in the dot-com bust where the value of small-cap stocks actually held on despite large price fluctuations.

Figure 2. Total Return Derived from Small Cap Stocks

Table 1 below shows that the annualized returns for all asset classes except for government bonds did poorly during this time period. Comparing these returns with those during the dot-com bust (refer to Table 3 in the previous article), we can see that everything except for government bonds fared much worse during the subprime crisis especially REITs which went from a +7% return to a whopping -54% loss.

Table 1: Annualized total returns of all asset classes during the subprime mortgage financial crisis

Portfolio allocations during the mortgage meltdown
As in the previous articles, we are requiring a 10% compounded return for our model portfolios. Portfolios are rebalanced monthly as new total return asset class performance data is made available. The portfolio allocation tool used for both approaches is the SMC Analyzer.

Table 2 below shows that a classic MPT portfolio would have had roughly 60 – 80% of their assets allocated to equities with the rest divided between REITs and corporate bonds. Table 1 above shows that it is exactly these asset classes that fared the worst during this time period.

Table 2. Classic MPT Historical Allocations During the Subprime Mortgage Financial Crisis for a Target 10% Compounded Annual Return

By comparison, the MMPT equivalent portfolio (Table 3) was already light in the large stock asset class, having benefited from the experience of the dot-com bubble collapse. For the entire period of the subprime meltdown, the MMPT portfolio was heavily weighted (70-100%) towards medium-term government bonds and T-bills with some minor exposure to small-caps and international equities.

Table 3. MMPT Historical Allocations During the Subprime Mortgage Financial Crisis for a Target 10% Compounded Annual Return

As Table 1 shows, it was this exposure to the equity classes that caused the most harm to both portfolios. It’s interesting to note that long-term government bonds fared the best in a so called flight to safety but MMPT did not allocate funds to it instead preferring the historical lower volatility (risk) of the intermediate-term bonds.

Comparison of portfolio returns
During the months of the dot-com bust, the MMPT portfolio lost at a rate of only 1.1% compounded annually (green line in Figure 3 below) while the classic MPT portfolio lost money at an annualized rate of -32.9% (magenta line). Further, the MMPT portfolio was much less volatile. It experienced a standard deviation of only 4.8% while the classic MPT investor was being whipsawed to the tune of 17.3%. Sure, suffering a small loss isn’t desirable but it’s certainly a lot more palatable than losing a third of your holdings. Which scenario would you have chosen?

[As an aside, I attended a conference of public fund and hedge fund managers who actually admitted to losing between 25 and 50% of their funds' assets during this period.]

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

Summary
We have shown that an MMPT investor during the subprime mortgage financial crisis was able to keep almost all of his money while most other investors were getting clobbered. 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.

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 these case studies that the MMPT approach combines the best of Modern Portfolio Theory with the desirability of a viable market timing strategy.

For further information on how you can save your nest egg from the devastation of market crashes, please visit our website.

The trade would be to short the stock today at $41 and ride it down to around the $32-$33 level, or until it shows signs of reversing direction. (Every reversal has always been accompanied by a bottoming tail.) Set a stop-loss for just above the upper channel–around $41.25 or above. There are options for this issue but they are very thinly traded and not recommended.

Note: Into channeling stocks? Check out our Daily Blue Plate Specials subscriber services which includes a database of channeling stocks. (Currently, there are 43 stocks in the channeling database.]

Times of economic normalcy are marked by a VIX below 20. Times of economic stress are typically signaled by a move in the VIX over 30 with extreme duress (such as in 2008) marked by sharp spikes at much higher values.

For the past several months the VIX has been oscillating between 30 and 45. It has only been in the past few days that the VIX has crossed below 30. If it can close below that level for a couple of days, that would be a compelling signal that air is starting to come out of the volatility bubble.

Futures traders can easily short the VIX but what if you’re not into futures or options? The inverse VIX exchange traded note, XIV, offers an attractive solution. The chart below shows that the XIV is rebounding off its October 4th low. Because XIV is a futures-based product, it’s subject to roll-over issues and like leveraged ETPs (exchange-traded products) XIV is reset on a daily basis. On top of that, the fund has only been around for less than a year. These peculiarities make direct comparison with the VIX difficult, but the charts below depict the general relationship.

The first half of this year saw the VIX ranging mainly between 15 and 20. In that time, the XIV was steadily increasing. It reached its peak of 19 in July when the VIX was at its lowest point of 15. Now does this mean that we can expect XIV to return to that level should the VIX fall back to 15? I honestly can’t say. Based on the 50% drop in the VIX last March where the XIV concurrently rose 45%, it’s not unreasonable to expect XIV to at least reach the $7-$8 range which I feel is a conservative estimate.

The major downside with this trade is if the VIX remains stubbornly high as it has been doing. This could cause further price erosion in XIV due to its nature so if you’re going to trade this, it would be wise to use a stop. Otherwise, why not risk a little mad money on risk itself?

Note: XIV is very actively traded with an average daily volume of over 8 million shares. It does not have options.

Disclosure: Dr. Kris has a long position in the XIV.

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.

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.