Technically Speaking, February 2015

LETTER FROM THE EDITOR

This year marks the 42nd anniversary of the MTA. We tend to ignore anniversary years unless they end in 0 or 5 but each year is important to the organization. Each of the past 42 years has presented the MTA with opportunities for growth along with occasional challenges that have to be met. The fact that we are now nearly 42 years old as an organization is a tribute to the volunteers who have led the MTA.

Most of us rarely think about the leadership of the MTA. That fact indicates that they are doing an outstanding job because we tend to worry only about major problems. No major problems means no worries about the MTA.

This month, I’d like to join Dave Keller, CMT, and Past President of the MTA in asking you to think about our organization’s leadership. In particular, as Dave notes, it’s time to nominate individuals to serve on the Board of Directors. Individuals in these positions will help set the pace for growth in the next 42 years. If you know of the right person to meet that responsibility, please nominate them. Getting the best people involved in the MTA has allowed most of us to ignore the problems that the Board solves effortlessly while keeping us on the right path.

Please submit your recommendations to nominations@mta.org and help us to continue growing the MTA.

Sincerely,
Michael Carr

What's Inside...

OMAHA, PROCESS, & SKIN IN THE GAME (AND MY PORTFOLIO FOR 2015)

Editor’s note: This was originally published at MebFaber.com and is reprinted here with permission. The first part of this reprint...

Read More

INTEGRATING MULTIPLE DISCIPLINES FOR ACTIVE PORTFOLIO MANAGEMENT: AN EVENING WITH FRANK TEIXEIRA, CFA, CMT

For far too long, it has been cliché to talk about the two schools of financial market analysis, fundamental analysis...

Read More

BEATING THE S&P 500 WITH MOMENTUM AND TREND FOLLOWING

Editor’s note: Riccardo Ronco is scheduled to make a presentation at the Annual Symposium in March. He provides research to...

Read More

AN INVITATION FROM THE MTA NOMINATING COMMITTEE

The Market Technicians Association (MTA) is a dynamic association focused on building a strong community of market professionals, maintaining the...

Read More

ROHRBACH'S FIRST LESSON IN INVESTING

“When an investment is not going the way you thought it would, it’s important to sell it and...

Read More

ETHICS IN FINANCE- ROBIN COSGROVE PRIZE 2014-2015

Competition for the Prize of $20,000 will be open until...

Read More

HOW TO LET PROFITS RUN AND CUT LOSSES

Cynthia Kase, CMT, MFTA, has decades of experience in the markets and understands how to consistently win. She has developed...

Read More

WHY PASSIVE INVESTORS GET HAMMERED

Editor’s note: This was originally published in Proactive Advisor Magazine and is reprinted here with permission. For a nocost subscription...

Read More

Editor’s note: Bucket investing is a well-known financial planning concept. Technical analysts might discover their techniques can be applied within...

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2015 NAAIM WAGNER AWARD CALL FOR PAPERS

In 2009, the National Association of Active Investment Managers (NAAIM), launched...

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MASTERS IN TECHNICAL ANALYSIS: JIM ROHRBACH

“There are really only two good feelings in investing. One is being in the market when it is...

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SHAKE OFF THOSE WINTER BLUES WITH THE RIGHT STOCK SELECTION

Editor’s note: This report was originally published by Phases & Cycles on January 20, 2015 and is reprinted here with...

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OMAHA, PROCESS, & SKIN IN THE GAME (AND MY PORTFOLIO FOR 2015)

Editor’s note: This was originally published at MebFaber.com and is reprinted here with permission. The first part of this reprint explains Meb’s basic portfolio allocation philosophy and was published in 2014. The second part is a January 2015 update. You can hear more of Meb’s thoughts on the market at the Annual Symposium in March where he is scheduled to make a presentation.

Every time Peyton Manning steps up to the line of scrimmage he is prepared to audible. He has spent thousands of hours of film study to get ready for nearly every situation. So when he shouts “Omaha”, he isn’t panicking or reacting emotionally, he is simply instituting a reaction to calculated probabilities from many years of experience and study.

The same should be true for your portfolio. Do you have a plan? Or do you simply have a portfolio for today, that you will emotionally react to if and when current events dictate?

You should be prepared for the possibility of an 80% decline or 100% rise in stocks. What would you do with bonds yields climbing to 10% again in the US, or declining to and staying at 1% for 10 years? Gold at 400, gold at 4000? Oil at 50, oil at 200? Did the volatility and losses of September and October scare you? Did they cause you to alter your plan? Do you even have a plan?

Much like the great book Checklist Manifesto, you should have a written investment plan – what real money institutions call a “policy portfolio”. I wrote a whole book on the topic (The Ivy Portfolio). If you promise to write a review I’ll even send you a copy. The simplest policy portfolio is just the global market portfolio which can be had for about 0.2% through ETFs. But it doesn’t matter what your policy portfolio is, just that you have one and you can fathom the possible outcomes. It could be 100% in CDs, or the Talmud, or anything else. Some like trend following, others, a farm and guns.

I’ve been in Asia for a few weeks and in general would love to add more to my foreign stock allocation on any weakness or declines. I have limit buy orders in every 10% down in foreign stocks for the next 50%. Likely? No. Possible? Sure.  But if and when stocks go down 20, 40, 60%, I don’t want to be at the line of scrimmage wondering if I will pull the trigger or not. I have a plan, and my portfolio has a roadmap for any possible outcome. While I am a trend follower at heart, I have a (very) long time horizon, and can be aggressive. Younger investors should relish market declines (hard but true). 

In June I sat down to chat with Samuel Lee at Morningstar. I think it is instructive to illustrate the way I think about process of my portfolio, as many investors don’t think about possible outcomes until they happen. You can see my broad allocation to public investments below, and I will update again at year end.

Lee: In a recent blog post, you disclosed the rough breakdown of your personal portfolio. Would you mind disclosing exact proportions for your liquid assets, and why you’ve made those bets?

Faber: I think it is hugely important to have a money manager with skin in the game. In addition, many commentators and portfolio managers are willing to provide you with plenty of advice, but just try getting them to disclose how they invest their own money–impossible! If you don’t believe me, or want to see how much your portfolio manager is invested in his own funds, the filings are public, so you can view them at any time. Next time you are chatting with your advisor or broker, or hear someone giving lots of advice at a conference, ask them one simple question: “Specifically, what do you do with your money?”

My net worth is dominated by my ownership in Cambria Investment Management. Next in line would be farmland and real estate owned with my two brothers. I also hold equity stakes in a few other private companies (including The Idea Farm and AlphaClone). On the liquid side, I have 100% invested in our funds. All of my cash flows simply funnel into these four investments on a periodic basis. My horizon is very long-term and I have a high risk tolerance.

The breakdown is currently:

  • 60% Global Tactical Hedge Fund (private)
  • 20% Global Value ETF (GVAL)
  • 10% Shareholder Yield ETF (SYLD)
  • 10% Foreign Shareholder Yield ETF (FYLD)

The percent allocation in the three ETFs is actually higher than stated above, as the Global Tactical private fund is composed of ETFs. I will be adding to this list as we launch new funds in the coming months. Specifically, my assets in the hedge fund will transfer to the Global Momentum ETF when it launches.

As you can see, my holdings are dominated by foreign stocks, portfolios that can and do have the ability to tactically move to cash (and have a high exposure to real assets), and stocks that are shareholder-friendly and returning lots of cash to investors. I am least exposed to traditional bonds, but for me they are not that attractive at these levels for my time horizon and goals. If stocks experienced a large drawdown of 30% to 90%, I would shift more and more of the allocation to the equity portion. As I’ve mentioned in our new book, I don’t think U.S. stocks are that attractive currently, but I am very positive on foreign stocks.

2015 Update

As I have detailed in the past, I think it is paramount for your money manager or advisor to have ‘skin in the game’. I am happy to be 100% transparent with my holdings, and have detailed my approach to investing my own assets in the past a number of times. You should ask your money manager what they do with their own money – it may surprise you! I place all of my assets in Cambria funds.

Not much is different for me going into 2015 as there exist the same themes from the old interview:

“As you can see, my holdings are dominated by foreign stocks, portfolios that can and do have the ability to tactically move to cash (and have a high exposure to real assets), and stocks that are shareholder-friendly and returning lots of cash to investors. I am least exposed to traditional bonds, but for me they are not that attractive at these levels for my time horizon and goals. If stocks experienced a large drawdown of 30% to 90%, I would shift more and more of the allocation to the equity portion. As I’ve mentioned in our new book, I don’t think U.S. stocks are that attractive currently, but I am very positive on foreign stocks.”

As a trend follower, I like the idea of having half of my portfolio being able to move to cash or hedges if markets trend down. As a value investor, I also want exposure to assets that may be cheap over long horizons. Main changes have been rolling the old private fund assets into GMOM, allocating to new funds (new private fund strategy, new launches GMOM and GAA), and rebalancing to buy more beaten down holdings (GVAL). I still have a few more allocations to make in January but by month end the allocation should be roughly:

Broadly, I will have 56% invested in long-only strategies with the rest in tactical or market neutral strategies. Within those categories:

  • GVAL 25%
  • GMOM 23%
  • Private Fund 21% (Cambria Special Situations – a leveraged, tactical fund investing in US stocks, is 200% gross long and can be 0 to 100% net long)
  • GAA 18%
  • FYLD 12%
  • SYLD 1%

I will update again in 2016!

Contributor(s)

Mebane Faber, CMT, CAIA

Mebane Faber, who holds the Chartered Market Technician (CMT) designation, is a co-founder and the Chief Investment Officer of Cambria Investment Management. At Cambria, he is the manager of Cambria’s Global Tactical ETF (GTAA), as well as private investment funds for accredited...

INTEGRATING MULTIPLE DISCIPLINES FOR ACTIVE PORTFOLIO MANAGEMENT: AN EVENING WITH FRANK TEIXEIRA, CFA, CMT

For far too long, it has been cliché to talk about the two schools of financial market analysis, fundamental analysis and technical analysis, as if they possessed the molecular structures of oil and water. Not only does this approach leave investment professionals at a disadvantage, it also does a huge disservice to investment professionals whose strategies incorporate both of these disciplines into some of today’s most powerful investment models.

Boston-based Wellington Management’s Frank L. Teixeira, CFA, CMT is an industry leader in this fusion concept. As a partner and senior vice president of the firm, he manages over a billion dollars in both domestic and foreign securities and leads the technical analysis division for Wellington. Mr. Teixeira manages his portfolio based on an investment philosophy that combines both fundamental and technical principles. On Thursday, November 20, 2014 the Market Technicians Association (MTA) and New York Society of Security Analysts (NYSSA) hosted industry professionals for a presentation delivered by Mr. Teixeira entitled FUSION: Integrating Multiple Disciplines for Active Portfolio Management.

With over 20 years’ experience at his disposal and a captive audience of nearly 200 industry professionals, Mr. Teixeira took to the stage with the knowledge and charisma that all great presenters possess, to share insight into what he’s learned about what works and doesn’t work, under a variety of market conditions.

A firm believer that the underlying fundamental and economic activities drive prices up and down, Mr. Teixeira orchestrated an interactive discussion that put the spotlight on the importance of technical analysis in portfolio management. Core principles that inform his investment philosophy are that markets and securities develop trends, whether up, down or sideways, and that “trends tend to persist.” Mr. Teixeira went on to explain that, “how quickly people come to appreciate a change to the primary trend of the market is distributed over time.” Technical analysis is adept at measuring the characteristics of those trends and when conditions begin to change.

Recognizing that many in the audience were not practitioners of technical analysis, Mr. Teixeira took great care to explain when certain market conditions demand the use of trend, momentum, and relative strength (ratio) analysis. For a large mutual fund, position sizing is critical to managing risk in the portfolio. Mr. Teixeira reiterated how important the technical toolkit is for assessing market internals and other leading indicators of a change in trend. He said “when fundamental momentum decelerates, it is first reflected in price.” Paramount throughout the CMT Program is that different market environments call for the use different technical tools. Relative strength analysis for sectors and individual securities can help portfolio managers scale in and out of positions and “determine when momentum has dissipated.”

Academics refer to behavioral economics when studying how investor behavior impacts securities markets, particularly market anomalies and irrational market behavior. According to Mr. Teixeira “market conditions change a lot faster in our minds than in real time, and our feeling of those shifts is often more pronounced.” As a money manager and practitioner of technical analysis, he encouraged the audience to employ tools which will help you “acknowledge what is rather than what will be.”

As a member of the Market Technicians Association’s Admissions Committee, I have seen first-hand the growing interest in the CMT designation by fundamental practitioners. In addition, as the Chief Technical Strategist at a respected economic research firm, I can attest to the fact that technical strategies have played a key role in identifying intermarket themes during this time of unprecedented monetary policy.

At the conclusion of the presentation, the CFA Institute hosted a cocktail reception where guests were able to network and share their views on the markets. During this period, Mr. Teixeira graciously shared his time answering additional questions from a number of guests eager to learn more about his process. The ability to converse and network with some of the top names in the business is another factor that makes these events so invaluable.

It’s probably safe to say that there will never come a day when the purest of fundamental and technical analysts accept the teachings of the opposition. For one night, both fundamental and technical analysts got together to benefit from what was clearly another successful collaborative effort by the Market Technicians Association, NYSSA and CFA Institute.

Contributor(s)

Michael Sacchitello, CMT

Michael Sacchitello, CMT directs Intermarket Research for Stone & McCarthy Research Associates located in Princeton, New Jersey. Stone & McCarthy has been a leading independent research firm providing economic and market analysis to a sophisticated clientele of central bank representatives, money managers...

BEATING THE S&P 500 WITH MOMENTUM AND TREND FOLLOWING

Editor’s note: Riccardo Ronco is scheduled to make a presentation at the Annual Symposium in March. He provides research to institutional investors and will be sharing his latest research ideas at that time.

If you like a pure long-only, fully invested momentum strategy for US equities, there is an ETF for that – the iShares MSCI USA Momentum Factor ETF (MTUM).

It is a young ETF that started trading in the summer of 2013, but if you check in the DES field on your Bloomberg terminal you can see the underlying index, M2US000$. This index goes back to 1988 and that is great news because we can compare its total return against the S&P 500’s total return (see Figure 1). Both time series have been normalized to 100 starting in January 1988. You get still a 50% drawdown in the 2008-2009 period, but it has beaten the S&P 500 by 2.33 times since 1988.

We can see that momentum outperformance compared to a buy & hold of the S&P 500 has its own cycles: there are times when
momentum outperforms the market substantially and other times when this just does not happen.

The ratio between these two time series offers, therefore, an excellent insight about if it is more appropriate to be a momentum
(buy breakouts) or a meanreversion (fade breakdowns in this case) investor.

We can see the concept of a “momentum crash” in the two bear markets of 2000-2003 and 2007-2009. Momentum strongly outperforms then it badly underperforms on the way down and also, crucially, in the first leg of the new bull market (the so called junk rally).

Studying this ratio offers invaluable insight, in my opinion, on the kind of market “mentality” we are working with and we can better tailor our market analysis with this simple tool. Can we do better than buy & hold MTUM and avoid those nasty “momentum crashes” and keep, at the same time, the strong outperformance of momentum?

To answer this question, we apply a 10-month simple moving average on the S&P 500 total return from January 1988. We go long only when the S&P 500 is above the average and flat (with no interest earned when cash) when below.

We invest $100,000 using 0.5% commissions/slippage (no taxes considered). The results are in the top right corner of Figure 2. Although it’s a small sample with just 15 trades, we can still see the way trend following works: protecting capital during bear markets and deploying it in the next bull market. Trend following has always to be judged on a complete market cycle because during bull markets alone, trend following inevitably lags due to its nature.

The S&P 500 total return in buy & hold form increases our initial capital by 16 times with two 50% drawdowns, whereas the 10-month simple moving average model grows our capital 10 times with a 20% drawdown. However, we do not consider interest earned when out of the market and this could improve the final result, something to be kept in mind.

Now, let’s repeat this very simple exercise on the MTUM underlying index, with the same conditions ($100,000 with no cash earned when flat, 0.5% commissions).

As can be seen in Figure 3, we have multiplied our $100,000 starting capital 19.2 times whilst the drawdown stays the same at around 20%.

We can translate this simple strategy into the real world on the MTUM ETF, once a month…in a basket of other strategies, of course. Momentum and trend following must be used together in my experience to the benefit of both capital protection in a bear market and maximizing “beta” when long. If trading is like shooting, consider momentum (ranking) like aiming at your best target and trend following like pulling the trigger. This is my working “philosophy”.

Note: iShares MSCI USA Momentum Factor ETF (MTUM) seeks to track the performance of an index that measures the performance of U.S. large- and mid-capitalization stocks exhibiting relatively higher momentum characteristics, before fees and expenses. It can be used to help manage exposure and risk within a stock allocation Expense ratio: 0.15%

Source: iShares.com

Contributor(s)

Riccardo Ronco

Riccardo Ronco is a Senior Technical Analyst at Caxton Europe Asset Management. In this role, Riccardo follows large- and mid-cap  European and U.S. equities, paying attention to domestic and foreign equity indices, currencies, commodities, and interest rates. As a medium-term trend follower, his...

AN INVITATION FROM THE MTA NOMINATING COMMITTEE

The Market Technicians Association (MTA) is a dynamic association focused on building a strong community of market professionals, maintaining the highest ethical standards in the industry, and promoting the use of technical analysis in the investment process. Participating in the leadership of an organization like the MTA can be a deeply rewarding experience. It is an opportunity to work closely with industry leaders, to significantly further the mission of the MTA, and to have a real impact on technical analysis in the financial industry. You will also find the experience to provide great opportunities to improve yourself both personally and professionally.

So what is actually involved in serving on the MTA Board? What qualities should you look for when nominating other members? Is this a good role for you personally? Here are the expectations of MTA Board members, which I have boiled down to the “5 P’s.”

An MTA Board member should be…

  1. Passionate- have a passion for technical analysis and furthering the mission of the MTA
  2. Positive- encourage a positive and collaborative debate and discussion with a diverse group of volunteer leaders
  3. Present- able to participate in regular conference calls, as well as attend the Annual Symposium and other events as needed.
  4. Prepared- eager to pursue a deep understanding of the organization, its structures, and strategic plans for the coming years.
  5. Proactive- be an active participant in discussions, bringing past experiences from inside and outside the MTA to help further the organization

For the fiscal year commencing July 1, 2015, three (3) At-large Director positions are up for consideration for a 3-year term. Members, Honorary Members and Emeritus Members in good standing are invited to submit recommendations for consideration no later than February 28, 2015, and can be submitted via e-mail to nominations@mta.org. Individuals may nominate themselves or others. If you have any questions, please contact Tim Licitra at tim@mta.org.

Contributor(s)

ROHRBACH'S FIRST LESSON IN INVESTING

“When an investment is not going the way you thought it would, it’s important to sell it and take the loss.”

That lesson makes sense. By taking a loss, you preserve capital for the future. Avoiding the bulk of a decline means you have more capital to put to work after the bear market ends and that should allow you benefit more from the bear market.

In addition to being logical, this lesson was proven mathematically by Crestmont Research. As the chart below shows, if an investor had perfect timing and always sold at the top, they would only need to capture 27% of the upside to match the market performance. The chart shows the size of the loss in percentage terms on the x-axis and the amount of upside capture required to match the market average on the y-axis. For example, if you suffer through 40% of the decline before selling (40% on the x-axis), you will need to participate in 55% of the subsequent recovery to match the market.

In other words, avoiding losses is among the most steps towards long-term investment success. This is mathematical proof that there is no need to call the top – exiting after the bear market is confirmed, perhaps halfway through the bear market,and buying after the bottom is reached, again catching maybe half of the bull market, still beats buy and hold. As Crestmont Research explains:

The stock market is much more volatile than most investors realize. Two volatility gremlins–the disproportionate impact of losses and the friction loss from the dispersion of returns–significantly reduce the compounding of returns. Many absolute return-oriented investment strategies recognize this dynamic and seek to enhance investors’ compounded returns by providing a more risk-managed and consistent return profile. “Capture” is one way to measure and illustrate the effectiveness and benefit of this approach. Whereas the ‘relative return’ investor (tracking stock market indexes) will generally experience 100% of the downside and 100% of the upside to achieve market returns, the ‘absolute return’ investor only needs a fraction of the upside when downside losses are limited. The graph above illustrates just how little of the upside is needed to match stock market returns over time and it demonstrates the way that many absolute return strategies exceed stock market returns without having to “beat-the-market” each year.

(http://www.crestmontresearch.com/docs/Stock-Capture-Graph.pdf)

Taking a loss is an important investment lesson and the importance of this simple idea is difficult to overstate. None of us have perfect market timing skills and the math shows that perfect skills aren’t needed to beat the market.

Contributor(s)

Amber Hestla-Barnhart

Bio coming soon.

ETHICS IN FINANCE- ROBIN COSGROVE PRIZE 2014-2015

Competition for the Prize of $20,000 will be open until April 15, 2015. The Ethics in Finance Robin Cosgrove Prize seeks to promote awareness of ethics, integrity and trust in the finance sector, especially amongst younger professionals aged 35 years or less. The Prize invites young people from across the world to submit a paper (in English or in French) on Innovative Ideas for Ethics in Finance.

The mission of the Prize is to stimulate innovative ideas for promoting ethics and integrity in the finance sector. The Prize reaches out to young people familiar with the banking, finance and investment sectors, with special attention to emerging markets, to attract innovative ideas, proposals and projects which could be promoted to major players in the business community. The aim is to strengthen the sustainability of ethics in banking and finance and to reinforce its implementation, especially in emerging markets throughout the world.

The Prize is in memory of Robin Cosgrove, a young investment banker who worked in Tokyo and London. He was passionate about success and about his integrity. Robin believed that banks and the finance sector in general bring benefits to people and to commerce. Sadly, he lost his life in an accident on Mont Blanc. His family created the Prize in 2005 to encourage other young finance professionals to adopt Robin’s high ideals.

Robin believed that young professionals throughout the finance sector, whether in private enterprises of public services, have the responsibility and many opportunities to influence the future shape and sustainability of the world of finance, based on building trust and promoting integrity. The Prize implements his vision.

The Prize is relevant to both the public and the private sector. The CFA Institute and ACCA Global (Association of Chartered Certified Accountants) are also sponsors of the Prize, which is managed by the Observatoire de la Finance, a not for profit foundation registered in Geneva, Switzerland.

The best papers from the first three editions of the Prize, 2006-2011, were published in the 2012 book, Trust and Ethics In Finance. The International Monetary Fund (IMF) recommended the book as essential reading for its 2014 Seminars.

If you are interested in participating in the Robin Cosgrove Prize, please complete the “expression of interest” form. Your expression of interest is compulsory if you wish to submit an entry to the Robin Cosgrove Prize and to receive formal information (rules, application form, etc.) from the organizers.

The jury is expecting a forward-looking paper of between minimum of 3,000 and maximum of 5,000 words (30,000 characters including blank spaces and annexes). Final papers must be submitted in English or French. To learn more, please visit the Prize web site.

Contributor(s)

HOW TO LET PROFITS RUN AND CUT LOSSES

Cynthia Kase, CMT, MFTA, has decades of experience in the markets and understands how to consistently win. She has developed a number of new tools in the past few years and recently shared some of those tools in a webinar that is available at her web site.

Cynthia provided a preview of some of the ideas in the webinar in “Technical Analysis Keeps Traders on Track,” an article published in the January 15, 2015 issue of Bloomberg Brief: Technical Strategies that offered an example of the value of stops. For that article, she applied some of her tools to an analysis of Apple (AAPL).

A fundamental trader’s goal might be to hold AAPL as long as possible without ever experiencing a decline of more than 5%. To meet their risk management goals, the trader would need to apply technical analysis to close positions when necessary. The chart below shows one method for doing that.

Source: Kase via Bloomberg

As Cynthia explained in the Bloomberg Brief article, “The stops shown on the KaseX weekly AAPL chart are similar to the statistically significant Kase DevStops, defaulted for equities. The first level stops are for the highly risk adverse, and the second level stops are for riding trends.

The first stop reflects about 8% of underlying risk, and the second about 12.8%. The circled green triangle is June’s long entry. There was one close below the first stop, shown in red, and two hits, in blue. The second stop held. Longer-term positions in AAPL require a weekly chart.”

This demonstrates to her that a daily chart can be too sensitive for longer-term traders. The first level daily stop would have been stopped out more than once a month on average. Long-term traders would have missed the long-term trend because of their stops.

This chart also illustrates that traders need to prioritize conflicting goals. Maximizing gains in AAPL cannot be done without accepting an intraday decline of more than 5%. Cynthia notes, “I would trade the weekly, taking on level two risk in exchange for riding the trend.  As a compromise, I’d use the weekly’s first stop, monitoring shorter-term for possible threats.”

The weekly chart, as she shows in the webinar, would have kept you in the trade for the long term. The move is “cleaner” on the
weekly chart and you “don’t get kicked out of the trade.”

In the webinar, called “Maximize Gains – Minimize Risk with Five High Value Methods from Kase,” she demonstrated how Kase DevStops not only show statistically significant exit points, but also help determine what bar length to trade. Kase’s Xrange Bars
help smooth market action while fixing bugs inherent in “regular” range bars. This requires the ability to create bars of custom lengths, for example using 2- or 3-day bars. The newly introduced “Kaos Ratio” measures the degree of stability or irregularity in markets across bar lengths in a given security, which helps to determine bar length choice, and also across different markets in the same bar length, which helps to determine which security to trade and which bar length to use.  The Risk of Ruin indicator will help you determine how many units or dollars to trade within your risk parameters. Finally, KaseX add a third dimension to trading decisions by scaling up and down in bar length as the webinar demonstrates with real-life illustrations.

DevStops are based on the average true range (ATR) and standard deviations to find important levels for trade management. For example, she might use 1.2 standard deviations of the ATR for the first level stop and 3.8 standard deviations of the ATR for the highest level stop she likes to use.  It’s also possible to use a multiple of the ATR, for example doubling the value to create the DTR or Double True Range. The webinar explains this idea in much more detail.

XRange Bars can be useful for those who are uncomfortable using weekly charts instead of daily charts. The 3-day chart of AAPL demonstrates the value of these bars since there are fewer signals than the daily chart but less risk than the weekly chart.

The Kaos Ratio can be used to determine which bar length to use and which markets offer the best opportunity. Kaos Ratio quantifies the amount of irregularity or choppiness of a market and provides a normalized value that can be used to compare markets. Higher Kaos Ratios indicate there could be more outliers in the nearterm market action.

The formula for the Kaos Ratio is the ratio of the standard deviation of the double TR (DTR) to the DTR. It’s shown in the chart to the right.

A low Kaos Ratio, less than 0.4, indicates a narrow stop could be used for trading. As the Kaos Ratio rises, traders should consider increasing the size of their stops to avoid being whipsawed if they are trying to trade the long-term trend.

The Risk of Ruin can be used to determine the position size of a trade. The calculation can be complex but the value of the extra work is that the proper position size can help maximize the gain of any position.

The importance of this webinar is that Cynthia uses indicators to develop a complete trading strategy. That is a unique concept in trading analysis. Many analysts focus on the status of a specific indicator or focus solely on buy signals. Kase indicators provide information about what to buy, when to buy and sell and how much to trade.

Contributor(s)

Michael Carr, CMT

Mike Carr, who holds a Chartered Market Technician (CMT) designation, is a full-time trader and contributing editor for Banyan Hill Publishing, a leading investment newsletter service. He is an instructor at the New York Institute of Finance and a contributor to various additional...

WHY PASSIVE INVESTORS GET HAMMERED

Editor’s note: This was originally published in Proactive Advisor Magazine and is reprinted here with permission. For a nocost subscription to Proactive Adviser, click here. This article illustrates Rohrbach’s first rule of investing in practical terms.

If I had a hammer, I’d hammer in the morning
I’d hammer in the evening, all over this land
I’d hammer out danger, I’d hammer out a warning
I’d hammer out love between my brothers
and my sisters all over this land.
–“If I had a Hammer” by Pete Seeger and Lee Hayes, 1949.

“If all you have is a hammer, everything looks like a nail.” –Abraham Maslow

I don’t know if American psychologist Abraham Maslow ever met Pete Seeger, but they seem to agree about the use of a basic hand tool. Over the years, I have heard many variations of Maslow’s statement though the meaning has remained the same—those good with a hammer tend to see every new challenge as a nail.

Unfortunately, many investors get caught up in Maslow’s limited tool selection by restricting their choice of investment strategies needed to reach their financial goals. In reality, investors would probably be better off if they could diversify their selection of investment strategies to add depth to their portfolios.

In today’s investment world, however, the “hammer” tends to be in the form of passive asset allocation strategies that distribute portfolios among various stock and bond asset classes. A typical allocation might be 60% stocks and 40% bonds, usually based on computerized models following the concept of Modern Portfolio Theory as developed in the 1950s by Dr. Harry Markowitz.

And what a hammer it is! Asset allocation strategies using low-cost index funds, and now ETFs, have become the 800-pound gorilla of the investment world.

Don’t get me wrong. I’m not saying that asset allocation strategies do not have a place in an investor’s portfolio. What I am saying is that asset allocation has its shortcomings and should not be the only strategy employed by investors who want to meet their financial goals. Using only asset allocation is like a tool box containing only a hammer—useful in some applications, but hardly a universal wrench.

Unfortunately, limited tool selection can affect the quality of the investment. For example, risk management in a passive asset allocation portfolio is generally expected to come from low correlations among the asset classes chosen. The only problem is that actual experience during bear markets has shown that these low correlations can increase during down market cycles (remember 2008?). The result is that asset allocation’s tool to manage risk may disappear just when you need it most.

The same goes for maximum portfolio drawdown, a statistic indicating the portfolio’s largest drop from a peak value to a subsequent valley. During the two bear markets that occurred in 2000-02 and then again in 2007-09, the S&P 500 Index dropped in value more than 40% and 50%, respectively. Since passive asset allocation was the only tool in many toolboxes, there was no way for portfolios to escape the carnage. What if you needed your money at the bottom of the drawdown? It would be your tough luck.

Asset allocation believers offer the standard line that the market will eventually regain value, and for proof, they point to the fact that every drawdown has eventually been erased by the market. Well, every one except for the NASDAQ Composite’s 75%+ drawdown, which has still not been erased even after more than 14 years of market action. But buyand-hold aficionados don’t talk much about that statistic.

But let’s appease the hammerheads and acknowledge that the stock market usually regains its losses eventually—but at what cost?

Unfortunately, the price paid by many investors for following a passive investment strategy is often the most valuable commodity of all: time.

While the financial press continues to gloat about hitting new record highs, it conveniently ignores the fact that since the year 2000, the stock market has spent much of the time either losing money or regaining lost ground. And, when we talk about investors meeting their long-term financial goals, time is money.

Common sense tells us that time is an integral part of compounding’s ability to work its wonders. We’ve all seen the illustrations of how someone starting early with small contributions can end up with a larger nest egg than someone starting later, even though the latecomer may make larger contributions. That’s why we always counsel investors to start saving as soon as they can, even if it’s not a lot of money. Yet periodic significant losses can render the time advantage impotent.

And it gets even worse: not only do losses require you to use valuable time to recoup portfolio losses after a drawdown, but you have to earn a higher return to get there. As we all know, a 40% loss requires a 66% return just to break even.  That’s a double whammy if I ever saw one.

What’s needed is a way to sidestep losses during bear markets and major corrections, while remaining invested during up markets. Active investment strategies provide the potential to do just that.

Investment professionals need to diversify their clients among different investment strategies—both passive and active—and not just within a selection of various equity and bond holdings. Doing so could help portfolios weather the next storm (which some say is overdue) rather than getting hammered.

Contributor(s)

Mike Posey

Mike Posey is Director of Marketing for Theta Research, Inc., a third-party performance tracking and publishing firm. Theta tracks and documents the investment performance of managed accounts, resulting in independently verified track records. Prior to working with Theta, Mike spent more than...

BUCKET INVESTING OVERVIEW

Editor’s note: Bucket investing is a well-known financial planning concept. Technical analysts might discover their techniques can be applied within this framework to improve returns for the client and to increase business opportunities for the analyst. This article details the bucket approach and includes references to behavioral finance heuristics that contribute to its success. Readers will readily see how technical analysis can be applied within the various buckets.

Designing an asset allocation approach to meet a client’s financial objectives often is cited as the most important component of the investment advisory process. Despite the advent of Markowitz and Modern Portfolio Theory, this process cannot be easily reduced to a financial engineering problem. Economists have long made a key assumption within their models that is highly flawed for the purposes of simplifying the mathematical implementation: they assume that human beings only make rational decisions.

Nobel Prize winner Daniel Kahneman, a renowned expert in the field of “behavioral finance,” has said that: “Economists think of what people ought to do. Psychologists watch what they actually do.” Statman (2005) suggested that investors are neither irrational nor rational but rather “normal”—that is, they display elements of both characteristics.

Empirical evidence has shown that investors are indeed far from rational. In a classic study by Dalbar, the average equity mutual fund investor made a return of 5.02%, while the S&P 500 made 9.22% over the same 20-year period. The 4.20% return differential could not be explained by financial theory, and was famously dubbed “the behavior gap.” Investors lost over 60% of the returns available to them through poor market timing that was driven by emotional decision-making.

It can be argued that the most important job for an investment advisor or financial planner is simply to protect investors from themselves. Creating an asset allocation approach that can keep them invested and avoid selling risky investments at the wrong time is a difficult challenge. The “bucket” approach to investing has emerged as a popular asset allocation methodology in the financial planning and advisory community because it is specifically designed to account for actual investor behavior (Benjamin, 2011). Furthermore, it is highly compatible with the traditional financial planning objectives which require matching assets to meet future liabilities.

The essence of the bucket approach is to divide a client’s portfolio assets into several pools, or “buckets,” each with different planned goals, needs, or time horizons, and then design a separate asset allocation policy for each “bucket.”

For different investors, an individualized bucketing approach also reflects financial planners’ and advisors’ emphasis on case-by-case tailored solutions for their feepaying clients.

Asset allocation using the bucket approach utilizes discrete “buckets” assigned to asset type, such as bonds for income and capital preservation, or equities/stocks for capital appreciation. The simplest implementation of bucket investing would use only two buckets: bonds or cash to meet short-term expenses, and stocks for long-term growth (Evensky and Katz, 2006).

There are also more complicated “bucketing” strategies that use three to six buckets (Beaudoin, 2013). Intermediate “buffer buckets” can have more refined planning time horizons designed for growth or spending goals and thus be targeted at layered return objectives. From an investment management standpoint, a more complex bucket approach could use different portfolios for each bucket, and these portfolios could be formed using either assets or strategies (or both) with either a passive or active management overlay.

Throughout this paper we utilize a “wasting” bucket approach whereby we drain the income bucket of its assets via a fixed percentage annual withdrawal for ten years before turning to the stock bucket to generate the requisite returns to support the ability to make the annual withdrawal. Many financial advisors instead use a “waterfall” bucket approach (as is illustrated in the 3-Bucket Retirement Income graphic).

In the “waterfall” bucket approach, the income bucket is replenished yearly with flows from the longer-term bucket. This takes time and discipline to accomplish especially if done more aggressively, for example, quarterly.  These replenishments occur whether or not these longer-term buckets have generated sufficient returns to fund the withdrawal needed each year. In this way in a bear market they can eat into “principal” but the result is a more consistent balancing of risk among all of the buckets in total. However, as some commentators have noted it can be seen as an inefficient use of capital in that it overly invests in liquid assets during rising stock markets. As the examples in the Appendix point out, this approach has further advantages as the number of buckets used increases.

There are many reasons why a distinct bucketing strategy design might be appropriate for different investors, such as different tax brackets and/or opportunities to shelter income from taxation, or different planning objectives. For example, some investors have relatively short-term objectives, while others may have longer-term goals like saving for college tuition payments, retirement spending, or estate planning. To address these specific needs within the context of a client’s unique situation, the “bucket” approach often works well in a planning or advisory practice (Lucia 2004 & 2010).

In addition, part of the reason the bucket approach has gained popularity in the investment advisory and planning community is the anecdotal evidence from peers that it improves client communication and retention. Behavioral finance proponents attribute this success mainly to the fact that most investors have a “mental accounting” bias.

Coined first by academic researcher Richard Thaler (1999), “mental accounting” describes a person’s tendency to categorize and evaluate economic outcomes by grouping their assets into a number of non-fungible (noninterchangeable) “mental accounts.” People may alter their perspective on money and investment according to the surrounding circumstances and make irrational decisions due to such a framing bias. Behavioral life cycle theory (Shefrin and Thaler, 1988) submits that people mentally allocate wealth across three classifications: current income, current assets, and future income. The propensity to spend is greatest from the current income account, while many treat the source of future income differently.

A time-horizon-based “bucketing” approach for wealth management was designed to address psychologically both the safety of near-term liquidity need and the goal of long-term growth of wealth. In practice, a floor level of assets designated as a short-term “spending bucket” is often kept as cash or in short-term securities that have little or no investment risk.  Further, from a portfolio management perspective, planning “buckets” of capital under the framework of “goals-based investing” (Nevins, 2004), does institute beneficial risk discipline into the investment process.

The Myth of Time Diversification

One of the most important assumptions underlying the bucket approach is the theory of “time diversification.” This refers to the concept that investments in risky assets such as stocks are actually less risky over longer periods than shorter ones. In a traditional two-bucket approach, the least risky asset—typically short-term bonds—is held in the first bucket and used to service income needs, while the risky portion of the portfolio is invested in stocks (for the second bucket) for sufficient time to overcome any “bad luck” in terms of the start date (i.e. beginning of a bear versus the start of a bull market).

This assertion that sufficient time will reduce the riskiness of stocks is the subject of much debate in the academic community (see Kritzman, “What Practitioners Need to Know … About Time Diversification,” Siegel, “Stocks for the LongRun,” and Samuelson, “The Long-Term Case for Equities—and how it can be oversold”).However, the numbers and the math are fairly straightforward and suggest that this matter is much more settled than in question.

Kritzman notes that the key point of confusion is that the probability of losing money—which is mathematically and empirically supported to be lower over time—does not consider the magnitude of the potential losses. Like any investment, the “expectation” is a function of both the probability of winning or losing and the ratio of the size of profits to losses. The dispersion of compound returns (percentages) does shrink over time, but the dispersion of ending portfolio wealth (terminal wealth—the dollar value) actually increases over time. All of this is captured in financial options theory and pricing—and, in fact, the cost of option premiums does increase over time, which reflects the truth that time diversification is illusory (Bodie 1995).  Failure to understand this can lead to some faulty construction of the longer-term buckets.

To illustrate this concept we performed a series of Monte Carlo simulations using Brownian motion, which is a typically accepted practice for modeling financial time series. Figure 1 shows the distribution of compound returns for 5-year simulations assuming that the market has a return of 8% and a standard deviation of 20%. This chart shows the results of 25,000 simulations. Notice that there is considerable variability when holding stocks for such a short time period. While the distribution is skewed, maximum and minimum values are nearly identical.

Subsequently, we performed a simulation using a long time period instead. In this case, to make the results clear, we chose 100 years (Figure 2). Clearly, it is easy to see that as more time passes the distribution shifts to be almost entirely positive at every point in the distribution. These results are exactly the same as the ones produced by other authors to support the notion of time diversification.

The problem is that investors do not just get 100-year returns. Instead, they must compound them over time—in other words, every year they must effectively re-invest their portfolio and have their entire wealth fluctuate as a function of the next year’s investment return. This is why risk management is so important, because a 50% loss can erase over ten years of investment gains.

In the next set of simulations we show the distribution of terminal wealth (ending portfolio wealth) as a function of an investor’s holding period using the same set of assumptions. Notice that the maximum terminal wealth is just over $750,000, while the minimum is close to $20,000. For comparison we ran the same study using a 20- and then 100-year time frame. In both the 20- and 100-year holding periods there are multiple instances of portfolios that have an ending wealth that is below $10,000 (i.e. a greater-than 90% loss!), and in some cases close to zero! Of course, the magnitude of the possible gains is also substantially higher than for the 5-year portfolio, in some cases with billions of dollars being earned in the 100-year portfolio. Clearly, the variation in the outcomes of terminal wealth increases substantially over time.

The Sequence of Returns Dilemma

There are other related assumptions that are important to consider when using the bucket approach. For example, the sequence of returns is essential to determining ending portfolio wealth and whether or not an investor will be successful in achieving desired results.  Milevsky (“Can Buckets Bail-Out a Poor Sequence of Investment Returns?” (2006) claims that using the bucket approach or any other type of time-based asset allocation methodology is, in fact, just an optical illusion. Using the bucket approach cannot protect an investor from a poor sequence of returns; although it can potentially shift the risk to a different point in time depending on when the investor is most exposed to equities.

The key point that Milevsky makes is that, in fact, without doing more, the asset allocation of an investor using the bucket methodology will change substantially over time. For example, in Figure 6, we perform a 20-year simulation with stocks and bonds with a 4% withdrawal rate using a two-bucket approach, with each bucket given a 10-year time horizon.

Starting with a 50/50 portfolio of stocks and bonds, the bucket investor eventually shifts entirely 100% to stocks. In this simulation, the actual average allocation was 77% in stocks and 23% in bonds—which is a significant departure from the original 50/50 portfolio. The actual average asset allocation and timing of the shifts will depend on the underlying market performance, the number of buckets, and the length of each bucket’s time horizon.

This implies that the bucket approach is not easily comparable to a withdrawal strategy with, for example, a constantly rebalanced portfolio. However, as a general statement, the bucket approach is most exposed to equity risk at the end of the period and somewhat less exposed to risk at the beginning of the investment period. At the outset, withdrawals will be taken from the less risky asset and therefore create less dependency on equity volatility than a systematic withdrawal approach from a constantly rebalanced portfolio. This can present problems depending upon when equity or fund income risk increase and losses are incurred.

Case Studies: Simulations of the Bucket Approach versus Systematic Withdrawal Methods

To better illustrate some of these concepts, we ran a series of case studies using Monte Carlo simulation. We compare three basic methods: 1) Bucket Approach—this used a simple two-bucket approach (50% in bonds for the first bucket and 50% in stocks for the second bucket) where the bucket was liquidated and shifted to the next bucket at the end of its respective time horizon. We chose ten years as the time horizon for each bucket. 2) Systematic Withdrawal (SW) — this assumes a constantly rebalanced portfolio fixed at 50% in stocks and 50% in bonds. 3) Systematic Withdrawal TimeWeighted (SWT)—this is designed to be somewhat more comparable to the average asset allocation of the bucket approach. We used 2/3 in stocks and 1/3 in bonds in this case to reflect the fact that the bucket method has an investment in the stock portfolio that is twice as long as the investment in bonds.

We assumed that stocks would have an 8% return with a 20% standard deviation, and bonds would have a 5% return and a 6% standard deviation. The correlation between stocks and bonds was assumed to be zero. These assumptions are fairly reasonable from a historical standpoint.

For withdrawal, we assumed the investor would withdraw 4% annually for a total time period of 20 years. Using the bucket approach, each bucket lasted ten years and the first bucket contained bonds while the second contained stocks. To make accurate conclusions, we ran 25,000 different simulations and averaged the results.

One of the key metrics that we used to evaluate “success” for the investor was the Omega statistic (see Keating and Shadwick 2002: “A Universal Performance Measure”). This is used in option pricing and is a comprehensive risk measure that captures the upside versus the downside given a threshold return. The calculation of the Omega statistic is shown in Figure 7.

The Omega ratio is a relative measure of the likelihood of achieving a given return, such as a minimum acceptable return or a target return. Omega represents a ratio of the cumulative probability of an investment’s outcome above an investor’s defined return level (a threshold level), to the cumulative probability of an investment’s outcome below an investor’s threshold level.

The Omega concept neatly captures the notion of continuous expectation on investment. It divides expected returns into two parts—upside and downside, i.e. those returns above the expected rate (the upside) and those below it (the downside). Therefore, in simple terms, consider Omega as the ratio of upside returns (good) relative to downside returns (bad). The higher the Omega value is, the greater the probability that a given return will be met or exceeded.

For the purposes of our simulations, we randomly generated 1-year returns until we had a 20-year sample. To calculate Omega, we used the annualized returns of each simulation as returns in the inputs into the function.

For a base case (Figure 8), we wanted to show that there is no difference between the bucket approach and systematic withdrawal under the assumption that one uses the same asset in each bucket. This implies that creating different time horizons or liquidation schedules has no impact on performance. In all cases “ATV” represents the average terminal value, and “MAR” represents the return relative to the maximum drawdown (mdd).

Notice that the statistics are nearly identical between SW and the bucket approach. This is to be expected, since it is the same investment with the same risk and return used. In the first case, we show a more realistic example using reasonable assumptions for both stocks and bonds.

In this first case (Figure 9) we see that the systematic withdrawal approach (SW) has the highest Omega value—implying that it is the best choice for achieving a 4% withdrawal rate in the long run. The time-weighted systematic withdrawal had the next best Omega, followed by the bucket approach.  The MAR shows identical reward to risk rankings as the Omega in this case.

What is interesting is that the probability of failure is, in fact, lower for the bucket approach versus the time-weighted systematic withdrawal approach. This is consistent with the literature that use probability of failure approaches to justify the use of the bucket approach. However, as we have indicated, the Omega is a more comprehensive measure to evaluate success.

Another predictable outcome was that the bucket approach had the highest average terminal value (ATV) among the different approaches. The maximum portfolio wealth was also substantially higher for the bucket approach. This reflects the fact that: 1) the bucket method has a higher average stock allocation over time; 2) withdrawals are deferred from the equity bucket for ten years which shields the compound returns from the damaging effects of withdrawing early under volatile conditions; and 3) by avoiding rebalancing between stocks and bonds, the equity allocation is allowed to compound over time and grow within the portfolio. In summary, while using the bucket approach with traditional asset classes can potentially increase the return to investors, it does so at the cost of exposing them to a potentially lower chance of financial planning success (i.e. reaching their expected annual goal).

To examine the impact of the sequence of returns, we take a look at two different circumstances, the first with bad luck at the end of the period in the form of a 50% bear market in stocks in the last year (Figure 10), and the other where the bear market occurs in the first year the portfolio is invested (Figure 11). Since the bucket approach is 100% in stocks after the first ten years, we would predict that it would be more adversely impacted by bad luck or a protracted bear market near the end than a systematic withdrawal approach.

As expected, the bucket approach is severely impacted by a bear market in stocks that occurs at the end of the period.  The same results would be true to a similar extent if the bear market occurs at any point near the end of an investor’s time horizon.

The average terminal value of the bucket method is nearly a third of the value for either SW or SW/TW. Note that average return for the bucket approach across simulations is actually higher than for SW or SW/TW; the expectation is substantially lower due to the presence of adverse outcomes. The % failure rate where an investor runs out of money is an alarming 5.97%, which is more than five times higher than the SW/TW approach. In terms of planning success, the Omega ratio for the bucket approach is substantially lower than both systematic withdrawal methods.

In contrast to the last example, we would expect that “bad luck” at the beginning of the investment period would be more favorable for the bucket method. This is because the stock bucket is shielded from withdrawals for ten years, giving it a chance to recover without having to withdraw too much proportionately at the wrong time. It is arguably even more favorable for the bucket method in real life because the stock market exhibits predictable mean-reversion tendencies.  Let’s examine the performance on the simulated time series.

As expected, the performance of the bucket approach is superior in terms of average terminal value and, relatively speaking, the Omega is roughly on par with SW. This is in contrast to Case 2, where the Omega for SW is much higher than the bucket approach. This implies that SW is hurt much more by initial bad luck, and this is consistent across both SW and SW/TW.

In fact, the SW/TW approach demonstrates the major disadvantage of bad luck at the beginning of the period. The probability of running out of money is nearly three times that of the bucket approach. Furthermore, the Omega for SW/TW is less than a third of the bucket approach.

These results are likely to be true regardless of whether a bear market starts in year one or in the subsequent years that follow—of course, with a lesser magnitude of severity.

The bottom line is that the bucket approach is likely to be superior to a traditional systematic withdrawal approach that is more heavily weighted in equities (like a traditional 60/40 portfolio) when there is “bad luck” early in the investment period.  This supports the use of the bucket approach. However, when the “bad luck” comes late, if the bucket approach is invested in traditional asset classes on a buy-and-hold basis, the approach is not as effective.

Let’s now look at a case study (Case 4, Figure 12) using some real-life examples to better illustrate the point. In this case we will use actual stock (S&P 500 Index) and bond (10-year Treasurys) data, and run a simulation to compare the bucket approach to the two different systematic withdrawal methods. We use equally sized buckets for the time period and, again, a 50/50 portfolio of stocks and bonds at inception for all strategies.

In this case, the bucket approach falls between both systematic withdrawal methods in terms of Omega and failure rate, but shows lower average terminal values. This is because the correlation between stocks and bonds is highly negative over the time period, and a constantly rebalanced portfolio therefore will have a higher return than the same portfolio mix allowing for drifting allocations. In either case, the bucket approach shows superior planning success metrics than the industry standard, stock-heavy, time-weighted, static, systematic withdrawal portfolio.

The Bucket Approach and Active Management

One of the key failures of static asset allocation approaches is that all of them fail to follow trends in both returns and risk.  As we have seen, bear markets have been devastating to all forms of static allocation—especially if they happen at the wrong time. This is true regardless of whether one employs a constantly rebalanced approach (nearly impossible to implement) or the bucket approach. The key difference between these two methods is that when buying and holding traditional asset classes, the bucket approach is most affected by bear markets that occur toward the end of the investor’s time horizon, while the constantly rebalanced approach (with systematic withdrawal) is most impacted by bear markets that occur at the beginning.

From a practical perspective, since both of these methods were designed for retirement planning, the bucket approach has more psychological appeal. In theory, people that have just retired are most sensitive to their nest egg and may make rash decisions if they encounter a bear market early on. It is harder for them to be concerned about what may happen if they run out of money at some point in the very distant future. Human nature is to focus on the shorter term. However, the cost of running out of money can be severe—this can mean having no financial options at a point when the client is unlikely to be able to return to work. The bucket approach is more sensitive to this outcome, especially when employing a traditional buy-and-hold approach. Yet as Milevsky stated: bucketing cannot bail you out of a sequence of poor returns.

Active management, in contrast to traditional buy-and-hold investing which penalizes the bucket approach for “bad luck” in the later years, may provide an excellent solution. It focuses on responding to trends in return and volatility by shifting asset allocation throughout the holding period. Most active management approaches that are trend-following based will outperform buy and hold in an extended bear market. As a tradeoff, they may trail on the upside in bull markets. However, in aggregate they produce the smoother return profile that is ideal for financial planning since it typically is not as sensitive to “bad luck.” By using active management with the bucket approach, it is possible to produce a nearly ideal scenario that is designed to keep investors invested for the long term while protecting them from events in the future that may devastate their portfolios.

Combining Fusion with the Bucket Approach

Fusion is our premier active management solution at Flexible Plan. We dynamically combine active management strategies with traditional asset classes into one portfolio to hit a targeted maximum drawdown. The goal is to provide an ideal solution that permits potentially superior returns for a given level of portfolio risk.

Fusion responds to trends in returns and risk and also to the correlations between strategies and assets to dynamically shift portfolio allocations at least monthly.

Fusion is the financial equivalent of “cruise control” in your car: as the car starts going too fast above the target speed, the cruise control tells the car to slow down, and if you are going too slow, the cruise control tells the car to speed up.

Fusion has six primary suitability profiles, and for this paper we will focus on the most conservative and the most aggressive (the performance breakdown of the different suitability profiles can be found in the Appendix). Because they have different targeted risk levels, each profile can fill the investment needs of individual buckets. Using the two most extreme Fusion profiles is comparable to a standard two-bucket approach that uses a very conservative investment in the first bucket and equities in the second bucket for maximum capital appreciation. In the simulation (Figures 13-15) we use the historical performance of the Fusion Indices from 1998 to the present (made available by the New York Stock Exchange on most quote platforms). We use a 4% withdrawal rate, which is consistent with our previous simulations.

In this case, the buckets are divided into two nearly equal-sized portfolios over the 15-year period. In Figure 13 we compare a traditional systematic withdrawal approach that maintains a 50% constantly rebalanced allocation (SW) to both Fusion Conservative and Fusion Aggressive, with a standard two-bucket approach (Bucket).

It is true that consistent with our previous simulations, the Omega is higher for the systematic withdrawal approach versus the bucket approach—thus the probability of financial planning success is higher at first glance. But the average maximum drawdown for the bucket approach was a very tolerable 17.4%—which is less than a third of the maximum drawdown of the S&P 500 over the same time period and only 6% greater than a constantly rebalancing approach. Most investors can tolerate drawdown levels of less than 20%.

Given that an investor’s risk and financial objectives are thus being met by either approach, it is worthwhile comparing the difference in returns between the two methods: the bucket approach has a compound return that is nearly 2.5% higher, and an average terminal wealth that is nearly 80% higher than for the systematic withdrawal approach.

Fusion is an active management approach that is designed to maximize returns per unit of risk. The cost of using the bucket approach and letting the aggressive portfolio “ride” while starting to withdraw from the conservative bucket is mitigated significantly through risk management.

In the graph (Figure 14), we compare a constantly rebalanced systematic withdrawal approach (SW—50/50 initial allocation, 4% withdrawal) using the Fusion Aggressive and Conservative Index values (purple line) versus the SW approach using the traditional, buy-and-hold S&P 500 and Treasurys portfolio (green line). Additionally, we display the two-bucket approach first using traditional assets (red line) and then replacing bonds with Fusion Conservative and stocks with Fusion Aggressive (blue line). The results are summarized in Figure 15.

Note that in this case we are able to calculate daily Omega values because we have daily returns available. This makes the difference in values and magnitude much less pronounced than using annual values as we did in the previous simulations.

What is striking is that the bucket approach outperforms the systematic withdrawal approach using active management (Fusion), but underperforms when using the passive approach with stocks and bonds as is typically employed in the financial industry. The daily Omega values are nearly identical for Fusion SW and Fusion with the bucket approach, but the returns are nearly 3% higher for the Fusion/bucket approach. In contrast, the returns are nearly 1% lower for the bucket approach with the passive portfolios, and the Omega was also slightly lower.

Whether using active or passive management, the drawdowns for the bucket approach are higher than for the systematic withdrawal method, but the Fusion actively managed bucket approach has a more tolerable 30% drawdown versus the nearly 60% drawdown with the passive portfolio.

History provides a good example of how the bucket approach can survive being unlucky, even if faced with a bear market near the end of the period. Investors in a passive portfolio would have been exposed 100% to stocks when the 2008 bear market began, which is why the resulting drawdown was so severely felt by them. Few investors would be able to sustain that level of drawdown (almost 60%) and still continue with the same asset allocation. Fusion experienced a maximum drawdown of about half that level.

Which Fusion Profile for which Bucket?

We performed 25,000 simulations to determine which Fusion suitability profiles were best for different levels of targeted returns (withdrawal rates). We compared these profiles to stocks (S&P 500), bonds (Treasurys), and a 60/40 portfolio of stocks and bonds.  In this case we used a standard systematic withdrawal method since there was only one suitability profile used in each of the groups in the simulations. The purpose was to determine which Fusion suitability index would be ideal for a bucket with a given target return.

Figure 16 illustrates that by simply using Fusion Enhanced Income and Balanced one can achieve the highest probability of success (bolded results).

Figure 17 shows the greatest MAR (ratio of return to max drawdown) can be achieved by the same profiles.

Figure 18 adds time horizon into the index to discover the probability of success for Fusion and traditional asset classes in meeting both the withdrawal needs and the requisite time horizon. All of the Fusion profile indexes demonstrate a better than 90% probability of success.  In contrast, the buy-and-hold asset classes and 60/40 portfolio seriously lag.

Summing up our findings, what is striking about the results deployed in Figures 16-18 is that all six Fusion profiles outperform the
asset classes and a 60/40 portfolio at all levels of return/withdrawal rates. As expected, as the target return increases, the optimal Fusion profile also increases its risk profile. However, since the maximum target returns are modest in relation to historical
Fusion Index returns, Fusion Balanced is the most aggressive portfolio required to maximize the probability of planning success at the 8% target return  level. In addition, it’s clear that rather than limiting one’s investments to both the more limited risk and return of the Moderate portfolio, the use of even more aggressive Fusion portfolios (designed for higher returns) can be justified and still potentially outperform the use of traditional buy-and-hold asset categories using the bucket system.  

Conclusion

In this paper we compared the bucket approach with a more traditional systematic withdrawal approach with a constantly rebalanced portfolio. We show through simulation that the bucket approach is a tradeoff that can increase returns versus a traditional approach and tends to reduce the impact of bad luck at the beginning of the investment period, but it is more sensitive to the impact of bad luck at the end of the planning period. In general, a traditional approach tends to have a higher probability of planning success because diversification is maximized and risk is minimized by rebalancing to a constant mix.

However, we discussed the possibility of using active management within the bucket approach—which has major implications at the aggressive end of the portfolio. Our studies show that this reduces the gap in planning success and downside risk between using either the bucket approach or the systematic withdrawal method to the point where there is a negligible difference between the two in practical terms. At the same time, however, the bucket method with active management shows the potential for much higher returns, and given its greater psychological appeal to investors, it is a more ideal combination.

Financial planning and investment management cannot be applied in isolation. Both need to be comprehensively integrated in order to achieve client objectives. Dynamic allocation across investment strategies and asset classes along an efficient frontier represents a theoretically desirable approach to optimize investment performance for a targeted level of return.

In our simulations, active management outperformed whether using the traditional systematic method or the more psychologically appealing bucket approach. Furthermore, in implementing the bucket approach we found that using different Fusion suitability profiles for different target return buckets proved to be a promising method of further integration to maximize the outcome from a bucket approach to financial planning.

Appendix: What is Bucket Investing and how does it work?

The example (Figure a) shows a 3-bucket system with a 5% systematic withdrawal each year. Bucket 1 has a 5-year lifecycle while Bucket 2 has a 10-year lifecycle. Bucket 3 remains open until its funds are depleted. The systematic withdrawal occurs only in the bucket that is currently “active.” After the 5th year, bucket 1 will transfer any remaining money into bucket 2, which will then begin experiencing yearly withdrawals. If any bucket’s money is depleted before the maximum holding period for that bucket has elapsed, the bucket system will transfer money out of the current bucket at the end of the year into the next bucket, which will then receive the annual withdrawals. This systematic withdrawal algorithm applies to all of the buckets in the system except for the final bucket, which will remain open in perpetuity or until depleted.

To build simulations of potential portfolio outcomes, we generated 10,000+ bucket system portfolios using a simulation application designed specifically to model the bucket system. We used the algorithms outlined in Figure b & Figure c to generate each portfolio’s yearly returns. Each equity path represents the portfolio’s year-end price streams. (Figure a shows one simulated equity path using end-of-year prices.)

Monte Carlo Simulation

To illustrate this concept, we performed a series of Monte Carlo simulations, which is a widely accepted practice for modeling financial time series within the industry. Monte Carlo simulation uses what is known as risk-neutral valuation to generate return simulations. We used stochastic differential equations with geometric Brownian motion to generate random time series based on a given mean and standard deviation.

A stochastic process (St) is calculated using a percentage drift (Mu), percentage volatility (Sigma) and Brownian motion factor (dWt). The variable, “dt,” is the time step used for Mu and Sigma values (Figure b). The analytical solution for Figure b is Figure c.

The Box-Muller transformation (Figure d) is used to generate normally distributed random numbers using independent random numbers: U1 and U2 are independent random numbers that are uniformly distributed between 0 and 1. We then use the Mersenne Twister, a high-quality, pseudo-random number generation algorithm to generate these independent, random numbers.

This gives you two independent random numbers, Z0 and Z1, each with a standard normal distribution.

To generate a full time series, we recursively call the above algorithm for the required number of data points. We used yearly CAGR and standard deviation for Mu and Sigma where the time step is one year and the initial portfolio value is 100,000 for all simulations.

Bucket Return Correlation

In the real world, single bucket returns have some degree of correlation to the other buckets. To simulate this important feature, we used the Cholesky Decomposition, or Cholesky Factorization algorithm, to integrate correlations into our individual simulations, for example, using the equations in Figure e to generate random returns for two correlated assets.

X1 and X2 are normally distributed, correlated random numbers, while Z1 and Z2 are normally distributed, uncorrelated random numbers. In applying the LU Decomposition algorithm to the correlation matrix to an uncorrelated sample, we can generate randomly correlated financial time series for the buckets.

Omega Values for Probability of Success

To calculate Omega on these portfolios, we calculate the CAGR (Compound Annual Growth Rate or Return) for each simulation using year-end prices for each bucket system portfolio.

The formulae of Omega (Figure f where F(x) is the probability density function of return x) is implemented as OMEGA = Excess Sum of All CAGR Values above Threshold / Deficiency Sum of All CAGR Values below Threshold Geometric OMEGA, or GOMEGA = Excess Average of All CAGR Values above Threshold /Deficiency Average of All CAGR Values below Threshold.

We also used a yearly % ranking of all simulations (year-end price series) to generate the 20th, 50th, and 80th percentile of equity paths.

Normal Investment Simulation vs. Bucket Investment Simulation for 20-Year Period (Monte Carlo Simulations):

  • 0.5 Correlation between all buckets
  • 5% Systematic Withdrawal
  • 4% Threshold for OMEGA
  • 10% CAGR and 10% Risk for all buckets
  • $100,000 Initial investment equally-weighted to each bucket
  • 10,000 Simulations for each system

REFERENCES

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Contributor(s)

Jerry C. Wagner
David Varadi
Z. George Yang, Ph.D. & CFA

Z. George Yang, Ph.D. & CFA, is the Co-Chief Investment Officer, Senior Portfolio Manager; Jerry C. Wagner, J. D., is the founder and President of Flexible Plan Investments, Ltd, a US registered investment advisory firm. David Varadi is the former VP Economic...

2015 NAAIM WAGNER AWARD CALL FOR PAPERS

In 2009, the National Association of Active Investment Managers (NAAIM), launched the NAAIM Wagner Award is designed to expand awareness of active investment management techniques and the results of active strategies through the solicitation and publication of research on active management. $10,000 is presented annually for the best paper submitted to the competition.

NAAIM is now accepting papers for the 2015 Competition. The deadline for the full papers is Monday, March 2, 2015. Along with a $10,000 first prize, the NAAIM Wagner Award competition also often awards a $3,000 second prize and $1,000 third prize (given at the judge’s discretion).

The competition is open to all investment practitioners, academic faculty and doctoral candidates who submit an innovative topic in the area of active investing. This can be either a documented and justified investing ap-proach or an exploration into the validity of active investing. Active investing topics can involve making invest-ment decisions using technical analysis, quantitative analysis, etc. Papers can also address related topics such as position sizing techniques, money management approaches, scaling into and out of trades, exit strategies, etc.

Papers must be of practical significance to practitioners of active investing. An ideal paper provides evidence of the validity of an active investing approach via an example of a trading system that outperforms the market by some well accepted metric such as risk adjusted return, annual return, drawdowns, etc. Examples of supporting evidence sought include backtesting details and parameter sensitivity analysis. Sufficient trading system detail should be provided such that practitioners could replicate the approach. Other criteria used in judging will in-clude the quality of exposition, analytical rigor, and novelty of results. A jury of scholars and investment profes-sionals will review entries and award the prizes.

To learn more or to submit a paper, click here.

Contributor(s)

MASTERS IN TECHNICAL ANALYSIS: JIM ROHRBACH

“There are really only two good feelings in investing. One is being in the market when it is going up, and the other is being out when the market is going down.” Jim Rohrbach

Jim Rohrbach is the President and founder of Investment Models®, Inc. He is a Registered Investment Advisor and has written a weekly stock market time newsletter for the past 37 years. His career as a market timer began after a 25-year career with AT&T where he held various operations and staff management positions. After that, he turned his attention to the stock market and has developed two Market Timing RIX® Indexes. With these indexes, each day he converts the stock market action into a number that represents the trend of the market. This allows for market timing signals that are precise with no what ifs, maybes, or hedged statements. 

Jim was repeatedly been ranked as the number 1 market timer by Timer Digest, most recently for the first six months of 2014. His newsletter has also been highly ranked by the Hulbert Financial Digest. Other honors include receiving the second highest number of votes for Guru of the Year on TheStreet.com in 2001. Jim has been the subject of a number of feature stories and his work has been widely quoted in the media.

Jim’s success is due to market timing. He doesn’t try to predict the future course of the markets. Instead he focuses on identifying changes in the direction of the trend that are confirmed after the top or bottom. These signals allow him to take advantage of the bulk of the up moves while avoiding most of the drop. This strategy has been successful as demonstrated by the extensive track record provided at his web site.

His investment philosophy is as important as his methods. Jim remembers that he learned the first lesson in investing in 1965. As he recalled,

“I used to go to the Boardroom at Merrill Lynch in Boston during my lunch hour to watch the market. I was just learning about investing at the time. Every day I would see this young man sitting there. One day I sat next to him and asked him if he worked in the area. He told me he didn’t work but was a trader. He said he went to the financial library every morning and spent his entire day watching the market. I told him I was just learning about investing and he asked me if I had learned the first lesson in investing. So I asked him what it was. He said it was learning to take a loss. I told him that I had taken losses. He then said, “But have you learned to deliberately take a loss. When you make an investment that is not going the way you thought it would do you sell it and take the loss.” I have never forgotten that lesson.

Taking a loss at the right time may be the best decision anyone can make. We tend to stay with a losing investment and hope that it will go back up. Sometimes we wait too long and say well I can’t sell now so I will just wait until it gets back up to what I paid for it and then sell. Well maybe it will take a long time or never get back to what we paid for it.”

The second lesson in investing is to ride winners as long as possible. This is where market timing comes in and that is what the Market Timing RIX® Indexes are designed to do.

To understand the value of selling, Jim uses several examples.

But people say, “I am in the market for the long term.” Nothing wrong with that concept, but personally I hate to see my investments take a big hit like the one that occurred in October 1987 when the value of portfolios took a 25% drop in one day. Or in the summer of 1998 when they went down 25 % in a few weeks. My clients avoided those drops and were able to repurchase the same mutual funds at much lower prices. In fact we have avoided every Major Drop in the market since I started selling my service in 1978. Just luck? No excellent Market Timing.

There are limits to market timing. In fact, a prolonged up market can outperform market timing. However the knowledge that we are in a prolonged up market is available only in hindsight. Over the long run, timing can outperform a buy and hold and strategy simply because timing signals should allow investors to preserve profits by avoiding large declines.  Timers strive to get out of bear markets early and repurchase when the prices are much lower. Jim notes that “they sleep well, and you can’t put a price tag on that.”

Timers avoid the problems of those trying to pick tops and bottoms. Although many investors are looking for the top in the current market, history tells Jim that no one will consistently time this top, the next bottom and the top after that. Jim learned years ago,

It’s impossible to get in at the exact bottom or out at the exact top. Seems like everyone is looking for the expert who can look into the future and tell them when the top or bottom is coming. If you haven’t figured that one out yet, let me be the first to tell you that person does not exist. Oh you hear it every day on the financial programs.

“So and so” says this market is going up for the next six months and the Dow will go up 2000 points. Or this market is going to crash like it did in 1929 and you better get out now and stock up on dried beans… For some reason I can’t seem to be able to look into the future, but I can mathematically identify changes in the direction of the stock market after they have started and close enough to the tops and bottoms to make the Ssgnals very valuable.

Timing signals are not perfect, but over the last 40 years, 4 out of 5 trades Jim’s signals identified have yielded positive results. This is true despite the fact that like all timers, he will occasionally experience whipsaws and take small losses which Jim believes are part of his success.

That’s the key, we take small losses. The gains, however, are sometimes very large, because we stay with the up trend for as long as it runs. To be a good market timer you have to be able to control your emotions. You have to believe and rely on the timing system and not say to yourself, this is the wrong time to get in or get out. If the timing system is good and has a long proven track record…you have to be able to go with it and not get excited about the daily market fluctuations. You have to stop thinking “gee, I should have gotten in or out last week.” Because last week you didn’t feel that way and only hindsight gives you that 20/20 vision this week.

Since 1970, Jim has beaten the market with an average annual return of about 17% at a time when the S&P 500 gained about 10%. For more information, please visit www.investment-models.com or email Jim at jrohrbach@investmentmodels.com.

Contributor(s)

Amber Hestla-Barnhart

Bio coming soon.

SHAKE OFF THOSE WINTER BLUES WITH THE RIGHT STOCK SELECTION

Editor’s note: This report was originally published by Phases & Cycles on January 20, 2015 and is reprinted here with permission.

The sixth gain in a row for the Dow, new all time-highs for the S&P 500 and double digit gains for the Nasdaq – no wonder the New Year’s parties featured large crowds dressed in bullish costumes shouting “wow” and “oh” and “bring it on!”

After such festivities it didn’t surprise us that investors woke up the next day with a headache. We wrote: “Expect an intense battle between bulls and bears to open the year.” This is exactly what happened in the first weeks of 2015.

Following a tour-de-force rally out of the October lows, the North American indices started on a series of rallies and selloffs. As usual, market participants found their “excuses” to sell or buy; one day it was euphoria about economic growth, another time it was panic about the currency tribulations and oils.

As a result, the U.S. indices started the new year violently, inside a wide horizontal trading range. The key indices slashed through (both up and down) their 50-day Moving Averages on several occasions – an indication of corrective forces at work. Most importantly, this action has been taking place above rising 200-day Moving Averages and long-term rising trend lines, affirming the long-term health of this tired but still bullish market.

A similar battle between bulls and bears has been playing out in Toronto; however, the stakes are much higher there.  Since October, the S&P/TSX composite has been trading mostly below its flattening 200-day Moving Average – dragged down by Resource and Energy stocks – but above the line of support connecting its October and December lows.

As usual in such range-bound trading, technical indicators send mixed signals. The recent volatility and nervousness has been peeling off bullish sentiment. The cycles currently at work allow for the markets to pause for an extended period – most likely until spring.

While the market correction may take investors on sudden swings, not all areas are affected equally. One of the trademarks of trading ranges is the increased discrepancy between sectors and stocks. While the leaders of the year-end rally in New York, technology and health-care stocks, may pause for a while, battered areas such as Energy and Banking stocks may stage recovery rallies. In Toronto, a relief rally in Energy and renewed interest in Golds could help the Index to challenge its 50-day Moving Average.

After a spectacular 2014 and an impressive end-of-the year rally, exhaustion has finally caught up with the markets. This fatigue manifests itself in increased volatility and range-bound trading, which could define the market action for the first months of 2015. This roller-coaster ride could trigger confusion and even bearishness among investors, but this is exactly what this bull market needs.

Investors should view the current volatility as a necessary evil and concentrate instead on individual names, which could lead the
next phase of this bull market. Those more adventurous could enter selective Gold stocks, anticipate recovery rallies in Energy and Banking stocks and use sell-offs as buying opportunities in leading Technology stocks.

The tug of war between bulls and bears is best viewed on the S&P 500 chart.

Following an impressive rally out of the October low (A-B), the S&P 500 settled into a horizontal trading range marked with a series of rallies and sell-offs. During this time the Index has been trading between the 2100 resistance and the 1975 support. A decisive move in either direction would be of great significance for the Index. However, be aware of fake violations and traps, which occur very often at this stage of a bull market.

A sustained decline below the 1960-1970 mark would be very negative.

Unlike its U.S. counterparts, the S&P/TSX composite has never fully recovered from its September-October sell-off (A). A relief rally brought the Index briefly above its 200-day Moving Average last November (B), however the heavily weighted Energy and Resource stocks caused the Index to tumble once again toward previous lows (C).

The fact that the 13,630 support was successfully tested twice suggests that the Index may try to regain its bullish footing.  A key resistance to watch is 14,500-14,750 area. A decisive rally above this level would not only put the Index above its 50-day Moving Average, but also cut through an important declining trend line (see dashed line).

The bulls must defend the 13,630 supports at all cost. A violation of this support would bury any chances for a positive resolution.

Contributor(s)

Ron Meisels

Ron Meisels is Founder and President of Phases & Cycles Inc. with over 50 years of stock market experience.  He specializes in the independent research of Canadian and U.S. securities and market using Behavior Analysis.  Institutions ranked him among the top three analysts...