Technically Speaking, December 2012

LETTER FROM THE EDITOR

This month, we are highlighting several examples of work that may be at the leading edge of technical analysis research. Robert Prechter, Jr., CMT, popularized Elliott Wave and is probably the individual most responsible for its worldwide popularity. He has continued studying wave patterns and extended that study to socionomics, a field he developed and discusses in this issue.

In addition to demonstrating his personal brilliance, socionomics demonstrates how the knowledge gained in the study of technical analysis can be applied to other fields. A detailed example of socionomics, demonstrating the link between the public mood, stocks prices and Presidential elections, is also included and readers should consider downloading the full paper. Manuel Amunategui then offers an intriguing idea that addresses some of the problems created by 24-hour trading. In some markets, the open and close have become less significant but the technique Manuel presents could help redefine price charts in these markets.

December marks the end of the year and an end to a special discount price available for the Annual Symposium. The speakers, including Robert Prechter who will be sharing his latest work, promise to deliver value to any trader and analyst. Please tell us what you think about the newsletter with an email to editor@mta.org.

Sincerely,
Michael Carr

What's Inside...

SOCIAL MOOD, STOCK MARKET PERFORMANCE, & US PRESIDENTIAL REELECTIONS

Many readers of Technically Speaking know that former MTA president Robert Prechter, Jr. has pioneered the field of socionomics, which...

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AN INTERVIEW WITH ROBERT R. PRECHTER JR.: WHERE I BELIEVE SOCIONOMICS IS HEADING

Socionomics Institute Director Mark Almand interviews MTA member and founder of the Socionomics Institute, Robert Prechter, Jr.

Mark Almand: Socionomics...

Read More

INTERVIEW WITH KATIE STOCKTON, CMT

How would you describe your job?

My job is to provide technical research to institutional clients, including mutual funds and...

Read More

THE THREE-BAR TRADING DAY

The Three-Bar Trading Day is a quick way to gauge market participation by separating the trading day into three parts:...

Read More

MTA BLOGS

Editor’s note: The blogs on the members’ section of the MTA web site are a valuable source of short-term trading...

Read More

AN INTERVIEW WITH ROBERT R. PRECHTER JR.: WHERE I BELIEVE SOCIONOMICS IS HEADING

Socionomics Institute Director Mark Almand interviews MTA member and founder of the Socionomics Institute, Robert Prechter, Jr.

Mark Almand: Socionomics seems to be gathering steam. You have a monthly publication called The Socionomist. In addition to the two you wrote, three books about socionomics have now been written by others and published, including Peter Atwater’s “Mood and Markets” this year.  Five academic papers are now in print, your annual socionomics summit is on its third year, you and others have presented socionomics at the world’s most prestigious universities, and a handful of professors have taught socionomics classes. Even the media is getting aboard with coverage of your recent Elections study. You must be pleased.

R.P.: I always feel that it’s taking too long for people to discover socionomics. But when I review the latest developments, I realize that progress is coming along nicely. So thanks for the reminder.

For the benefit of new readers, how about an “elevator speech” definition of socionomics?

Socionomics is the study of social mood and its consequences in social action.

What’s the hardest thing for most newcomers to grasp?

That social mood motivates social actions instead of the other way around.

Can you give me an example of how this causality works?

There are millions! Here is one: Most people think that recessions make businesspeople cautious. Socionomics says the opposite: Cautious businesspeople make recessions. So, the mood is the cause, and the event is the result.

Why is this insight important? What can it do for people?

Start with the above example. If you grasp that social mood is what moves the economy, and you can measure mood, then you can identify when and where recessions are most likely to occur. You can get out of the way.

And socionomics says that you can measure mood via the stock market?

Yes. For a variety of reasons, the stock market is an excellent meter of society’s mood. People can act on their moods immediately by buying or selling stock. But decisions they might make at the same time to expand or contract a business, or to draft a peace treaty or declare war, take time to  effect. So there is a lag. This is why the stock market predicts the character of news, not the other way around.

How did you first realize that socionomics is a force in society?

I was working for the Merrill Lynch Market Analysis Department. I studied the Wave Principle, cycles and technical analysis and watched the stock market confound the fundamental analysts time and again. It became obvious to me that news lagged prices, not the other way around. So I became committed to the idea that the market moves independently of such outside events as elections, the Fed, interest rates, economic news and social events. I realized that those events have no predictive value as far as the stock market is concerned, at least not in the way most people read the news.

When did you start writing about socionomics?

In 1979, I went independent and started a publishing company. In December that year I wrote my first socionomic declaration. It’s at the start of Pioneering Studies. In 1984 I wrote another one. Then in 1985, I wrote a report titled “Popular Culture and the Stock Market,” which was boiled down for a Barron’s article. That sort of kicked things off. Then a small segment of the public got interested.

Were you a pure socionomist from the start?

Socionomics is deeply counter-intuitive. I had to go through a long process of weeding out misconceptions from my mind that had taken root there long ago. An early example was the idea that interest rates buffet the stock market. Economists are sure it’s true. My colleagues were convinced of it. It makes sense. It’s also quite wrong. If someone told you the course of interest rates in advance, you couldn’t predict stock prices. The stock market moves on waves of social mood. If you know that, you know more than the person who knows where interest rates are going. And, of course, no one knows where interest rates are going. Except that sometimes socionomists do know, because we study the history of waves and their attending social attributes.

What was the next big insight?

By 1999, I had become an almost complete purist. I was able to turn every exogenous-cause argument on its head: prove it was wrong, and then show that socionomic causality successfully explains the very same data. But I still had this residual belief, carried from the past, that the Federal Reserve had the power to control the money supply and thereby move markets around.  One day I realized that this idea, if it were true, challenged the whole socionomic model. I posed the same question I always did: When I reverse the order of causality, how does it re-form the question? So instead of asking how the Fed controls the markets, I asked how the mood behind the market controls the Fed. I discovered that people create central banks at certain times in the wave structure. I plotted interest rate data and realized that the Fed just follows the T-bill rate, which is set by the market. I studied the Fed’s historical actions and realized that the Fed does not act; it reacts. The whole Wizard of Oz image went up in smoke. That was my last bout with exogenous causality.

Was it useful?

Oh, yes. This specific exercise proved very useful, because it led me to an understanding of credit and the Fed that allowed me to write a unique book predicting deflation.

I am sure that along the way, you had several additional major breakthroughs. What were the key one or two?

Well, I had to tie all my ideas together theoretically. For one thing, I realized that the causality attending economics and finance are completely different. This is also an idea that, as far as I can tell, no one had proposed before. I wrote about it with Wayne Parker in a paper for the Journal of Behavioral Finance in 2007.

Realizing that the Elliott wave model described the structure of waves of social mood—not just financial pricing—was another
insight. I also figured out that most financial thinking is rationalization, not reasoning. One evening in 2004, I developed a diagram that shows how all the related ideas fit together.

Has anyone ever shared an “aha moment” of their own regarding socionomics with you?

A number of people have come up with valuable insights about socionomics.

Wayne Parker proposed a metatheoretical context for the theory, which was very important. Also, Wayne and I collaborated to come up with the distinction between mood and emotions. Alan Hall and I figured out that the center of wave 3 is the mood-direction delineator, an idea that we wrote up for The Socionomist. Other people have done some excellent supportive studies. Pete Kendall showed how the sport of basketball has grown and contracted in concert with social mood, and he has linked the
outbreak of fighting in the Middle East with worldwide social mood peaks.

Working from a suggestion from Pete Kendall, Professors John Nofsinger and Kenneth Kim demonstrated a strong relationship between stock market trends and the timing of when the government adds and removes regulations on investing. Mark Galasiewski connected stock market trends to the popularity of automobile colors; DuPont included it in its annual Automotive Color Popularity Report, and Radar magazine wrote it up. And Brian Whitmer used socionomics to predict the Greek debt crisis and a coming breakup of the European Union. There must be three dozen such contributions.

When Brian published his report, the media said nothing. There was no interest. Then a few months later when the Greek debt crisis occurred, it was a bit late to take action. This kind of thing happens regularly, doesn’t it?

Socionomic insights are their most useful precisely when most people are least inclined to pay attention to them. It is unfortunate and ironic, but socionomic theory explains why it is also axiomatic.

You also mentioned mood versus emotions. What is the difference?

Emotions are exogenously referred, consciously experienced feelings, regulated by a combination of mood, conditions and events. Mood is an endogenously regulated, unconsciously experienced mental state, regulated by Elliott waves.

Mood predisposes people toward certain emotions. But before a person can experience an emotion, he must have a referent. People in a positive mood trend might credit a political leader or a musical group for their happy feelings. People in a negative mood trend might blame a political leader or their spouses for their unhappy feelings. So unconscious moods can produce conscious emotions via an external referent, but the root cause—mood—goes unrecognized.

Which brings me to another point. People have no capacity to remember their shared moods. They do remember emotions, however, which are expressed with reference to exogenous circumstances. 

You said people cannot remember their moods. Is that because mood is unconscious?

Exactly. People will remember a powerful emotion their whole lives. For example, if you ask them how they felt when their child was born or when a beloved pet died, often they can tell you. But if you ask them how they felt at the last market top, they have forgotten it already, and they think that any fool should have seen it was a terrible time to own stocks! Clearly the brain has no storage mechanism for social mood. It exists only for the moment. It fluctuates in a fractal pattern. People sense it unconsciously, so they don’t recognize it, which is why they don’t remember it.

If I understand the concept of a “fractal” properly, mood can be in a negative and positive trend simultaneously, at different degrees. This is hard for most people to understand.

You are so right. Theorists who talk about financial or social tipping points think the market or society is going in one trend and then reaches some point at which it “tips” in the other direction, as if it were a tree leaning over and finally falling due to one last wind gust. But the market is a fractal.  It is changing direction every split second. Is every one of those changes a tipping point? People who reason from mechanics take some major trend change as an example of the point that “tipped.” But doing so is selective, because at smaller degrees the market had multiple other trend changes.  And there are larger ones as well. Once you see it graphically, it’s pretty clear. The market and the social mood behind it move according to the Wave Principle. It’s not mechanics.

Are you saying that social mood is completely endogenous? That nothing, no matter how wonderful or calamitous, has any effect on it at all?

We have investigated every exogenous-cause argument we have heard, and we have tested every socionomic cause-and-result claim that we can think of. Usually they are two sides of a coin, and the established theory fails, and ours works. Now, we have yet to demonstrate all our conclusions with rigorous statistics. We recently published a paper about political forecasting. But I will also say that we have found no papers that prove exogenous causality in the stock market. The theory is simply assumed, as if it were a law of physics. And that’s exactly what it is, which is why it doesn’t apply to social behavior. I would welcome any challenge to socionomics that someone thinks we may have overlooked.

If I accept, as you say, that mood drives events, I then have to ask this: What drives mood?

Social mood arises when humans interact socially. It is not passed from one person to another as in contagion. It is not imparted by leaders. It is not imposed by authorities. If anything “drives” the emergence of social mood, it is the herding impulse. At least the process seems closely related to the herding impulse.

How exactly do herding impulses interact in a group setting?

We don’t know. Maybe someone well-versed in fMRI studies can figure it out.

What role do Elliott waves play?

Elliott waves describe the fluctuations of social mood, just as branching rules describe the pattern of trees. Elliott waves probably constrain social mood fluctuations, just as branching rules constrain branching systems.

Meaning that social mood does not move outside the form of an Elliott wave?

Correct.

You have written about Fibonacci relationships, golden spirals and so on in the natural world and noted that those same growth principles turn up in human behavior. Do you have a theory connecting physical manifestations in nature and social manifestations in groups?

Many living systems display Fibonacci relationships. So do Elliott waves, which describe a living system.

How are fractals involved?

A special type of fractal is found in living beings and systems. I call it a robust fractal.

Most fractals in non-living nature are indefinite, or random, fractals, and a few are self-identical fractals. Clouds and seacoasts are indefinite fractals.  Heated silicone oil produces a self-identical fractal of stacked hexagonal patterns.

Robust fractals do have a specific pattern, but they do not repeat it exactly; there are quantitative differences; a robust fractal is self-similar but not self-identical. Trees, circulatory systems and pulmonary systems are all robust fractals. The small branches look a lot like the larger ones but not exactly like them. That’s how component waves look relative to encompassing waves.

Are you also saying that there absolutely is never a case in which an event drives the markets?

Not quite. Transitory emotional reactions move prices occasionally for a few seconds or minutes. The market quickly adjusts to where it would have been without the disturbance. Larger trends are completely independent of exogenous cause.

Now recall my observation that people remember their emotions. This is a big reason why people think that news moves markets. They remember the big up opening on news, or the sharp one-minute reaction. But they cannot consciously register the unconscious mood that guided the vast bulk of the market’s moves. They do not sense the causality, so they don’t remember it. 

Where do you see the science heading next?

We need to test all of our ideas rigorously. We are doing so little by little. The Socionomics Foundation offers grants to interested academics.

What is your biggest dream for socionomics?

I would like to see departments of socionomics in universities. The demand is growing, and some professors are teaching socionomics courses. So it is beginning to happen.

Will you see it in your lifetime?

It depends on how long I live!

This interview originally published in The Socionomist.

Contributor(s)

Robert Prechter, CMT

Robert Prechter is CEO of Elliott Wave International, an independent market analysis firm. He is also Founder of Socionomics Institute. Robert has written 20 books on finance, beginning with Elliott Wave Principle in 1978, which predicted a 1920s-style stock market boom. His 2002 title, Conquer...

INTERVIEW WITH KATIE STOCKTON, CMT

How would you describe your job?

My job is to provide technical research to institutional clients, including mutual funds and hedge funds. My focus is primarily on U.S. equities, although inter-market analysis is a big part of my discipline. I always have a stance on crude oil, gold, the U.S. dollar and the 10-year Treasury yield, among other things. Indicators are essential to my work because they allow me to take an objective approach to the market, which helps our clients manage risk and generate alpha. My typical day starts early with our morning firmwide call, followed by the creation of a pre-market report called Morning Technicals. The balance of my day is dedicated to client projects, preparing the next day’s research and keeping our trading desk abreast of important technical developments in a large universe of stocks, indices and ETFs. Of course, I am on the road from time to time for marketing purposes.

What led you to look at the particular markets you specialize in?

My focus on U.S. equities is a function of location and demand. My employers have always been headquartered in the U.S., where most of our clients are domiciled. Of course, the market has become more global over the years, and so have I. Fortunately, my indicators translate very well to overseas markets, allowing me to have an opinion about anything that trades actively.

Do you look at any fundamental or economic inputs to develop your opinions?

I believe the market is driven by earnings and macro data, so this sets the tone for the long term and creates the story behind every stock.  Fortunately, I am surrounded by experts in fundamental analysis and macroeconomic research, so I incorporate their valuable input into my analysis. The charts are great for “filling in the blanks,” where either there is a dearth of data or something just doesn’t make sense from a fundamental or macro perspective. This is the primary reason I have gravitated toward short- and intermediate-term time horizons, where my inputs are solely technical.

What is the most interesting piece of work you’ve seen in technical analysis recently?

There has been some fascinating work out there on seasonality. It is not something I analyze in depth, so I welcome input from other technicians, particularly Mary Ann Bartels, who does great work on the subject. This year I have found it helpful to be armed with historical monthly returns during Presidential election years, with comparisons to average seasonal patterns.  Themes like “sell in May and go away,” the January effect and the Santa Claus rally are good to have on the radar, as well, and there is some great quantitative research out there regarding these phenomena.

What research area do you think offers the greatest potential in technical analysis at this time?

I value any tool that helps me identify shifts in trends and potential areas of support or resistance. To this end, I think three areas of technical analysis deserve extra attention from practitioners and academia: the cloud model (a/k/a Ichimoku), the DeMark Indicators™ and Relative Rotation Graphs.  The cloud model is widely followed globally, but still seems to be catching on in the U.S. It provides a forward-looking gauge of support and resistance, which is invaluable. Tom DeMark’s indicators can be used for timely counter-trend indications, with macro takeaways at times. Finally, Julius deKempenar’s Relative Rotation Graphs provide a great visual gauge of relative strength, allowing comparisons versus a benchmark and simultaneously versus peers.

What advice would you have for someone starting in the business today?

This is a relationship-driven business, so the obvious advice is to constantly be networking. It is important to be visible while maintaining a high level of professionalism. The MTA provides a great outlet for meeting like-minded people; it is has been the one constant throughout my career in technical analysis, helping to smooth the inevitable transitions. The other recommendation I would make is to pursue the CMT if you want to be taken seriously as a technical analyst, whether on the buy side or sell side. It provides education and credibility and shows dedication to future employers. I recommend it to those already in the business, too, as a way to expand one’s horizons as the headcount on Wall Street contracts.

Contributor(s)

Katie Stockton, CMT

Katie Stockton, CMT is Founder and Managing Partner of Fairlead Strategies, LLC, an independent research firm and investment advisor focused on technical analysis. Prior to forming Fairlead Strategies, Katie spent more than 20 years on Wall Street providing technical research and advice...

Amber Hestla-Barnhart

Bio coming soon.

THE THREE-BAR TRADING DAY

The Three-Bar Trading Day is a quick way to gauge market participation by separating the trading day into three parts: the pre-market, the regular session, and the post-market. This isn’t revolutionary. Some financial charting packages and websites offer this as a canned option. But those that aren’t familiar with this way of looking at things may be missing out on part of the story.

By applying basic correlation analysis between bars, one can learn a lot about a particular market’s behavior. Even a brief glance at the pre-market can offer an educated guess at the coming market volatility. It also adds that many more bars for classic candlestick pattern interpretation. This should enrich any trading system that may benefit from an advanced peek at the interest level and participation in a particular market.

Below is a snippet of market data seen from a run-of-the-mill candlestick chart. Each candlestick bar represents the regular, daily market session – basically a snapshot of a traded product from 9:30 a.m. to 4 p.m. EST.

To view the after-hours market without reverting to a minute or hourly chart, most software packages offer the option to add the extended session onto the regular one, yielding daily bars that record the market from 8:00 a.m. to 6:30 p.m. and look like the following:

The difference between each chart isn’t obvious and will be of little benefit to the analyst needing to correlate market behavior between pre/post and regular sessions. This is where a three-bar daily chart comes in handy. Here we separate the trading day into the three parts, the pre-market, the regular session and the post-market, in that order, and get:

A vertical gray line is used to separate trading days. The largest bars tend to be the regular traded session, but there are exceptions (such as earning releases, disruptive news and/or deep-pocketed interest outside regular trading hours) and that is bound to be of value to the analyst and the trader.

One way to make this even easier on the eye is to highlight the regular trading session by bolding its boundaries (other approaches could include changing the background color, introducing lighter and darker shades, displaying thick and thin candlestick bars, labels, etc). The chart below highlights the main trading session. It rapidly, yet precisely, educates the viewer on the level of activity around regular market hours:

Most software packages offer some form of time-frame customization and each approach will vary. The examples in this article use NinjaTrader 7.0. This software package offers interesting time and display customization features. Here is a quick overview of how to create the above chart in NinjaTrader 7.0.

The first step is to define trading hours (all times mentioned here are Eastern Standard Time). The first session of the day starts at 3 a.m., the second at 9:30 a.m., and the final one at 4:00 p.m. The trick here is to use sessions of six and a half hours, as it affords the use a single time frame for all three bars. Most actively traded ETFs and stocks will see activity when the exchange opens the pre-market session around 8:00 a.m., so the first bar will capture that activity.

The second bar is the regular session that covers the entire 9:30 a.m. to 4:00 p.m. time frame. And the last bar covers the final session, i.e. the post-market that usually goes from 4:00 p.m. to 6:30 p.m. The fact that the pre/post sessions are comprised of longer periods than their actual allocated trading time is irrelevant and used solely as a trick to chop each session into equal time frames (saving us from more complicated programming).

The screen grab below shows how to set that up in NinjaTrader 7.0 (Control Center – Tools – Session Manager):

When a new chart is created, the above session needs to be applied to the data series. Also, as such a display model requires a custom time frame, the chart’s period has to be set to 390 minutes (6 and ½ hours of minute data for each bar/session).

Most trading approaches can benefit from measuring pre/post market activity. If they don’t take that into consideration, they may be leaving money on the table or taking needless risk.

Unfortunately, not all financial products have pre/post trading activity (which is in and of itself telling), so less active products will have spotty data during illiquid times. Also, the way the sessions are setup, this approach will not work on 24-hour traded products such as futures. The pre/post bars ignore a few hours of the day (i.e. from 10:30 p.m. to 3 a.m.). For those products, it is necessary to further customize the Session Manager by adding more rows to account for the different time frames of each bar.

Contributor(s)

Manuel Amunategui

Manuel Amunategui has worked on Wall Street in the options industry for over six years. He now lives in Portland, Oregon and spends most of his time in the data and data-mining industry but still finds time to experiment and run trading...

MTA BLOGS

Editor’s note: The blogs on the members’ section of the MTA web site are a valuable source of short-term trading ideas as the first reprint below demonstrates. They are also a resource for those managing portfolios with examples of how to apply technical analysis beyond price charts as the second example reprinted below highlights.

Spot Gold: Looking for $1768 on a Pattern Breakout by Bhaskar Radadiya

The price of spot gold has been trading based on the effects of an inverse Head & Shoulders (H&S) formation since reaching the last pullback level of $1735, a price that was also equal to 78.6% of the previous wave. A clear picture of the pattern can be seen on the 1-hour chart which highlights the $1768 target and expected resistance.

Chart of 1-hour price data

We can see that there is a likelihood of a strong move above $1735 with two kinds of breakout possible – one is a breakout from the inverse H&S formation and the second is a triangle breakout. Hence, the next move in gold should be quick and powerful, offering a potential reward of approximately $33 for a momentum trade. Indicators shown in the next chart support this analysis.

Chart of oscillator and indicator movements for gold

The last minor correction in gold took prices from $1795 to $1675. That move ended with an engulfing bullish candlestick pattern, a two candle pattern that offered a strong signal that the trend was reversing near $1675.

However, gold prices are still under pressure and $1675 cannot become a key reversal point until the price decisively breaks through previous resistance at $1795. Once it crosses $1795, I expect another pattern will drive gold to further gains and I will discuss the pattern at that time and its breakout range.

Posted on November 25, 2012

The Fallacy of Owning Gold Mining Equities by Brennan Basnicki

Ample research supports the notion that the addition of gold and other commodities to one’s portfolio produces a higher efficient frontier, or more plainly stated: a higher expected return with lower risk. Unfortunately, many portfolios have been constructed to include commodity exposure through the inclusion of commodity related equities, especially with gold.  While this approach may have worked at lower gold prices, it has failed since early 2011 when gold traded above $1400. Not only has this approach failed, but gold miners have been one of the poorest performing sectors. The failure of this approach of portfolio optimization is most easily seen through the following charts:

  • The first chart shows how poorly gold miners (GDX) and junior gold miners (GDXJ) have performed compared to Gold (GLD). Note that while gold is up over 25%, junior gold miners are down 45%.
  • One can often blame the equity market for underperformance in gold miners versus gold, as miners are companies with earnings, and when equity markets are weak, most stocks are weak. However if one compares the GDX and GDXJ to the S&P500 (SPY), this arguments collapses. Not only have gold miners underperformed gold, they have also significantly underperformed the S&P500.
  • The idea that one can gain exposure to gold through mining companies clearly has not held. A look at the correlation between the miners and gold clearly shows the failure of this historic relationship.  The chart below shows the correlation over the last 20, 50, and 100 weeks between gold and gold miners. Note that while although the correlation remains high over the shortest (20 week) period, over the long term (100 weeks) the correlation has trended to zero.
  • The case is even worse for the junior gold miners ETF. The correlation moved into negative territory.

Why has this relationship changed? I don’t have the answer to that, but one potential source of the discrepancy may be that as gold reached historic highs at the end of 2010 mining companies may have increased hedging activities. This would obviously limit their ability to participate in any gold appreciation above that level ($1400).

The eccentric hedge fund manager Hugh Hendry makes a different argument for further weakness in gold mining stocks, having stated that:

“There is no rationale for owning gold mining equities. It is as close as you get to insanity. The risk premium goes up when the gold price goes up. Societies are more envious of your gold at $3000 than at $300. And there is no valuation argument that protects you against the risk of confiscation.”

Basically, the more expensive gold is, the higher probability gold mines will be nationalized. This leads to a higher risk premium required for gold miners and accordingly a lower stock price when completing any sort of fundamental valuation.

The paradox is that if nationalization continues the market ends up with less supply because in most cases a public government will not be nearly as efficient as a private company. Less supply means higher prices and accordingly a higher probability of further nationalization. And while nationalization may only be possible in developing countries, higher tax rates or government royalties are equally likely in developed countries. Recent examples of such actions include the ongoing dispute over Kyrgyzstan’s gold, and Venezuela’s move to nationalize gold just over a year ago.

While I’m sure there may be evidence to counter this argument, the failure of miners to participate in gold’s appreciation above $1400 does support this argument. I am not an expert in gold, however I have spent significant time studying technical analysis. One thing you learn earlier in technical analysis, and probably one of the most important rules is that “the trend is your friend,” simply inferring you always want to establish positions alongside the trend. Well the trend has been towards less and less correlation and under performance for gold miners. Hendry himself is long gold and short gold miners. Until new evidence is available of a change in this relationship, it is likely that the current trend will persist.

To return to portfolio management, it should be clear at this point that the addition of gold related equities does not raise the efficient frontier (higher return with lower risk). One should look at allocating a portion of their portfolio to outright gold exposure, either in the form of a gold ETF such as GLD or even physical ownership.

It looks like Goldmember had it right in the 2002 Austin Powers movie when he rather enthusiastically stated “I love Goldddd”. Interestingly enough, gold was under $300/ounce back then, and 2002 marked the breakout of the 10 year secular bull trend gold remains in today.

Posted on November 21, 2012.

Contributor(s)

Bhaskar Radadiya

Bhaskar Radadiya is the head of technical research at ANS Pvt Ltd in India. He has held this position since April 2008.  Prior to that, Bhaskar worked as an advisor with ANS Pvt Ltd and several other firms. He completed an MBA...