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January’s First Five Days Indicator—Forewarned is Forearmed January 26, 2009

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Oft expectation fails, and most oft where most it promises.

– William Shakespeare

Let’s do a little myth busting today—that savory task of uncovering another of the indicators that just don’t indicate what they’re supposed to. An indicator that gets lots of press early each year is the First Five Days indicator. Rest assured it just doesn’t work.

At the core of human nature is the desire to understand complex systems in simple terms. The problem is this: we tend to apply this simplistic cause and effect model to very intricate problems, and expect similar easy-to-understand answers.

One good example is the Groundhog Day Indicator. Like the financial markets, weather systems are complex and difficult to predict. But we have devised many simplistic ways to predict the weather, including the infamous groundhog, Punxsutawney Phil. If he sees his shadow on February 2, there will be six more weeks of winter weather.

Because we like simple explanations, we are more than willing to believe cause-and-effect explanations that really don’t make logical sense.

Maybe that’s why there are so many stock forecasting tools that use shaky logic and even shakier statistics to predict what will happen in the market in the days and months to come.

So let’s look at one of the most hyped indicators this week…

January’s First Five Days—It’s Popular, But it Ain’t Useful

Many market watchers and analysts are looking at the well-known First Five Days indicator, which has been popularized by Yale Hirsch’s Stock Trader’s Almanac.

For the record, I think the Almanac contains a wealth of useful information. I keep one on my desk and gave two as Christmas gifts to friends and family. But back to our indicator…

The First Five Days indicator holds loosely that the direction of the first five trading days of the year is a valid predictor of the direction of the market for the remainder of the year.

As proof of the indicator’s effectiveness, it’s proponents look at a 59-year record and state that of 36 First Five Days that finished up, the stock market finished up in 31 of those years—an impressive 89% win rate for the predictor.

It has been quoted by such venerable sources as The New York Times, U.S. News & World Report, CNN and Money Magazine. Nevertheless, it’s a useless indicator, or worse, it’s potentially dangerous to your wealth.

Don’t Waste Your Time on This Meaningless Myth

Let me be blunt. The First Five Days indicator is the lowest form of analysis. It is the opposite of cause and effect. This is the type of analysis that looks for any cause to tie to an end effect, regardless of logic, and as we shall see, regardless of statistical support.

The indicator is no more valid or useful than predicting the stock market based on Super Bowl winners or groundhog shadows. Here are three reasons why:

1. The logic is arbitrary. The raw numbers for this indicator show that the market has gone down during the first five days of January 23 times in the last 59 years. In those 23 occurrences, the market finished the year up 11 times and down 12 times.

So, the authors conclude that the indicator has no predictive value if it starts out to the downside. Looking at the same data, they like the results if the market starts out to the upside where it has “been right” 31 out of 36 times. Working in one direction but not the other is too arbitrary for me!

If the data doesn’t fit our hypothesis, then change the hypothesis to fit the data. This is classic “curve fitting” mentality. Do you want to risk any of your money based on that logic?

2. The triggering event is not statistically significant. For this indicator, all you need to trigger a yearlong market prediction is any up move for five days. This means that trivial moves in the market could shape your outlook for the coming year.

Suppose after five days the market was up only one quarter of a point. This would still trigger the indicator’s prediction for an up year.

What’s the problem with having a move of any magnitude trigger an indicator? A tiny move doesn’t tell us anything about what the market is doing. A small move either up or down is just random; it’s just part of the background “noise” of the market.

So how do we decide what is meaningful and what is just background noise? One measure that many analysts use is the average volatility of a price movement. Long-time readers know that I use the Average True Range (ATR) of price as a measure of volatility. (In simple terms, ATR measures the average size of the daily range, the high minus the low, while accounting for gaps between bars.)

If we look at the ATR for a five-day move, we would want our trigger to move up or down at least half of the average. Anything less would almost have to be considered random.

With that in mind, your industrious writer dug deep into the details of the First Five Days indicator’s raw data. I calculated the S&P 500 index’s ATR during the first five days for the last 25 years and checked to see how many of the First Five Days trigger signals could be considered more than random. The answer: only 7!

3. The sample population is too small. When we eliminate the trigger signals that are mere noise, we now only have 13 to 16 triggers of the indicator over the last 55 years. This is not a statistically significant sample to base any predictions on, and this indicator is uncovered as just some simplistic curve fitting that doesn’t mean a thing for traders and investors.

There is plenty of good analysis for you to use to help guide your trading and investing decisions. So it makes a lot of sense to throw out the overly simplistic, statistically meaningless ones like the First Five Days indicator.

One last note of caution—the indicator worked last year. This brings another psychological bias into play: we tend to assign an excessive amount of meaning to the most recent data points. Don’t fall into this trap with the First Five Days indicator.

You can still use it for cocktail party discussions, but don’t waste any money trying to use it to help you make sense of the markets. We’ll pick back up on our volatility series next week. Until then…

Great Trading,

Volatility: The Real “Back Story” in Today’s Market, Part IV January 26, 2009

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Have you ever known any of those people who are true math geeks? I’m talking about folks that see everything in a mathematical way. They “mathematize” a way to many things—things that “normal” people would think about in terms of formulas. My daughter, Meg, and my son, Josh, both go to a great high school—the Charter School of Wilmington (Delaware). It’s consistently ranked in the top 50 high schools in the country. And being a math and science magnet school, it is chock full of math geeks.

So, when I needed a math geek reference, I asked my progeny for one. Meg piped up, “This morning, I heard some kids talking about Eulerizing their route between classes.”

Pause for effect. I’m hoping that you, like me, didn’t know what this meant the first time you heard it. Let me explain (and then we’ll get on the volatility goodies).

Leonhard Euler was an 18th century Swiss-born mathematician and physicist. To be brief, his contributions to math and science are manifold and legendary. The one my daughter was referring to was the Eulerian circuit. It is the same math that is used to determine the routes for mail carriers, etc. Indeed, Meg’s pals were just trying to determine the most efficient path from homeroom, to all of their classes, and back to homeroom at the end of the day…but in a very math geeky sort of way.

I’m far from a math geek. In fact, since I was a junior in high school, I had to beat myself about the head and neck just to force myself to study to get through math classes.

Yet I persevered. In fact, I was only two courses away from a math minor in college because of all the stinkin’ math courses my chemical engineering curriculum required.

What I really do like, though, is the useful application of math (and science, for that matter) to everyday life. And this brings us back to VIX as a volatility measure.

Don’t worry, though, we’re not going to dig into the math equations. But we will talk a bit about what VIX is trying to accomplish. Understanding this foundation makes it a much more useful indicator. If you want to dig into the math (for all those lovely self-professed math geeks, and the closet variety as well), you can go to the CBOE website. They have a whole subsection on the VIX with white papers that will take you as far into the weeds as you’d like to go.

Math Geeks Unite: VIX Really Is Useful

The stated goal of VIX is to represent expected volatility for the next 30 days. From its inception in 1993, VIX did this by measuring the variation between put and call prices in indexes.

That general concept still applied after significant changes were made to the calculation in 2003. In that year, the following major revisions to the calculation were implemented:

· S&P 500 options are now used instead of S&P 100 options.

· A full range of active strike prices is used instead of just the at-the-money strike.

· Black Scholes option model is not longer used to calculate an implied volatility. Rather, expected volatility is derived by averaging the weighted prices of out-of-the-money puts and calls.

Back in 2003, some of my analyst friends were up in arms about the changes in the VIX. Admirably, the CBOE did historical calculations for both the new VIX (symbol $VIX) and the old VIX ($VXO) so that data is available for comparison back into to 1986.

So here are the main questions that traders and investors have:

1. Is VIX useful?

2. Has the 2003 calculation methodology change made it more or less useful?

Let’s look at a weekly chart of the markets that DOES NOT include the Fall of ’08 meltdown.

Sorry for the busy chart. To keep you from squinting, the top symbol is the S&P 500 cash index, the next one down is $VIX, below that is $VXO and lastly, ATR. This is a weekly chart. In short, on a weekly basis, the difference between $VIX and $VXO is pretty small.

Also notable is that the $VIX is much more useful in identifying intermediate and longer term bottoms than it is for finding tops. However extended periods of moderate to low $VIX activity are useful for identifying up trends that are likely to plod onward.

Now let’s look at the recent market activity, but since moves have been so severe, let’s look at the action on a daily chart.

As we mentioned in our last volatility article (two weeks ago), VIX has been effective in identifying the increase in volatility. As you can see from the chart, it has also been at its intermediate extremes when the market hit intermediate highs and lows. But in this market environment this has really been more evident in hindsight than at the hard right edge of the chart. For example, was anyone screaming that we were at a top on 11/4 just because the VIX dipped down to 44.25?

The last item of note is that the VIX vs. VXO is really not that important. I’ve shown two spots on the chart (above) where they were a bit different. But in general the two give very similar information. Only if you’re using them as part of more in depth calculations for options pricing, etc. will the differences matter much at all.

Next week we’ll look at more tools to add to the volatility toolbox. Until then…

Great Trading,

D. R.

Volatility: The Real “Back Story” in Today’s Market, Part III January 2, 2009

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The more I dig into volatility measurements, the more intriguing the journey becomes. There are lots of thoughts on measuring it, mitigating its effects, and even capitalizing on it. But, in fact, there is really no standard definition for volatility in the financial community.

A general definition might be “the measure of variation in the price of a security.” But this is a little too broad to be useful. I just saw it defined as “variation of price over time” and “rate of change of price” and as “change versus a standard or mean.” Perhaps the simplest definition that resonates with me is “the relative rate at which the price of a security moves up and down.” But there are definitely lots of different ways to define this elusive concept. And almost as many ways to measure it.

In our quest to better understand volatility, one logical way to try to get a handle on this idea would be to see how the pros react to expanded price ranges and increasing rates of change. In our previous articles on volatility, we’ve looked at beta and Average True Range (ATR) as measures of volatility. But there are folks who look at volatility and its effect all the time—options traders. Since these folks watch volatility ever so closely (because it has a significant effect on options pricing), understanding how they see volatility should be a useful concept.

A professor from Duke University named Robert E. Whaley thought that tracking option pricing information was a good way to quantify volatility. His paper from 1983 formed the basis for the CBOE Volatility Index or VIX.

VIX has been called a “measure of investor fear,”—when the index is at its highest levels, volatility and investor fear are high.

By the CBOE’s description, VIX is a measure of market expectations of near-term volatility conveyed by S&P 500 stock index option prices. Next week we’ll dig into the details of how VIX is calculated. But for today, I wanted to focus on the current usefulness of VIX. As we have seen, “beta” has a difficult time adapting to market changes because of its time horizon. ATR is much quicker. How about VIX? Let’s look at a chart.

At first glance, we can see in this weekly chart that as ranges increased, VIX expanded significantly. This is a very good first sign. It gave useful information during the range expansion. As you can see from the smaller arrows, VIX has also given some useful indications in the past about high fear levels leading to intermediate market lows.

Next week we’ll look more deeply into VIX, talk about its big change in 2003 and investigate some ways that we can use it that are more useful (and some that are less so!). Until then…

Bonds and Gold: Talk of Bubbles and Bugs January 2, 2009

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We’re going to take a break from our volatility series to take a closer look at two markets: bonds and gold.

One has reached bubble proportions— with bonds attaining unsustainable price levels. And in the other one, the gold bugs are starting to whisper quite loudly, “I told you so,” perhaps a bit prematurely.

With the FOMC announcing a monstrous rate cut to unchartered levels, the financial markets have entered yet another era of completely unprecedented existence. While the Fed hasn’t shot its last bullet, it certainly needs a microscope to find its remaining ammo.

And with the Fed Funds rate all but disappearing below single digits, bond prices have absolutely exploded. By any measure, they have made an asymptotic move.

Markets can remain overbought for longer than we expect, but the correction in bonds will most certainly be a violent one when it comes.

Gold on a Run, But It’s Far from a Bull

Meanwhile, gold has been on a short-term tear, gaining $100 per ounce in just two trading weeks. While gold’s relationship to the dollar has improved quite a bit over the short run, its climb relative to crude oil has been absolutely dizzying.

A mere six months ago, an ounce of gold would buy a scant 6.6 barrels of crude oil. With oil’s recent plunge and gold’s strengthening price, that ratio has almost tripled! An ounce of gold currently buys 18 barrels of oil – the highest level since early 1999!

So gold’s strength relative to other weakening commodity prices is impressive. And yes, massive amounts of paper money have been printed and more will have to be printed to make good on the non-stop promises made by (most notably) the U.S. government, as well as others around the globe. Fundamentally, gold certainly wins the “most likely to appreciate to new highs never seen before” award. The gold bugs shout it from every blog. But just when it will reach those lofty heights is far from certain. There is one inescapable fact standing in the way of gold’s coronation – gold is decidedly in a bear market! Before you call for my head on a platter, let’s look at the facts (as represented by price).

The classic and purest definition of a downtrend is a market that is making lower highs and lower lows. And clearly gold’s movement fits that definition to a tee over the past nine months.

There are no fewer than three obstacles in the way of gold moving from “having a nice up move in a bear market” to “bullish shiny metal”:

1. It has to make a few closes above the 200 day moving average for the first time since July. The descending 200 MA is not very far away.
2. It needs to break the downtrend line that is currently at ~900.
3. It needs to make a higher high, above the last one set at 938.50.

When we get all of that done, then we can talk about $2,000 gold. Until then, it’s just another bear market with loads of potential.

Volatility: The Real “Back Story” in Today’s Market December 5, 2008

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by D. R. Barton, Jr.

I’ve written a bunch about volatility over the past several months. And with good reason, I believe.

While the price drops over the past 12 months are some of the biggest that we’ve seen, the volatility that has accompanied the market action is arguably the highest in the modern history of the markets. Add to this the fact that this exceptional volatility has been sustained for months now, and we have to acknowledge that the markets are acting in a truly unprecedented fashion.

And the increased volatility has been seen in almost all areas—stocks, most commodities, currencies, and even bonds.

This heightened volatility affects investors and traders in many ways. But the effects are wide reaching and must be understood well to thrive (or even survive) in these market conditions.

I’d like to take an in-depth look at volatility over the next several weeks. We’ll investigate the many ways it can be represented, which calculations are more and less useful, how volatility affects investors and traders in obvious and subtle ways, and finally what we can do to protect ourselves and even use it to our advantage. I hope you have as much fun reading the series as I do researching and writing.

Let’s start by taking a look at one of the most overused, misunderstood and misused measures of volatility: Beta.

Beta: Take It with a Grain of Salt (and Understand What It REALLY Tells You)

Let’s imagine that your great aunt calls up and asks for your help. She’s read Buffett’s New York Times editorial and thinks it’s time to get more heavily invested in stocks. She’d like five low-risk stocks on the NASDAQ to add to her portfolio, and wants you to give her five names to discuss with her husband.

You’ve heard the Wall Street talking heads mention beta many times on CNBC. “Beta is the standard measure of a stock’s volatility. The lower the beta, the lower the risk.” These guys are on CNBC, so they must know how to pick low-risk stocks…

So you do a quick stock screen on the Internet. You know that high volume stocks are best for your great aunt, since they’ll have the liquidity to help her get into and out of positions with no problem. You screen for all stocks on the NASDAQ with a volume greater than two million shares per day and then rank them from highest to lowest beta.

You pick stocks with a low beta and with names that your great aunt will recognize: JetBlue Airways, Direct TV, Huntington Bancshares, Comcast and Staples. That was easy. You figure that by picking stocks from the bottom of a list ranked according to beta, you’d be picking low volatility, low- risk stocks.

And you’d be dead wrong.

“Beta”: Do You Really Want to Use THAT To Measure Volatility?

First, let’s understand how beta is calculated and how to interpret it. Beta attempts to measure volatility by comparing the monthly change in price of a given instrument (stock, mutual fund, index, etc.) to an established index, usually the S&P 500. In the most common beta measurement, 60 end-of-month returns are plotted for the stock and also for the S&P 500. A “best fit” straight line is drawn through the data points for the stock and for the S&P 500. This is done using a standard mathematical tool called linear regression. (If you want to see how a line is regressed through scattered data, there is a very cool web application that will do this for you in real time! Go to: http://www.math.csusb.edu/faculty/stanton/m262/regress/regress.html. You will need to have a Java plug-in for your browser to make this to work.)

Now we have two straight lines—one for our stock and one for the S&P 500. Beta is a comparison of the slope of our stock’s line to the slope of the S&P 500 line for the same time period.

How is beta interpreted? Here’s the interpretation found on every financial dictionary site on the web: The beta of a stock that exactly matches the S&P 500 would be 1.0 while a stock that has 50% more volatility than the S&P 500 would be 1.5. A stock with a volatility of 50% less than the S&P 500 would be 0.50.

Now we’ll look at the stocks you chose and their current beta measurements.

Stock Beta
Comcast (CMCSA) 0.81
DirectTV (DTV) 0.80
Staples (SPLS) 0.76
Huntington Bancshares (HBAN) 0.24
JetBlue Airways (JBLU) 0.16

Based on their beta measurements, this looks like a good low risk list. The stocks are all below the volatility of the S&P 500 (at least according to their beta measurements and the traditional definition of Beta). But as we shall see, beta doesn’t tell the whole story. In fact it can be very misleading, as is the case with the five stocks that were chosen for your great aunt.

Conceptually, Beta was meant to compare volatility to the S&P 500. But we can see from the calculation where 60 months of data are compared (five full years!), that this measure may have little to nothing to do with what’s happening in the market and the individual stocks.

Next week we’ll look at how Beta compares with one of my favorite measures of volatility: the Average True Range. And we’ll revisit the list of stocks you picked for your great aunt to see if they really are “low volatility”. Until then –

Great Trading,
D. R.

Crude Oil Climbs up the Stairs and Jumps out the Window, Part II November 21, 2008

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Driving home from the airport yesterday, I paid $1.84 for a gallon of gas. I felt like I was in a time warp. These are gas prices from back when the Yankees had a good baseball team…

Just a few short months ago (during the summer), gas prices were shaping up to be THE defining issue of the presidential election. Then the credit markets crashed and the health of the broader financial system quickly pushed crude oil and gas prices down and pushed news about the cost of filling a gas tank off the front page.

The drop has been amazing – here is a chart that I really like. The source of the data is the Department of Energy weekly survey. Take note of the time scale for the graph; it is very compressed and shows over 40 years of data. This is important because you’ll see that the incredible gains that took many years to get us up above $4 per gallon were erased in a matter of a few months.

112008gaschart

I’m sure very few people are overly sad about the drop in gas prices (and now heating oil prices). In fact, this huge drop has helped ease the pain of the financial woes brought on by the credit crisis.

And oil prices continue to drift lower, with crude oil futures trading as low as $53.66 per barrel – down more than 65% from the July highs.

Last week, we talked about the part that weakening demand and the strengthening dollar have played in the drop in oil prices. But few people have talked about the bubble-like ascent of prices. There a was an oil bubble and its end was like that of any other bubble. Technical and sentiment indicators were screaming, “Overbought! Overbought!” right up to the top.

So, yes, demand and dollar valuations did help drop oil prices – but they only account for a part of the fall. Most of the fall can be explained in this way – when bubbles burst, buyers flee. And prices drop harder and farther than could ever be expected. Next week, we’ll look at some of the technical analysis and sentiment indicators that signaled a bubble.

But for now, the crude oil market is getting very oversold – the pendulum has swung the other way. Here’s a chart that illustrates the point:

The notes in the chart highlight the key points: Momentum indicators are divergent at current price levels, including my favorite Chaikin Oscillator, which shows that money is not flowing out of this instrument as fast as it was a couple of weeks ago. In addition, we’re staying way oversold on the stochastic and volatility is clearly decreasing.

With these things lined up, it’s a tough bet to say there’s a lot of downside left in crude oil in the near to intermediate term time frames. A rounded bottom or a fairly violent spike up would seem quite likely from here.

Tune in next week as we revisit the bubble months.

Until next week…

Great Trading,

Smart Trade Pro – Stock Market Training Courses October 1, 2008

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