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Tharp's Thoughts Weekly Newsletter

November 28, 2007 — Issue #349
  
Article

Using Buy and Hold with Real S&P 500 by Van K. Tharp Ph.D.

Education

The Ultimate Home Study Course for Traders

Trading Tip

Learning from My Own Mistakes by D.R. Barton, Jr.

Melita's Corner

Quick to Judge, by Melita Hunt

Feature

Historical Testing of Efficient Markets

Part V: Using Buy and Hold with Real S&P 500

by

Van K. Tharp, Ph.D.

In Part IV of this series, we looked at what would happen if we bought $200 worth of each of the S&P 500 stocks on April 2005 on October 3, 1980 or when the stock was first issued, whichever came first.  We did not sell any of the stocks.  We did historical testing of an efficiency signal on today’s S&P 500 data going back to the year 1980.   We sold everything on April 4, 2005, which is when our database ended.   Our initial $100,000 in equity became $3,025,960 while paying $31,356 in commissions.  Our gain amounted to a compounded return of 14.89%. 

Now we are going to compare buying and holding two databases.  We have an accurate S&P 500 database (i.e., it is split and dividend adjusted), which only has stocks while they are a member of the S&P 500.  In other words, it drops stocks when they are dropped from the S&P 500 and it adds them when they are added to the S&P500.  Thus, Microsoft doesn’t become part of our database until July 1, 1994 rather than its first publicly traded date of March 17, 1986.  And Dell isn’t included until October 1, 1996 rather than its first publicly traded date of June 24, 1988.  In the previous article (Part IV), Dell produced a huge R-multiple of 1700R, whereas, in the new study it is reduced to 711.6R (where 1R is assumed to be our entire up front investment of $200).

However, our database does not begin until February 1, 1990, so we are missing ten years of data.  As a result, we decided to repeat the study with the April 2005 S&P 500 database beginning on February 1st and then compare that with the accurate S&P 500 data.  Thus, the data for both databases will begin on Feb 1, 1990 and end on April 20, 2005.

Part I:  Buying and Holding the April 2005 S&P 500 (from 1990 or on the date when they first came out as stocks)

In our first study, we simply bought $200 worth of today’s S&P 500 in October 1980 or whenever they came out as stocks.  Thus, we were still purchasing $100,000 worth of stock, but once we bought we didn’t sell unless 1) the stock stopped trading or 2) the database ended on April 20, 2005.   Those were the only two exits.  Thus, this is a real buy and hold situation.  However, we are basically buying the BEST American companies.  We were also buying them either on the start date or when they first came out as stocks.

In Part IV, we started with $100,000 and ended up with $3,025,960.  Our gain amounts to a compounded return of 14.89%.   We made money on 94.78% of our trades and the average gain was 71.35 times the average loss.

The only difference between the study reported in Part IV and this data set is that we started later in this data set.  And the results show that when we start our buy and hold in 1990, our ending equity is $1,745,611.   This is about 1.3 million less than our prior ending equity, but the average yearly compounded return on equity increased from 14.89% to 20.66%.   However, the prior dates include the 1980-1982 bear market and the 1987 crash.   Buying and holding isn’t too profitable during such times even when you have the best stocks in America.  We still had a drawdown of 48.6% on August 31, 2002 and we were still in a drawdown when the data ended in April of 2005.   In this particular run we had 466 wins and 33 losses for a 93.39% win rate.  And the average gain was 27.42 times bigger than our average loss.

Figure 1 shows the equity curve of buying and holding America’s top stocks for 15 years.


Figure 1: Equity Curve over 15 Years

While the results are great from 1990 through 1999, it’s also clear that if you had bought everything in 2000, you still be down by 2005.

Table 1 shows all of the stocks in the database with R-multiples of 30 or more.  And since our risk was 100%, this means that they increase by 30 or more times our original buy-price.  This occurred despite the price drop from 2000 through 2005.  Most of the stocks were purchased in 1990 with those purchased later showing a shaded entry date.  DELL is still the top stock with an R-multiple gain of 711, but that’s a significant drop from 1700 when we started in 1980.

Table 1: Top Stocks from 1990 through 2000
Rank Symbol Profit R-Multiple Entry Date Exit Date
1 DELL $142,318.40 711.59 01/31/1990 4/20/2005
2 CSCO $42,343.25 211.72 02/21/1990 4/20/2005
3 UNH $35,535.90 177.68 01/31/1990 4/20/2005
4 EMC $27,999.20 140 01/31/1990 4/20/2005
5 BBY $25,704.81 128.52 01/31/1990 4/20/2005
6 TWX $25,560.48 127.8 03/23/1992 4/20/2005
7 ERTS $19,364.12 96.82 01/31/1990 4/20/2005
8 APOL $18,439.69 92.2 12/08/1994 4/20/2005
9 MXIM $13,854.03 69.27 01/31/1990 4/20/2005
10 APCC $13,617.49 68.09 01/31/1990 4/20/2005
11 CCU $12,612.64 63.06 01/31/1990 4/20/2005
12 LLTC $12,383.72 61.92 01/31/1990 4/20/2005
13 IGT $11,880.61 59.4 01/31/1990 4/20/2005
14 AMGN $11,540.08 57.7 01/31/1990 4/20/2005
15 QCOM $11,539.10 57.7 12/17/1991 4/20/2005
16 DG $10,955.30 54.78 01/31/1990 4/20/2005
17 ESRX $10,093.23 50.47 06/11/1992 4/20/2005
18 PAYX $8,071.74 40.36 01/31/1990 4/20/2005
19 ALTR $7,953.31 39.77 01/31/1990 4/20/2005
20 CFC $7,870.83 39.35 01/31/1990 4/20/2005
21 QLGC $7,858.90 39.29 03/02/1994 4/20/2005
22 HDI $7,443.30 37.22 01/31/1990 4/20/2005
23 MSFT $7,427.44 37.14 01/31/1990 4/20/2005
24 BBBY $6,958.10 34.79 06/09/1992 4/20/2005
25 PHM $6,758.32 33.79 01/31/1990 4/20/2005
26 AMAT $6,748.78 33.74 01/31/1990 4/20/2005
27 SCH $6,523.66 32.62 01/31/1990 4/20/2005
28 VRTS $6,256.91 31.28 12/13/1993 4/20/2005
29 SPLS $6,132.63 30.66 01/31/1990 4/20/2005
30 SBUX $6,045.70 30.23 06/30/1992 4/20/2005

Part II:  Buying and Holding the Real S&P 500 Stocks (from 1990 until they were delisted or until April 2005)

In our second database, we will simply buy $200 worth of the real S&P 500 stocks on February 1, 1990.  We will sell them when they are no longer part of the S&P 500 and buy new stocks when they become part of the S&P 500.  We will then sell everything at the end of our database in April 2005 (we actually had the data through 2007 but cut it off so as to compare both databases for the same time period).

Figure 2 shows the equity curve for this new database.


Figure 2 : Equity Curve of New Data

For this database, our final equity was $771,198 for a 14.36% compounded annual rate of return.  This is much less than the $1.7M and the 20.66% figures of the first database.  Also remember that we were fully invested with the real S&P 500 database, getting the 14% annual ROI,  but not fully invested until near the end with 2005’s S&P 500 database, yet still getting the 20.66% investment.

Something else that really stands out is that the drawdown during the subsequent bear market is much less for the real database.  Compare the two figures.  The worst drawdown for the real S&P 500 was on October 11, 1990 at 21.95%, which certainly says we were not holding the best performing stocks at that time.  And the longest drawdown is from September 1, 2000 to June 16, 2003.

In this database we took 858 trades and rejected 4 because of a lack of money.  We had 636 winners and 222 losers for a win rate of 74.13%.  Our average winner was 7.28 times our average loss.   Of the 858 trades, there were 139 with obsolete symbols (i.e., the stock no longer exists) amounting to 16.2%.   Only 20 of the 139 lost money.

Table 2 shows our summary returns to date with a beginning equity of $100,000.  Also, please note that we were only fully invested from the very beginning in the last study.  All the rest represented a gradual build-up of positions.

Table 2: Summary Results to Date
Study Conditions/Variables Database Ending Equity Annual % ROI Peak Drawdown
Efficiency  “Close – Close” Smoothing
(coding bugs fixed), starts in 1980
2005
S&P 500
$48.347M 28.59%2 18.34%
Efficiency “Close/Close” Smoothing
Starts in 1980
Same $2.835M 14.58% 21.78%
Buy and Hold all Stocks from
1980 or Issue Date through 2005
Same $3,026M 14.89% 51.27%
Buy and Hold all Stocks from
1990 or Issue Date through 2005
Same $1.746 M 20.66% 48.60%
Buy and Hold all Stocks from
1990 through 2005 – real S&P 500
Real
S&P 500
$0.771 M 14.36% 21.95%

In summary, the efficiency with “close minus close” smoothing is clearly better than buy and hold on the 2005 S&P 500 database.  And even the “close divided by close” smoothing is similar in terms of returns but better in terms of drawdown, suggesting that we could get much better performance with a position sizing algorithm designed to meet whatever our objectives might be.

However, at this point I’m not convinced that the efficiency trades that are being taken automatically by the studies are adequate.  In addition, notice at this point I still have not made position sizing adjustments to see what’s really possible with this sort of trading.  As a result, there is still a lot more research that we’ll do in this series, including:

1.   We’ll  determine what happens when we allow ourselves to take as many as 250 trades (i.e., half the S&P 500 database) at any one time with the two smoothing functions.  With 1% risk and a 25% trailing stop we are limited to 25 trades.  With a 0.1% risk and a 25% trailing stop, we are limited to 250 trades.  We’ll simply increase our starting equity to $1M so that we’ll be investing the same amount ($4000) with each trade. 

2.   As I’ve said, I’m not convinced, given these results, that I’m really buying the stocks I’d normally buy when looking at a chart.  As a result, I plan to look at charts of the 100 trades from both smoothing algorithms to determine how many of them look like “efficient” stocks.  This will give us a good idea to determine if we are looking at efficient stocks or not.  I still have not had the time to do this, so if any of you would like to do that and save me some time, I’d appreciate it.  Please let us know and we’ll send you the data. 

3.   We’ll also try other trend following algorithms including 1) an 180 day channel breakout and 2) linear regression to pick our trades.

All of that is still to come in subsequent articles and it looks like this series might continue for some time.

I think that Mechanica is capable of really answering a number of significant questions about comparing buy-and-hold versus various trend following.  We were fortunate enough to obtain an accurate 17 year database of the S&P 500 that was adjusted for splits and dividends and included numerous stocks that no longer exist.  However, our database was only 17 years (because it goes to Sept 07).  Since the S&P 500 was created in 1957, we’d be interested in knowing if anyone has an accurate database going back that far that we could use or even knows where I might obtain one.  That is, you have prices (dividend and split adjusted) for all stocks in the S&P 500 from 1957 through 2007 while they were members of the S&P 500.

 

1. If you have some interest in Mechanica, which we are using in these tests, then  go to the Mechanica web site -- http://www.mechanicasoftware.com.  Mechanica is the new windows version of Trading Recipes.

2.  We originally showed the compounded annual return to be 33.3%.  But when I was looking for the data set to fill in the rest of this table, the results were slightly different.

 

About Van Tharp: Trading coach, and author, Dr. Van K. Tharp is widely recognized for his best-selling book Trade Your Way to Financial Freedom and his outstanding Peak Performance Home Study program - a highly regarded classic that is suitable for all levels of traders and investors. You can learn more about Van Tharp at www.iitm.com.

Trading Education

Van Tharp's Trading Masterpiece
The Peak Performance Home Study Program

The Ultimate Home Study Course for Traders. How you think when you make and lose money. Stress reduction. How not to repeat your mistakes. Trading unemotionally. Contains five books and four CDs.

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Trading Tip

Learning from My Own Mistakes

by D.R. Barton, Jr.

I recently had a trade where I messed up.

I find that I’m really good at learning from mistakes that others make – and not so good at learning from my own missteps.  This time was different.

I’ve been using a new strategy that has me trade lower volume stocks than I normally use.  I scaled into a fairly large position (scaling in means to start with a smaller amount and then add at pre-determined points during the trade).  And the stock (which happened to be a short sale) was moving nicely in my direction.

That’s when I made my mistake.

Moving my stop down to protect my profits was the right thing to do.  The mistake I made was moving my stop too close for the type of stock I was trading.

When I trade stocks, I normally trade very high volume stocks.  Moving a stop fairly close is almost never a problem when trading RIMM, EBAY, AMZN or AAPL.  But I was trading a lower volume stock – and I forgot that important piece of volume and volatility information.  And it cost me a bunch of money.

The stock had a “hiccup” – within literally five seconds, it traded up to hit my stop. Then kept going fast against me, giving me an extra 10 cents of slippage (slippage is the difference between where you wanted your trade executed and where it actually got executed) and knocking me out of my position with a minimal profit.

To add insult to injury, after this little five-second “hiccup,” the stock was back down and trading at its original “pre-hiccup” levels.  Had I put my stop in a more rational place given the stock’s characteristics, I would have still been in a very profitable trade.  As it stood, I made a few bucks, but gave away a bunch because of a mental error.

But now the real battle started.  I’m talking about the emotional battle that takes place in a trader's or investor’s head when he or she makes a mistake.  I’ll describe the battle that took place in my head and then talk about how you can save yourself a bunch or money – or make a bunch more – by following a few simple guidelines.

Emotions – Good Company but Poor Guides

I had just given away a good chunk of money.  I was using good trading tactics, but I failed to properly take into account all of the conditions of my trade.  To be honest, I was mad.  I was mad at myself.  I was mad at this stupid stock (which, by the way, had been a brilliant stock just moments ago!). I was mad at the nameless, faceless traders that bought this stock for a few moments when I wanted them to sell.

In my emotional state, I did something I almost never do.  I jumped right back in and shorted the stock at its low.  (Shorting “in the hole” as some of my fellow traders call it.)

Then a wonderful thing happened. 

This second mistake of the morning cleared my head.  I had made this mistake before.  Sirens were going off in my head.  I was seeing red flags.  My gut clenched up.  And I did the exact right thing – I immediately got out of this ill-advised, emotionally driven trade.  No thought involved. No analysis to see if, in fact, the stock could drop further.  Nothing but a click of the mouse and out for a scratched trade (or a breakeven trade).

So the story does have a bit of a happy ending.  Within minutes, the stock moved strongly the other way and I was safely on the sidelines.  And with my emotions now in check, I could go back and analyze this stock and the markets rationally.  My strategy was done for the day on this stock.  So there were no more signals to act on.  It was time to move on.  And so, my lessons of the past really saved my bacon this time around.

Trade and Invest Based on Your Strategy, Not Your Emotions

I know of no trader or investor who makes better decisions when he or she is emotional.  Not one. So let’s look at three steps to take that will ensure that you can make your trading and investing decisions based on proven strategy, and not your current emotional state.

To follow a strategy, you have to have a strategy.  Why do you enter and exit your trades and investments?  If your answer is anything other than, “I base my entries and exits on a written strategy,” then you have left yourself wide open to make emotion-driven trades.  Every good trader and investor I know has a clearly defined strategy that guides all of their decisions.  Strategies can include written trading systems, computerized trading systems, following every pick from a newsletter and many others.  But you must know and apply your strategy to get consistent results.

If you know you are in an emotional state, don’t take any action.  If you find yourself getting emotional, just walk away and come back later.  This applies to traders who are in front of a computer screen or investors looking at the stock tables in the newspaper.  When you are emotional, your decisions are compromised.  This is true for any extreme emotional state.  Euphoria can cause bad decisions just like anger.  So if your stock has just made a huge move and you are ecstatic, you may want to buy every other stock in the sector.  Take a deep breath and a long break.  Then come back and go over your decision when you’re in a less elated state.  And most of all -- make your decisions based on your strategy!

Learn to change your emotional state.  When I made my second mistake in this trade, I used a psychological tool that I learned from Van to immediately change my emotional state.  There are some good resources for learning these valuable “state change” techniques, but Van’s home study course is the best one I know.  For more on this great resource (and every serious trader and investor should use it), click here.

Emotions are a wonderful part of the human experience.  But rarely do they help us make right decisions for trading and investing.  Stick with your proven strategy and leave your emotions for other areas of enjoyment.

Great Trading!

D. R.

About D.R. Barton:  A passion for the systematic approach to the markets and lifelong love of teaching and learning have propelled D.R. Barton, Jr. to the top of the investment and trading arena where he is one of the most widely read and followed traders and analysts in the world.

He is a regularly featured guest analyst on both Report on Business TV,  and WTOP News Radio in Washington, D. C., and has been a guest analyst on Bloomberg Radio.  His articles have appeared on SmartMoney.com and Financial Advisor magazine. You may contact D.R. at drbarton@iitm.com.

 

Melita's Inspirational Corner

Quick to Judge

by Melita Hunt

 

This morning as I walked to my car, I had to pass by four guys unloading a truck and it was interesting to watch my own reaction. The thought popped into my head “Oh geez, these guys are going to check me out, and they might even make a comment.”  But I was also quick enough to catch the thought and let it go. So what if they did make a comment or even whistle? I’m a pretty woman, dressed nicely, getting into a lovely sports car. A nice compliment usually feels pretty good.

I continued on my way, got in my car and drove off. There were brief glances, but there was no actual interaction at all. In my unconscious state, I chose to be judgmental of people I didn’t even know and just scurried off. I probably looked like a real snob. That is a prime example of past experiences and beliefs guiding behavior. I am not going to go into the ins and outs of these particular beliefs, where they came from, etc.  Suffice to say most of us have enough “men and women” interaction stuff to last us a lifetime!

In hindsight, I could have actually just said “Hi!” and given a friendly good morning wave to four other human beings who probably would have smiled and returned the greeting.

This in turn reminded me of an incident two days ago when I was walking into a chemist, and I saw a woman who was having trouble walking. It looked like she was experiencing some type of back pain, and she needed assistance. I remember thinking “I wonder how sick she is? Is she as sick as me? Does she have a terminal illness or is she just being a drama queen?” Ouch. Where did that come from?

Once again, I managed to “catch” the thought pretty quickly and let it go, replacing it with something much more compassionate but I also took the time to take note of it for future reference and analysis. I like to look at where my thoughts and beliefs come from.

Thoughts are continually racing through our brains a mile a minute, day in and day out. How often do we really pay attention to the actual thoughts that we are having? And how many of them are judgmental?

Neither of the thoughts that I “caught” in the above examples had anything to do with the actual people that I experienced in those moments. It was all “my stuff.” It was all based on beliefs, past experiences, and my projections.

So see if you can “catch” some of your own judgments and interpretations as they flash through your mind every second, disguised as thoughts.

And if you don’t think that you are quick to judge, then you are either living the life of a saint, and/or you tend to lie to yourself a lot. I would hazard to guess that we all have an arsenal of things that we are judgmental about:  politics, religion, Hollywood anyone?

Did I hear a scoff?

Melita Hunt is the CEO of the Van Tharp Institute. If you would like to keep up with Melita’s progress regarding her recently diagnosed lung cancer. Please feel free to read her blog at www.myleftlung.com.

You can contact Melita at mel@iitm.com

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