Tharp's Thoughts Weekly Newsletter (View On-Line)
An Interview with 2011 Wagner Award Winner: Part 1 by RJ Hixson
Trading Range Markets Continue by D.R. Barton
R-multiple Distribution Simulator in Excel
Have you ever wondered if the material covered in the Van Tharp Institute workshops is right for you? For just one day and one low price, you can get a taste of what the rest of our workshops are all about
Learn the Eight Core Areas of Successful Trading
- How to think about risk.
- How to think about your reward-to-risk ratio.
- How to think about position sizing™ strategies.
- How to think about trading systems as statistical distributions.
- How to think about trading systems in terms of sample theory.
- How to think about your trading success in terms of achieving your objectives.
- How to think about self-sabotage. What is self-sabotage?
- How to think about the psychology of trading.
There will be time to ask Dr. Tharp questions to ensure that you truly understand what you have learned and that you can easily apply it when you go home.
And, as a bonus, Dr. Tharp will present his famous System Quality Number® Talk.
An Interview with 2011 Wagner Award Winner Thomas Krawinkel: Part 1
Thomas Krawinkel recently won the 2011 Wagner Award for his submission to NAAIM’s annual research paper competition. He has been studying Van Tharp’s material for several years and cited Van Tharp in the References section of his paper. We conducted this two-part interview with him after he returned from presenting his paper at the NAAIM annual conference.
What kind of trading do you do?
Well I am not really trading yet. I wanted to start trading full time a few months ago, but I ran into problems testing some swing systems last fall. My analysis of those issues and the lessons learned became the foundation of my NAAIM paper. I expect to be trading later this year on a full-time basis and am preparing for that now.
What did you do before trading?
I was a financial controller and, more recently, I was a director of a small company. I left that position last year so I could focus full time on trading. Even though I’ve been getting ready to trade for a living for a total of five years now, about two years ago I realized that I wanted (and needed) to spend all my time in preparation. My wife has a good position, so we decided to take a chance and allow me three years of full-time devotion to trading. I hope to last as a trader much more than three years though.
How did you find out about the NAAIM competition? What made you want to submit an entry?
I was not out looking for a competition. I heard about NAAIM in Ken Long’s chat room where I was posting some research and a number of test results. One of the chat room members, had attended NAAIM’s annual conference and suggested that I submit a paper to their competition. The National Association of Active Investment Managers is a US-based organization that has two to three hundred members who are traders and active investment managers.
Jerry Wagner at NAAIM started the research competition about three years ago to attract attention and new members to the organization. To make the competition attractive, he put up $10,000 for first place. That’s why they call the winning prize the Wagner Award.
What was your paper about?
I had been doing a lot of back testing and found some pretty good looking systems. However, when I added in position sizing™ rules to the testing, I was stunned to see how severely the performance deteriorated. It was so bad that at first I thought I had mathematical errors in my spreadsheet. After looking into it I saw that the results were bad because the system had to skip lots of trades. Missing trades really hurt the profitability of the system.
As I looked into the root cause of why so many trades were not taken, I saw there was a limit to the buying power of my capital—sometimes there was not enough money to take all the trades because the signals were clustered together.
What were the main lessons of the paper?
When you look at a system you probably think about expectancy, variation and frequency of trades, which are the three core indicators in Van’s SQN® score and expectunity. However, one factor, in my opinion, is missing: the number of times the system would try to enter multiple trades.
Every concurrent position uses a portion of capital or more accurately capital and leverage—that’s what I call buying power. I found that even a system with a high SQN score (of 3.0) that signaled 600 trades spread out over 16 years had occasions when there were many signals clustered tightly together. I could have only taken all of the trades if I risked less than 0.2% of my capital per trade, which was too small of a position size for me to meet my objectives.
Overlapping trades consume buying power. If there are enough signals or already open positions all at once, your buying power (which is finite) prevents you from taking all the new signals. You have to skip trades, which is not part of your system design and therefore is not reflected in any backtesting results.
Skipping trades introduces an element of randomness into your real life performance that would not be there if you were able to execute each trade according to your rules. You simply can’t control when your buying power has been used up and which trades will be skipped.
How could a trader deal with this?
- Increase your leverage or trade leveraged vehicles, which effectively increases your buying power.
- Shorten the duration of the trades, which gives you less overlap.
- Reduce the amount of clustering the system experiences (signals firing at almost the same time).
- Reduce the number of vehicles in your trading universe so you have less clustering.
If all these fail, reduce the risk per trade. These strategies, individually and as a whole, have led to my personal solution: day trade. As a result of my research, I may no longer trade swing or intermediate term systems.
What was it like to present the paper at the annual NAAIM conference?
I'm not used to giving presentations, especially in English, so it was quite exciting for me. The audience seemed to listen, and everyone said I did well.
What surprised you about the conference?
I was really surprised by how professional investment managers approach trading. If you have studied Van Tharp's material, you probably think in terms of trading signals, defining risk, measuring reward in terms of risk, and making a profit at the end of the year. They don’t think along those lines. Investment managers don't mind a loss at the end of the year—as long as the market was down more than their fund. They justify their losses: “Even though I was down, I beat the market.” My position as a client of such a manager, though, would be that they lost money—MY money.
Also, most of their systems seem to be rotational systems that are always invested in some sector of the market. With this method, the buying power problem does not exist: they always rebalance the equity but never have any clustered signals. They simply allocate their money where they think it will perform best. This is not the way I approach trading. If there are no signals, I'm happy to sit in cash and wait for signals. If there are many signals, I will be very active and exploit the opportunities.
Aside from the award and prize money, what did you gain from the experience?
I found most precious the appreciation of my ideas by knowledgeable people. Until last year, I didn’t know any other traders and felt quite lonely. When you are working hard for so long on something, it’s good to get validation that the work is valuable and interesting. It was also good to learn that I didn’t get disconnected from reality in the process—especially since I have little trading experience.
Do you have any advice for others about submitting a paper for a competition?
Find any competition you can and submit something—but not for money or an award.
The biggest benefits come from sitting down and formulating your thoughts in a way that other people will be able to comprehend. Writing this paper helped me organize my own thinking in a way that would not have happened if I had not submitted it. As a result of the research and writing the paper, I have changed my approach to trading.
When I look at systems now, I'm looking for little clustering and short time horizons. As I mentioned, the solutions to the problems that I found in my backtesting of swing systems seems to point to day trading. Personally, though, I don’t want to sit in front of a screen all the time; therefore, I intend to use my programming skills to make the trading process fully automated. Having talked to quite a number of traders during the last year, I now believe I am probably the most extreme mechanical trader that I know of. Maybe there just aren’t many purely mechanical traders out there but that is the direction that I am heading.
Thomas continues the interview next week in part two where he shares his extensive experience and thoughts on backtesting. In the mean time, you can download his paper from the NAAIM web site and you can download Thomas’ Buying Power tool by clicking here.
This Excel file will be available for downloading for a limited time only. You will need Microsoft Excel 2007 (or 2010) to use the tool. If you are asked for a password in the download process, just “x” the box to close that window and the file should still open.
The Buying Power tool spreadsheet helps traders understand the relationship between margin, 1R, and the position sizing strategy. It also provides a calculator to help identify limiting factors. Thomas provided this tool to the NAAIM evaluation committee in support of his paper. There are no instructions with the Buying Power spreadsheet tool, and you will need a good working knowledge of position sizing concepts in order to interpret its results.
You can contact Thomas by email - “TKrawinkel at GMX.de”
Introduction to Position Sizing™ Strategies
This course is perfect for busy professionals who need a practical way to understand risk and understand how to keep losses to a minimum.
Hard-working, avid learners like you want top-quality information presented in an efficient and orderly way.
Students who have completed this course have told us that they love the straightforward and methodical presentation, which has easy-to-follow audio, video and interactive features. You even get to play one of Dr. Tharp’s famous marble games.
Visionary trading coach, Van K. Tharp breaks down a complex topic into easy-to-understand lessons that you can repeat as often as you like during your subscription.
The on-line format also allows you to start and stop the course when you need to and pick up right where you left off.
The information contained in this course will open your eyes to the importance of position sizing strategies and how they can reduce your losses and increase your profits. The profits gained by applying the information contained in this course could easily pay for the course over and over again.
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Trading Range Markets Continue
In successive articles on June 15 and June 22, I outlined a likely turning point in the equity markets and presented some targets for the move off of those intermediate lows. The market hit the turning point and rebounded with a vengeance, but then it turned again to put us in yet another new and interesting spot.
As an overview, we have been looking at a combination of technical analysis and sentiment analysis to judge the market at near term and intermediate term extremes. While almost all of our readers are familiar with technical analysis, fewer are grounded in the study of market sentiment. In short, sentiment analysis gives us strong clues about when the psychology (and actions) of market participants have swung too far to one side. When this happens, a move away from the extreme sentiment is likely to occur.
Think of this as a rebalancing—when too many people are on one side of a boat, some move back from the edge realizing the boat is leaning too far. In mid-June, too many people were at the bearish side of the boat and others recognized it.
Where are we now? For perspective on our current situation and how we got here, let’s go back and look at the midmorning chart for the S&P 500 cash market on June 15th.
I wrote the article that day based on the chart above and the day after, the market pushed lower to the first area defined: the 2010 close combined with the rising 200-day simple moving average (SMA), providing a confluence of support levels. The 2010 close is an important psychological level—above that level the market is in positive territory for the year; below it, the market is in the red. At the same time, the market sentiment indicators I discussed in the article hit extreme oversold levels, which added to the probability of a short-term market turn.
The second day after that article, the market responded as expected and bounced off the support area in fine fashion.
Nothing Is Easy in This Market Environment
However, as mentioned in a previous article, this year’s market action has defied all attempts at extended trends, and such was the case with this move. More negative news out of the Euro zone and reduced Chinese growth numbers led to a pullback right down to the 200-day SMA as you can see in the following chart.
The subsequent bounce off of the second touch of this well-watched moving average was of such impressive magnitude (5.5% in one week) and thrust (up volume eclipsed down volume by the largest margin for a single week since 1970!) that many exceptional analysts were swayed strongly back to the bull camp.
But once again, this pogo stick market refused to continue in one direction for long. A combination of a dismal US employment report, continued deterioration of the debt picture in Italy, and Moody’s further downgrade of Ireland has once again pulled us off of the highs.
What’s more, we received some ominous technical indications in the last week. See the chart below of SPY—the S&P 500 ETF that mirrors the S&P action.
The island reversal top and the unfilled gaps have returned the bearish technical tone to the markets. However, with the market now neither overbought nor oversold, the current negative technicals are balanced on the other side of the equation by the longer term uptrend of the market and the overwhelming evidence of buying pressure shown when the market charged up after the second touch of the 200-day SMA.
This is a traders’ market. Longer term positions holders will continue to cycle from frustration to elation and back again, especially until the Euro zone debt crisis is moderated (this means pushed further down the road, since any type of short to intermediate term “fix” is but a fantasy).
As hedge fund trader John Thomas said this week, “All I can say is if Paul Tudor Jones, Louis Bacon, and John Paulson can’t make money in this market, I bet you can’t either. Better to watch in awe from the sidelines until the dust settles and let others do the bleeding.” Thomas’ insight was in full agreement with the theme of my article last week that the markets, like fishing, require patience and sometimes you just have to be happy not to give any back.
Two Events Added in July
This one-day workshop is perfect for those who would like to learn an overview of our basic tenets taught exclusively by Van!
This popular transformation workshop usually sell out. Register early to ensure your seat.
Click here to see our full workshop schedule with details
Click here to see locations, logistics, etc.
R-Multiple Distribution Simulator in Excel
Q: I'm reading Trade Your Way, and I'm totally amazed by this book. Like all the other publications by Dr. Tharp it contains so many important information and useful suggestions.
In one of his books it says that one can simulate the R-multiple distribution of a trading-system using Excel.
I've already done a few simple Monte-Carlo simulations in Excel, but to be honest, I have no clue how to simulate the R-multiple distribution.
I'd be very grateful if you could help me with this one.
A: What I meant is that you can develop a simulator into which you plug in an R-multiple distribution. You can then simulate 50 trades 10,000 times to find out the typical results from trading that system. In this process, you would assume that the R-multiple distribution of the trade sample reflected the population of the trading system. The simulation would let you know what to expect in terms of results, drawdowns, etc.
We had such a simulator, but I was reluctant to sell it because it could be misused. Its main purpose was to help you know how to craft a position sizing strategy to help you meet your objectives. Instead of releasing that simulator software, I wrote the Definitive Guide to Position Sizing as an alternate way to help people understand how to reach their objectives without needing such a simulator.
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