A good read that adapts Leonardo Da Vinci precepts to trading.

Feedback:

Hey Michael, Hello, I am a mathematics and philosophy student at Michigan Tech University. I loved reading your book twice; I am going to read it a third time. I find the trend trading philosophy to be very stoic and the concept, rather simple yet eye-opening. Often I find myself teaching others about your style of trading and even debating with others about indicators (basically all indicators never stack up to price in the long run or any run for that matter)…When you say “turn your philosophies into computer code” what exactly do you mean by this. If I am more of a risk taker, make bigger bets that sort of deal?

Real straightforward. If your rule, for example, is to buy when a market makes a 100 day high – then make that a rule you can put into computer code. That’s it. Of course that can expand out to cover much more than my simple example.

I received this feedback:

“Jim Sinclair said that just relying on computers and computer models cannot be a substitute for the real knowledge of the markets. What is your opinion about that?”

I responded: “Do you think his opinion makes sense given the public performance data of the traders you say he criticizes?”

He responded:

“Well, he seems to know a lot about gold and gold markets. He also seems to have forecasted correctly the present gold price action. It is not a bad idea to read first his comments.”

Here are the comments in question. I don’t understand how these comments refute trend following performance data.

Trading is not about hero worship. Meaning just because someone of note says something – do some homework. The numbers are either there or not. If trend following performance numbers did not exist for the many traders I have interviewed and or profiled, I never would have mentioned their names.

James Montier recently wrote about the lack of acceptance of systematic trading:

“The industry has a large dose of inertia contained within it. It is pretty inconceivable for a large fund management house to turn around and say they are scrapping most of the processes they had used for the last 20 years, in order to implement a quant model instead. Another consideration may be the ease of selling. We find it ‘easy’ to understand the idea of analysts searching for value, and fund managers rooting out hidden opportunities. However, selling a quant model will be much harder. The term ‘black box’ will be bandied around in a highly pejorative way. Consultants may question why they are employing you at all, if ‘all’ you do is turn up and run the model and then walk away again. It is for reasons like these that quant investing is likely to remain a fringe activity, no matter how successful it may be.”

In a zero sum world, Montier nails yet even more reasons why strategies like systematic trend following will excel into the future.

A good piece of wisdom from Bill Eckhardt:

“If you make a bad trade, you have money management, you have a whole bunch of things that will come to your aid, and you’re really not in so much trouble if you make a bad trade. But if you miss a good trade there’s really nowhere to turn. If you miss good trades with any regularity you’re finished, you’re doomed in this game.”

Feedback received today:

“Hi, I was just experimenting using different moving averages to react to price movement in equities and futures. I notice that in your book, you mention only exponential moving averages of different time lengths. What do you think of using moving averages with different calculation methods (say exponential and triangular or time series) in order to track recent price movement in a stock as opposed to price movement in the past? It seems like that would be a pretty good way to track breakouts. Thanks. Joe.”

I look at these issues in a different way. The key is answer the 5 questions presented in Chapter 10 of my book:

1. How do you determine what market to buy or sell at any time?
2. How much of a market should you buy or sell at any time?
3. How do you determine when you enter a market?
4. How do you determine when you exit a losing position?
5. How do you determine when you exit a winning position?

If after testing you determine that your variation or choice of moving average works to help you answer those 5 questions (to meet your personal goals of profitability, drawdown, etc.), then you are on to something. If it doesn’t work, lesson there too. But don’t get fixated on the entry indicator…

I was quoted today in The Minneapolis Star Tribune. The article was titled Computer Algorithms Increasingly Call Shots in Stock Trades. While the article may come off as a little simplistic, we should all appreciate this reporter tackling a subject still foreign to most traders and investors. [source]

Van Tharp, thinking appropriate for my audience, emailed me one of his white papers (PDF) regarding “trading systems”. Take a read!

Ed Seykota includes a section on data verification at his web site.

This report from The Economist contains the following excerpt:

“Beyond worries over market stability, might an even greater danger be lying in wait? Mr Hooper proposes a doomsday scenario. Some day, advances in natural-language processing and statistical analysis might lead to robo-traders capable of analysing news feeds, deciding which shares to buy and sell, and devising their own strategies. Given that companies are very keen to patent their algorithms, it is quite possible that just one company could then emerge as the victor in this algorithmic arms race, says Mr Hooper. This outcome would create a particularly challenging problem for regulators. “It is a possibility that you could have an unfair advantage and there would be nothing governments could do about it,” he says. It is an interesting idea. But it seems unlikely, since there are so many possible trading strategies, and unlike simpler problems in computing (such as sorting a list) it is doubtful that there will turn out to be a single trading algorithm that outperforms all others. Yet perhaps such a suggestion should not come as a surprise. For whenever robots are being discussed–even if they are merely the software-based, share-trading variety–the idea that humans will lose their jobs and the robots will take over the world always seems to be lurking in the background.”

A Simple Trading System: Exponential Average Crossover from Ed Seykota. An online tutorial worth checking out.

One of the favorite questions by beginners is, “Can I trade your system or invest with a trend follower with $5000?” Not sure where this number comes from, but it always seems to be the same $5000 for all beginners!

I noticed the other day that Ed Seykota was asked at his site Seykota.com (and I paraphrase):

“I have $5000…should I keep trading or stop until I gather equity to diversify?”

In true Seykota style he responded:

“Say you want to buy a car and only have a few dollars. I wonder if you: Go out and purchase something in your budget, like a spare tire (or) wait until you can afford to buy a whole car.”

He then added:

Plan A:
Drive this around for a while.

Plan C:
Develop a trading system and attract capital.

Another long standing view on the “capital” needed to trade.