Systematic trend following is a great form of technology:

tech·nol·o·gy [tek-nol-uh-jee] noun

1. the branch of knowledge that deals with the creation and use of technical means and their interrelation with life, society, and the environment, drawing upon such subjects as industrial arts, engineering, applied science, and pure science.
2. the terminology of an art, science, etc.; technical nomenclature.
3. a technological process, invention, method, or the like.
4. the sum of the ways in which social groups provide themselves with the material objects of their civilization.

Neal T. Weintraub had a great line:

“You will run out of money before a guru runs out of indicators…”

Meaning, don’t get caught up looking for the perfect entry or the magic entry indicator. It is a waste of time. Find a robust trading system and use discipline. That is the best bet.

From FT:

Systematic trading may inherently be guided by the same considerations. But this approach goes about investing in an automated way, based on intricate algorithms based on years of historical performance that restrict input of sentiment and hunches. Computers monitor and interpret market trends. They ignore theories, only concerned with how markets are moving. And they make investment decisions based on short, medium, and longer term time horizons. “I don’t believe in efficient markets,” says Rob Friedl, co-founder of Wisconsin-based Fall River Capital, with more than $200m in assets under management. “Markets reflect human nature, and human nature is often wrong.” He trades across seven distinct markets: agriculture, metals, energy, stock indices, short rates, bonds, and currencies. This gives him access to more than 80 specific trades, ranging from unleaded fuel, wheat and zinc to UK gilts, Euribor rates and the Hang Seng index. And because he can bet them either long or short, Mr Friedl has the potential to perform well in any kind of market. “No one time is any more challenging than another – so long as markets trend,” he says. Mr Friendl does not care if Opec is cutting oil production or who wins an election. His transactions are focused exclusively on when the price of a commodity, currency, or an index breaks out of a trading range. He will be long if it is going up, short if it is heading lower. And when the trend breaks down, he will get out of the trade. Since inception in August 2000, his fund has generated annualised returns of 16.17 per cent. In contrast, the S&P 500 was down 3.08 percent over the same period. Roy Niederhoffer refines the systematic approach, using ultra-short trades to profit from volatility. Last year the R.G. Niederhoffer Capital Management Diversified Program, with $560m in assets, was up 51 per cent. Since inception in 1993, his average annualised return is 11.1 per cent. But the historically strong trends of this year’s first and second quarter has revealed the one scenario in which he cannot excel. Year-to-date, as of June, he is down 1.19 per cent. Like Mr Friedl, Mr Niederhoffer ignores company fundamentals and macro-economic trends. With a background in neuroscience he has created computer models that focus on short-term investment biases hard-wired into the human mind. He explains: “Investors overemphasise recent experience when making decisions; people hate to lose more than they love to win; investors become more predictable as markets become more volatile; and when they are emotional, investors tend to be herd-like in behaviour. That last tendency leads to selling when stocks are near a bottom, and buying when rallies are overextended.” Mr Niederhoffer endeavours to capitalise on the predictability of these response patterns by targeting quick gains. His Diversified Program makes thousands of trades a year, ranging in duration from several hours to a week, and occasionally longer. Being right just a little more than half the time is all he needs to generate large profits.

A great reminder from technical analyst John Murphy:

“The statement ‘market action discounts everything’ forms what is probably the cornerstone of technical analysis. [...] The technician believes that anything that can possibly affect the price–fundamentally, politically, psychologically, or otherwise–is actually reflected in the price of that market.”

That is a great piece of wisdom. It is exactly the wisdom seen throughout my book Trend Following. Sure, I like to know how politics and economics intersect to bring about massive stupidity, but beyond that is the “price”. More great expressions of technically minded traders recently added as side margin quotes to my new edition of Trend Following follow. First, Jesse Livermore adds:

“It may surprise many to know that in my method of trading, when I see by my records that an upward trend is in progress, I become a buyer as soon as a stock makes a new high on its movement, after having had a normal reaction. The same applies whenever I take the short side. Why? Because I am following the trend at the time. My records signal me to go ahead!”

Alfred Cowles adds:

“This evidence of structure in stock prices suggests alluring possibilities in the way of forecasting. In fact, many professional speculators, including in particular exponents of the so-called Dow Theory widely publicized by popular financial journals, have adopted systems based in the main on the principle that it is advantageous to swim with the tide.”

William Dunnigan adds:

“We think that forecasting should be thought of in the light of measuring the direction of todays trend and then turning to the Law of Inertia (momentum) for assurance that probabilities favor the continuation of that trend for an unknown period of time into the future. This is trend following, and it does not require us to don the garment of the mystic and look into the crystal balls of the future.”

Richard Donchian adds:

“When I first got into commodities, no one was interested in a diversified approach. There were cocoa men, cotton men, grain men they were worlds apart. I was almost the first one who decided to look at all commodities together. Nobody before had looked at the whole picture and had taken a diversified position with the idea of cutting losses short and going with a trend.”

William Dunnigan adds:

“Let us believe that it is possible to profit through economic changes by following today’s trend, as it is revealed statistically day-by-day, week-by-week, or month-by-month. In doing this we should entertain no preconceived notions as to whether business is going to boom or bust, or whether the Dow-Jones Industrial Average is going to 500 or 50. We will merely chart our course and steer our ship in the direction of the prevailing wind. When the economic weather changes, we will change our course with it and will not try to forecast the future time or place at which the wind will change.”

Ed Seykota adds:

“All trends are historical, none are in the present. There is no way to determine the current trend, or even define what current trend might mean; we can only determine historical trends. The only way to measure a now-trend (one entirely in the moment of now) would be to take two points, both in the now and compute their difference. Motion, velocity and trend do not exist in the now. They do not appear in snapshots. Trend does not exist in the now and the phrase, “the trend” has no inherent meaning…There is no such thing as a current trend. When we speak of trends we are necessarily projecting our own definitions. With that in mind, we can proceed to examine ways to define, compute and use trends.”

Samuel Clemens:

“Figures don’t lie, but liars figure.”

The article is titled “Why Can’t Economists Get It Right? Because They Don’t Go To Las Vegas”. Sounds plausible. Makes good points, but ultimately why does it matter whether an economist gets it right or wrong? Unless they are offering a precise trading strategy, opinions and predictions, whether right or wrong, mean squat. The average person needs more precision than simply a good indicator that cement demand will be down, they need rules to make money if cement doesn’t go down.

From the International Herald Tribune circa February 1, 1992 comes this article “The New High-Tech Investing: Computer as Fund Manager” By Philip Crawford:

The specter of a computer-dominated society has long been the stuff of science fiction, conjuring chilling scenarios of a world that values only efficiency. Welcome to the cutting edge of investment management. The use of computers to automatically trigger moves in a variety of markets is growing, portfolio managers and traders say. Although they acknowledge that the true stars of the industry outperform computers today, they contend that the days of homo sapiens as the highest form of investment strategist are numbered. “Put it this way,” said David Harding, research director of Adam, Harding, & Lueck, a London-based commodity trading advisor, “I don’t expect the world chess champion to be a human being in the year 2000, and I don’t expect the world’s top investment manager to be one either. We’re already at the point where the best computer systems are better than the average manager.” Why the increase in computer-managed portfolios? Investment company executives cite the seemingly age-old reasoning that first struck fear into automobile workers a generation ago when assembly-line robotics initially appeared: that a well-programmed machine performs more consistently, and less expensively in the long run, than a human being. “The computer is not subject to human frailties, other than its design and how it’s programmed,” said Michael Quenington, European manager of E.D. & F. Man International, a London investment firm. “A person can have a huge row with his wife one morning, crash his car, or have any number of things happen that can affect his emotions and judgment. And all the information a person has in his head might rest only with him. A person dies, but a computer just keeps churning out numbers.” Mr. Quenington cited a program recently devised by his firm that, given a revolving input of 100 highly liquid equities chosen by staff researchers, electronically monitors the stock market and produces profit-maximizing decisions on how much of each stock to buy or sell, and when. He declined to elaborate on which market characteristics prompted the program to make its choices, saying only that it employs a mathematical model, and is performing well. Using computers to signal an opportune moment to trade large blocks of equities is, of course, nothing new. Program trading, which involves taking advantage of discrepancies in prices between stock-index futures and the underlying stocks, came into vogue during the 1980s bull market and is sharply on the rise internationally, according to a recent study by Greenwich Associates, a U.S. research group. The practice, also known as stock index arbitrage, can cause huge swings in the market as electronic “buy-sell” programs are tripped off when prices reach a certain level. Many securities industry professionals have maintained that program trading contributed to the crash of ’87. But the search for greater returns has led to the evolution of ever more sophisticated software that monitors developments in numerous markets simultaneously, taking trading action when a list of programmed criteria are met. “We devised a set of hypothetical rules, such as ‘buy this product if the price goes over the 60-day moving average,’ or something like that,” said Peter Matthews, chief portfolio strategist for New Jersey-based Mint Investment Management Co., in describing the development of his firm’s in-house software. “Then we took the rules and applied them to the behavior of markets going 20 to 30 years back. Once you find out what works historically, then you can write a program that goes forward.” Mr. Matthews said Mint’s programs determine when the firm, which deals primarily in commodities and foreign exchange markets, should sell soybeans, for example, or buy gold. “Particularly in futures,” he said, “things move so fast that when things start to go badly, you tend to panic. The computer is totally unemotional – it never panics. It really improves consistency. You can sleep more soundly at night knowing it’s there.” Mr. Harding, acknowledging that total reliance on computers might be unsettling to some, maintained that the advantages of human perceptional abilities are largely outweighed by the computer’s capacity to process staggering amounts of information instantaneously. The use of programs based on historical trading patterns, he added, “actually helps mesh the world of the computer with those of the researcher and trader, rather than polarize them. If someone has an idea or theory he wants to test, it takes only 20 minutes, not 20 years, to simulate it.” But despite apparently impressive performances by 100 percent-computerized firms such as Mint and AHL – both claim compound annual rates of return in excess of 23 percent over the past eight years, compared with 12.4 percent for the S&P 500 – not everybody is jumping on the bandwagon. “We don’t do this type of computer program-driven trading,” said Barry Holman, a quantitative analyst at Legal & General Investment Management in London, “because we haven’t found (software) which we feel is reliable enough. But there’s no doubt that some computers are a real challenge to fund managers. There’s a lot of market knowledge out there that never gets acted on, because people don’t always do things they intend to.” Computers cannot, of course, be programmed to predict market reaction to random events, or to feel fear when perhaps fear is called for. Some say that a harbinger of a doomed race might be the creation of a computer that could get angry or fall in love. And machines obviously need humans to feed them data in the first place. But in the investment world, well-programmed computers that figure out what to do, and then do it, are the wave of the future, say many market pundits. The next generation of machines, moreover, may not attempt to emulate the human mind better, but try to incorporate it. “We’re seeing research on machines which would theoretically interface with a human mind, in which a person can be totally immersed, by being placed inside an electronic body-suit, or some similar concept,” Mr. Harding said. “It’s very sci-fi, I know, but maybe it really is possible to get the best of both worlds.”

17 years ago this was printed? Yes. 17 years ago.

An excerpt of an interview with Art Collins and Richard Dennis follows. First the question from Collins and then the answer from Dennis:

Q. How hands on are you behind the programmers? Are you standing behind them explaining exactly what you want optimized, etc?

A. I spend most of my time talking to programmers and waiting for results. I’ve been working with most of these people for 20 years so I•m able to get into that intermediate zone between computer-ese and real English. I call them up and say here’s the idea in English. Here’s my idea of how it would go in the program, but you’re the guys who are going to have to decide that ultimately. It’s actually quite an adventure because a good programmer will get the first iteration wrong half the time.

From Hedge Fund Daily comes the hedge fund world through the lens of a newbie reporter:

For hedge funds, it does not compute to use human analysts, when an electronic version can do basically the same job. And thus, Reuters reports, hedge funds, which were early to adopt new investment methods, are being credited (or perhaps, blamed, if you’re an analyst), for the burgeoning growth of quantitative strategies. “It’s all about trying to create an artificial analysts,” one unnamed portfolio manager at a quant hedge fund told Reuters. “It may not do it as well (as a human), but it makes up for it in volume.” Reuters cites as evidence of quant success to two of the industries top hedge funds that use them, D.E. Shaw and Renaissance Technologies, which were formed by math professors and are well-staffed with scientific types. Following their example, even non-quant hedge funds are expanding their use of computer models. “It doesn’t necessarily mean that Wall Street analysts are going to go out of business,” Ron Papanek, director of strategy at RiskMetrics Group, said in a Reuters interview,” but it does mean that there are other ways to be successful in identifying value.” He further noted that the fact that the biggest hedge funds are using its means “this form of analysis has legs.” Taking some of heat off hedge funds for equity analysts woes, Brad Hintz of AllianceBernstein, said the human kind are “doomed” also because regulatory investigations into analyst conflicts years ago has resulted in lower trading commission, and that’s put research on the cutting block as firms try to save on operating costs.

How can an author write about quantitative trading strategies in June 2007 and with a straight face make the case that these efforts are innovative or new? Systems trading has been around since the time of Richard Donchian – that’s back to the 1950s and earlier. Don’t get me wrong, Simons is a trading stud, a legend, but the basic ideas of 100% mechanical systems is not ground breaking.

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.