Designing a Trading System: The First Step, Worry about Making Money Instead of Being Right

By Michael J. Carr, CMT

To be successful in trading means that you make money and the most important rule new traders must understand is that it’s more important to make money than it is to be right. The goal is simply to make more money on the winning trades than you lose on the inevitable losing trades. Just like in baseball, it is possible to be wrong 60-70% of the time but still make money in trading. A batting average of .300 is usually good enough to be immortalized in the Baseball Hall of Fame, yet traders often try to be right at least 90% of the time.

Grasping this idea is actually the first step towards becoming a winning trader. It requires you to see the logic that the winning percentage isn’t as important as the dollars gained. Trading is a logical undertaking, but it means thinking differently than the average person does. First, you need to ask yourself if you’d rather be right or make money. If you choose the latter, then you’ll need to find a way to let winners run and cut losses quickly (it really is that simple).

In order to find winners, you will need to study the markets and decide when to buy and sell. This again requires you to look at things differently. As old traders will say, “to know what everyone knows is to know nothing.” This means you can’t win by simply applying standard indicators with their default settings. You need an edge, the logical idea that separates you from all the others. Warren Buffett explained this when he said, “If you’ve been playing poker for half an hour and you still don’t know who the patsy is, you’re the patsy.” The patsy is the person playing without an advantage, the one the sharp players are making money from. Patsies like to play in the markets, as well.

Markets consist of millions of traders. Some are professionals and they will generally have long-term winning records, otherwise they would lose all their money and wouldn’t be professionals. Every buyer needs to find a seller willing to take the other side of the trade, and vice versa, so half of all trades must be losers, by definition. However, most markets have an upward bias in prices because of inflation and general economic growth. This is why you can make money by being wrong so often, the net number of dollars the markets is worth generally rises in the long-term even though only half the trades will ever be winners.

To profit from trading, you can’t be the patsy. You have to know something that offers you an edge. Successful traders can use a well-defined system or rely on their instincts to generate signals. Discretionary traders use instincts and can be successful, as George Soros has shown. He trades on macroeconomic trends and has earned a personal fortune of several billion dollars while creating billions more in wealth for his investors and favorite charities. Soros has also said that in addition to following the news, he trusts his own body to offer signals and will sell when his back hurts too much. Few have the intellectual gifts of Soros or the other great discretionary traders, and rules-based systems offer an attractive alternative trading style for most traders.

Despite the differing approaches to entering and exiting trades, systems and discretionary trading strategies share a common goal. Both are trying to make money based on the moves of the markets. To be successful, both rely on a logical approach that works for the individual trader. Maybe “works” is too strong a word to use since most traders fail. It may be better to say that any trading strategy begins with an underlying logic that offers some kind of appealing feature to the trader using the strategy.

Discretionary traders apply outside knowledge to the markets. They may buy a tech stock because their neighbor works at the company and says the company’s new product can’t miss. Or they buy crude oil futures after reading on their favorite website about how prices will keep going up. These traders rarely have an exit strategy, but they believe their entry is logical since they have some kind of special information which indicates prices are about to move. Soros based his most famous trade on the logic that the British Pound was overvalued. He had a detailed understanding of the fundamental economics and political situation of Great Britain and he knew precisely how the Euro would work. He backed this knowledge with billions of dollars of capital, and hung on for the long haul even as his initial losses amounted to a few hundred million dollars. Eventually, he broke the Bank of England and made $1 billion in day. But in order to win, Soros had invested well over $2 billion in his trade, and the size of his bet helped him win.

Systems traders use strategies designed to provide a mathematical edge, one that has proven to be profitable in the past. While past performance is not likely to be repeated exactly in the future, the past is the only guide we have to what might happen in the future. Readily available trading software packages allow anyone to test a variety of systems in a short amount of time. This is called data mining since there is no underlying logic as to why the rules should work. Without a reasonable explanation for why the rules worked in the past, there shouldn’t really be any expectation that they will work in the future.

This is often overlooked by new traders. They read about an indicator, like RSI or any of the hundreds of others, and decide to test it. With just a few clicks of the mouse, they can backtest the indicator against hundreds of stocks using every available parameter to determine the best buy and sell rules. But, there is no logical reason that the indicator and the optimal parameters will work in the future because there was nothing except random chance that made them work so well in the past.

Good trading systems start with a logical reason for why prices should move, followed by a test to see if that idea is correct. That’s important – the reason should come first, then the backtest. If the reasoning is sound, the system is more likely to perform well in the future. As an example, we might want to build a system that tries to find out what large traders like Soros are doing.

Logically, since they are large traders, they need to acquire big positions in order to profit from any price moves. They’ll also want to establish their positions over time since a single large purchase would drive the price higher instantly. As a starting point, we could look for stocks that have seen the largest percentage increase in trading volume over the past three months. The volume increase would satisfy our first assumption that they are acquiring large positions. We use a three month timeframe to account for our belief that they build the position over time rather than all at once.

We could then add a condition that the stock price needed to show more relative strength than the overall market. This means it would gain more on a percentage basis than a market index in a bull market, or lose less in a bear market. Relative outperformance would indicate with numbers that the reason for the volume increase was because demand (buying pressure) was greater than supply (selling pressure). If sellers outnumber buyers, prices will fall since sellers have a greater motivation to trade and will be the primary drivers of the price trend.

Further refinements to this logic-based system would include setting a minimum dollar threshold for trade volume times share price. To make a difference in their performance, Soros or Buffett need to acquire positions worth at least several hundred million dollars. Multiplying volume times price shows whether or not this criterion is met, and eliminates lower priced stocks that wouldn’t attract the attention of investment legends.

We could sell after six months if filings with the Securities and Exchange Commission don’t confirm a purchase was made (large traders must disclose significant trades they make with the SEC every 90 days). We could also sell if there is price weakness on large volume, or if the price fell by an amount that exceeded our comfort zone. Over time, this approach will spot occasional big winners, and experience a lot of small losers. This adds up to more winning years than losing years, when we look at dollars gained, and can form the basis of a profitable trading system.

This is just one example of how logic comes first, and specific buy and sell rules follow from the reasoning. Relative strength systems use this system design approach, as do many indicator based trading strategies. Logic offers an edge to traders, especially if they are more interested in making money and willing to be wrong on any individual trade, because the future is actually very likely to be similar to the past in the markets.

See also: Designing a Trading System: What Should You Trade