Deconstructing the Seykota Crossover: A Guide to His Moving Average System

The Elegance of Simplicity

In a world of complex algorithms and esoteric indicators, Ed Seykota's preferred trading system stands out for its remarkable simplicity. At its core, Seykota's system is a moving average crossover strategy. This approach, which he pioneered in the early days of computerized trading, is a evidence to his belief that a trading system does not need to be complicated to be effective. In fact, he has often argued that simplicity is a virtue in trading, as it reduces the likelihood of errors and makes it easier to follow the system with discipline. This article will deconstruct Seykota's moving average crossover system, exploring the specific indicators he used, the entry and exit signals, and the underlying philosophy that makes this simple system so effective.

The Basics of Moving Averages

A moving average is a technical indicator that smooths out price data by creating a constantly updated average price. It is a lagging indicator, meaning that it is based on past prices, but it is an invaluable tool for identifying the direction of a trend. There are several types of moving averages, but the two most common are the simple moving average (SMA) and the exponential moving average (EMA). An SMA is calculated by adding up the closing prices for a certain number of periods and then dividing by that number of periods. An EMA, on the other hand, gives more weight to recent prices, making it more responsive to changes in market direction.

Why Seykota Favored Exponential Moving Averages (EMAs)

Ed Seykota is a proponent of using exponential moving averages (EMAs) in his trading system. The reason for this preference lies in the nature of the EMA itself. Because the EMA gives more weight to recent price action, it is quicker to react to changes in the trend. This increased sensitivity can provide an earlier entry into a new trend and a quicker exit from a trend that is reversing. For a trend follower like Seykota, who seeks to capture the majority of a major market move, this early entry and exit can make a significant difference in profitability. The EMA's ability to hug the price action more closely than an SMA also provides a more accurate representation of the current trend.

The Specific EMA Combinations He Used

While Seykota has never publicly revealed the exact parameters of his trading system, it is widely believed that he uses a combination of a short-term EMA and a long-term EMA. The specific lengths of the EMAs can be adapted to different markets and timeframes, but a common combination is a 13-period EMA and a 40-period EMA. The 13-period EMA represents the short-term trend, while the 40-period EMA represents the long-term trend. The interaction between these two moving averages is what generates the buy and sell signals.

Entry and Exit Signals Based on the Crossover

The entry and exit signals in Seykota's system are generated by the crossover of the two EMAs. A buy signal is generated when the short-term EMA (e.g., 13-period) crosses above the long-term EMA (e.g., 40-period). This is known as a "golden cross" and it indicates that a new uptrend may be underway. A sell signal is generated when the short-term EMA crosses below the long-term EMA. This is known as a "death cross" and it indicates that a new downtrend may be underway.

The exit strategy is just as important as the entry strategy. A position is typically held until the EMAs cross back in the opposite direction. For example, if a trader entered a long position on a golden cross, they would exit the position when the short-term EMA crosses back below the long-term EMA. This ensures that the trader rides the trend for as long as it lasts and exits the position when the trend shows signs of reversing.

The Importance of Backtesting and System Validation

Seykota is a strong advocate for the use of computers to backtest and validate trading systems. Backtesting is the process of testing a trading system on historical data to see how it would have performed in the past. This is a important step in the development of any trading system, as it can help to identify potential flaws and to optimize the system's parameters. Seykota was one of the first traders to use computers for this purpose, and it gave him a significant edge over his competitors. By backtesting his moving average crossover system, he was able to prove its effectiveness and to gain the confidence to follow it with unwavering discipline.

How to Adapt the Crossover System to Different Markets and Timeframes

One of the great strengths of the moving average crossover system is its versatility. It can be adapted to a wide variety of markets, including stocks, futures, and forex. It can also be used on different timeframes, from intraday charts to weekly charts. The key to adapting the system is to find the EMA combination that works best for the specific market and timeframe that you are trading. This can be done through a process of backtesting and optimization. It is important to note that there is no single "best" EMA combination. The optimal parameters will vary depending on the volatility and trendiness of the market.

Conclusion

Ed Seykota's moving average crossover system is a effective example of the elegance of simplicity. It is a system that is easy to understand, easy to implement, and, most importantly, effective. By focusing on the core principles of trend following and by using a simple yet robust trading system, Seykota has been able to achieve a level of success that most traders can only dream of. His legacy is a effective reminder that you don't need a complex system to succeed in the markets; you just need a system that you can follow with discipline and consistency.