Using a set of mathematically based objective rules for buying and selling is a common method for swing traders to eliminate the subjectivity, emotional aspects, and labor-intensive analysis of swing trading. The trading rules can be used to create a trading algorithm or "trading system" using technical analysis and fundamental analysis to give buy and sell signals.
Simpler rule-based trading approaches include Alexander Elder's strategy, which measures the behavior of an instrument's price trend using three different moving average of closing prices. The instrument is only traded Long when the three averages are aligned in an upward direction, and only traded Short when the three averages are moving downward. Trading algorithms/systems may lose their profit potential when they obtain enough of a mass following to curtail their effectiveness: "Now it's an arms race. Everyone is building more sophisticated algorithms, and the more competition exists, the smaller the profits," observes Andrew Lo, the Director of the Laboratory For Financial Engineering, for the Massachusetts Institute of Technology.
Identifying when to enter and when to exit a trade is the primary challenge for all swing trading strategies. However, swing traders do not need perfect timing—to buy at the very bottom and sell at the very top of price oscillations—to make a profit. Small consistent earnings that involve strict money management rules can compound returns over time. It is generally understood that mathematical models and algorithms do not work for every instrument or market situation.
Risks in swing trading are commensurate with market speculation in general. Risk of loss in swing trading typically increases in a trading range, or sideways price movement, as compared to a bull market or bear market that is clearly moving in a specific direction.
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