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Swing trading is commonly defined as a stock, index, or commodities trading practice whereby a traded instrument is bought at or near opposite cycle swings caused by daily or weekly price volatility. A swing trade is open longer than a day, but shorter than trend following trades or buy and hold investment strategies. Swing traders prospect changes in stock price caused by, or occurring with oscillations between its price bid up by optimism and alternatively down by pessimism over a period of a few days, weeks, or months.

Swing Trade Strategies

A Predictive market trading algorithm is defined as a calculable set of trade rules which results in entry, exit and stop loss trade points. Investment in researching trading algorithms has skyrocketed, particularly by investment banking firms like Goldman Sachs which spends tens of millions on trading algorithm research, and which staffs its trading algorithm team more heavily than even its trading desk.

Trading algorithms can be as esoteric as extrapolated biology theories like neural networks applied to derivatives trading by Rutgers University's Gang Nathan Dong. Even more simple is Alexander Elder's strategy measuring the behavior of a stock above and below a baseline where a moving average identifies the typical baseline on a stock chart. The stock is to be invested long at the baseline when the stock is heading up, and short at the baseline when the stock is headed down.

Trading algorithms may lose their profit potential when their trading strategies 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. Swing traders do not need perfect timing - to buy at the bottom, and sell at the top. Small consistent earnings will compound returns significantly. Most important is to have or develop a trading algorithm that is mathematically certain and successfully tested on historical prices of the time dimension a swing trader is trading, be it by the minute, hour, day, week, or month.

The Risks Involved

Swing trading may have unique challenges in a market trading flat or sideways, than in a bull market or bear market. In a market trending in a definite direction the most active stocks tend not to exhibit the up-and-down oscillation amplitude that they would when the markets are relatively stable for a few weeks or months. In trending markets (either a bear market or a bull market), momentum may carry stocks for a much longer than usual time in one direction only, making swing trading strategies that do not incorporate this trending, less profitable than trend following strategies. Identifying whether a market is currently trending higher or lower, or trading sideways is a challenge for many swing trading and long-term trend following trading strategies. As with all financial instruments risk of loss in trading is considerable, and only mitigated by the trading strategy that is back tested on any particular equity, index, or commodity, and continues to prove its worth with successful trades.

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