A trading strategy is a systematic methodology used for buying and selling in the securities markets. A trading strategy is based on predefined rules and criteria used when making trading decisions. A trading strategy may be simple or complex, and involve considerations such as investment style (e.g., value vs. growth), market cap, technical indicators, fundamental analysis, industry sector, level of portfolio diversification, time horizon or holding period, risk tolerance, leverage, tax considerations, and so on. The key is that a trading strategy be set using objective data and analysis and is adhered to diligently. At the same time, a trading strategy should be periodically re-evaluated and tweaked as market conditions or individual goals change.

Understanding Trading Strategies

A trading strategy includes a well-considered investing and trading plan that specifies investing objectives, risk tolerance, time horizon, and tax implications. Ideas and best practices need to be researched and adopted then adhered to. Planning for trading includes developing methods that include buying or selling stocks, bonds, ETFs, or other investments and may extend to more complex trades such as options or futures. Placing trades means working with a broker or broker-dealer and identifying and managing trading costs including spreads, commissions, and fees. Once executed, trading positions are monitored and managed, including adjusting or closing them as needed. Risk and return are measured as well as portfolio impacts of trades and tax implications.

Why Is Trading Strategies Important?

Trading strategies are employed to avoid behavioral finance biases and ensure consistent results. For example, traders following rules governing when to exit a trade would be less likely to succumb to the disposition effect, which causes investors to hold on to stocks that have lost value and sell those that rise in value. Trading strategies can be stress-tested under varying market conditions to measure consistency.

The Bottom Line

Profitable trading strategies are difficult to develop, however, and there is a risk of becoming over-reliant on a strategy. For instance, a trader may curve fit a trading strategy to specific backtesting data, which may engender false confidence. The strategy may have worked well in theory based on past market data, but past performance does not guarantee future success in real-time market conditions, which may vary significantly from the test period.