Attempting and In-depth Understanding Stock Market Trends Using Simple Moving Average (SMA) and Exponential Moving Average (EMA) Indicators
Ilayda Tunc
EHL Hospitality Business School (Switzerland), Lausanne, CH
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http://doi.org/10.37648/ijps.v18i01.019
Abstract
Moving averages are among the most widely used tools in technical analysis because they translate noisy price series into smoother signals that are easier to interpret. This paper explains how the Simple Moving Average (SMA) and Exponential Moving Average (EMA) work, why they behave differently, and how traders and analysts commonly use them to study stock market trends. We review key academic evidence on moving-average-based trading rules, including classic results on the Dow Jones Industrial Average and later research that highlights pitfalls such as data snooping, sensitivity to transaction costs, and changing market regimes. Building on this literature, we outline a practical, research-friendly workflow for designing and evaluating SMA/EMA trend systems: selecting horizons, defining entry and exit rules, avoiding look-ahead bias, incorporating realistic costs, and reporting performance using risk-adjusted and drawdown-aware metrics. While moving averages can be valuable for organizing market information and creating disciplined decision rules, they are lagging indicators and can perform poorly in sideways or rapidly reversing conditions. The paper closes with guidance on responsible use: treating SMA/EMA signals as hypotheses to test, not truths to trust, and emphasizing robust validation over parameter “tweaks” that only fit the past.
Keywords:
technical analysis; trend following; moving average crossover; stock returns; backtesting; transaction costs; data snooping
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