Simple Moving Average
A simple moving average (SMA) is the unweighted arithmetic mean of a security's closing prices over a specified number of periods, updated each period by adding the most recent closing price and dropping the oldest, creating a smoothed trend-following indicator that filters out short-term price noise. SMAs are among the most widely used technical analysis tools and form the basis of numerous trading signals and crossover strategies.
Key takeaways
- The SMA is calculated as the sum of closing prices over N periods divided by N; common lookback periods include 20-day (short-term), 50-day (medium-term), and 200-day (long-term).
- When price is above its SMA, the trend is considered bullish; when below, bearish. The 200-day SMA is widely watched by institutional and retail traders as a key long-term trend indicator.
- The 'golden cross' (50-day SMA crossing above the 200-day SMA) and 'death cross' (50-day crossing below 200-day) are widely cited, if not universally reliable, long-term trend signals.
- SMAs lag current price by construction — longer lookback periods produce smoother but more lagged signals, while shorter periods respond more quickly but generate more false signals.
- Exponential moving averages (EMAs) address the lag problem by assigning exponentially decreasing weights to older observations, making them more responsive to recent price changes.
Explanation
The simple moving average is the foundational indicator of trend-following technical analysis. Its construction is straightforward: at each point in time, the analyst sums the closing prices for the previous N trading days and divides by N. As each new day passes, the newest closing price enters the calculation while the oldest drops off — hence 'moving average.' The result is a line that tracks the average price over the specified lookback window, smoothing out day-to-day volatility and providing a cleaner visual representation of the prevailing trend.
The selection of lookback period fundamentally shapes an SMA's behavior. A 10-day SMA closely follows the current price and signals trend changes quickly but is susceptible to false signals from short-term noise. A 200-day SMA is far smoother and more stable, identifying major multi-month trends but reacting slowly to genuine trend reversals. The 50-day and 200-day SMAs have become particularly institutionalized as reference points: brokerage reports, financial media, and institutional research routinely cite these levels as key support and resistance thresholds.
Trading signals derived from SMAs typically involve crossovers. Price-over-SMA crossovers signal trend changes: a close above the 50-day SMA following a period below it is interpreted as a bullish regime change, while a close below suggests bearish momentum. Dual SMA crossovers compare a shorter and longer SMA: the golden cross (short-term SMA crossing above long-term) is a classic long signal, while the death cross is a sell signal. Empirical research finds these signals have modest predictive power in certain equity and futures markets, particularly when implemented as part of a systematic trend-following strategy.
In the context of hedge fund and systematic trading, SMAs play a role in time-series momentum strategies. Trend-following CTAs (Commodity Trading Advisors) frequently use moving average crossover rules across hundreds of futures markets to generate long and short positions based on the direction of the prevailing trend. Research by Moskowitz, Ooi, and Pedersen (2012) documented robust time-series momentum across equity indices, commodities, currencies, and fixed income — and simple moving average rules capture much of this effect. However, SMA-based systems suffer during range-bound, mean-reverting markets ('chop'), generating false signals and transaction costs.
It is important to recognize that the SMA assigns equal weight to all observations in its window, which means a single extreme data point (a large daily move) affects the average equally whether it occurred last week or a month ago. Exponential moving averages (EMAs) and other weighted variants address this by placing greater weight on recent observations, making them faster to respond to genuine trend changes. Modern quantitative trend-following systems often use risk-adjusted or volatility-scaled signals rather than raw price SMAs, normalizing signal strength by the realized volatility of each market to produce comparable position sizes across diverse instruments.
Formula
SMA_N = (P_1 + P_2 + ... + P_N) / N, where P_i is the closing price N-i+1 periods ago
Example
Consider Microsoft (MSFT) trading at $380 per share. Its 50-day SMA is $365 and its 200-day SMA is $340, meaning the stock is in a confirmed uptrend above both key moving averages. A technical trader using a simple crossover rule is long the stock. Over the following two months, a broad market selloff pushes MSFT to $330. The 50-day SMA falls to $355, and the stock is now below both the 50-day and 200-day SMAs. When the 50-day crosses below the 200-day at $342, a death cross is signaled. A systematic SMA crossover model would exit the long position (or initiate a short in a two-sided system) at this point, locking in the gains accumulated since the prior golden cross at $280.
Related terms
Basis Charting Cup And Handle Pattern Equity Head And Shoulders Pattern Hedge Fund Momentum Indicator Moving Average Stock Time Series Momentum Triangle Pattern Volatility