Short term moving average

What Is Short Term Moving Average?

A short term moving average is a widely used tool in technical analysis that calculates the average price of an asset over a relatively brief period, typically ranging from a few days to a few weeks. Its primary purpose is to smooth out short-term price fluctuations, or "noise," to help identify the prevailing market trends more clearly. This indicator belongs to the broader category of technical analysis and is particularly valuable for traders focused on capturing immediate price movements. By constantly updating with the latest data, a short term moving average provides a dynamic line that reflects recent price action.

History and Origin

The concept of moving averages, as a method for smoothing data and identifying trends, has roots in statistical analysis dating back centuries. Its application to financial markets gained prominence in the early 20th century. Pioneers of technical analysis, such as Charles Dow and later figures like Richard Schabacker, laid the groundwork for using these averages to understand price action and predict future market direction⁹, ¹⁰. The widespread adoption of computers in the latter half of the 20th century significantly enhanced the accessibility and calculation of moving averages, making them a staple for market participants. The debate between using technical analysis and fundamental analysis in predicting market behavior has been ongoing for decades, with early discussions from institutions like the Federal Reserve Bank of St. Louis exploring their respective merits⁸.

Key Takeaways

A short term moving average smooths price data over a brief period to highlight immediate trends.
Common periods for short term moving averages include 5, 10, 20, or 50 days.
It is a lagging indicator, meaning it is based on past price data.
Traders use short term moving averages to generate trading signals and identify dynamic support and resistance levels.
The responsiveness of a short term moving average makes it particularly useful in fast-moving markets or for short-term trading strategies.

Formula and Calculation

The most common type of short term moving average is the Simple Moving Average (SMA). It is calculated by summing the closing prices of an asset over a specified number of periods and then dividing the sum by the number of periods.

For a Simple Moving Average (SMA), the formula is:

\text{SMA} = \frac{\sum_{i=1}^{n} P_i}{n}

Where:

(P_i) = The closing price of the asset at period (i)
(n) = The number of periods (e.g., days, hours) in the calculation for the short term moving average. This (n) represents the look-back period for the average.
(\sum_{i=1}^{n} P_i) = The sum of the closing prices over the (n) periods.

For example, a 10-day short term moving average would sum the closing prices of the last 10 trading days and divide by 10. While the Simple Moving Average treats all data points equally, other types like the exponential moving average (EMA) assign more weight to recent prices, making them more responsive to new information⁷.

Interpreting the Short Term Moving Average

A short term moving average provides a visual representation of recent price action. When the current price of an asset is above its short term moving average, it generally suggests an upward trend or positive momentum in the short run. Conversely, if the price is below the short term moving average, it may indicate a downward trend or negative momentum.

Traders often look for specific patterns:

Slope: A rising short term moving average indicates an uptrend, while a falling one indicates a downtrend.
Crossovers: When the price crosses above the short term moving average, it can be interpreted as a bullish signal. A cross below signals a bearish outlook.
Support/Resistance: In trending markets, the short term moving average can act as dynamic support and resistance levels, where prices tend to bounce off or break through. Understanding these dynamics requires an awareness of market volatility.

Hypothetical Example

Consider a hypothetical stock, "DiversiCo Inc." (DCO), with the following closing prices over 5 consecutive trading days:

Day 1: $100
Day 2: $102
Day 3: $101
Day 4: $104
Day 5: $106

To calculate the 5-day short term moving average for Day 5, we sum the closing prices for the last 5 days and divide by 5:

\text{SMA}_{\text{Day 5}} = \frac{(100 + 102 + 101 + 104 + 106)}{5} = \frac{513}{5} = 102.60

Now, for Day 6, assume the closing price is $108. The calculation would shift, dropping Day 1's price and including Day 6's price:

\text{SMA}_{\text{Day 6}} = \frac{(102 + 101 + 104 + 106 + 108)}{5} = \frac{521}{5} = 104.20

As new data becomes available, the oldest data point is dropped, and the newest is added, causing the average to "move" over time. This continuous adjustment helps analysts track the evolving market cycles and underlying historical data.

Practical Applications

Short term moving averages are integral to various trading and analytical strategies across financial markets, including equities, commodities, and foreign exchange. They are commonly employed by:

Day Traders and Scalpers: These traders rely on rapid price movements and use very short periods (e.g., 5-period, 10-period) to identify quick entry and exit points.
Swing Traders: For those holding positions for a few days to weeks, a 20-period or 50-period short term moving average can help identify the direction of medium-term swings within a larger market trend.
Algorithmic Trading: Automated trading systems frequently incorporate short term moving average crossovers as triggers for executing trades, leveraging their responsiveness to market changes. The speed required for such strategies is often discussed in the context of high-frequency trading⁵, ⁶.
Trend Following: Traders use the short term moving average to confirm the direction of a nascent trend or to signal potential reversals when the average flattens or changes direction. For example, analysts might use these averages to interpret shifts in currency markets, as seen in analyses of the Chinese yuan⁴.

Limitations and Criticisms

Despite their widespread use, short term moving averages have limitations and are subject to criticism.

Lagging Indicator: By their very nature, moving averages are derived from past prices, meaning they always lagging indicator behind current price action. This lag can lead to delayed signals, potentially causing traders to enter or exit trades after a significant portion of the move has already occurred.
Whipsaws: In choppy or sideways markets, a short term moving average can generate numerous false signals, known as "whipsaws." This occurs when the price repeatedly crosses above and below the average without establishing a clear trend, leading to potential losses if each signal is acted upon. This highlights the importance of incorporating risk management principles.
Efficient Market Hypothesis (EMH): Critics, particularly proponents of the Efficient Market Hypothesis, argue that technical analysis, including the use of moving averages, cannot consistently generate abnormal returns because all available information is already reflected in asset prices³. The Bogleheads investment philosophy, for instance, emphasizes passive investing and often expresses skepticism about the efficacy of actively timing markets using technical indicators¹, ².
Over-reliance: Over-reliance on any single indicator, including a short term moving average, can be risky. Market conditions change, and an indicator that works well in one environment may perform poorly in another. Combining the short term moving average with other forms of analysis, such as chart patterns or oscillators, is generally recommended.

Short Term Moving Average vs. Long Term Moving Average

The primary distinction between a short term moving average and a long term moving average lies in the number of periods used for their calculation and their respective applications in market analysis.

Feature	Short Term Moving Average	Long Term Moving Average
Periods	Typically 5 to 50 periods (e.g., days)	Typically 100 to 200 periods (e.g., days)
Sensitivity	More sensitive to recent price changes	Less sensitive to recent price changes
Lag	Shorter lag behind price action	Longer lag behind price action
Purpose	Identifies immediate trends, entry/exit points	Identifies major trends, overall market direction
Users	Day traders, swing traders	Long-term investors, trend followers
Signals	More frequent signals, higher chance of whipsaws	Fewer signals, often more reliable for broad trends

While a short term moving average quickly reflects changes in market sentiment, a long term moving average provides a broader perspective on the underlying trend following. Traders often use combinations of both, such as a short term moving average crossing above a long term moving average, as a bullish signal (a "golden cross"), or below it as a bearish signal (a "death cross").

FAQs

What are common periods for a short term moving average?

Common periods for a short term moving average typically include 5, 10, 20, or 50 periods (e.g., days, hours, or minutes), depending on the timeframe of the analysis. A 50-period short term moving average is generally considered a popular benchmark for assessing near-term trends.

Can a short term moving average predict future prices?

No, a short term moving average is a lagging indicator based on past prices and does not predict future price movements with certainty. Instead, it helps to identify the current direction and strength of the trend based on historical data, assisting traders in making informed decisions.

How does a short term moving average differ from an exponential moving average (EMA)?

A simple short term moving average (SMA) gives equal weighted average to all data points within its calculation period. In contrast, an exponential moving average (EMA) gives more weight to the most recent data, making it more responsive to new information and quicker to react to price changes.

Is a short term moving average useful in all market conditions?

A short term moving average is most effective in trending markets, where it can clearly delineate the direction of the trend. In choppy, non-trending, or sideways markets, it can generate numerous false signals or "whipsaws," making it less reliable for guiding trading decisions.