Long term moving average

What Is Long Term Moving Average?

A long term moving average is a widely used indicator in technical analysis that smooths out price data over an extended period, typically 50, 100, or 200 days. It falls under the broader category of market trends indicators within financial analysis, helping investors identify the prevailing direction of a security's price movement over a significant timeframe. By averaging past prices, the long term moving average filters out short-term fluctuations and "noise," providing a clearer picture of underlying momentum. This indicator helps traders and investors make more informed investment decisions by highlighting persistent trends rather than temporary shifts.

History and Origin

The concept of using averages to smooth out time series data has roots in various fields, but its application to financial markets gained prominence with the rise of modern technical analysis. Early proponents of technical analysis, such as Charles Dow, one of the founders of Dow Jones & Company and The Wall Street Journal, laid foundational principles that observed patterns in market behavior and price movements. While Dow did not explicitly use modern moving averages, his work in the late 19th and early 20th centuries focused on identifying underlying market direction through various observations, which implicitly set the stage for later quantitative methods. The formalization and widespread adoption of the moving average as a technical indicator evolved over time, becoming a staple tool as financial data became more accessible and computational methods advanced. The work of Charles Dow in analyzing market behavior provided key insights into what would become foundational Dow Jones principles.

Key Takeaways

A long term moving average smooths price data over an extended period (e.g., 50, 100, or 200 days) to identify dominant market trends.
It helps filter out short-term volatility, making the underlying trend clearer.
The long term moving average is commonly used to confirm the direction of a trend, identify potential support level and resistance level areas, and generate trading signals.
Crossovers between different moving averages (e.g., a short-term crossing a long-term) are often interpreted as significant buy or sell signals.
While useful, the long term moving average is a lagging indicator and does not predict future prices, but rather confirms existing trends.

Formula and Calculation

The most common type of moving average, and the basis for a long term moving average, is the Simple Moving Average (SMA). The formula for a Simple Moving Average is:

$SMA = \frac{A_1 + A_2 + ... + A_n}{n}$

Where:

( A_n ) = The price of an asset at period ( n ) (e.g., closing price for a given day).
( n ) = The total number of data points in the period (e.g., 50 for a 50-day SMA).

To calculate a long term moving average, one would sum the closing prices of a security over the specified long period (e.g., 200 days) and then divide by the number of periods. For example, a 200-day moving average would sum the closing prices for the past 200 days and divide by 200. This calculation is updated daily as new price data becomes available, creating a continuous line on a price chart.

Interpreting the Long Term Moving Average

Interpreting a long term moving average involves observing its direction and its relationship with the current price and other momentum indicators. When the price of an asset is consistently above its long term moving average, it generally suggests an uptrend. Conversely, if the price remains below the long term moving average, it typically indicates a downtrend.

The slope of the long term moving average itself provides insight into the strength and direction of the trend. A sharply rising moving average signals a strong uptrend, while a steep decline suggests a powerful downtrend. When the moving average flattens, it can indicate a consolidating or ranging market, where the trend is losing momentum or reversing. Investors also look for crossovers; for instance, if a shorter-term moving average crosses above a long term moving average, it can be seen as a bullish signal, while a cross below can be bearish.

Hypothetical Example

Consider an investor analyzing the stock of fictional "TechGrowth Inc." The investor wants to identify its long-term trend using a 200-day long term moving average.

Collect Data: The investor gathers the closing prices for TechGrowth Inc. for the past 200 trading days.
Calculate Initial Average: The closing prices for the first 200 days are summed, and the total is divided by 200 to get the initial 200-day long term moving average value.
- Example: If the sum of the first 200 days' closing prices is $20,000, the 200-day moving average is $20,000 / 200 = $100.
Update Daily: On the 201st day, the oldest day's price (day 1) is dropped, and the newest day's price (day 201) is added to the calculation. This process is repeated daily.
Observe Trend: Suppose for several months, TechGrowth Inc.'s stock price consistently trades above its 200-day moving average, and the average itself is steadily rising. This suggests a strong long-term uptrend for TechGrowth Inc. However, if the price then falls below the 200-day moving average and the average begins to flatten or decline, it could signal a shift to a bearish long-term outlook, prompting the investor to reassess their trading strategy.

Practical Applications

Long term moving averages are foundational tools in financial markets and find numerous practical applications across investing and analysis:

Trend Identification: They are primarily used to identify and confirm the direction of major trends in stocks, commodities, currencies, and market indices. A steadily rising long term moving average, such as a 200-day moving average, often indicates a bullish trend, while a declining one points to a bearish trend.
Support and Resistance: Long term moving averages often act as dynamic support level or resistance level lines. During an uptrend, prices may pull back to the moving average and then rebound, using it as support. In a downtrend, the moving average can act as resistance, with prices bouncing off it before continuing lower.
Trading Signals: While typically lagging indicators, crossovers between different moving averages (e.g., a 50-day moving average crossing a 200-day moving average) are common trading signals. These "golden cross" (bullish) and "death cross" (bearish) signals are widely followed.
Portfolio Management: Fund managers and institutional investors may use long term moving averages as part of their portfolio management strategies, adjusting allocations based on confirmed long-term trends to manage risk or capture broad market movements.
Market Analysis: Economists and analysts frequently incorporate long term moving averages of broad market indices, such as the S&P 500, to gauge the overall health and direction of the economy. Publicly available economic data from sources like the Federal Reserve Bank of St. Louis often features these indicators.
Risk Management: Using a long term moving average as a stop-loss level or a trailing stop can help manage risk by automatically exiting positions if a long-term trend reverses.

These applications underscore the long term moving average's role in providing a smoothed, trend-focused perspective on market behavior, enabling a more strategic approach to trading and investing.

Limitations and Criticisms

While a widely used tool, the long term moving average has notable limitations and faces criticism, particularly in the context of modern financial theory and rapidly changing markets.

Lagging Indicator: The most significant criticism is that the long term moving average is a lagging indicator. It is based entirely on past price data and thus reflects what has already happened, not what will happen. In fast-moving markets or during sudden reversals, a long term moving average will signal a trend change only after a significant price move has already occurred, potentially leading to delayed entry or exit points for traders.
Whipsaws in Sideways Markets: In sideways or choppy markets, a long term moving average can generate frequent false signals, known as "whipsaws." When prices oscillate around the moving average without a clear trend, it can lead to repeated buy and sell signals that result in losses from transaction costs and incorrect trades.
Arbitrary Period Selection: The choice of the period (e.g., 50, 100, 200 days) for a long term moving average is often arbitrary. Different periods can produce different signals, and there is no universally "best" period that works for all assets or market conditions. This subjectivity can lead to data mining, where an analyst selects a period that historically worked well, but may not be predictive of future performance.
No Predictive Power: Critics argue that technical indicators, including moving averages, do not possess inherent predictive power over future price movements. This perspective aligns with the Efficient Market Hypothesis, which suggests that asset prices already reflect all available information, making it impossible to consistently profit from past price patterns¹, ², ³, ⁴, ⁵. Eugene Fama, a Nobel laureate from the University of Chicago Booth School of Business, extensively developed this hypothesis.
Ignores Fundamental Data: The long term moving average, as a tool of technical analysis, solely focuses on price and volume data, disregarding underlying fundamental factors such as company earnings, economic reports, or industry-specific news. A purely technical approach may miss crucial information that drives long-term asset value.

These limitations underscore the importance of using long term moving averages as one tool within a broader analytical framework, combining them with fundamental analysis and other indicators to form a comprehensive view.

Long Term Moving Average vs. Simple Moving Average

While a long term moving average is a type of Moving average, the distinction often lies in the timeframe and the purpose of their application. A Simple Moving Average (SMA) can refer to any moving average calculated over a specific number of periods, whether short, medium, or long. The "long term" designation specifically refers to SMAs calculated over extended periods, typically 50, 100, or 200 days or more, designed to smooth out substantial price data noise and reveal broad, enduring market trends. In contrast, short-term SMAs (e.g., 10 or 20 days) are used to identify immediate price movements and capture short-term fluctuations, offering quicker signals but also more "noise." The confusion often arises because the calculation method is the same, but the duration of the calculation period fundamentally changes the indicator's sensitivity and the type of trend it reveals.

FAQs

What is a long term moving average used for?

A long term moving average is primarily used to identify the underlying direction of a security's price trend over an extended period, filter out short-term market noise, and act as dynamic support level or resistance level.

What are common periods for a long term moving average?

Common periods for a long term moving average include 50 days, 100 days, and 200 days. The 200-day moving average is particularly popular for gauging the overarching health of an asset or market.

Is a long term moving average a leading or lagging indicator?

A long term moving average is considered a lagging indicator because it is calculated using historical price data and therefore only reflects past price movements, confirming trends after they have already begun.

Can a long term moving average predict market crashes?

No, a long term moving average cannot predict market crashes. As a lagging indicator, it will only reflect a significant downturn after it has already occurred. Its primary use is to confirm existing market trends, not to forecast future events. Understanding market data disclosure from regulatory bodies like the SEC helps clarify what information is available and what can be reliably inferred.

How does a long term moving average differ from a short term moving average?

The main difference between a long term moving average and a short term moving average lies in the number of data points used in the calculation. Long-term averages use more data points (e.g., 200 days), making them smoother and less reactive to daily price changes, thus highlighting sustained trends. Short-term averages (e.g., 10 or 20 days) use fewer data points, making them more volatile and responsive to immediate price shifts.