From K-line to quarterly line: Mastering the practical interpretation of multiple moving averages

Why Should You Look at Monthly and Quarterly Lines? Basic Knowledge Is Key

Technical analysis of stocks shouldn’t focus solely on daily K-line charts. Many investors consider multiple timeframes such as weekly, monthly, and even quarterly data. The key reason behind this is that how you interpret quarterly lines directly impacts your ability to accurately judge the strength and weakness cycles of the stock.

Moving averages across different timeframes reflect the purchase costs of different investor groups. For example, the 20-day moving average represents the average cost over the past month, while the 60-day moving average covers the entire quarter. When the stock price is above these moving averages, it indicates that participants who bought during that period are in profit; conversely, if below, they are all at a loss.

How Are Moving Averages Calculated? A Table to Help You Understand Instantly

Simply put, a moving average is the arithmetic mean of the closing prices over the past N trading days. Taking NVIDIA (NVDA) as an example:

Date Closing Price Last 5 Trading Days Average
2024/3/26 925.61 927.318
2024/3/25 950.02 920.992
2024/3/22 942.89 907.898
2024/3/21 914.35 894.994
2024/3/20 903.72 888.012

The calculation formula is straightforward: (Close1 + Close2 + Close3 + Close4 + Close5) ÷ 5

Depending on the number of trading days, the trading community typically focuses on these lines:

Cycle Type Corresponding Days Actual Meaning
Short-term 5-day, 10-day One week, two weeks
Mid-term 20-day, 60-day One month, one quarter
Long-term 120-day, 240-day Half a year, one year

Short-term traders mainly watch the 5-day and 10-day lines; mid- and long-term investors pay more attention to cycles longer than 20 days.

How to Use Multiple Cycle Moving Averages? Start with Simple Signals

Basic interpretation: the relationship between the stock price and the moving averages

When the candlesticks are all above the 5-day, 10-day, 20-day, and 60-day moving averages, it indicates that buyers in the short, medium, and quarterly periods are all in profit. For example, on March 4, 2024, NVIDIA’s stock price traded above these moving averages throughout the day, forming a relatively safe buy zone.

Conversely, if the stock price remains below these moving averages, holders within these cycles are facing losses. The larger the loss, the greater the pressure to close positions later, which can trigger a stampede.

Advanced application: Golden Cross and Death Cross

Golden Cross occurs when a short-term moving average crosses above a long-term moving average. For example, the 5-day moving average crossing above the 20-day indicates strong short-term buying power, with most market participants in profit, signaling an upward trend.

Death Cross is the opposite, occurring when a short-term moving average crosses below a long-term one. When the 5-day drops below the 20-day, it indicates increasing selling pressure, with most participants at a loss, suggesting a downward trend.

How to Read the Quarterly Line to Truly Optimize Your Decisions? Look at the Arrangement Pattern

Beyond simple crossovers, the arrangement of multiple moving averages itself is a strong signal.

Bullish Arrangement: Moving averages are ordered from top to bottom from short to long cycles (e.g., 5-day above, 60-day below), and all are trending upward. This indicates the stock has completed consolidation and is about to rise, a positive buy signal.

Bearish Arrangement: The order is reversed, with long-term averages above short-term ones, all trending downward. The stock is in a sustained downtrend, likely to continue falling, and it’s advisable to exit.

Sideways Consolidation: All moving averages are parallel, indicating a temporary equilibrium between bulls and bears. Patience is needed until new signals emerge.

Tight Consolidation: Multiple moving averages intertwine, with fierce battle between buyers and sellers. The market awaits clear positive or negative news to break the deadlock.

The Limitations of These Tools You Must Know

Technical indicators are not perfect tools; moving averages like the monthly and quarterly lines also have obvious flaws:

1. Lagging Issue
Moving averages are based on historical prices, so they tend to react slowly when trends change. You might want to buy after a golden cross appears, but the stock may have already risen significantly. This often causes traders to miss the optimal entry point.

2. Interference from Unexpected Events
Major positive or negative news in the short term can cause sharp stock price fluctuations, producing false crossover signals. Key events like earnings reports or macroeconomic data releases can significantly reduce the reliability of moving average signals, requiring extra caution.

3. Need for Multiple Indicators for Confirmation
Relying solely on moving averages for decision-making is risky. Smart traders combine volume, Relative Strength Index (RSI), MACD, and other tools for cross-verification to ensure signals are valid.

Practical Tips: How to Apply These in Actual Trading

  • Establish Your Trading Cycle: Short-term traders focus on 5-day and 10-day crossovers; mid-term investors watch 20-day and 60-day relationships. Avoid mixing timeframes haphazardly.

  • The Importance of the Quarterly Line Is Often Underestimated: The 60-day line represents the average cost over a quarter. When the stock price breaks through the quarterly line, it often signals a significant trend change and warrants close attention.

  • Combine with Fundamental Analysis: Technical indicators are only auxiliary tools. The actual operational status and profit prospects of a company are fundamental factors that determine the long-term direction of the stock.

  • Set Stop-Loss Points: When the stock price falls below important moving averages (especially the quarterly line), consider setting a stop-loss. This helps you cut losses timely and prevent further damage.

Mastering how to read the monthly and quarterly moving averages hinges on understanding their underlying logic: they reflect the average costs of different participant groups over various timeframes. By combining arrangement patterns, crossover signals, and fundamental factors, you can build a relatively complete trading decision framework.

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