Understanding Hull Moving Average (HMA) on Google Finance

Google Finance, while offering a streamlined interface for tracking market data, doesn’t natively include the Hull Moving Average (HMA) as a built-in indicator. However, users familiar with the HMA’s advantages can still leverage it within the Google Finance ecosystem through workarounds and alternative charting platforms.

What is the Hull Moving Average?

The Hull Moving Average, developed by Alan Hull, is a type of moving average designed to address the lag associated with traditional moving averages. It achieves this by placing a greater emphasis on recent price data, resulting in a smoother and more responsive indicator. The HMA effectively reduces lag without sacrificing smoothness, making it a popular choice for traders seeking faster signals.

The HMA calculation involves weighted moving averages and square root transformations, resulting in a more sophisticated approach than simple or exponential moving averages. This complexity leads to its responsiveness and ability to identify trends more quickly and accurately.

Why Use HMA?

Traders use the HMA for several reasons:

• Reduced Lag: Offers faster signals compared to other moving averages, potentially leading to earlier entry and exit points.
• Smoother Curve: While responsive, the HMA avoids the jagged appearance often seen with extremely sensitive indicators.
• Trend Identification: Helps identify the direction and strength of trends effectively.
• Crossover Signals: Can be used in conjunction with other indicators to generate buy and sell signals based on crossovers.

Using HMA with Google Finance

Since Google Finance doesn’t directly support the HMA, traders can explore a few alternative strategies:

1. External Charting Platforms: Use charting platforms like TradingView, Thinkorswim, or MetaTrader 4/5, which offer HMA as a built-in indicator. You can track the stock on Google Finance for basic information and then analyze its price action using HMA on these external platforms.
2. Custom Indicators: Some platforms allow users to create custom indicators using their programming languages. If possible, create or import an HMA script into the chart.
3. Spreadsheet Calculation: Calculate the HMA manually using spreadsheet software like Google Sheets or Microsoft Excel. This requires retrieving historical price data from Google Finance (or another source) and implementing the HMA formula. Although time-consuming, it allows complete control over the calculation.
4. Approximate with other Indicators: Experiment with combinations of other moving averages on Google Finance to see if their interaction approximates the signals provided by HMA. This can involve using shorter period Exponential Moving Averages (EMAs) and adjusting the weighting.

While the lack of native HMA support on Google Finance presents a challenge, it doesn’t preclude traders from using the indicator. By leveraging external charting platforms or manual calculations, you can still incorporate the HMA into your trading strategy alongside the market information available on Google Finance.