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# How Hull Moving Average (HMA) Are Calculated?

The Hull Moving Average (HMA) is a technical indicator that aims to reduce lag and produce more accurate signals than traditional moving averages. It incorporates weighted moving averages and the square root of the period to deliver smoother and more responsive results.

The calculation of the HMA involves several steps. Firstly, a weighted moving average (WMA) is calculated using the half-length of the period. The half-length is derived from the square root of the period being considered.

Next, a second WMA is calculated using the original data and the full period. This step smooths out the values further.

Finally, the difference between the two WMAs is calculated to generate the Hull Moving Average line. The result is a moving average that attempts to filter out noise while still being responsive to price movements.

By combining the weighted moving averages with the square root of the period, the HMA aims to create a moving average that is more accurate and timely in identifying trends and potential reversals in the price data.

Traders and analysts often use the Hull Moving Average in conjunction with other technical indicators to make informed trading decisions. It can help identify the overall direction of the market and provide signals for entering or exiting positions.

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## What data points are required to calculate the HMA?

To calculate the Hull Moving Average (HMA), the following data points are required:

1. Price data: The historical or real-time price data of the asset you want to calculate the HMA for. This could be the closing price, high price, low price, or any other price data point.
2. Period: The period or lookback window length that you want to consider for calculating the HMA. For example, if you want to calculate the HMA for the last 10 periods, you need the price data of those 10 periods.

The formula for calculating the Hull Moving Average (HMA) involves three steps:

Step 1: Calculate the Weighted Moving Average (WMA) of the price data using the period/2. Step 2: Calculate the WMA of the price data using the period. Step 3: Take the difference between the WMA from Step 1 and the WMA from Step 2, and calculate the WMA of this difference using the square root of the period.

Hence, with the price data and the period, you can calculate the HMA using the above formula.

## How is the HMA indicator derived from the weighted moving average (WMA)?

The Hull Moving Average (HMA) is derived from the weighted moving average (WMA) by incorporating additional calculations to improve its responsiveness and reduce lag.

The process of deriving the HMA from the WMA involves the following steps:

1. Calculate the Weighted Moving Average (WMA) of the price data over a specified period.
2. Divide the specified period by 2 to determine the HMA's period (e.g., a 20-period WMA will result in a 10-period HMA).
3. Calculate the WMA for the first half of the HMA period.
4. Calculate the WMA for the second half of the HMA period.
5. Calculate the square root of the period and round it to the nearest integer.
6. Multiply the WMA of the first half by 2.
7. Subtract the WMA of the second half from the WMA of the first half, resulting in the "difference."
8. Apply the square root calculation obtained in step 5 to the "difference."
9. Calculate the WMA of the "difference" from step 8 using the rounded square root as the period.
10. Multiply the WMA of the "difference" by 2.
11. Subtract the multiplied WMA of the "difference" from the sum of the two WMAs obtained in step 6.

The final result is the Hull Moving Average (HMA), which is a weighted moving average that attempts to reduce lag while providing a smoother and more responsive trend line.

## What are the common criticisms of using the HMA in technical analysis?

There are several common criticisms of using the Hull Moving Average (HMA) in technical analysis:

1. Lagging indicator: Like other moving averages, the HMA is a lagging indicator. It is based on past price data and may not provide timely signals, especially in volatile or rapidly changing market conditions.
2. Complex calculation: The calculation of the HMA involves multiple steps, including the use of weighted moving averages. This complexity can make it difficult for some traders to understand and apply effectively.
3. Whipsaw signals: The HMA can generate false signals or whipsaws during periods of consolidation or sideways markets. This can lead to erroneous buy or sell signals, resulting in losses for traders.
4. Over-optimization: Some traders may tend to optimize the parameters of the HMA to fit historical data, which can result in overfitting. Over-optimization can lead to poor performance in real-time trading as the optimized parameters may not work as well on new data.
5. Limited use in trending markets: The HMA is primarily designed to identify trend reversals. However, in strongly trending markets, it may not perform well as it may produce late signals or fail to capture the full extent of the trend.
6. No consideration of fundamental factors: The HMA, like other technical indicators, solely focuses on price and ignores fundamental factors such as news events, economic data, or company fundamentals. This can limit its effectiveness in certain situations where these factors may have a significant impact on price movements.

It is important to note that while the criticisms mentioned above are common, they do not render the HMA or technical analysis useless. Traders and analysts often use a combination of indicators, tools, and techniques to make informed decisions, taking into account both technical and fundamental factors.

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