Weighted Moving Average (WMA) Explained & Reliability Tested

I tested 30 Dow Jones stocks with four Weighted Moving Average (WMA) on 960 years of data to analyze their success rates and reliability.

The Weighted Moving Average (WMA) is a technical analysis trend indicator that assigns greater significance to recent data points. This weighting reduces the inherent lag in moving averages and creates more losing trades.

But does it mean the WMA is more reliable or profitable than other moving average indicators?

Our research reveals that the WMA underperforms other moving averages, with only a 7% win rate on a standard OHLC chart. However, using it on Heikin Ashi charts produces excellent results. Due to its incredibly poor performance, using WMA on candlestick charts is not advised.

What is a Weighted Moving Average?

A weighted moving average (WMA) is a technical analysis indicator that uses the same principles as other moving averages but with different calculations. In contrast to a simple moving average (SMA), where each data point has an equal weighting, in a WMA, more recent data points are given greater weight, while older data points are given less weight.

A weighted moving average (WMA) is a moving average that assigns different weights to each data point within the period. The most recent data points are given more weight than earlier ones, which reduces noise and increases the sensitivity of the average to short-term movements in price.

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How does it work?

A WMA is calculated by multiplying each data point by an exponential multiplier and then summing up the total. The exponential multiplier used in a WMA is typically based on the length of the period (the number of previous periods to consider).

It can be calculated using the formula n/(n+1)^2.

A WMA is used to identify trends and potential reversals in a stock price or other assets. It can also be used for smoothing data points, as the exponential multiplier gives more weight to recent data points and less weight to older ones. The goal of using a WMA is to reduce the noise in the data points, making them easier to compare and analyze. Ultimately, it can help traders make informed decisions about their investments.

The benefits of using a WMA over other moving averages include its ability to be responsive to short-term changes in an asset’s price. This means it can detect trends and changes faster than longer moving averages. Additionally, WMA’s are slightly less prone to whipsaw signals, meaning that the trader pays less in trading costs when using a WMA.

Although traders use the weighted moving average to identify market trends, this strategy falls short, according to our testing. It’s not recommended as a tool for determining when to buy and sell assets based on their historical performance.

Instead, it’s best used as a support or resistance indicator, offering insight into potential price movements. Remember, successful trading strategies incorporate multiple indicators for decision-making.

Example Chart: Weighted Moving Averages

This chart shows the weighted moving average traffic light system. Three moving averages are plotted on the chart: the 10-period WMA in green, the 50-period WMA in amber, and the 100-period WMA in red.

Chart Created with TradingView

Calculation

To calculate a weighted moving average, the most recent price is multiplied by the weight assigned to it. This product is then added to the next most recent price, times its weight, and so on, until all prices within the specified period have been factored in. The sum of these products is then divided by the sum of all weights, which yields the average.

The weighted moving average formula.

The formula for a simple Weighted moving average (WMA) is as follows:

WMA = (P1*W1 + P2*W2 + ….+ Pn*Wn) / (W1+ W2+ …..+ Wn) 

Where:

• P1, P2, Pn = the most recent to oldest prices
• W1, W2, Wn = the weights assigned to each price, with the most recent being the highest weight.

The weighted moving average can be smoothed out further by adding more data points and assigning different weights to them. For example, instead of a simple 3-day moving average, you could use a 9-day weighted moving average where the most recent days have higher weights and the older ones have lower weights.

How to trade WMA

Traders often use WMAs to enter and exit trades. A buy signal is generated when the price crosses above the WMA, and a sell signal is generated when the price crosses below the WMA.

Traders may choose to assign higher weights to more recent prices and lower weights to older ones to better reflect significant short-term price movements. Additionally, some traders may opt for an exponential weighting scheme, in which each successive price is assigned a higher weight than the preceding one.

This emphasizes the most recent prices and gives them more influence over the outcome. Whatever approach is used, traders should always know how their chosen weights will affect their moving average calculations. Furthermore, choosing an appropriate range for the formula is also important, as the range should match the trader’s investing time horizon.

For instance, a long-term investor might use a 200-day moving average, while a short-term scalper may only look at prices over the last five days. Finally, some traders will choose to use multiple moving averages with different ranges to identify strong trends in the market.

Pros

The advantage of using a weighted moving average is that it gives more influence on recent prices. This can be beneficial in quickly identifying short-term price shifts, which traditional averages may have overlooked. Most charting software packages already have the calculations built-in, so there’s no need for complicated formulas or manual calculations. The WMA also provides a clear visual representation of price trends, which can be easier to interpret than other types of technical analysis.

Cons

The main disadvantage of using WMA is that its performance is incredibly poor. Our research exposes the risks of using this indicator in trading strategies, especially during market consolidation.

One major drawback of using moving averages is that they tend to underperform during market or stock price consolidation periods, which can translate to negative returns.

However, one of the drawbacks of using the WMA is that it doesn’t consider short-term volatility. Prices can gyrate wildly in the short term, but a long-term average like the 200-day WMA might not capture these swings. Investors relying solely on a WMA may miss important short-term buying and selling opportunities. Additionally, the WMA is a lagging indicator, meaning it can only confirm trends after they’ve already started. This means investors must use other indicators in conjunction with a WMA if they hope to stay ahead of the markets.

Is WMA Indicator Accurate?

No, the weighted moving average indicator is inaccurate, averaging only a 7% win rate. The WMA causes many small losses when asset prices consolidate. Backtesting the WMA indicator on 30 Dow Jones Industrial Average stocks over eight years resulted in an average 7% win rate, meaning it underperformed a buy-and-hold strategy 93% of the time.

WMA Backtesting Methodology

To backtest the WMA indicator, I used TrendSpider, the leading AI stock trading software with pattern recognition and a codeless backtesting engine. Testing was configured using OHLC with an exit on the next open. The Heikin Ashi daily chart used the “next trading day HL2 ” exit criteria (Price High + Low /2).

I test all indicators, including the WMA, on their standard recommended settings, on different timeframes, and using different chart types; this provides an unbiased result. Also, the entry and exit prices use an average of the high and low prices for the day, making the testing more realistic.

How I Set Up WMA Backtesting in TrendSpider

To set up backtesting in TrendSpider, follow these steps. Register for TrendSpider, select Strategy Tester > Entry Condition > Add Script > Add Parameter > Condition > Price > Greater Than > WMA. For the Sell Criteria, select > Add Script > Add Parameter > Condition > Price > Less Than > WMA. Finally, click “RUN.”

To set up backtesting, I used TrendSpider, our recommended trading software for serious traders. The screenshot below shows the exact configuration for our WMA backtesting.

Testing WMA on OHLC Charts

This is a typical example of a 20-day WMA on an OHLC chart. Over 8 years, a trader using the 50-day weighted moving average on Apple Inc. (Ticker: AAPL) would make 300%, but a buy-and-hold investor would have made 456%. The average results for the weighted moving average on OHLC charts mean it is a poor choice for trading on candlestick charts.

Testing Performed With TrendSpider – The Best Software for Traders

Testing the standard WMA settings on a daily candlestick/OHLC chart proves this indicator is poor, with a 12% chance of outperforming a buy-and-hold strategy on all tested timeframes.

Results for Daily OHLC Charts

Testing 960 years of data shows the average win rate for weighted moving averages is 7%. The table below shows that the WMA 100 has a 10% chance of beating a buy-and-hold strategy, and the 200-day WMA only has a 7% chance of success.

I tried many backtesting solutions, but this testing was only possible using TrendSpider.

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Testing WMA on Heikin Ashi Charts

The weighted moving average performs considerably better on a Heikin Ashi chart. If a trader used the 20-day weighted moving average on Apple Inc. (Ticker. AAPL) over 8 years, they would have made an 837% profit beating a buy-and-hold strategy profit of 455%.

The table below shows that even using the advantages of Heikin Ashi charting, the weighted moving average indicator should be avoided except for the WMA 20, which has a good record of profitability.

Results for Heikin Ashi Charts

Testing 960 years of data shows the average win rate for weighted moving averages on a Heikin Ashi chart is 43%. This means 57% of stocks traded using this strategy will fail to beat a buy-and-hold strategy. The 20-period WMA performed better than all other moving averages we tested, with an 83% success rate.

Powerful Point & Click Backtesting With TrendSpider

Why are Heikin Ashi’s WMA results better?

Why do Heikin Ashi charts perform slightly better with WMA and other indicators like Keltner Channels and Price Rate of Change? I believe it is due to the price averaging, which removes the extreme price highs and lows associated with traditional OHLC bars. This means fewer trades in consolidating markets and fewer small losses.

Professional traders may assume, as I did, that the Heikin Ashi chart distorts the pricing because it averages the OHLC of the candles. But we can achieve realistic entry and exit criteria by using TrendSpider’s HL2 setting, meaning the average of the price candle high and low. I proof-checked individual trades, which were reasonable but not entirely realistic.

Combining WMA with Other Indicators

Incorporating the WMA with additional chart indicators, such as Price Rate of Change or bullish chart patterns, is optimal. The WMA excels in markets trending either up or down. However, it provides multiple false buy and sell signals during consolidation, leading to many minor trading losses. Therefore, avoid using this indicator in consolidating markets.

Should the WMA be used for buy and sell signals?

Our research backtesting shows that the 20-period WMA on a Heikin Ashi chart is a good indicator for identifying buy and sell signals. Over 960 years of data across 30 Dow Jones stocks, the 20, 50, 100, and 200-period WMA on candlestick charts lost to a buy-and-hold strategy 93% of the time. This is a very poor indicator by a significant margin.

The Best WMA Settings

Our research shows the best setting for the WMA indicator is 20 days on a Heikin Ashi chart. This is the only setting outperforming a buy-and-hold strategy with an 83% win rate. All other settings on OHLC charts and timeframe produce losses and a failure rate of 93%.

Although WMA isn’t the most reliable indicator, the optimal solution is to choose the least bad option. If it is necessary to use this indicator, it is recommended to set it according to period 20 and utilize a daily Heikin Ashi chart.

For this indicator to be most effective, it’s best to use it when the asset moves in strong trends. Many small losses will likely be incurred whenever the asset goes through a period of price consolidation.

Limitations of Using Weighted Moving Averages

The biggest limitation of weighted moving averages is they produce 77% of their losses in consolidating markets. Markets only have two phases: trending and consolidation. Moving averages should not be used when an asset’s price is consolidating.

Summary

After testing for 960 years, it’s safe to say that using weighted moving averages as trading indicators for buying and selling is a losing strategy. Avoid it. You only have a 7% chance of outperforming a buy-and-hold strategy.

You may also be interested in the incredible alligator indicator based on moving averages; with the optimal settings, it has proven highly profitable.

Trading the Alligator Indicator Profitably Based On Data

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