The McGinley Dynamic is a little-known yet highly reliable indicator invented by John R. McGinley, a chartered market technician and former editor of the Market Technicians Association’s Journal of Technical Analysis. Working within the context of moving averages throughout the 1990s, McGinley sought to invent a responsive indicator that would automatically adjust itself in relation to the speed of the market.

His eponymous Dynamic, first published in the Journal of Technical Analysis in 1997, is a 10-day simple and exponential moving average with a filter that smooths the data to avoid whipsaws.

Simple Moving Average (SMA) vs. Exponential Moving Average (EMA)

A simple moving average (SMA) smooths out price action by calculating past closing prices and dividing by the number of periods. To calculate a 10-day simple moving average, add the closing prices of the last 10 days and divide by 10. The smoother the moving average, the slower it reacts to prices.

A 50-day moving average moves slower than a 10-day moving average. A 10- and 20-day moving average can at times experience the volatility of prices that can make it harder to interpret price action. False signals may occur during these periods, creating losses because prices may get too far ahead of the market.

An exponential moving average (EMA) responds to prices much more quickly than a simple moving average. This is because the EMA gives more weight to the latest data rather than older data. It’s a good indicator for the short term and a great method to catch short-term trends, which is why traders use both simple and exponential moving averages simultaneously for entry and exits. Nevertheless, it too can leave data behind.

The Problem With Moving Averages

In his research, McGinley found moving averages had many problems. In the first place, they were inappropriately applied. Moving averages in different periods operate with varying degrees in different markets. For example, how can one know when to use a 10-day, 20-day, or 50-day moving average in a fast or slow market? In order to solve the problem of choosing the right length of the moving average, the McGinley Dynamic was built to automatically adjust to the current speed of the market.

McGinley believes moving averages should only be used as a smoothing mechanism rather than a trading system or signal generator. It is a monitor of trends. Further, McGinley found moving averages failed to follow prices since large separations frequently exist between prices and moving average lines. He sought to eliminate these problems by inventing an indicator that would hug prices more closely, avoid price separation and whipsaws, and follow prices automatically in fast or slow markets.

McGinley Dynamic Formula

This he did with the invention of the McGinley Dynamic. The formula is:

$\begin{aligned} &\text{MD}_i = MD_{i-1} + \frac{ \text{Close} – MD_{i-1} }{ k \times N \times \left ( \frac{ \text{Close} }{ MD_{i-1} } \right )^4 } \\ &\textbf{where:}\\ &\text{MD}_i = \text{Current McGinley Dynamic} \\ &MD_{i-1} = \text{Previous McGinley Dynamic} \\ &\text{Close} = \text{Closing price} \\ &k = .6\ \text{(Constant 60\% of selected period N)} \\ &N = \text{Moving average period} \\ \end{aligned}$​MDi​=MDi−1​+k×N×(MDi−1​Close​)4Close−MDi−1​​where:MDi​=Current McGinley DynamicMDi−1​=Previous McGinley DynamicClose=Closing pricek=.6 (Constant 60% of selected period N)N=Moving average period​

The McGinley Dynamic looks like a moving average line, yet it is actually a smoothing mechanism for prices that turns out to track far better than any moving average. It minimizes price separation, price whipsaws, and hugs prices much more closely. And it does this automatically as a factor of its formula.

Because of the calculation, the Dynamic Line speeds up in down markets as it follows prices yet moves more slowly in up markets. One wants to be quick to sell in a down market, yet ride an up-market as long as possible. The constant N determines how closely the Dynamic tracks the index or stock. If one is emulating a 20-day moving average, for instance, use an N value half that of the moving average, or in this case 10.

It greatly avoids whipsaws because the Dynamic Line automatically follows and stays aligned to prices in any market—fast or slow—like a steering mechanism of a car that can adjust to the changing conditions of the road. Traders can rely on it to make decisions and time entrances and exits.

The Bottom Line

McGinley invented the Dynamic to act as a market tool rather than as a trading indicator. But whatever it’s used for, whether it is called a tool or indicator, the McGinley Dynamic is quite a fascinating instrument invented by a market technician that has followed and studied markets and indicators for nearly 40 years. In creating the Dynamic, McGinley sought to create a technical aid that would be more responsive to the raw data than simple or exponential moving averages.

Some traders and investors denounce technical analysis (TA) as a superficial study of charts and patterns without any concrete, conclusive or profitable results. Others believe it is a sort of Holy Grail that once mastered will unleash sizable profits. These opposing viewpoints have led to misconceptions about technical analysis and how it is used.  

Technical analysis tries to capture market psychology and sentiment by analyzing price trends and chart patterns for possible trading opportunities. Contrary to fundamental analysis, technical analysts do not necessarily care much about the companies behind the stocks they trade or their profitability.

Some misconceptions about technical analysis are based on education and training. For example, a trader trained in using only fundamentals may not trust technical analysis at all. But that doesn’t mean someone who is trained in technical analysis can’t use it profitably.

Other TA assumptions are based on bad experiences. For example, the incorrect use of technical indicators often leads to losses. That doesn’t mean the method is necessarily wrong; possibly the person just needs more practice and training. The negative sentiment can be perpetuated by unscrupulous marketing, promising overnight riches if a simple TA indicator is bought and used. It rarely is that easy.

Here are eight common technical analysis myths—and why they simply aren’t true. 

1. Technical Analysis Is Only for Short-Term Trading or Day Trading

It is a common myth that technical analysis is only appropriate for short-term and computer-driven trading like day trading and high-frequency trades. Technical analysis existed and was practiced before computers were common, and some of the pioneers in technical analysis were long-term investors and traders, not day traders. Technical analysis is used by traders on all time frames, from one-minute charts to weekly and monthly charts.

2. Only Individual Traders Use Technical Analysis 

While individuals do use technical analysis, hedge funds and investment banks make ample use of technical analysis as well. Investment banks have dedicated trading teams that use technical analysis. High-frequency trading, which encompasses a significant amount of the trading volume on the stock exchanges, is heavily dependent on technical concepts. 

3. Technical Analysis Has a Low Success Rate

A look at the list of successful market traders, who have decades of trading experience, debunks this myth. Successful trader interviews have cited significant numbers of traders who owe their success to technical analysis and patterns. For example, Market Wizards: Interviews With Top Traders (Wiley, 2012) by Jack D. Schwager features interviews with many professionals who’ve profited solely by using technical analysis.

4. Technical Analysis Is Quick and Easy 

The internet is full of technical analysis courses that promise trading success. Though many individuals enter the trading world by placing their first trade based on simple technical indicators, continued success in trading requires in-depth learning, practice, good money management, and discipline. It requires dedicated time, knowledge, and attention. Technical analysis is only a tool, only one piece of the puzzle.

5. Ready-Made Technical Analysis Software Can Help Traders Make Easy Money 

Unfortunately, this is not true. There are many online ads for cheap and costly software that claims to do all your analysis for you. In addition, less-experienced traders sometimes confuse technical analysis tools in broker-provided trading software for trading models that will guarantee profit. Though technical analysis software provides insights about trends and patterns, it doesn’t necessarily guarantee profits. It’s up to the trader to correctly interpret trends and data.

6. Technical Indicators Can Be Applied Across All Markets

While technical analysis can be applied to many markets, specific asset classes have specific requirements. Equities, futures, options, commodities, and bonds all have differences. There may be time-dependent patterns like high volatility in futures and options nearing expiry, or seasonal patterns in commodities. Don’t make the mistake of applying technical indicators intended for one asset class to another.

7. Technical Analysis Can Provide Precise Price Predictions 

Many novices expect recommendations from technical analysts or software patterns to be 100% precise. For example, inexperienced traders may expect a prediction as specific as, “stock ABC will reach $62 in two months.” However, experienced technical analysts usually avoid quoting prices so specifically. Rather they tend to quote a range such as, “stock A could move in the range of $59 to $64 in the next two to three months.”

Traders betting their money on technical recommendations should be aware that technical analysis provides a predictive range, not an exact number. Technical analysis is also about probability and likelihoods, not guarantees. If something works more often than not, even though it doesn’t work all the time, it can still be very effective at generating profits.

8. The Winning Rate in Technical Analysis Should Be Higher

It’s a common myth that a high percentage of winning trades is needed for profitability. However, that is not always the case. Assume Peter makes four winning trades out of five, while Molly makes one winning trade out of five. Who is more successful? Most people would say Peter, but we don’t actually know until we get more information. Profitability is a combination of win rate and risk/reward. If Peter makes $20 on his winners but is down $80 from his one loss, he ends up with $0. If Molly makes $50 on her win and losses $10 on her losses, she walks away with $10. She is better off, even with fewer wins. Proper trade structuring allows for profitability even with few winners

The Bottom Line

Technical analysis provides a large basket of tools and concepts for trading. There are successful traders who don’t use it, and there are successful traders who do. Some believe technical analysis is the best way to trade, while others claim it is misguided and lacks a theoretical basis.

Ultimately, it is up to each trader to explore technical analysis and determine if it is right for them. It doesn’t guarantee instant profits or 100% accuracy, but for those who diligently practice the concepts, it does provide a realistic possibility of trading success.