Crypto Trading Tips: Momentum Indicators Explained (Moving Averages)

Cryptocurrency trading follows many of the same patterns as other assets. In this article, Dr. Merav Ozair looks at one of the most common tools at the analyst's disposal.

Cryptocurrency traders have many tools they could use to evaluate the cryptocurrency market. The two most tried-and-true methodologies are technical analysis and fundamental analysis. Technical analysis focuses on predicting the direction of prices through the study of past market data, primarily price and volume. It applies various indicators to get a better sense of market sentiment and identify key trends. Hence, it is mostly used for short-term to intermediate-term trades. Fundamental analysis, the counterpart of technical analysis, focuses mainly in determining what an asset, digital or otherwise, “should” be worth. Thus, it is the primary tool used by long-term investors, such as Warren Buffett.

One of the most common indicators to predict market sentiment and trend is momentum. There are several measures used to measure momentum, such as Moving Averages Convergence Divergence (MACD), Price Rate of Change (ROC), Relative Strength Index (RSI) or different types of Moving Averages (MA). This article focuses on the MA family measures and explains how traders could use it.

Before we dive into the calculations, let’s understand first why any trader, crypto or otherwise, cannot ignore momentum when deciding when to trade, or better yet, deciding whether to trade.

What momentum is and why you should never ignore it

There is an old saying on Wall Street – “the trend is your friend” – which encapsulates the meaning of momentum. This is especially true if you are making short-term bets. Sometimes, however, momentum can last for years, as in the case of the bull equity market we experienced since 2010 up to early 2018.

Momentum is truly an anomaly. Both financial practitioners and academics are yet to figure out the reason for its existence, as it goes counter to any finance theory. Quants modelers know that you must switch up the factors in your strategies, as they may fade away. One factor, however, never changes – momentum – no matter the time-period you are using or the circumstances of the events. Even Nobel Prize Laureate professor Eugene F. Fama, a strong-minded proponent of the efficient market hypothesis, which states that stock market prices are essentially unpredictable, cannot explain momentum and calls it an anomaly.

Therefore, if there is one indicator that you must always use, no matter what methodologies you follow – it’s momentum.

Now that we understand the importance of momentum, let’s see how we could measure it.

There are many measures as stated above. The MA family is one of the most common measures used in the financial industry, which we will address below.

Types of moving averages

The three most popular types of moving averages are Simple Moving Averages (SMA), Exponential Moving Averages (EMA), and Linear Weighted Moving Averages (LWMA). While the calculation of these moving averages differs, they are used in the same way to help assist traders in identifying short-term, medium-term, and long-term trends.

Simple Moving Average

The most common type of moving average is SMA. It simply takes the sum of all the past closing prices over the time-period and divides the result by the total number of prices in the calculation. For example, a 10-day simple moving average sums-up the last ten closing prices and divides them by ten.

Critics of SMA see limited value in this measure, because each point in the time series has the same impact on the results, regardless of when it occurred in the sequence. For example, a price jump 199 days ago has just as much impact on a 200-day moving average as a price jump one day ago. This criticism led traders to identify other types of moving averages designed to solve these problems and create a more accurate measure.

Linear Weighted Moving Average

The LWMA is a the least common moving average. It takes the sum of all closing prices, multiplies them by the position of the data point, and divides by the number of periods. For example, a five-day linear weighted average will take the current closing price and multiply it by five, yesterday’s closing price and multiply it by four, and so forth, and then divide the total by five. While this helps resolve the problem with the simple moving average, most traders have turned to the next type of moving average as the best option.

Exponential Moving Average

The exponential moving average leverages a more complex calculation to smooth the data and place a higher weight on more recent data points. The calculation of EMA is beyond the scope of this article, but you could use the function “exponential smoothing” in Excel to calculate it (see tutorial.) EMA is more responsive to new information relative to SMA and is the MA of choice for many technical traders.


Chart 1

Chart 1 is an example of an EMA calculation, where 0.9 and 0.6 represent the weight of alpha. The lower the alpha the more weight the calculation gives to the most recent observations (i.e., new information). (Again, you do not need to know the EMA formula when you work with Excel. Simply remember what alpha (i.e., “damping factor”) represents.)


Chart 2

Chart 2 clearly shows that even with a high alpha measure of 0.9 (less weight for recent news), EMA follows more closely the changes in prices than the short-term 50-day SMA.

How to use moving averages

Fast, medium or slow

When it comes to MA, you have three choices for your indicator settings: a fast (short-term), a medium (medium-term) or a slow (long-term) setting.

Here are a few common examples:

  • Fast: typically, anything from 5-period to 15-period.
  • Medium: anything from 20-period to 50-period.
  • Slow: above 50 with 100 and 200 as popular long-term MA.

Identifying trading signals

Moving averages are helpful for identifying current trends, support or resistance, as well as generating actual trading signals.

The slope of the MA can be used as a gauge of trend strength. When the slope is relatively upward steepening, you are most likely in a bullish market. When the slope is somewhat flat, you are in a sideways period. When the slope is steepening down, you are plausibly in a bearish market.

Many technical analysts often look at multiple moving averages when forming their view of long-term trends. When a short-term MA is above a long-term MA, that means that the trend is bullish and vice versa for short-term MA below long-term MA.

Moving averages can also be used to identify trend reversals:

  • Price crossover: the price crossing over the MA can be a powerful sign of a trend reversal. Price crossing above the MA indicates a bullish breakout ahead. Often traders would use long-term MA to measure these crossovers. Price frequently interacts with shorter-term MA, which creates too much noise for practical use.
  • MA crossover: short-term MA crossing below long-term MA is often a sign of a bearish reversal, while a short-term MA crossover above long-term MA could precede a breakout higher. Longer distances between MA suggest longer term reversals as well. For example, 50-day MA crossover above a 200-day MA is a stronger signal than a 10-day MA crossover above 20-day MA.


Chart 3

Chart 3 of the price of Bitcoin (BTC) is an example for the following:

  • Price crossing the 50-day SMA on January 11th, 2018, is an indication of a trend reversal, moving into a bearish territory.
  • 50-day SMA crossing below 200-day SMA on March 28th, 2018, is a sign of a bearish reversal.

The analysis above indicates that BTC is currently in a bearish market until other indicators signify otherwise.

Caveats – no magic bullet

There is no perfect system or method and trying to look for one is futile. Instead, you should focus on learning the flaws of your system and understanding when it does work and when it does not.

A moving average is no magic tool and it does not matter whether you have a 15-period, 50-period or a 100-period, an EMA or SMA. It is imperative, however, to have a large sample of your trades, constantly analyze and follow these steps:

  • What do your winners have in common? Market conditions? Price relation to the MA? How did price trade into the moving average? How did price break the moving average? Etc.
  • What do your losers have in common?
  • Understand when the market conditions favor your tools and when they do not.
  • Add other indicators as no one indicator is never enough.
  • Learn, adjust and adapt.
  • Trade and reiterate the process above.

Trading is a never-ending learning process. No methodology is perfect, and losses are inevitable. Make sure, however, to minimize them as much as possible.  Keep at it. Learn from each trade and adjust.