Momentum Indicator: Is It Worth Using It in Our Strategies?

by Andrea Unger

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Among the most widely used indicators in technical analysis are oscillators to measure momentum, or the tendency of a trend to persist and continue in the same direction in the short to medium term.

In this video, we'll discuss a very simple momentum indicator and evaluate its real performance in different markets, from cryptos to traditional futures.

By watching the video you'll discover:

- How to build the momentum indicator and insert it into a trading system

- How to interpret the performance obtained on Bitcoin, Ethereum, a crypto portfolio and a futures portfolio 

- Why it's better to use this type of oscillator as a filter instead of an entry signal

Enjoy! 😎



Hey everyone, it's good to be back, welcome back! Today we're going to be talking about one of the most popular indicators, the Momentum indicator.

Well guys, one of the coaches at Unger Academy here, and as anticipated in the intro, I’d like to introduce this indicator that I'm sure you're already familiar with, namely the Momentum indicator, which you can see plotted in this chart under Bitcoin. Bitcoin with a daily timeframe.

What is Momentum?

As you can see, it's an oscillator, so it alternates between overbought and oversold moments and fluctuates around a zero line.

One of the most common uses in technical analysis of this indicator is to buy by opening a long position when the oscillator crosses to the upside of the zero line and conversely open a bearish short position when it crosses the zero-line downward.

Let us see with a simple trading system, the efficacy of this indicator at this point.

First, however, let me just explain how this indicator is built, which is very simple.

So, we're talking about a price difference, meaning the difference between, for example, today's close and the close of n bars ago, okay? And that's it.

Evaluate momentum's efficacy on crypto

Now, let's check how a very trivial trading system works, for example on Bitcoin, when using this indicator.

So, it's going to be a system that's always at market, stop and reverse, and we're going to enter arbitrarily 30 days as a period.

Here is our system that buys $10,000 worth of Bitcoin every time there is this zero-line crossing.

As I said earlier, the indicator is set at 30 days, so let's change the period. Here it is. And let's go look at the results of our trading system.

The results may look promising: we have equity going up, even quite well. The system earns $24,000 over a time frame of three years and six months.

We can see that the profit comes mainly from the long component, while the short component breaks even. Let's also take a look at the equity line. This is the long trades equity line and this is the short trades equity line.

These are the results. They depend on the long-term trend in Bitcoin, which has been very bullish, so it's normal that the long trades equity line is better than the short trades equity line.

As I told you, it may sound like a promising system, and at this point, I'd apply it using the same parameters on another underlying asset, for example, Ethereum.

Trading system optimization

So, let's change charts, activate the same system, leave 30 periods, and see what it generates on a different underlying asset.

Again, we see a good equity line, okay? At this point, a newbie might perhaps be led to think this indicator is quite good and might be a good entry signal.

But let's tale a look at this in more detail. For example, let's try to do a parameter optimization to evaluate its stability. So, we can ask MultiCharts to do an exhaustive optimization and optimize the momentum from 5 to 150 periods. 

Let's run the optimization on MultiCharts and see the results. Here they are. Let's take a look at them plotted on a 2D chart. Let me eliminate what we don't need and just leave the net profit.

First of all, we can see that there isn't a lot of stability in returns, and this is the point I wanted you to think about. As we slightly change these parameters, we’ll notice profits that appear, then disappear, then return, and then disappear again.

Then there seems to be a more stable area. However, look at the variability of results here as well. And this is the first problem in using these indicators as entry signals.

The same applies to moving averages, for example. Within trading systems – and I'm saying this partly from experience – generally, it's preferable to use these indicators more as trend filters than as entry signals.

That said, let's do the same analysis on Bitcoin as well. So, let's go back to the initial chart and run the same optimization. Now, let's vary the momentum period from a value of 5 to a value of 150 in steps of 1. Okay, let's launch it and wait for the running time of MultiCharts.

Here it is. Let's go back to the two-dimensional chart. Let's eliminate gross profit and gross loss and leave only net profit.

Now we can see a completely different chart from the previous one. On Bitcoin, it seems that short-term momentum gives better results than long-term momentum.

And even in this case, we notice that the results change significantly as we vary even one period. So, the instability of the entry signal remains. It's true that in this area, all things considered, there seems to be underlying stability.

Backtest on a portfolio of futures

That said, to dig even deeper we could do a portfolio test by applying the same signal to a portfolio of different cryptocurrencies, such as BNB, Bitcoin, Ethereum, Light Coin, Cardano, and Eos.

At this point, we'll arbitrarily choose a 30-period value, run the backtest, and see the results together.

I'd say that the overall equity line isn't bad at all. We have an equity line that has been quite sideways in the last period. However, we know that there has been a moderate slump in the last few months in crypto so I'd say that on the whole, this system hasn't performed badly at all.

And so, at this point, it's worthwhile to do the same test we did earlier on the stability of these parameters.

Let's go and do it right away. Let's go do an exhaustive optimization, again from the value of 1 to the value of 150 and in steps of 1. Now let's go and check the results together.

Let's put it on the two-dimensional chart. We'll remove what we don't need. So, we'll always leave only the net profit. And in this case, we can see more stable results.

Why's this? Because the different equity lines of the different underlying assets tend to offset each other somewhat. It's the concept of diversification that produces a positive effect on this portfolio of trading systems.

The greatest area of stability seems to be in the range of 35 to 65. So let us take 50 as an indicative value and look at our backtest.

There you go. we can see a disappointing trend, with a really big drawdown right now, but if we take a look at the close-to-close drawdown, we can see that on the whole, the trading system seems to be working pretty well.

However, just keep in mind one important aspect: cryptocurrencies are strongly trend-following underlying assets, and therefore, regardless of perhaps how good the entry signal is, if we can stay in position in a manner consistent with the underlying trend, we can reap good returns.

And this is regardless of whether or not our entry signal has predictive value. We'll simply try to stay in a position that is consistent with the market trend.

Why am I telling you this? Because I've prepared another test on a traditional portfolio of commodity futures. I've included Crude Oil, Gold, the Mini SP 500, Live Cattle, T-Bond, Wheat, Coffee and Euro-Dollar.

So, by doing the same test with the same period of 50 on this portfolio of commodities, we don't obtain the same results at all. 

This is the trading system that runs on this futures portfolio. It does have a rising equity line, but it has a completely different result compared to what we saw before.

In this case, the profit factor is 1.12. By contrast, on the system working on cryptocurrencies, we have got a profit factor of 3.29.

Final thoughts

So, the question is: What's good about momentum and how much of the results that we're noticing depend on the nature of the cryptocurrency market, which is a volatile instrument that can also stay on trend for a long time?

So, in this video, I just wanted to emphasize two things. The first is that it’s very easy to also get fooled by a backtest if you don't completely understand what you're doing.

On the other hand, what I want to emphasize is that the market we trade on is just as important, if not more so, than the system used for trading.

Lastly, going back to the momentum indicator, my advice is to use it primarily as a filter, beyond these nice results we’re seeing, rather than as an entry signal.

It does indeed show greater stability of results as a filter and is quite effective. Conversely, as an entry signal, I can assure you that it's much easier to find more consistency in traditional setups such as the breakout of the highs of the previous day or the previous week, rather than using different types of oscillators, including momentum, moving averages, etc.

If you have any questions, please feel free to write them down in the comments, and we will answer them, and maybe even leave us some feedback for new videos to make!

Finally, if, as I imagine, you're interested in systematic trading, I’d like to leave you with a suggestion. At the link in the description of this video you can access a free presentation by Andrea Unger, introducing you to his trading method, the Unger Method, which he used to win 4 times the World Cup Trading Championships. So, check it out if you're interested in systematic trading.

You can also get the best-selling "The Unger Method" covering only the shipping costs, or book yourself for a free strategy consultation with one of our coaches.

Well, guys, that's it for today.

Please leave a Like if you enjoyed the video, and also don't forget to subscribe to our channel!

Until the next video! Will see you again, bye-bye!

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Andrea Unger

Andrea Unger here and I help retail traders to improve their trading, scientifically. I went from being a cog in the machine in a multinational company to the only 4-Time World Trading Champion in a little more than 10 years.

I've been a professional trader since 2001 and in 2008 I became World Champion using just 4 automated trading systems. 

In 2015 I founded Unger Academy, where I teach my method of developing effecting trading strategies: a scientific, replicable and universal method, based on numbers and statistics, not hunches, which led me and my students to become Champions again and again.

Now I'm here to help you learn how to develop your own strategies, autonomously. This channel will help you improve your trading, know the markets better, and apply the scientific method to financial markets.

Becoming a trader is harder than you think, but if you have passion, will, and sufficient capital, you'll learn how to code and develop effective strategies, manage risk, and diversify a portfolio of trading systems to greatly improve your chances of becoming successful.