AI Moving Average: The Future of Trading

So you’ve got your standard old-fashioned moving averages, right? They’re kind of like the GPS that helps you navigate the messy streets of financial markets. But the thing is, they only know what’s happened in the past. They’re like a rear-view mirror that tells you where you’ve been, but not necessarily where you’re going.

And then we have artificial intelligence. It’s like your super-smart buddy who’s always a step ahead, predicting what might happen next. Now imagine if we could combine the two. That, my friends, is exactly what AI-based moving averages do. Instead of just looking at the past, AI moving averages learn from it. They use AI to adapt and change as market conditions shift, giving you a heads-up on possible twists and turns in the market.

The Power of AI Moving Averages

It’s like having a supercharged GPS that not only knows the route but can also predict traffic jams. What’s really cool about AI moving averages is that they don’t just react, they anticipate. By using machine learning, they can interpret loads of data, think about loads of variables, and update themselves in real-time. This gives you a better shot at forecasting trends and might just give you that extra edge you need in the market.

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What is AI Moving Average?

This indicator is called the Machine Learning and Optimization Moving Average. It was published by Zionman. In this video, I will show you how this indicator works, as well as some strategies you can try with it to make really good profits.

Once applied to the chart, access the indicator settings and head over to the inputs. There are many parameters available for customization. The first section includes the settings for machine learning. Here we have the amount of historical data and the optimization goal. The amount of historical data is the time period in bars used for calculations. Generally, the more data we use, the more accurate the results. Depending on your preferences, you can select all data or custom data. We will select all data.

Next, we have the optimization goal, which allows you to choose between performance win ratio or both. If you choose the win rate, machine learning will calculate the data and select the most optimal moving average length that gives the highest win rate. According to performance, you get the best moving average length based on the percentage of profits you’re able to catch. For example, you buy when the price rises above the moving average and close the position when the price falls below the MA. The earlier you enter and exit the trade, the higher the percentage of profit caught.

Once you’ve selected the optimization goal, you will need to turn on the machine learning. The indicator also allows you to select up to two different moving averages. For now, let’s disable the second one and set the first one as the whole MA. The length will be set to 100. The indicator will then perform its calculations and come up with a moving average length anywhere between 1 to 100.

In the upper right corner, we can see all the info about the AI moving average, such as loading time, stored data, and the best whole MA period.

Using AI Moving Average in Practice

How can we use this indicator in practice? Let’s begin with Strategy Number One.

For this strategy, two more tools will be added. The first one is called Machine Learning Lorenzine Classification by JD Haughty. This is also an AI-based tool. It will be used to confirm buy and sell trades. Before you start using it, open its inputs and uncheck some components.

For the second indicator, add Supply and Demand Visible Range by Lux Algo. Open its settings and change the supply color to yellow. The demand color will be changed to green.

Here’s the way we can use these indicators to identify strong trend reversals. This strategy is effective in both trending and ranging markets. The rules are very simple. Let’s start with a Buy Signal. First, a price must have been rejected at least twice by the level of demand. After the latest retest, machine learning must print a Buy Signal. At the time of the signal, the closing price must be above the AI moving average. Pay close attention to the equilibrium zone. The closing price must not be at or above the middle level. Our goal is to open the trade at the best possible price before the market makes its move. Place the stop-loss below the demand level and exit a winning trade when the price falls below the moving average.

In this example, the price moves in our favor, but then it gets rejected off the equilibrium zone. It then falls below the MA. However, we cannot close the position right now since the trade is not running in profit. Make sure you follow this rule.

The next example shows how the price found strong support at the demand zone. You can see how many times it got rejected yet never had a chance to break through. A valid Buy Signal was given, and the trade was very successful.

Strategy Number Two

Set the MA type to volume-weighted moving average. This time we will be using the AI moving average for finding support and resistance in price. For example, when the price makes a strong move to the upside after a downtrend, it usually rises above the moving average. This price action signals a trend change. However, we cannot purchase the security yet since selling pressure remains significant and the breakout could be false.

What often happens after such a move is a correction and a pullback to the moving average. So a better idea would be to buy somewhere on the pullback. In this case, the probability of a trend continuation to the upside is way higher.

A very interesting tool I want to present to you is called the Breakout Probability indicator. Thanks to the creator Xiamen for this amazing tool. This indicator displays levels on the charts and the chance of them being reached by the price in the near future. If the bullish percentage is greater than the bearish, the price is expected to rise.

If the indicator tells us that a further drop in price is expected, we simply skip the long trade. If you’re looking to sell the stock, wait for a big price drop after a bullish rally. A large bearish candlestick must break below the VWMA. After that, the price must retrace to the moving average and get rejected. If at the time the rejection happens, the breakout indicator gives a high chance of a sell-off, we open a short position.

These are currently my top strategies using the artificial intelligence moving average indicator. If you want to see more videos like this more often, hit that like button and subscribe to Trade IQ. Thanks for watching until next time.