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All right, let's talk about moving averages now, and I love moving averages.
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I think they're a real powerful and pretty simple way to apply some technical analysis easily and quickly
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and really get a good visual on that.
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And one thing we know is that, you know, prices you could probably see from all these price charts,
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they don't move in a nice straight line and they don't move real nicely.
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They get all of these ups and downs and all that and kind of, you know, doing that in a moving average
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helps to kind of smooth that out so we can kind of, you know, have a picture of what might be happening
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with the prices in an easier to identify manner.
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So in this section, we're all going to be moving averages and how we can apply them to our trading,
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to our trading.
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So moving averages are also known as dynamic analysis.
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So if we think of what a moving average is as far as just what is it, it's a while.
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I want to it's a key component of technical analysis for sure.
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I mean, it's one of the things that you see often use often as a default on charts.
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We see these lines going across the chart.
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A lot of times those are moving average line.
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Again, it's going to smooth out the pricing.
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So you're not going to have that choppy up and down.
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It's going to have a smooth kind of line.
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It's going to kind of smooth out those pricing depending what moving average you use and it kind of
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just repricing outliers where you might see prices going up and down, up and down.
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So there's a big high and it comes down those big low and comes down a moving average will smooth that
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out in effect and basically account for those price outliers, either high or low.
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And they're also work well with using them with other indicators, whether it's candlesticks or sentiment
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or volatility or momentum, whatever it might be.
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There's different types of indicators out there that we're learning about.
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And you can the pair well with moving averages so they can be used for these other indicators.
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And they're very good at helping to identify trends and in helping it to take certain actions around.
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When you see something happens with a moving average indicator, you know, what do you do next to buy?
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You sell.
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They actually can be very, very apparent looking at these different trends and the ways that you can
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apply moving averages, which is what this section is all about.
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How can we apply that?
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How can we be better trading traders around them?
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Now, one thing done, a couple of things to understand about moving averages was one is they are a
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lagging indicator, right?
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They're looking at averages going back over a certain period of time that you decide how long you want
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to look back as far as that period of time.
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But it is because it's looking backwards is a lagging indicator.
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So it's not a forecasting type tool or trend following, too.
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It's more like looking a little bit backward.
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So it's a lagging indicator that can still is still very helpful as far as what you might decide to
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do going forward, but it's not designed to look for it.
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So and also, you don't have to try to figure out, you know, the starting endpoints of it, which
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is nice.
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You know, when you start looking when we're looking at, like trend lines, are we to figure out well
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worth the start?
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Where is the end then?
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Going to draw my trend line?
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You don't have to doing that.
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You don't have to do any Hendron trend line drawing or anything like that.
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It's all basically mathematical.
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And the trading platforms do this all automatically for you.
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You just set the parameters.
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How many days basically you want your moving average to look at and the type of moving average you want
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to use, which we're going to learn about.
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And then it's all shown right on the chart and then you can make decisions based on that.
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And so the subjective part is really just choosing that moving average you want to use and how many
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periods the rest of it's mathematical and automatically done for you.
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So let's get into that a little bit, how that would really work and some of the different types of
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moving averages that are out there.
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We start with the simple moving average, really the most common one.
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