Greetings traders and welcome back.
Thank you for joining me again for another In Depth with Chris episode.
Today, we'll be discussing the weighted moving average.
This is one of those technical analysis tools that is so widely used, yet
it's not always talked about. We're going to talk about exactly
what it is, a little bit about where it came from, how the
calculation is done, and why it can be valuable to us as traders.
Before we dive into all of that, let's show you how you can apply it to your charts,
that way you can follow along for the entire ride.
We're go up here towards the top center and click the
show indicator options button, and at the very bottom of
the center column, you'll see weighted moving average. If we give that a click,
it'll add it over here on the right to the section one column
where we'll then have the option to change some of the settings
if we click the cogwheel. I don't want to change anything right now
so I'm going to leave it alone and go back to my home screen
here, and we'll see that we now have a weighted moving average
working its way through price, so we're good to go.
This is one of those tools that I see a lot of traders using
to pass the Gauntlet Mini, so make sure you check it out as well
if you are planning on passing the Gauntlet Mini in your journey here at Earn2Trade.
Other than that, let's dive on into it. Here we go.
Most traders will agree that technical analysis is an essential
requirement if you plan on trading any of the smaller time frames,
or just being a day trader by the definition. When we use
indicators like a weighted moving average, we are in fact
using a technical analysis based tool that is based on historical price data.
Today that's exactly what we're going to cover.
Technical analysts have been using moving averages for many, many years.
They are often categorized under a group of tools that deal with time series analysis.
We have other things in this category that you might be familiar
with, like the arithmetic mean, covariance, and correlation
coefficient if any of those ring a bell. The development
and use of moving averages is believed to date as far back as the 1900's,
I believe somewhere around 1901. It wasn't until a few years after
1901 that the name was associated with the technique for
smoothing data points over a given period. In the very
beginning, we didn't even have the name that we're using today
for it. A man by the name of P.N. Haurlan was the first to use
moving averages to track stock prices, and they considered
this "exponential smoothing". At the time,
he referred to them as "trend values", and measured data and
trend direction by smoothing their constants.
Later, it became known as exponentially weighted moving average.
What we call the "nineteen period exponential moving average"
today, is what he called the "ten percent trend" back then. Over
the years, moving averages have evolved and are used across
many different financial markets and are part of a variety
of different trading strategies.
As we know, the weighted moving average is a technical analysis
indicator, but what it's doing for us is, it's attempting
to generate trade signals by identifying: 1. The trend direction
and 2. Weighing more recent points in price data heavier
than past points in price data.
Essentially, more recent price is going to be weighted
heavier than the previous price is farther back in time.
It's a step further and more accurate generally speaking
than in a simple moving average, which we refer to as an
SMA. The WMA, the weighted moving average, it essentially computes
the average of given input values over specified time periods
by giving greater weight to the more recent data, and it does
this by multiplying a weighting factor by each bar's price
in a given set, and it then sums up the resulting values. It is
then used to smooth the data series to help filter out market
noise and make it easier for traders to identify trends.
For example, when price moves towards, or goes above, the
WMA line on the chart, it could signal that a price drop
in the short term may be ready to happen.
Therefore, traders could use this as a signal to exit their
position. However, if price dips near, or just below, the WMA
line like we have over here, we have a situation where it
might be a favorable time to enter the trade, because we were
closer to the historical average.
As mentioned, the weighted moving average and the simple moving
average are not the same thing. With the weighted moving average,
when we sum up the values, we should have a total weight that is equal to 100% when
we're all said and done. We're going to dive into that in just a moment,
but with the simple moving average, the math is relatively very simple.
We are just adding up all the data points within a given
period, and then we're dividing the value by the number of
periods. It's a very simple average, but the WMA, not as simple
as that when it comes to the math, so get your notebook ready,
we're gonna do a little bit of math. I'll walk you through it,
and if you need to pause the video at any point definitely feel free. It is okay.
Also remember folks, a lot of the platforms out there will
do the math for you, so don't feel overwhelmed.
Here's the formula to calculate the weighted moving average,
Good luck, have fun. I'm just kidding,
but this really is the formula to calculate the weighted
moving average where M equals the average value, the V equals
the actual value, and the W equals the weighting factor.
Then we have our n's equaling the number of periods in the weighting group.
If you are actually interested in doing the math like this, here you go.
It is here for you. You can always return to the video at any point in time,
but for the rest of you, you can stop sweating because I'm
going to make it easier.
Let's use an example where we have a stock. We'll say its stock
XYZ, and for the past three days, it traded at $50, $45, and $60.
We're going to calculate the weighted moving average based on these numbers.
The first step is to identify the numbers to average.
We have the three numbers provided, which is the 50, 45,
and 60, which were recorded over that three day period. Then
step number two is to assign the weight
to each number. Since there are three periods, the most recent
day, $60, gets the largest weight of 3. The second recent day
is $45 and receives a weight of 2, and the last day, $50, receives
a weight of just 1. Step three is to multiply each price
by the assigned weighting factor and sum them up.
Using the WMA formula, the calculation would be something like (3 x 60) plus
(2 x 45) plus (1 x 50), which all equals 320. Then step
four comes along, and we divide the resulting value by the
sum of the periods to the MMA.
The sum of the periods is 1 plus 2 plus 3, which equals 6.
So we have 180 plus 90 plus 50 divided by 6, and this equals
53.33 as a three period weighted average. The WMA value
of 53.33 compares to the SMA calculation of 51.67 to give
you an idea. The division by 6 in this step is what brought
us to the weighting sum, to that 6 divided by 6 equals 1
scenario, which is what we said is always a requirement.
Remember, it should always add up to 100%, or 1.
With the help of another example, let's say that we wanted
to calculate the weighted moving average of five stock prices
over a seven day period. The prices will be the 50.25,
the 56.39, the 58.91, 61, and so on and so forth.
You can see them, they're right here in front of you.
With the last price being the most recent, that is going to be the 54.65.
Now we have the numbers that we want to average,
so the next step is to assign the weighting to each of these
numbers based on how recent they are on any given period, and
that's what we've got going on in this column here.
Next, we want to multiply each of the five closing prices
by their corresponding weighting factor to find the average.
We have our 50.25 with the weighting factor of 1, over
28, giving us a 1.79, and so on and so forth.
You can follow it all the way down and do the math yourself
of course, just to make sure you've got some good practice
in. When we add up all of the weighted average individual
values, we'll arrive at the WMA. The WMA for the five stock
prices here over the seven day period is going to be $57.05.
Even though the answers for this one are already on the screen,
try running back through the video and making sure that you
can actually come to these numbers on your own as well.
Now that we understand how to calculate the WMA,
let's talk about the juicy stuff as why we even care, the
good reason behind why the weighted moving average can become
a powerful trading weapon in our arsenal.
The first is a big one, and that is it helps us determine
the trend direction with a strong clarity. This is because
when price is above the weighted moving average line, it
means that on average, price is trading higher than it has
over the period being analyzed, which in turn confirms an
uptrend. If we are aware that we are in an uptrend, it can
provide us with the knowledge that we may want to consider
only buying opportunities. If we're in a downtrend because price is trading below it
obviously the converse would be true, and we'd be anticipating
only selling opportunities, assuming we were trying to trade
with the trend. Then we also have the ability for it to indicate
support and resistance areas. A rising weighted moving average
can indicate support for price action itself,
when a falling moving average does the opposite and can
indicate resistance to price action over whatever specified
period of time. Traders usually tend to use this as a
strategy to place buy orders when price is near the rising
WMA, or place sell orders when prices near the falling WMA.
We also have to validate price strength and market momentum.
Price action above the moving average shows that the market
is getting stronger relative to where it was in the past
since the most recent prices now sit higher on the average.
On the flip side, when price action is below the moving average,
this shows that the market is getting weaker relative to
where it was in the past. Finally, we have to measure price movement.
The weighted moving average is generally more sensitive to
price movement, making it a better measure as well as identifying
trends sooner than a standard moving average, the SMA.
However, this can definitely be a double-edged sword because
the WMA is likely to experience more volatility than the corresponding SMA.
In conclusion, the weighted moving average, even though
seemingly simple in concept, can be a relatively powerful
tool when coupled with strong price action and/or other indicators
as part of an overall trading strategy.
It's a strong trend confirming tool, and can even provide
seemingly dynamic areas of support and resistance.
Let's take a look here at this one hour E-mini S&P 500 chart
that we already added a weighted moving average to.
We have a situation here where we saw a strong
bullish trend during this period of the market here to here,
and look at the weighted moving average as it moves along
price, I'm highlighting it with my white line,
we noticed that price comes down and continuously bounces
off of this moving average, almost to the tick, many times
over. As long as the bullish trend maintained, the weighted
moving average seemingly provided that dynamic area of support,
which can be very, very valuable to us as traders.
What did we see as soon as price came falling through the moving average over
here? As soon as we began falling through, we saw a temporary
downturn in the market. When things got sloppy, the weighted moving average
let us know. When things were trending strongly, the weighted moving average
let us know, and also gave us potential entry areas based
on that dynamic area of seeming support.
The weighted moving average is a pretty cool tool despite
my inability to say "the weighted moving average" when I'm
saying it too quickly. But guys, if you are diving into the
Gauntlet Mini, I strongly recommend you check out the weighted moving average.
It's simple, and sometimes keeping it simple is the best route to go.
Thank you for joining me again everybody.
Have a great day, and I will see you all very soon. Cheers everyone!