0:01 there are countless strategies that
0:02 investors have come up with over the
0:05 years to maximize their returns and
0:06 while none of them are foolproof
0:07 measures to get the most out of your
0:10 money or even beat the overall market
0:11 some of them have been surprisingly
0:13 successful the majority of the time
0:15 today we discuss one such strategy
0:17 here's one surprisingly simple way
0:19 regular investors can get more out of
0:21 their money and possibly beat the market
0:23 in the process but before we get going
0:24 be sure to like this video if you
0:26 haven't already as it really does help
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0:41 investing for free today today's
0:43 strategy is known as the moving average
0:45 method and it comes from the world of
0:47 technical investing on the surface it
0:49 really is quite simple to understand and
0:51 implement but it does have some caveats
0:53 that need to be kept in mind if you
0:54 decide to try it out for yourself today
0:56 we'll discuss how to implement the
0:57 strategy as well as some of those
0:59 considerations so first things first
1:02 what is a moving average a moving
1:03 average is simply a way to cut out the
1:05 short-term noise produced by an
1:07 investment's price fluctuations thus
1:09 making it easier to spot trends as you
1:10 can see from this chart the price of
1:12 this hypothetical investment was pretty
1:15 volatile over this 30-day stretch
1:17 sometimes rising or falling by 10 or
1:20 more but its general trend was upward a
1:21 moving average can be calculated in a
1:23 few ways the first and simplest method
1:25 is by taking the average of an
1:26 investment's price over a specific
1:28 period of time in this chart i used a
1:30 five-day moving average to smooth out
1:32 the trend but investors use a wide
1:34 variety of durations to calculate their
1:36 moving averages depending on their goals
1:37 short-term investors may use time frames
1:39 of hours or even minutes to get their
1:41 averages while longer term investors may
1:43 use intervals of several months to a
1:45 year or even more to get their averages
1:47 anyway technical investors often compare
1:49 these moving averages to the current
1:50 price of an investment or a second
1:52 moving average to determine if they
1:54 should sell or buy in this more
1:56 simplistic variation we're just looking
1:57 to see if the current price of the
1:59 investment has recently fallen below the
2:01 moving average if it has that tells the
2:03 investor that it may be a good time to
2:05 cut their losses and sell if the price
2:07 should rebound and rise back above the
2:09 moving average it's usually seen as a
2:11 good time to buy back in according again
2:12 to this simplistic variation of the
2:15 strategy a second somewhat more complex
2:16 way of calculating the moving average is
2:19 to use an exponential moving average
2:20 this approach is still ultimately trying
2:22 to accomplish the same thing as the
2:24 simple moving average it's just that
2:25 instead of taking a simple arithmetic
2:27 average of an investment's price it
2:29 weighs recent prices more heavily this
2:31 tends to make exponential moving
2:33 averages much more responsive to sudden
2:34 shifts in price movements which can be a
2:36 good or bad thing depending on your
2:38 goals and the situation other investors
2:40 use multiple moving averages to help
2:42 them make investing decisions for
2:44 instance you could use a 50 and 200 day
2:45 moving average to determine the
2:47 investment's trend if the shorter term
2:49 moving average in this case the 50-day
2:52 average rises above the longer-term
2:54 average than you buy if it falls below
2:55 the longer-term average then you sell
2:58 those are the basics behind the strategy
2:59 like i said it's pretty simple you're
3:01 just analyzing investments price
3:03 movements to determine its trend and
3:04 then deciding if that trend is favorable
3:06 enough for you to buy the investment or
3:08 unfavorable enough for you to cash out
3:10 as you can imagine this approach has its
3:12 fair share of pros and cons where this
3:14 approach really excels relative to your
3:16 standard buy and hold strategy anyway is
3:18 inconsistently trending markets and as
3:20 we'll see with examples here in a minute
3:22 it doesn't really matter whether that
3:23 trend is positive or negative all that
3:25 matters is that it's reasonably
3:27 consistent this is because it enables
3:29 the moving average investor to avoid the
3:31 worst of market crashes while still
3:33 participating in the majority of market
3:34 run-ups for instance take a look at
3:36 these hypothetical returns for an
3:38 investment it starts off at 100 a share
3:40 but over the next handful of years it
3:42 gets hammered losing half of its value
3:44 before finally rebounding a buy and hold
3:46 investor with 100 put into the markets
3:48 would invest their money right away and
3:49 just let it sit there regardless of how
3:51 the market performs meaning that by the
3:53 end of this 10-year period their
3:55 investment would be worth around 122
3:57 dollars the same as the investment
3:59 itself that equates to an average
4:01 annualized return of about two percent
4:03 per year which is not great on the other
4:05 hand a technical investor making their
4:06 trades based on indicators like a moving
4:08 average may have been able to get out of
4:09 the markets before the worst of the
4:11 damage occurs and thus achieve a higher
4:13 overall return during this time period
4:15 as you can see in this hypothetical i've
4:16 assumed that our technical investor is
4:19 using a simple two-year moving average
4:20 under these assumptions they would have
4:23 wound up with a net worth of roughly 146
4:24 dollars in this admittedly very
4:27 oversimplified hypothetical that equates
4:29 to an average annual return of about 3.9
4:31 percent per year still not great but at
4:33 the same time it's nearly double what
4:35 the buy and hold investor achieved
4:37 during this decade where moving average
4:38 approaches can struggle is when the
4:40 markets experience a lot of volatility
4:42 and as a result don't really produce a
4:44 consistent trend in one direction or
4:46 another this is mainly because these
4:48 choppier markets can create a lot of buy
4:50 and sell signals in a relatively short
4:52 period of time which can lead to higher
4:54 trading costs and possible undesirable
4:56 tax consequences in addition to possibly
4:58 missing out on sudden and big market
5:00 reversals kind of like what happened
5:02 between years five and six in that
5:03 hypothetical the markets experienced a
5:05 sudden reversal after bottoming out in
5:07 year five and rose by a whopping 50
5:09 percent but because the moving average
5:11 hadn't had enough time to adjust to that
5:13 new reality our technical investor
5:14 missed out on that year's gains and as
5:16 we've seen in previous videos on this
5:18 channel it's not uncommon for markets to
5:20 bounce back in a big way in the first
5:23 year or so of a market rally for a great
5:24 real world example of a time period in
5:26 which the markets were generally
5:27 trending upward in a way that produced
5:29 superior returns from moving average
5:31 investors we need look no further than
5:33 the most recent decade of the 2010s the
5:35 markets peaked in october 2007 before
5:37 beginning a precipitous drop during the
5:38 great recession that would see them
5:40 bottoming out roughly 50 below their
5:43 previous highs in march 2009 from there
5:44 they would more or less be on the rise
5:46 for the next decade until this most
5:48 recent downturn in early 2020 got
5:50 started during the near 11-year time
5:51 period between the bottom of the great
5:53 recession and the peak in early 2020 if
5:55 you had simply invested ten thousand
5:57 dollars into an s p 500 index fund and
5:59 held it there that investment would be
6:01 worth roughly 50 000
6:03 if you had used a simple 50-day moving
6:05 average to determine whether you should
6:06 be buying or selling your net worth
6:08 would be around sixty thousand seven
6:09 hundred dollars by the time the market
6:11 peaked in twenty twenty that's an
6:12 average annualized return of about
6:14 fifteen point nine percent per year for
6:16 the buy and hold investor before
6:18 dividends are reinvested and about
6:20 eighteen percent per year again before
6:21 dividends for the simple moving average
6:23 method for a great example of a time
6:24 period when the stock market was
6:26 crashing and burning we can look to the
6:27 stock market crash during the great
6:29 depression in the early 1930s the
6:31 markets had recently experienced a crazy
6:33 run-up during much of the 1920s with for
6:35 the last five years of the decade even
6:37 posting price returns meaning without
6:40 dividends of 19 or more but in september
6:42 and october of 1929 the markets started
6:44 showing signs of turbulence which would
6:46 turn into the worst crash in the history
6:48 of the us stock market when the dust
6:50 finally cleared in june 1932 the markets
6:52 had lost nearly 90 percent of their
6:54 value buy and hold investors naturally
6:56 fared horribly during these years with a
6:58 hypothetical 10 000 investment falling
7:01 to less than 1400 by the summer of 1932.
7:02 that's the equivalent to an average
7:05 annualized return of negative 52.4 per
7:08 year however amazingly technical traders
7:10 using a simple 50-day moving average
7:12 would have actually made money in the
7:14 stock market during this period a ten
7:15 thousand dollar investment for our
7:17 hypothetical moving average investor
7:19 would have grown to be worth just over
7:21 eleven thousand nine hundred dollars
7:22 that's the equivalent to a six point
7:25 eight percent per year annualized return
7:26 and given the market environment we're
7:28 talking about here that's enormously
7:31 impressive of course not all markets are
7:32 as great for investors as the bull
7:34 market of the 2010s just as not all
7:36 markets are as difficult for investors
7:38 as those of the early 1930s and as i
7:40 said earlier one of the things that need
7:41 to be remembered about using moving
7:44 averages is that they tend to work best
7:45 in consistently trending market
7:47 environments again it doesn't really
7:48 matter whether the markets are
7:49 consistently trending upward or
7:51 consistently trending downward just so
7:53 long as they are fairly consistently
7:54 trending in whichever direction they're
7:56 trending in but not all market
7:58 environments are so consistent take last
8:00 year for instance 2020 was pretty
8:02 volatile and as a result may have
8:04 resulted in a few buy or sell signals
8:05 for those keeping an eye on those moving
8:08 averages from march 23rd 2020 to the
8:10 same time next year a 10 000 investment
8:12 in the s p 500 would have grown to
8:13 around seventeen thousand five hundred
8:16 dollars that same ten thousand dollars
8:17 under a fifty day moving average method
8:19 would have only grown to around thirteen
8:21 thousand five hundred dollars with that
8:23 being said there are definitely some
8:25 caveats or at least considerations that
8:27 we do want to keep in mind when it comes
8:29 to using indicators like moving averages
8:31 to help us make our investing decisions
8:33 one as i already mentioned is that this
8:35 more active style of trading can
8:37 sometimes lead to higher costs namely in
8:39 the form of trading costs and or some
8:41 potentially serious tax consequences
8:42 depending on your situation in some
8:44 cases the difference in the costs
8:46 incurred by a more active technical
8:48 investor and a buy and hold investor can
8:50 be significant enough to make up for
8:52 most or even all of the additional
8:55 pre-tax pre-cost gains that the moving
8:57 average approach earned the technical
8:59 investor for instance in the post-grade
9:00 recession example that we explored a
9:02 minute ago we saw that the active
9:04 investor using a simple 50-day moving
9:07 average ended up with roughly a 20 edge
9:08 in terms of net worth over a buy and
9:10 hold investor before things like taxes
9:12 and trading costs were taken into
9:13 account unfortunately for the active
9:16 investor literally all of their gains
9:17 during these years would have been taxed
9:20 as short-term capital gains at their
9:22 ordinary income tax rate this is because
9:24 there wasn't a single instance of them
9:25 buying into the market and holding that
9:27 investment for at least a year and a day
9:29 in fact it was rare for them to go more
9:31 than a few months without cashing out
9:32 which means that if the investor was in
9:35 the 22 federal tax bracket which is not
9:37 all that unlikely given that they were
9:39 realizing several thousand dollars worth
9:41 of capital gains virtually every year
9:43 and that 22 tax bracket starts out at
9:46 around 40 000 a year for singles as of
9:49 2022 literally their entire edge would
9:51 have been wiped out by federal income
9:53 taxes alone it would have been even
9:55 worse if they'd lived in a state that
9:57 also taxed their gains so that's
9:58 definitely something worth taking into
10:00 consideration if you're looking at
10:02 trading actively in this manner and are
10:04 investing in a taxable account now you
10:06 might be thinking well dan that's
10:08 irrelevant because i can just use longer
10:09 moving averages so that i'm not
10:11 realizing those short-term capital gains
10:13 and on the surface that seems like an
10:14 obvious and simple solution to the
10:16 problem but there may be a catch the
10:19 catch is not all look back periods or
10:21 the amount of time you use to calculate
10:23 your moving averages will be as
10:25 successful as others in any given market
10:27 environment as we saw in the great
10:29 recession example using a shorter 50-day
10:31 look-back period we managed to produce
10:33 superior returns compared to a buy and
10:35 hold investor on a pre-tax pre-cost
10:37 basis however a longer look-back period
10:39 say 200 days since that's a pretty
10:41 common one to use wouldn't have been
10:43 nearly as successful if we had used a
10:45 200-day moving average to make our
10:47 trading decisions during the great bold
10:48 run of the 2010s our ending net worth
10:50 would have come out to around thirty six
10:52 thousand seven hundred dollars or a good
10:54 thirteen thousand dollars short of the
10:56 buy and hold approach before taxes and
10:58 costs are factored in a 250-day
11:00 look-back period which is roughly
11:02 equivalent to a year because the markets
11:03 aren't open on weekends and holidays
11:05 would have produced similar results with
11:08 a 36 400 ending net worth so yeah
11:09 different market environments will lead
11:12 to different advantages or disadvantages
11:14 for different look-back periods shorter
11:15 look-back periods or using an
11:17 exponential moving average instead of a
11:19 simple moving average tend to do better
11:21 in markets where the trends are sharper
11:22 since it can react quicker to those
11:24 changes but market environments that are
11:27 more of a slow burn can favor longer
11:28 back periods a bit more than their
11:30 shorter counterparts and without having
11:32 a crystal ball it's darn near impossible
11:34 to tell ahead of time which variation
11:35 will outperform and that's not to
11:37 mention that the longer your look back
11:39 period is the more likely it is that
11:40 you'll start missing out on dividends
11:42 from your investments which can give the
11:43 buy and hold approach a little bit of an
11:45 extra edge so there you have it that's
11:47 one relatively simple way that regular
11:50 investors can sometimes beat the market
11:51 it's not a foolproof strategy to beat
11:53 the market i mean as far as i'm aware
11:55 such a strategy doesn't actually exist
11:57 but because the markets tend to rise
11:59 more often than they fall and because
12:00 human psychology and emotion tends to
12:02 lead to markets building and sustaining
12:04 momentum better than a random chance
12:05 would suggest it should it is an
12:07 approach that can be surprisingly
12:09 effective in a lot of situations at
12:11 least as long as you figure out a way to
12:12 manage the potential costs associated
12:14 with those more frequent trades such as
12:16 utilizing tax advantaged accounts to
12:18 minimize your income tax burden and that
12:20 you're willing and able to stick to the
12:21 strategy over the longer haul without
12:23 shooting yourself in the foot but what
12:24 do you think have you ever used moving
12:26 averages to help make investment
12:27 decisions what other metrics do you take
12:29 into consideration when investing let me
12:31 know in the comments section below but
12:33 that'll do it for me today once again if
12:35 you enjoyed this video be sure to smash
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12:48 let's really get this information out
12:50 there and start our own financial revolution
