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I Coded fxalexg’s Trading Strategy. Does It Work? — Transcript

by Revelio Trading · 2,459 words · 397 segments · language en · Watch on YouTube

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0:00A YouTube trader claims he turned $100
0:02into a million dollars in 90 days and I
0:05kept seeing people ask about him on
0:07Reddit, in trading forums, and many of
0:10you asked me about him, too. So, I
0:12decided enough was enough. This looks
0:15like a case for Revelio Trading. So, I
0:17went down the rabbit hole. I watched 32
0:20of his videos for a total of 34 hours,
0:2351 minutes, and 52 seconds. I read his
0:27website, found a spelling error, watched
0:29Coffeezilla's video on him, read a fan's
0:32summary of his strategy on Scribd,
0:35and then I rebuilt his entire strategy,
0:38rule for rule, and ran it through 10
0:40years of data. All to answer one simple
0:44question:
0:45Does his strategy actually work?
0:50His name is Alex Gonzalez, also known by
0:53his YouTube name FX Alex G.
0:56His strategy is called set and forget.
1:00And I have to give him credit. Unlike
1:02most YouTube traders, he explains his
1:04strategy in a very clear way with
1:06defined rules, and this made backtesting
1:09much easier. But before getting into the
1:11strategy, we need to understand the size
1:14of the claim.
1:16>> direction of the entire market. So,
1:18swing trading you can have a win rate
1:19anywhere from 60 to 65%, but the risk to
1:22reward is by far the greatest and but I
1:25would always aim for the trade to have a
1:27potential of a 1:4 risk to reward
1:30because
1:31>> He says that swing trading, which is his
1:33trading style, gives a 60 to 65% win
1:37rate and he aims for a risk to reward
1:39ratio of 1 to 4.
1:4265% win rate with a 1:4 risk to reward
1:46ratio?
1:47This made me suspicious right away. So,
1:50I ran a simple Monte Carlo simulation.
1:53A Monte Carlo simulation is basically a
1:55way to test many possible future
1:57outcomes. Imagine you want to predict
2:00how long it will take to drive to work
2:01tomorrow. You might hit every red light.
2:04There might be an accident, and so on.
2:06So, you can't predict tomorrow exactly.
2:09A Monte Carlo simulation does the next
2:11best thing. It plays out thousands of
2:14possible versions of the same trip and
2:16shows you the full range, the typical
2:18trip, the worst, and the best.
2:21In our case, each trip isn't a drive to
2:23work. It's a full 10-year trading career
2:26using Alex's numbers.
2:28Here's what comes out. On average, you
2:30would turn $10,000 into $88.05
2:35trillion.
2:36If you happen to be lucky and run the
2:38best path of the simulation, you end up
2:40with $7.12
2:42quadrillion.
2:44If you are unlucky and run the worst
2:46simulated path, you get $389.49
2:50billion.
2:52So, even on your worst run after 10
2:54years of trading this strategy, you
2:56should be the second richest person in
2:58the world.
3:00So, if your goal is to take down Elon
3:02Musk from number one in 10 years, this
3:04strategy is not for you.
3:07Jokes aside again, it looks suspicious
3:09to me. But without data, I won't express
3:11my opinion.
3:12I just want to show that the bar is set
3:14pretty high.
3:16Now, let's see how this strategy
3:17actually works.
3:22The strategy relies on two main ideas,
3:25trend and areas of interest.
3:28Let's start with trend.
3:29A candle has a body, showing the open
3:31and the close price, and wicks, showing
3:34the high and low.
3:36Alex focuses on bodies for almost
3:38everything, including trend. So, to keep
3:41it clean, I'll switch to a line chart.
3:43In an uptrend, we track two points, a
3:46higher low and a higher high.
3:49As long as price stays between them, the
3:51trend doesn't change. Every little swing
3:54in between is just noise. The structure
3:57only updates when price breaks one of
3:59these two points.
4:01Break the higher high, the uptrend
4:03continues. That new high becomes the new
4:06higher high, and the most recent low
4:09becomes the new higher low.
4:11This is now the range defining the
4:13uptrend.
4:15What if price had broken the higher low
4:17instead? The trend shifts. That low
4:20becomes the lower low, while the last
4:22swing high becomes the lower high. And
4:25now, we're in a downtrend.
4:28Let's put a full example on screen and
4:30read the trend according to the set and
4:32forget strategy.
4:3420 swing points. Can you call the trend
4:36at every step?
4:38From 1 to 2, we're in an uptrend. Point
4:411 is the higher low. Point 2, the higher
4:44high.
4:452 to 3, price retraces, but nothing
4:48breaks. So, point 3 is just a swing low.
4:52We are still in an uptrend.
4:54From 3 to 4, price breaks the higher
4:57high. The structure changes. Now, point
5:004 is the new higher high.
5:03What about the new higher low?
5:05We take the most recent swing low, so
5:08point 3. That's our new leg. It only
5:11changes again if price breaks either
5:13point 3 or point 4.
5:16From 4 all the way to 11, price moves up
5:19and down, but every one of these swings
5:22lives inside the 3 to 4 leg, so none of
5:25them changes the structure. The trend is
5:27still defined by points 3 and 4.
5:31That changes from 11 to 12. Price breaks
5:34the higher high again. Point 12 becomes
5:37the new higher high, while point 11, the
5:40most recent swing low, becomes the new
5:43higher low.
5:45Still an uptrend, just a new leg.
5:48Then, from 12 to 13, price breaks the
5:51higher low. The trend shifts from
5:53bullish to bearish, and the leg from 12
5:56to 13 now defines a downtrend. And
5:59here's the first interesting part,
6:01because many traders would still say
6:03this is an uptrend and draw a trend line
6:06like this. By Alex's rule, this is
6:09already a downtrend, and we play by his
6:12rules since we are testing his strategy.
6:1613 to 14 is just a retracement. Nothing
6:19breaks.
6:2014 to 15, price breaks the lower low.
6:24The new lower low is at 15, while the
6:27most recent swing high becomes the lower
6:29high, and the downtrend is now defined
6:32by the 14 to 15 leg.
6:35From 15 to 20, we have a structure that
6:38most traders would call bullish. Alex
6:41doesn't, because the structure hasn't
6:43actually broken according to his rules.
6:45Until price breaks this lower high, the
6:48market is in a downtrend.
6:50One final detail about trends. They are
6:53studied on the weekly, daily, and 4-hour
6:55time frames. We need two consecutive
6:58time frames in line to confirm a trend.
7:01So, either the weekly and the daily need
7:03to be in the same trend, or the daily
7:05and the 4-hour.
7:07And that's the entire trend engine. But,
7:10the trend only tells Alex which
7:11direction to trade, not where to take
7:14the trade. For that, he uses the second
7:17core concept of his strategy, areas of
7:19interest.
7:20An area of interest is a support or a
7:23resistance. So, simply a price area the
7:25market keeps reacting to.
7:28Just like for trends, Alex only
7:30considers the bodies of the
7:31candlesticks, not the wicks.
7:33So, how do we find areas of interest?
7:36A level is considered an area of
7:38interest only if price has touched it at
7:40least three times. The area cannot be
7:43bigger than 60 pips and cannot be
7:46smaller than five pips. We mark them
7:48only on the weekly and daily time
7:50frames.
7:51Levels on the weekly time frame are
7:53valid for up to five years, while levels
7:56on the daily time frame are valid up to
7:58two years.
7:59You can only enter a trade if the price
8:02is inside an area of interest. No area
8:05of interest, no trade.
8:07Again, credit to him for having very
8:10precise rules.
8:11So, we have established that he checks
8:13the trend for the direction of the trade
8:15and support and resistance for entering
8:18the trade. But, what triggers a trade?
8:21The trigger is a candlestick pattern
8:23among the ones you can see from his list
8:25here.
8:26The ones crossed out are the ones he
8:28doesn't use.
8:29What about stop loss and take profit?
8:32Stop loss goes five to seven pips beyond
8:35the area of interest, while the take
8:37profit goes to the nearest structure
8:40level with a minimum risk to reward
8:42ratio of one to two, but ideally aiming
8:45at one to four.
8:47No partial take profits, no break even,
8:50no trade management.
8:52Once you place stop loss and take
8:54profit, they are set in stone. That is
8:57why his strategy is called set and
9:00forget.
9:01We have a complete strategy breakdown
9:04and the rules are clear enough to back
9:05test it quite accurately.
9:08At this point, I was pretty excited. Are
9:10we going to make it to the top 10
9:12richest people?
9:13So, I ran the test.
9:19This is every result, the exact pairs
9:21and time frames he trades. And no, we
9:24did not make it to the top 10 richest
9:26people. The strategy actually lost
9:28money.
9:29But in all these numbers, there are two
9:31things that stand out. First, the
9:34strategy lost 4% per configuration on
9:37average. So, it's actually bleeding
9:39money.
9:40Second, there is not a single time frame
9:43that finished with a positive return.
9:46That's disappointing because we were
9:47expecting to turn $10,000 into billions
9:51of dollars in 10 years.
9:53But, what if we had actually traded this
9:55strategy with $10,000 over the past 10
9:58years?
9:59We'd be left with $21.
10:02A loss of nearly 100% of our account.
10:07But, the biggest question is not even
10:09the return. The biggest question is the
10:11win rate.
10:12Because Alex talks about a 60 to 65% win
10:16rate while aiming for trades around 1 to
10:184 risk to reward.
10:20So, I was really curious. Is there any
10:23version of the strategy that gets even
10:25close to that?
10:26And the answer is no.
10:29Across all the tests, the average win
10:31rate was around 21%.
10:34Even the best currency pair, dollar
10:36Swiss franc, only reached around 28%.
10:39The worst pair, Australian dollar
10:41Canadian dollar, sits at 5%. Though,
10:45that's only 61 trades, so not really
10:47statistically significant.
10:49And if anything, these numbers are
10:51generous. In the back test, the average
10:54risk to reward ratio was around 1 to
10:563.5, not 1 to 4.
11:00Smaller targets are easier to hit, so
11:02they move the win rate up. If I'd forced
11:05a strict 1 to 4 risk to reward ratio on
11:08every trade, the win rate would be even
11:10lower.
11:12At this point, Revelio Trading could
11:14have closed the case and said that this
11:16strategy simply doesn't work.
11:18Instead, I decided to put my obsessive
11:21hat on, and I went back through Alex's
11:23videos, even the ones in which he just
11:25smokes cigars and drives fancy cars
11:27instead of trading.
11:29Because we are not slightly below the
11:31claim. We are not missing by five or 10
11:34percentage points.
11:36We are missing by more than 30
11:38percentage points.
11:40So, where is this missing edge? Is it in
11:42the pair selection, the time frame, the
11:45candlestick patterns, the session, the
11:47month?
11:49So, I grabbed a coffee and started
11:51scanning every single piece of data.
11:54And this brings us to the next chapter
11:56of the story.
12:01So, let's start from the data we already
12:03have. The return by pair and time frame.
12:07I spent some time looking at it, trying
12:08to find patterns and clues.
12:11One thing that I noticed was that all
12:13the pairs containing the Canadian
12:14dollar, the British pound, or the New
12:16Zealand dollar were negative, with the
12:18exception of Euro pound that was just
12:21slightly positive at plus 0.6% average
12:24return.
12:26So, what if we remove these currencies?
12:30We have six currency pairs left, but the
12:32board looks much better than before. The
12:34average return is finally positive at
12:3611.9%.
12:39Let's check the win rate.
12:40The average win rate is 25%.
12:44Better than before, but nowhere near the
12:4660 to 65% claim.
12:49What about our $10,000 in 10 years?
12:52It would have turned into $11,646,
12:56which is about 1.5% a year.
12:59And the maximum drawdown would have been
13:00minus 66%.
13:03Not great.
13:05These numbers don't seem to reveal any
13:07hidden edge. Besides, I couldn't find
13:10any logical reason to exclude Canadian
13:12dollar, British pound, and New Zealand
13:14dollar from our tests.
13:16Yes, they were the worst performers, but
13:19removing the worst performers without a
13:21logical reason is just plain
13:23overfitting.
13:25So, maybe this hidden edge is not in the
13:27pair selection. Maybe it's in the time
13:30frame.
13:31But, when we look at the original table
13:33showing results by pair and time frame,
13:36we can see that all the time frames had
13:38negative returns. So, it must be
13:40something else. Something that we
13:42haven't analyzed so far.
13:45So, I took the next logical step and
13:47looked at the entry conditions.
13:49Alex says that he uses all these
13:51candlestick patterns to enter the
13:53market. But, what if some of them were
13:55performing poorly and dragging all the
13:57results down?
13:59So, I checked the performance by
14:00candlestick patterns.
14:02Sure, there is one candlestick pattern
14:04that has a very low win rate, and we
14:07could make an argument about removing it
14:09to improve the performance of the whole
14:10strategy. But, with only 37 trades, it
14:14barely moves the needle on the win rate
14:16of the entire strategy.
14:17This chart seems to confirm what the
14:19rest of the data has shown us so far.
14:22Win rate clusters around 17%
14:26miles away from the 60%
14:28claim.
14:30Rewatching his videos, Alex says that
14:32the best session to trade is the overlap
14:35between the London and the New York
14:36session. Also, the best months to trade
14:39are January to March and October to
14:42December, while June and July are slow
14:44months. So, let's do it. Let's sort the
14:47data by session and by month.
14:50The same 19% win rate everywhere.
14:55We opened this video with a simple
14:56question. Does this strategy actually
14:59work?
15:00I looked everywhere. Pair selection,
15:03time frames, candlestick patterns,
15:05trading sessions, months of the year.
15:08Every door led to the same place.
15:11So, here's my opinion. No, the set and
15:14forget strategy does not work.
15:16But, I was not going to give up because
15:19I still believed we could make this
15:20strategy profitable.
15:22For example, are we sure the higher time
15:24frame trend filter is actually helping?
15:27In other strategies we've tested, this
15:29bias actually hurt profitability.
15:32Also, if this entire system is based on
15:34catching trends, why restrict it to
15:37Forex? What happens if we use it on
15:39markets that tend to have strong trends,
15:42like gold, indices, and Bitcoin?
15:45What if we let machine learning analyze
15:47the strategy? Maybe it will discover
15:49patterns that we missed.
15:51All these questions needed answers, and
15:53maybe these answers could finally lead
15:56to a profitable strategy.
15:58All of this in the next video.

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