Claude 4.5 tested: Is it Good for algo-trading strategies? — Transcript
Full transcript
- 0:00Hey guys, the Anthropic team just
- 0:02released Claude 4.5 which is supposed to
- 0:05be the king of the coding and in the
- 0:07past they have proven to indeed be the
- 0:09king of the coding but what I'm
- 0:11interested as always is the performance
- 0:13of these models for algo trading in
- 0:16Python. So let's test it to see if the
- 0:18model can write us some good strategies,
- 0:20whether it can help us to debug our
- 0:22existing strategies and also whether or
- 0:25not the model has some actual trading
- 0:27knowledge to improve the result of an
- 0:29existing strategy. So if all that sounds
- 0:31interesting to you, let's get right into
- 0:33it. So here's a blog model that they
- 0:35just released. And according to this,
- 0:37the performance of this model is
- 0:39supposed to be even better than Opus
- 0:414.5, which was indeed a really, really
- 0:44good model. but it costed like a kidney.
- 0:48But this one costs exactly as much as
- 0:50the Sonnet 4, which wasn't that
- 0:53expensive. It was definitely affordable.
- 0:55Not the cheapest model, but good enough
- 0:57for most users. And here you can also
- 0:59see a benchmark of it compared to the
- 1:01previous models such as GPT5, which is
- 1:03also a really good model. And Gemini 2.5
- 1:05Pro, which at this point is considered
- 1:07an old model, and I'm not even sure why
- 1:10they are including it in this table. But
- 1:12anyways, in agent encoding, you can see
- 1:14that it definitely holds up even
- 1:16compared to opus. But one that is really
- 1:19important to us is this one. So, high
- 1:21school math competition because it is
- 1:23basically telling us how good the model
- 1:25is in mathematics, which is also what we
- 1:27use in algo trading. And you can see it
- 1:29is beating all the other models by a
- 1:31high margin except 5. So, that one is
- 1:35also really good in math. So, that's
- 1:36really interesting. So I guess the cloud
- 1:40models in the past were really good at
- 1:42coding but not as much good at
- 1:44mathematics like the GPT5 was but in
- 1:47this model they really made up for that.
- 1:49So that's really brilliant. And here's
- 1:51also another interesting metric and that
- 1:53is financial analysis which is of course
- 1:55what we care about and it is beating all
- 1:58the other models including GPT5. So this
- 2:00is also really nice to see. And here's
- 2:02also another benchmark chart for
- 2:04finance. And as you can see, Cloud 4.5
- 2:06is beating all the other models, even
- 2:09the Opus 4.1. And that is just
- 2:12brilliant. Now, before I continue, I got
- 2:13to say that since our point is to test
- 2:16the model for algo trading. I don't want
- 2:18to just run the vanilla model. I want
- 2:21one that has some custom instructions
- 2:23for algo trading. For that, you have two
- 2:25options. So the first one is to use the
- 2:27cloud version, which I call JessPT. I
- 2:30made it myself. you can get started for
- 2:32free or upgrade for more limits and that
- 2:34one now has access to cloud sonet 4.5
- 2:37and all the other models that are out
- 2:39there. So feel free to use this one or
- 2:41if you don't want to do that let's say
- 2:43you have some privacy concerns or you
- 2:45don't want to pay me anything that is
- 2:47perfectly fine just go and watch my
- 2:49previous video where I teach you how to
- 2:51build your own AI for algo trading from
- 2:53a scratch. So if you use that one you
- 2:55don't have to pay me anything and you
- 2:56will keep full privacy for yourself. But
- 2:58if you want to get started as fast as
- 3:00possible, Jess GPT is the best option
- 3:03and that's the one that I'm going to use
- 3:04in this video. Now, we're going to ask a
- 3:06model 10 questions and see the results
- 3:08and give it rating. And the first
- 3:09question is really simple. Write a
- 3:11golden cross strategy. So that's like
- 3:13hello world question in the world of
- 3:14algo trading, right? So let's give it a
- 3:16hit. All right. So let's copy the code
- 3:19and go back to Jess's dashboard. And
- 3:22here I'm going to create a new strategy
- 3:24and I will call it test cloud 4.5.
- 3:30Actually let's put it like this because
- 3:31this is supposed to be the name of a
- 3:33Python class. So let's create it and
- 3:36let's paste the whole thing here. And
- 3:38let's also give it a read. So let's zoom
- 3:40in a little bit. All right. So it named
- 3:43it golden cross. It defined an EMA 50 by
- 3:47simple syntax. return TA. EMA which is
- 3:49the correct syntax in just for defining
- 3:51an indicator. Then it is passing the
- 3:53current candles and then it is defining
- 3:56the period. So perfect. It did another
- 3:58one for EMA 100 and then it is defining
- 4:00the entry rule which is should long like
- 4:02whether or not we should open a long
- 4:04position in it. It is simply saying if
- 4:06the current EMA 50 is bigger than EMA
- 4:08100. So it is detecting the moment that
- 4:11the crossing is happening. This is
- 4:13perfectly correct. And then in the
- 4:15golang function which is where we define
- 4:17the position sizing it is defining the
- 4:19quantity using the size to quantity
- 4:21utility function of Jesse. It is passing
- 4:24the entire available margin that we have
- 4:26and then the current price as the entry
- 4:28price and the fee of the current
- 4:29exchange. And to submit the buy order it
- 4:32simply says the quantity and then the
- 4:34price which is the current price. So we
- 4:37want to use a market order to open the
- 4:39position. So this is perfect. And of
- 4:41course for short positions it's doing
- 4:43the opposite. So instead of self buy it
- 4:45is using selfell and then you define the
- 4:47update position which is where we
- 4:50basically say if it's long position but
- 4:52the entry rule is now the opposite
- 4:54liquid the current position or vice
- 4:57versa for a short position. Again this
- 4:59is perfectly correct. It also defined
- 5:01the should cancel entry function which
- 5:03isn't really necessary in this strategy
- 5:06because we are using market order to
- 5:08open the position. If we were using a
- 5:10limit order or even a stop order, we
- 5:12would have had the question of like what
- 5:14should happen if the order didn't get
- 5:16filled and now another candle has
- 5:18closed. So, should we cancel it to maybe
- 5:21submit a new one or should we just leave
- 5:22it as it is? So, that's why we use this
- 5:25function in Jesse. But in this case,
- 5:27because we're using a market order, we
- 5:29don't need that. So, we could even
- 5:30remove the sync and it should still
- 5:32work. But I'm going to leave it be. So,
- 5:34let's go to the back testing page. Now,
- 5:36the exchange is Binance Piocial Futures.
- 5:38The route let's choose BTCUCT
- 5:41and for time frame let's use hourly and
- 5:45change this into test cloud 4.5 and for
- 5:50period could be anything really. Let's
- 5:52just pick since the beginning of 2025
- 5:55and ensure the fast mode is on and is
- 5:59the benchmarking. All right, so let's
- 6:01run the first back test. It's a perfect
- 6:04go. But actually, you know what? Because
- 6:06this was a really hard period to trade,
- 6:08just to make sure it is fun, let's
- 6:11change this into 2024. So, we could see
- 6:15some profitable results, right? I mean,
- 6:17it doesn't really matter because the
- 6:19point of this testing isn't that, but
- 6:21still, I'd like to see some positive
- 6:23results if possible. All right. So, this
- 6:25looks a lot better now. Now, it executed
- 6:2879 trades. It made 42% in profit. The
- 6:32maxon is minus almost 30%. So this is
- 6:34fairly okay. The venote is 34%. All
- 6:38right. So this is definitely a pass.
- 6:40Next question. Convert this pine script
- 6:42into Python code. Now for this next
- 6:44part, we need an actual pine script of
- 6:46trading view. Right. So let's go to it
- 6:48and look up the word super trend
- 6:52strategy. Yeah. So this one here. I
- 6:55should be able to get the pine script.
- 6:57All right. So here we go. Let's copy it.
- 6:59And now I should be able to paste the
- 7:01whole thing. Hit enter. All right. So
- 7:04let's copy the whole thing. Go back and
- 7:07paste it here. All right. So let's take
- 7:09a look at the code. So it define some
- 7:11hyperparameters. Now I don't like it
- 7:13when the models do this. Maybe I need to
- 7:15fine-tune the instructions to
- 7:17specifically tell them to avoid doing
- 7:19this because I prefer them to actually
- 7:21write the period of the indicators
- 7:22instead of trying to optimize like since
- 7:24the beginning. But anyways, it defined
- 7:26the super trend like this and this is
- 7:30the correct syntax dispassing the
- 7:32candles. The period is this which again
- 7:34is the syntax it is using for uh
- 7:36parameter optimization in Jesse. Then it
- 7:38defined the inter rule. So basically
- 7:40when the trend is one we want to go
- 7:43long. Now here's the thing though this
- 7:45isn't right because in Jesse's
- 7:46indicators with the super trend at least
- 7:48the trend value actually gives us a
- 7:51single value. So it's a scalar value
- 7:54like you know in here it will give us
- 7:58this line here and then we're going to
- 8:01know that if the current price is bigger
- 8:02than this it's an uptrend. If the
- 8:05current price is below it then it's a
- 8:06downtrend right? So it will give us
- 8:09that. It won't just give us one or minus
- 8:11one. So this syntax just won't work. So,
- 8:15actually, let's just give it a run and
- 8:18see if it runs or not because I know it
- 8:20probably won't. Okay, I think I forgot
- 8:23to save it.
- 8:24Yep. Let's run it one more time. And you
- 8:27see it didn't execute anything because
- 8:29just those rules were true. So,
- 8:31unfortunately, this is a fail. Next,
- 8:33develop a mean reversion strategy using
- 8:35the Ballinger bands and the RSI with the
- 8:37seven period. Let's copy this. Go back
- 8:41and change the code.
- 8:43Save it this time. So this is really
- 8:45important and let's run it. All right.
- 8:47So we got an error saying that the mult
- 8:50argument is incorrect. So let's go and
- 8:52see what's going on. So apparently when
- 8:54it defined the Ballinger bands, it also
- 8:56defined this which is incorrect. So
- 8:58let's remove this. By the way, let's
- 9:01also take a look at other code. So it
- 9:03defined the RSI with this syntax which
- 9:05is correct. The ATR indicator with this
- 9:08which is also correct. The shoot long is
- 9:10saying if the current price is below the
- 9:12lower band of the current Ballinger
- 9:14bands and the RSI is below 30 which is
- 9:18considering it an oversold situation and
- 9:21for shorting positions it's doing the
- 9:23opposite. It is indeed risking 2% perish
- 9:26trade using the risk to quantity utility
- 9:28function of Jesse. So this is also
- 9:30perfectly correct. And once it opens the
- 9:33position, it is submitting the stop loss
- 9:35and the track take profit using this
- 9:37syntax which passes the quantity of the
- 9:39current position and the price using the
- 9:42middle band. So this is perfect really.
- 9:45So let's just give it another run. Now
- 9:48while that's going, I want to quickly
- 9:49remind you guys about our Telegram. It's
- 9:51the fastest way to get notified about my
- 9:53future work, whether it's a new tutorial
- 9:55or a tool that I create. Also, don't
- 9:57forget to check out our free Discord
- 9:58where more than 5,000 members like you
- 10:00and I are hanging out there and helping
- 10:02out each other with algo trading so we
- 10:04can all succeed together. The links for
- 10:06both are down in the description. And
- 10:08there we go. So, it executed
- 10:09successfully. Now, the problem is it is
- 10:12executing too many trades. So, that's
- 10:14why it is losing a lot because we are
- 10:16paying a lot of money in trading fees.
- 10:18But otherwise, it just went fine and I'm
- 10:21going to give it a pass. But because it
- 10:22made one mistake, I'm going to give it a
- 10:249 out of 10. Next, write a strategy that
- 10:27uses Fibonacci retracement levels for
- 10:29entry and exit points. All right, let's
- 10:32copy the code and give it a read. All
- 10:34right, so it defined the swing high as
- 10:36this return MP.max. So the maximum value
- 10:40of the last 50 candles and then it is
- 10:43selecting the high value of every single
- 10:46one of them. So this is perfect. And
- 10:47then for swing low, it did the opposite.
- 10:50So it is using MP.min and then it is
- 10:54selecting the low value of the candles
- 10:57and then it define the fib levels with
- 10:59this syntax. So the diff equals swing
- 11:01high minus swing low and then it's
- 11:03returning a dictionary with the level
- 11:06value. So this is perfect. It's also
- 11:09very simple to read. I like it. And then
- 11:11for the trend, it's using the EMA is
- 11:14saying whether or not the current price
- 11:16is above or below the EMA to return one
- 11:19for an uptrend and minus one for a
- 11:21downtrend. So this is also great for
- 11:23shoot long. It is saying if it's not an
- 11:26uptrend return. Okay, so that's cool.
- 11:28Now assuming it is, it's saying if the
- 11:31price is near 61 or 78 Fibonacci levels,
- 11:36we want to go into a long position. So I
- 11:38love what it did here. This is really
- 11:41good. And then for a short position,
- 11:43it's doing the opposite. It defined the
- 11:45position sizing and it is submitting the
- 11:48stop loss and take profit again using
- 11:50fib levels. So this is also correct. All
- 11:54right. So I think it nailed this
- 11:55question overall. So let's go and run
- 11:58it. And it does. It's executed a fairly
- 12:01good number of trades actually. So this
- 12:03was really really good. Like one of the
- 12:05best I've ever seen. The next question
- 12:08is update my code to display the values
- 12:11of important indicators of my strategy
- 12:13in back test for debugging purposes. So
- 12:16basically we wanted to update an already
- 12:18existing strategy and we needed to show
- 12:21us some charts for it. Now there is a
- 12:23specific syntax for this in Jesse. So we
- 12:25just need the model to understand that
- 12:28syntax and use it correctly. Now to feed
- 12:30it a strategy I'm going to get it from
- 12:31our website the strategies page. So this
- 12:34one is called temo trend following. So
- 12:37let's click here and here to copy the
- 12:39code of it and paste it here. Now I'm
- 12:42going to remove these because this is
- 12:44exactly what we want the model to give
- 12:46us. So let's just remove it to make sure
- 12:48it won't cheat and hit enter and see
- 12:51what it gives us. All right, let's copy
- 12:54the whole thing, paste it here, save it.
- 12:57All right, so this is exactly what I was
- 12:58hoping it would give me. It defined the
- 13:00after function and it is using the add
- 13:02line to candle chart syntax to add the
- 13:06values of the tema indicator to the
- 13:08current candle chart which I will show
- 13:10you in a second and then it defined the
- 13:13another chart using the add extra line
- 13:15chart. So you define a new chart because
- 13:18the values for the ADX which is an
- 13:20oscillator. So it's going to be between
- 13:231 to 100 it's going to differ from the
- 13:26values of TMA indicator right. So for
- 13:28BTC this could be in like 100,000 but
- 13:31this one is going to be between 0 and
- 13:33100. So we needed another chart and it
- 13:36did the same is for CMO. So this seems
- 13:39perfectly fine. Let's just go and run
- 13:41it. Now this error we're getting is
- 13:43because the strategy is using the 4our
- 13:45time frame but we didn't define the data
- 13:48route for it in our back test. But in
- 13:50the when you run the back test with JC
- 13:52it is smart enough to take care of it
- 13:53behind the scene but it will still let
- 13:56you know about it because when you're
- 13:58live trading the same strategy you need
- 13:59to ensure those routes exist otherwise
- 14:01you will face an issue. All right so it
- 14:04went just fine but I forgot to enable
- 14:07the interactive chart so we can actually
- 14:09see those charts. So let's run it one
- 14:11more time. And now if I click here,
- 14:14here's the chart.
- 14:17And you see not only we have the
- 14:19candles, we also have the demo values
- 14:21which are these blue, green and red
- 14:24line. So we can see for example when it
- 14:26took this trade were the values
- 14:28correctly in line or not. And then we
- 14:31have the values of CMO and the ADX. It
- 14:34also define the thresholds. The same
- 14:37goes for here. So we have the long level
- 14:39and the short level for CMO and we can
- 14:41see whether or not the value of it is
- 14:42above these threshold. So this is
- 14:45perfect. So this is another 10. Next
- 14:47write a trend following strategy that
- 14:49uses 50 minutes time frame for entry and
- 14:514hour time frame for confirmation. It
- 14:53named it trend following 50 minutes.
- 14:56That is okay. Define the 4our time frame
- 14:59using the get candles method of Jesse.
- 15:02When we use this, we need to pass the
- 15:04name of the current exchange, the name
- 15:06of the current or whichever symbol we
- 15:07want and then the time frame for that it
- 15:10hardcoded four hours. So this is
- 15:12perfectly correct because when it
- 15:13defines it as a property like this, we
- 15:16are able to use it in multiple points in
- 15:18our strategy. So I really like this
- 15:20syntax. Then it defined the EMA fast,
- 15:23EMA slow, the big trend. So for big
- 15:26trend it is using the bigger time frame
- 15:29candle. So this is perfectly correct. If
- 15:32it's an uptrend, it's just returning
- 15:33one. If it's a downtrend, it returns a
- 15:36minus one. And then it define the ADX,
- 15:38the ATR, and the shoot long. So it's
- 15:42checking for the trend, the ADX, and
- 15:45whether or not the fast is bigger than
- 15:47the slow. Once the position is open, it
- 15:49is submitting the stop loss and take
- 15:51profit using the ATR indicator. So this
- 15:54might be actually a good profitable
- 15:57strategy. So let's give it a try. But
- 16:00you know what? I'm going to disable this
- 16:02interactive chart now because the back
- 16:04test will go a little bit faster when it
- 16:06is off. All right. So, this is
- 16:08profitable. It's not that bad. Of
- 16:10course, it's not beating the market
- 16:11because we didn't really work on the
- 16:12strategy, but the win rate is also
- 16:14acceptable. The sharp is also
- 16:16acceptable. So, yeah, this is perfectly
- 16:18a pass. Now, next, we're saying here's
- 16:20the code for my current trend following
- 16:22strategy in the 15 minutes time frame.
- 16:24the strategy is losing money because it
- 16:26is taking too many trades and there are
- 16:28too many false breakouts during the
- 16:30ranging markets. Please improve the
- 16:31strategy. So I'm talking about the
- 16:33strategy that we just back tested but
- 16:36you know in the period that we selected
- 16:38it isn't actually losing money but I'm
- 16:40guessing that is because in the code it
- 16:43was smart enough in the first place to
- 16:45use the ADX indicator right. So if that
- 16:47wasn't the case I believe it would have
- 16:49lost money. So, you know what? Let's
- 16:51just go back and remove that single line
- 16:53cuz I want to see if it is able to
- 16:56improve the result or not. So, let's
- 16:58just remove this one and this one. All
- 17:00right. So, no more checking for the ADX
- 17:03because it is actually the best defense
- 17:06against a ranging market. So, this is
- 17:08good. Now, let's go back and run it one
- 17:10more time. There we go. So, you see now
- 17:12it's almost losing money because it is
- 17:14taking too many trades. Now again it's
- 17:16still is losing my almost losing money
- 17:19because the result are still good. So
- 17:21anyways let's just go back and copy the
- 17:24whole code and here I'm going to paste
- 17:26it in and we're going to see what the
- 17:29obvious version is going to be. All
- 17:30right let's copy it. Actually let's read
- 17:33what it did. So it added the ADX filter
- 17:35so it only trades when the ADX is above
- 17:3725 which is what it did in the first
- 17:39place. It also added the choppiness
- 17:41index which is also another great
- 17:43indicator against a ranging market. So
- 17:46it avoids choppy or sideway markets when
- 17:48it's below 50. Yes, that is perfectly
- 17:50correct. It added the Ballinger bands
- 17:53with again a really good one because it
- 17:55measures like what's the strength of the
- 17:58current wave or or price action that we
- 18:02are in. And we want it to be above
- 18:03three. So basically when this is really
- 18:05low like below three, it's like the
- 18:07market doesn't even know where it wants
- 18:08to go. Like the changes are really
- 18:10small. It is also waiting a little bit
- 18:12between the trades to not take too many
- 18:15trades and it is exiting on a weak
- 18:18trend. So it liquidate the position when
- 18:20the ADX drops below 20. So these are
- 18:22really great. Let's go and update our
- 18:26code and re-execute it. So yeah, it
- 18:30definitely improved. So it is now taking
- 18:34124 instead of like 400 or something. It
- 18:37is also making more. The max rodon is
- 18:39lower. The win rate is also better and
- 18:43the sharp is also acceptable. But it
- 18:45isn't as good as like the first version
- 18:47that it wrote. But it doesn't matter
- 18:49because still the version that I fed the
- 18:51model I specifically asked that like
- 18:54avoid ranging markets and it added
- 18:56multiple filters to do just that. So it
- 18:59was really good. Next, develop a
- 19:02strategy that combines the Williams
- 19:03percentage R, MACD, and Ballinger bands.
- 19:06Okay, so it defined the Williams R
- 19:08percentage with this syntax, which is
- 19:10perfectly correct. Defined the MACD with
- 19:12TA MACD is also correct. The Ballinger
- 19:16bands, it named it BB, which I really
- 19:19like. Then it defined the ATR. uh for in
- 19:22rules of the strategy is saying open a
- 19:24long position if the volume's percentage
- 19:27r is below minus 80 and the maxis h
- 19:31value is bigger than zero and the
- 19:33current price is below the ballinger
- 19:35bands but it is multiplying it by 1% so
- 19:40why is it doing that all right so it
- 19:42wants to make sure we are near the lower
- 19:45band not like right next to it so this
- 19:49is interesting I don't how I feel about
- 19:51it. I It's not exactly what I asked it
- 19:54to do, but it is interesting
- 19:56nonetheless. Let's see if there's any
- 19:58explanation about this. Well, no, there
- 20:00isn't. All right, let's go and run it.
- 20:04There we go. It runs just fine. It
- 20:08didn't make any profit. The max is minus
- 20:1015. So, this is good enough and it's
- 20:13definitely a pass.
- 20:15Next, write the entry functions of the
- 20:17strategy for me in a way that it should
- 20:19use two limit orders for opening the
- 20:21position and it should only risk 2% of
- 20:24capital per trade. So, in this test,
- 20:27what I want the model to do is to just
- 20:29give me two functions. I don't want it
- 20:31to write two whole strategies because
- 20:33some models, they're good, but they
- 20:35overdo stuff like you ask them to write
- 20:38a function and they give you a hold of
- 20:39strategy and I just don't like that. So,
- 20:42let's see how this one does. There we
- 20:44go. So it actually gave me just a
- 20:46function the entry function with the
- 20:48correct syntax in Jesse. It defined two
- 20:51entry prices using ATR
- 20:55and then it defined the surplus. It does
- 20:57know the correct syntax in Jesse for
- 21:00submitting multiple entry orders which
- 21:02is you know you define a list instead of
- 21:04just giving the quantity and a price. So
- 21:07this is perfect. It gave us the short
- 21:09version of it. All right. So this is
- 21:11definitely a pass.
- 21:14And last but not least, write a pair
- 21:16trading strategy for ETH and BTC. So for
- 21:20this one, it's going to be a bit more
- 21:22complicated because it needs to write
- 21:24two strategy classes. And the way P
- 21:27trading strategy works is that one of
- 21:29them goes long while the other one goes
- 21:31short. Now, if this is confusing to you,
- 21:34watch one of my previous videos called
- 21:35Praing Strategy from Scratch in Python
- 21:38where I explain everything including the
- 21:40math behind it from scratch. All right,
- 21:43so here's the leading strategy. So,
- 21:45let's copy the name of it and go to
- 21:48Jesse and paste it in. I will name it
- 21:53cloud 45 and then whatever name it gave
- 21:56me. Let's copy the whole thing. All
- 21:58right. So you see it defined the BTC
- 22:01returns. So it's using the prices of the
- 22:03BTC prices but using the prices to
- 22:06returns utility function of Jesse. It is
- 22:08converting them into returns. It's doing
- 22:10the same thing for ETH. So yes in Jessie
- 22:12you have access to prices of other
- 22:15trading routes from one single class. So
- 22:18it's really cool. It define the Z score.
- 22:21Again if this is confusing to you just
- 22:24watch my previous video about pair
- 22:26trading if that's what you're interested
- 22:27about. But what I'm curious about is if
- 22:30it knows how to communicate between
- 22:33multiple trading strategies of Jesse.
- 22:35So, and it does because it's using the
- 22:37shared wires property which is exactly
- 22:39how you're supposed to do it. This seems
- 22:41perfectly fine. So, let's go back and
- 22:43see the following strategy which is
- 22:45supposed to be for ETH. So, for this
- 22:47one, it's define the entry and exit
- 22:50functions and in them it is simply
- 22:53reading from shared VS. So for example,
- 22:55if position is supposed to be one, we're
- 22:57going to go long on this. If it's minus
- 23:00one, we're going to go short on it. And
- 23:02then in here, if it's supposed to be
- 23:03closed and we do have a open position,
- 23:05it will just liquidate it. So this is
- 23:07perfectly great. Let's just copy the
- 23:09whole thing and create another one. So
- 23:12I'm going to name it Claude 45
- 23:15follower and paste it here. So let's go
- 23:18here and choose claude 44 BTC ETH pair.
- 23:24Let's add another one for ETH.
- 23:29Change the time frame to hourly to be
- 23:31the same as this. And then claude 4.5
- 23:36follower. Now we need to disable the
- 23:38fast mode or otherwise we'll get an
- 23:40error. Now let's just run it and see how
- 23:42it goes. There we go. So you see these
- 23:45are the prices of BTC and ETH and you
- 23:48can see they are correlated and
- 23:51configurated together which means like
- 23:54the cases where the price of ETH is
- 23:56higher than BTC. So for example if we
- 23:58were to short ETH here and long BTC like
- 24:02at this point it would have been vice
- 24:03versa. So we would have been sitting on
- 24:04a profit or in here we could have done
- 24:07the other way around. So we could have
- 24:09longed ETH and went short on BTC and
- 24:13then at this point it would have been
- 24:15the other way around. So we would have
- 24:17been sitting on a profit. So the logic
- 24:19of the strategy makes sense. But you got
- 24:21to be careful not to take too many
- 24:23trades and that's exactly what it's
- 24:24doing here. So it took way too many
- 24:26trades. It's paying way too much for
- 24:29trading fees. So in fact if we added
- 24:31this to this number here we would have
- 24:33been on a profit already. Right? But
- 24:36since trading fees are a fact of
- 24:38trading, so we just need to keep working
- 24:41on the strategy. But nonetheless, it is
- 24:44working and it is definitely a pass. So
- 24:48there you go guys, here's the final
- 24:50score. 89 out of 100. So in this
- 24:53question, it got a nine. In this one, it
- 24:56got a zero. So that's just it. And the
- 24:59result that we seeing here is beating
- 25:02Cloud 4. So it definitely had some
- 25:04improvements. But if we compare it to
- 25:06GPD5 mini that's I did a while ago. It's
- 25:10not beating that one because that one
- 25:12got 100 out of 100. So it was perfect
- 25:15score with every question. But this one
- 25:17isn't beating that. But I wouldn't say
- 25:20that GPT5 mini for example is a better
- 25:22model than this because it depends on
- 25:24what you're doing. So in oneshot
- 25:26questions like this yet GPD5 is beating
- 25:29this but when it comes to actual coding
- 25:31or debugging my experience during the
- 25:35past months has been that the cloud is
- 25:37still a better model but when it comes
- 25:39to debugging something really complex
- 25:42GP5 beats clot. So that was my
- 25:44experience. Now, this one, here's the
- 25:47result of it oneshotting the questions.
- 25:49But when it comes to like iterating over
- 25:52them, we don't know yet until we give it
- 25:55some try. But overall, it seems like a
- 25:58good model, and I'm happy that they gave
- 26:00us this upgrade. Now, I hope you enjoyed
- 26:02this video. If you did, please make sure
- 26:04to give it a like and subscribe to the
- 26:06channel for more videos like this. Thank
- 26:08you so much for watching. I'll see you
- 26:10in the next one. Now what does CL
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