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CODING TRADING AUTOMATIONS | August 7 | Michele Rossi — Transcript

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0:00Thank you.
0:01Hello and welcome back. Hello everyone.
0:04Here we go. Test test 1 2 1 2. Here we
0:08are again. Welcome back beautiful
0:10people. Today we have reached the fourth
0:13and final lesson of our series. And
0:16today we are going to answer the
0:18question that probably matters the most.
0:23And the question
0:27And the question is
0:29um
0:31can the bot
0:33that we created actually pass a prop
0:37firm challenge?
0:39Not theoretically, not because the
0:41equity curve looks good, even if it's a
0:44small test. This is educational.
0:47We are going to take the real trades
0:50generated by our strategy, give them to
0:53Codex,
0:54simulate thousands of possible challenge
0:58attempts, and calculate one estimated
1:02probability of passing phase one,
1:04passing phase two, reaching the funded
1:06account, and receiving a first payout.
1:10We already did
1:12um
1:13the Monte Carlo simulation with the data
1:16that we have. We did a bootstrap. We did
1:20the reshuffle. We did a block three,
1:22block five. We tested everything. You
1:25can go back and watch the previous
1:27videos right here on Funded Prop YouTube
1:30channel. If you're watching in Italian,
1:32it is in my channel and Funded Prop
1:34Italy channel.
1:36But yes, we did all the tests. So, we
1:39started by
1:41uh started with an idea with the orb.
1:45What is an orb?
1:47Opening range breakout. So, we define
1:51the strategy with a
1:54critical thinking and we created a list
1:57of very simple if this then that.
2:01So, it's a mechanical strategy. The
2:04entry, exit, and take profit and stop
2:06loss are pretty clear. And so, we coded
2:09it with Codex. Then we gave the the the
2:14full code to find editor. We fixed some
2:17errors. We tried some back test
2:20very quickly because it is a live. We
2:22cannot stay here hours, but you can do
2:25it on your own. This is
2:27just to show you the process and how you
2:31can
2:32actually do it yourself in a very very
2:36easy way.
2:37And then deploy it live. What I like so
2:41much is the two-step
2:44classic
2:46challenge
2:47of Funded Pro.
2:50I love it.
2:51I I mean, I trade prop since I can
2:54remember.
2:55It's been more than 15 years that I'm
2:57trading. And since the prop started, the
3:00first prop that we had around was the
3:03two-step. We had a
3:0630 days to pass phase one, 60 days to
3:09pass phase two. So, it was extremely
3:11difficult.
3:12Today, you don't have these limits. So,
3:16I'm not saying is easy, but we have
3:19better chance.
3:21And also, you have AI. I didn't have
3:24that. So, it was extremely difficult.
3:28>> [snorts]
3:28>> Uh nonetheless, I was able to do
3:32um to to bring live uh
3:35more than if I remember correctly, about
3:396 millions of funded account and nailed
3:43the props
3:46for a very long time. And that's how I
3:48constructed my
3:50That's how I built my personal that I'm
3:52trading today.
3:53Um
3:54so,
3:56what we're going to do
3:58and
4:00we're going to see today
4:03how to move from TradingView to Funded
4:06Pro. And we're going to use a simple
4:10cloud copier. So, I'm not going to show
4:13it because it's not sponsored by us, but
4:15you can just Google and
4:18write down type down TradingView to
4:21MetaTrader 5, TradingView to Trade
4:23Locker, TradingView to if you're trading
4:26futures Trade Away, whatever cTrader,
4:29everything. You can Google it and you
4:30will find different options. I'm
4:33mentioning today just one of the many,
4:36which is very famous. It's called Meta
4:38Copier.
4:39Uh before we begin, let me thanks
4:42Funded Pro once again for supporting
4:44this educational series and for allowing
4:48algorithm trading. This is huge, guys.
4:51You will find the link in the
4:52description or on screen. Use the code
4:55live to receive the best discount
4:58currently available at this very time
5:00during our live stream. And if you're
5:03rewatching the video on Funded Pro
5:05YouTube channel, you can enjoy a 20% off
5:08any funded challenge. So, straight to to
5:12to funded instant funded challenges, one
5:14step, two step, or futures. And if you
5:17want to know how to build your own
5:20trading bot from zero, super easy. You
5:23have four videos, four videos for free.
5:26I
5:27taught you how to do this. And what
5:30we're going to do next is going to be
5:32super crazy. This is the first prop firm
5:34allowing this. I'm going to deploy a bot
5:38that we created on a challenge. It
5:41doesn't matter.
5:42I mean, the objective is to deploy it
5:45and make it pass the challenge and make
5:47pay out, of course. But it doesn't
5:48matter if it does that uh because the
5:52important thing is to show you the
5:54process and how
5:57it's super
5:59not easy, but possible to do that with
6:03logic, mathematics, AI, trading goods
6:06super easy.
6:08If you want to then learn more, learn
6:11more, have a personalized guidance on
6:14how to do that, follow me on Instagram
6:16and send me a direct message.
6:18Um
6:21tell me what you'd like to trade and
6:22what would you like to automate and I
6:25will provide you with personalized
6:27learning paths based on your experience
6:29and your jet.
6:30All right, let's discover where there
6:33are bodies ready for a a challenge.
6:36>> [snorts]
6:37>> So, again, quick recap. In the first
6:39lesson that you can go back and rewatch,
6:42we discussed the complete process
6:44required to transform an idea into an
6:47automated strategy.
6:49In the second lesson, we selected the
6:51opening range breakout and we
6:52transformed the idea into uh precise
6:56rules and asked Codex to create the Pine
6:59Script code.
7:01We installed the strategy on
7:02TradingView, corrected the first
7:04problems, and generated a working
7:06backtest. In the third lesson, we
7:09optimized the strategy very quickly. We
7:12tested different
7:14uh target, different scenarios,
7:16different take profit and stop loss, uh
7:19risk reward, everything. And uh
7:23we enabled the reverse trade, compared
7:27long and short results, and we studied
7:30the day filter.
7:32Do not trade on Monday, do not trade on
7:34Thursday, do not trade during the
7:37high-impact news, for example. And we
7:40also added a little bit of commission,
7:44slippage, and
7:47um
7:50execution delay.
7:52And we added even more detailed intraday
7:55data, and the final candidate produced a
7:58the result that you can see here.
8:00So,
8:02it looked interesting. It's not a final
8:04result. It's just a small amount of
8:07trade, just 77. I highly suggest to have
8:10at least 1 year of data, so more than
8:13300 trades, 250 trades.
8:16Uh but again, we cannot stay here all
8:19day long optimizing. You will do it on
8:21your own, so we took just a small
8:23portion.
8:25Um
8:27So, this looked interesting, but the
8:31historical sequence represent only
8:35um one
8:37possible sequence of trades.
8:40If the same losses had arrived closer
8:43together, so if we reshuffle
8:47these trades,
8:49I
8:50um
8:54we might have failed the account before
8:56reaching the profit target.
8:59That is exactly what we are going to
9:01investigate today.
9:04Uh imagine that you buy a
9:07$100,000
9:09funded pro classic challenge. In this
9:12example, I need to make 10%
9:17during phase one. If I pass, I move to
9:21phase two, where I need to make another
9:245%. All right.
9:27At the same time, I cannot exceed the
9:30daily or overall drawdown limits.
9:34For the daily, I'm good because I'm only
9:37taking one trade per day,
9:39but I should not go below the 10%
9:43maximum drawdown.
9:45And what our backtest
9:48is saying is that we have a 9% drawdown,
9:51right?
9:52Um
9:53after, let's say we pass both phases,
9:56and
9:58we go
10:00to we receive the funded account, then I
10:02need to survive long enough and generate
10:07sufficient profit to become eligible for
10:10a payout.
10:11So, looking at our 25%
10:16historical return,
10:18we might think perfect. The strategy
10:20made more than 10%, so it would have
10:23passed.
10:24But it is not
10:26as simple.
10:27The backtest also experienced it a
10:30drawdown of approximately 9%, and the
10:33maximum permitted overall drawdown is in
10:36our example 10%. So, the historical
10:40result came quite close to the limit.
10:43If the trades had arrived in a slightly
10:45different order, the account might have
10:48failed before reaching the target.
10:51The question is therefore
10:53not this did this particular backtest
10:56finish in profit. The better question is
10:59if we replay it statistically similar
11:03trading histories 1,000 times,
11:08if we reshuffle them, how many times
11:11would the strategy pass?
11:14That is much more useful.
11:17So,
11:19we go to the strategy tester on
11:21TradingView, what we do. From here, we
11:25export, once again,
11:27the complete list of trades as a CSV
11:30file,
11:32And this is important because Codex
11:35needs the individual wins and losses,
11:38not only the final performance
11:40screenshot.
11:43I will also provide a screenshot showing
11:45the strategy results, the input, the
11:47TradingView properties containing
11:49commission, slippage, order delay, and
11:51position size. And finally, I will
11:54provide the exact FunderPro rules I want
11:58to simulate.
12:00FunderPro, please do not ban this
12:03content because this is pure gold.
12:08Um I'm not going to ask Codex to search
12:13for the rules or guess them. I copied
12:16them directly from the challenge page or
12:21my uh FunderPro dashboard.
12:24For this demonstration, I'm using an
12:27example of 100,000 classic challenge
12:30with two phases. Phase one has a as we
12:33said, 10% target. Phase two has a 5%
12:37target. The daily drawdown is 5%. The
12:39maximum overall drawdown is 10%. There
12:42are at least four trading days in each
12:45phase. The duration is unlimited and
12:49there is no consistency rule. On the
12:51Funder account, I will use an uh an 80%
12:56profit split and a bi-weekly reward
12:59cycle for the example. Before running
13:02your own simulation, always replace
13:05these values with the exact rules shown
13:09for your account, assuming that
13:13let's say you're using a one-phase or an
13:15instant or a futures or whatever, okay?
13:21Now, we're ready to ask Codex the main
13:25question. This is the most important
13:28prompt of the lesson.
13:30So, I'm going to send it once. Codex
13:33will audit the data, run the simulation,
13:36compare several risk levels, and prepare
13:39a simple report, right? So, we just
13:42downloaded the CSV file. We're going to
13:45take a couple of screenshots right here.
13:54Put it on our desktop. One.
13:59Two.
14:02More information, better data.
14:07Better answer, sorry.
14:10All right.
14:12Returns.
14:15We're going to have these.
14:17Then, we want to give, once again,
14:20the settings that we used.
14:24>> [snorts]
14:34>> All the settings.
14:36All right.
14:42Let me close these.
14:44Let me pick up
14:46Codex.
14:57All right.
15:02There it is, our Codex.
15:12Let's give it all the data.
15:14All the screens that we took.
15:21And
15:22the exported
15:27version.
15:29The exported CSV file.
15:32This guy right here. With all the
15:34trades.
15:36There it is.
15:37Then we're going to give Code X
15:40this XR prompt. Let me copy and paste. I
15:44prepared it.
15:46Just need to find it.
15:53Where is it?
15:55There it is.
16:19There it goes.
16:21Here it is. So,
16:26this is the the prompt. It's it's huge.
16:29I'm going to read it very quickly.
16:31So,
16:33uh
16:34let me let me open up the the text file
16:37so you can see.
16:39Let me put it on on overlay
16:42on the screen
16:43while he's running.
16:46All right.
16:47So, this is the prompt.
16:51I'm providing a TradingView CSV
16:54containing
16:56every trade generated by my validated
17:00orb strategy. Screenshot of the
17:02TradingView performance, trade strategy
17:04input and execution properties, the
17:07exact rules of the prop firm challenge I
17:09want to simulate.
17:11Start by auditing the CSV. Confirm the
17:13number of complete trades, the test
17:15period, the profit and loss column,
17:17whether commissions are already included
17:20in whether each row represent a complete
17:22trade or only part of a trade. Reconcile
17:25the CSP total with the TradingView
17:27screenshot. Do not invent missing data.
17:30Then simulate a complete 100,000 funded
17:33Pro Classic two-phase process using
17:35these example rules. Phase one profit
17:3810, phase two five, maximum drawdown
17:40five, maximum overall drawdown 10,
17:42minimum trading day per phase four,
17:44duration unlimited, consistency rule
17:46none, split 80%. First payout after 14
17:50days minimum, reward request $100. Treat
17:54the result the rules I provide
17:55separately from the trading data so I
17:57can easily replace them later.
18:00Run at least 1,000 complete simulations
18:03for each of these risk levels. 0.5 risk,
18:070.50, 0.75, 1% per over sampling. If
18:12multiple trades occurred on the same
18:14day, which is not the case for our
18:16strategy, keep them together and in
18:18their own original order. Use block
18:22bootstrap sampling of trading days so
18:24that winning and losing streaks are not
18:26completely destroyed by random
18:29reshuffling. Every simulation must begin
18:32at the start of phase one. If phase one
18:34reaches target without violating a rule,
18:37reset balance and continue to phase two.
18:39If phase two passes, reset the balance
18:42and continue into the funded account. On
18:45the funded account, simulate the first
18:4714 days reward period and calculate
18:49whether the account survives and becomes
18:51eligible for a payout.
18:54For every risk level report, probability
18:57of passing phase one, passing phase two,
19:00uh passing both phase, violating the
19:03daily drawdown, violating the overall
19:05drawdown,
19:06uh median number of trade and trading
19:08days required for each phase, surviving
19:10the first funded reward period,
19:12receiving first payout.
19:14Median gross profit at the profit at the
19:16first payout, median trader payout after
19:19the 80% split and the fifth 50th and 95%
19:25outcomes. Also calculate the expected
19:28economic result after accounting for the
19:30challenge fee that I provide.
19:33Clearly distinguish probability of
19:35passing phase one, conditional
19:37probability of passing phase two,
19:39overall probability of reaching the
19:41funded account and probability of
19:43receiving a payout after the starting
19:45phase one. If the CSV does not contain
19:49enough intraday equity information to
19:51model the daily drawdown exactly, state
19:53the limitation and create standard
19:56estimate, conservative estimate. Do not
19:59describe these figures as guaranteed
20:01futures probability. Disclaimer is
20:04always explain that they are conditional
20:06estimates based on the historical trades
20:09distribution.
20:11Finish by recommending the risk level
20:15that creates the best balance between
20:18probability of passing,
20:21time required, account failure
20:24probability and expected first payout.
20:29Create then a clear summary table and
20:32simple charts that I can show during uh
20:36YouTube live, which is what we're doing
20:39right now.
20:43So, this is the prompt.
20:47Let's see. He's thinking.
20:51He's
20:53counting.
20:55He's running the numbers.
20:58Job place.
21:04So,
21:06um
21:07this might sound a little bit complex.
21:13Let me
21:15explain
21:17what it is happening in a very simple
21:19terms. So, we gave it our historical
21:23trades from
21:24from the list
21:27right here.
21:29Right? We exported the list.
21:34Let me move these out of the way. We
21:36exported the the full list of trades.
21:39Then,
21:40um
21:41imagine those trades
21:43are cards in a deck.
21:47Okay? Some are winners, some are losers.
21:52Okay? Let me clean up
21:54this.
21:56Some are winners, some are losers.
22:00Um
22:02Someday
22:04contain only the first trade, while
22:06other days also contain a reverse trade.
22:11So, Codex is going to create a new
22:14possible journey by sampling complete
22:17trading days from that historical
22:21evidence.
22:23It then starts with
22:25a new 100,000 phase one account.
22:29Trade after trade, the account moves up
22:31or down. If it reaches
22:34the
22:35the 10% needed to pass phase one,
22:40so let's say it goes like this.
22:42Win, loss, win, loss, win, win, loss,
22:45loss, win, loss, win, win, win, win,
22:49loss, loss, win, loss, loss, win, win,
22:52and we reach the 10% needed to pass the
22:55phase one
22:57before violating a drawdown rule.
22:59Phase one passed. Codex then start phase
23:02two and repeat the process with a 5%
23:06target.
23:07Win, loss, loss, win, win, loss, loss,
23:10win, loss, win, win, win, win, loss,
23:14win, loss, win, win.
23:165% reached.
23:18Got a bit of of a drawdown. We didn't
23:22cross the 5% maximum draw the the 10%,
23:26sorry. The 10% maximum drawdown, right?
23:29And we see the 5%. Phase two,
23:33the process is repeated and the phase
23:36two is passed. If phase two also passes,
23:40the simulation continues on the funded
23:43account until the first possible reward
23:46period.
23:48Then Codex starts again from the
23:50beginning
23:51and it start to
23:55uh
23:55repeat the experiment at least 1,000
23:59times
24:00over and over 1,000 times.
24:05By
24:06mixing up all these things, adding some
24:09slippage, adding some
24:11randomness.
24:14And at the end
24:16we can see how many simulated accounts
24:19passed, how many failed, how long they
24:22took, and what happened after funding.
24:28It's still thinking, right? Still
24:30thinking.
24:32Um
24:35It is like sending 1,000 version of our
24:38bot into 1,000 possible challenge
24:41journeys.
24:43And
24:45the most interesting part is that we can
24:48repeat the entire experiment with
24:51different risk levels, different
24:53strategies, different
24:56type
24:58of challenges instant funded futures,
25:02right?
25:03Um
25:06So, let's say at 1% risk per trade, the
25:09strategy can reach the target more
25:10quickly, but the losses also become
25:13larger. This mean we may see a higher
25:16number of fast passes and a higher
25:19number of failed account.
25:21At 0.25%
25:24risk per trade, the account is much
25:26safer, but reaching 10% can require
25:29many, many, many more trades because the
25:32challenge duration is unlimited. In this
25:34example, slower is not necessarily a
25:38problem.
25:39Uh so, the best settings is not
25:42automatically the one that create the
25:44highest historical profit. For a prop
25:47firm challenge, the most useful settings
25:49may be the one that gives us uh the
25:52highest probability of sur- viving both
25:55phases and reaching a payout.
25:59So, this is a very a completely
26:02different optimization target because
26:04we're no longer asking, "How can I make
26:08the largest possible return?" We are
26:10asking, "How
26:12can I
26:15reach the target without touching the
26:18failure limits?"
26:20Right?
26:21And this is very, very important to
26:24understand.
26:26Um
26:27I have my own
26:29community with thousands of traders
26:31inside and what I'm teaching today
26:34is
26:36actually
26:38how to understand the market, how what
26:42what are your
26:44um
26:45weapons to understand
26:48why and how market moves.
26:52And I start from a simple four pillars,
26:56which is called fist, f i s t, which is
26:59my method. Fundament- I didn't invented
27:02it, but I just put together some stuff.
27:05Fundamentals, so
27:07geopolitical and economic data.
27:10Intermarket, how markets are
27:12interconnected.
27:14Sentiment, are we fearful? Are we
27:17greedy?
27:18And then technicals.
27:20Right? Once we understand these, we move
27:24to the next level. We pick up a simple
27:27yet
27:29usable and good and profitable, let's
27:33say, strategy, and we start to
27:36adapt this method. And when every single
27:42pillar, the fist, is aligned, let's say,
27:45everything is pointing upwards.
27:48Fundamental says that that is good. Uh
27:51intermarket says Nasdaq is going to go
27:54is is good to go up. Sentiment is
27:57greedy, so the Nasdaq going to go up.
27:59Technical, we have the orb having a
28:01breakout above the range, we're going to
28:04go up, we're going to go buy.
28:06This doesn't mean we're going to win,
28:07but we have a higher
28:10chance, higher probability
28:13that
28:14we're doing
28:16and we're approaching the market in a
28:18very logical and reasonable way.
28:22And when something is logical, it's
28:24reasonable, and of course we can back
28:27test this manually, but I do prefer
28:31automatic, and we're going to go to that
28:32in a second, because this is the core of
28:34this lesson.
28:36You can
28:38follow on that every single day. Every
28:40day you can repeat the process because
28:44it's been 20 years
28:46since I started investing. I'm 39 years
28:49old.
28:50So, I started when I was
28:5219, I guess.
28:55And about 15 years that I'm trading.
28:59I've been trading the market.
29:02Um
29:04So, I would say a lot of experience.
29:08A lot of time in the market, and here we
29:10have the results.
29:11Um
29:17So, what you want to do is to find
29:20a repeatable process
29:23that is logical, that makes sense, that
29:26you can repeat time over time over time
29:29over time. Because staying in the market
29:32as long as possible is your best chance
29:36to
29:37be profitable into the long term.
29:40Prop firm are the best leverage and
29:43chance that you have today to create
29:45your own capital.
29:47What you do on prop firm is not the same
29:50that you want to do on your private
29:52account, personal account. I do treat
29:54them completely different ways.
29:58And remember that I I like to use this
30:04um this
30:07I don't know how to say it in English.
30:09This
30:11figure. Okay, let's let's let's try to
30:13figure this out.
30:16Y- If you are trading the real market,
30:20the live market, you're trading actually
30:24in a field with the best
30:27and most powerful
30:30fast, intelligent, smart algorithm,
30:34institution, and minds
30:37from all over the world.
30:39And
30:40trading is a zero-sum game. So, one is
30:44winning, the other is losing.
30:48In a prop firm,
30:50you're not competing against them.
30:56Right? You're not in the market.
31:00In the real market. It's like the
31:03question that I ask myself is, can I
31:06beat
31:08I don't like and I don't understand
31:10soccer, but I know Cristiano Ronaldo is
31:13one of the top player.
31:16Can I beat Cristiano Ronaldo
31:19in a soccer game?
31:21I cannot,
31:22definitely.
31:24Can I beat Cristiano Ronaldo playing the
31:27PlayStation?
31:30I have higher chance,
31:32even if I'm not good even at the
31:34PlayStation.
31:36But, you're playing in a simulated
31:39environment.
31:41Let's say,
31:43you're opening just for fun, it's not
31:45possible, but let's say in a prop firm
31:47account of $10 million, it does not
31:50exist, you open
31:5210,000 lots or 10,000 contracts.
31:56The market is not going to react because
31:59you're not placing the trades inside the
32:01real market, right? Hope this makes
32:04sense.
32:05So,
32:06completed the audit on an 80,000 total
32:11simulations. The CSV contains 77
32:14complete trade across 57 trading days,
32:17net profit 25 and 1,000 commission
32:20reconcile exactly with TradingView.
32:22Commissions are already included. The
32:24provisional recommendation is 0.75%
32:28risk. Conservative estimate, pass both
32:31phases 99%.
32:34Overall drawdown violation 0.18%.
32:38first payout from phase one 71.94%
32:42medium phase one two duration 55 25
32:47trading days medium trader payout when
32:50eligible 1,768.
32:54These estimates are probably optimistic
32:57because only 77 historical trades are
33:00available and bootstrapping
33:03cannot model a new market regime.
33:06We said this from the beginning. This is
33:08just to understand the process. The
33:11challenge fees was not provided so I
33:14forgot to give the the challenge fees.
33:15So the report gives the economic formula
33:18and break even fee instead of inventing
33:20one. Um conservative founder per
33:24simulation 10,000 paths per risk
33:26challenge and payout probability.
33:28So
33:29with a 0.5
33:32percent
33:34risk on each trade
33:38we have
33:40um
33:42we have a very high chance.
33:45It says
33:47um
33:49first payout from phase one 71.94.
33:52Let's let's give it some
33:56worse scenario. Let's say we have more
33:59numbers and let's put it down let's say
34:0265 68%.
34:05It's
34:06it's a very good number to me.
34:10Because what I'm going to do is I'm
34:12going to differentiate.
34:14Maybe I find
34:16I found this strategy I can find
34:19another strategy
34:21another variation. Let's say this I'm
34:24running I don't even remember on Nasdaq
34:27uh in the afternoon I can run the same
34:30strategy on the DAX
34:33in the morning.
34:34I can then find
34:37a different strategy or again, the same
34:39strategy with running on gold in the
34:43afternoon. And then another one running
34:45on the S&P 500 in the morning. I don't
34:48know. I'm just in the in the night
34:50during the night during the power hour.
34:53Right? Then I have four prop account
34:55with four different
34:58strategies with all these numbers and I
35:01do have a realistic
35:04the most realistic possible
35:06possible outcome
35:10validated
35:11with
35:12mathematic
35:14and probability statistics.
35:17Right?
35:19Um
35:21These are the numbers that matter
35:23because the probability
35:27is everything
35:30that you want to know
35:33when you approach a
35:37challenge when you approach a prop
35:39account.
35:40Right?
35:42Um
35:45Let Let's give it another another
35:47example. Let's Let Let's imagine that
35:51um
35:53Let's imagine that Codex tells us that
35:56we have a not a 71.94
35:59but a 50% probability of passing both
36:02phases.
36:04Now, sorry. Both phases he says 90 99.
36:07Let's say 50%. Does that mean the
36:10strategy is bad?
36:13No. Not necessarily. It means that under
36:16the assumptions of our model
36:19approximately half of the simulated
36:22challenge journeys reached the funded
36:25account before violating a rule. It also
36:28means that buying one challenge does not
36:30guarantee success. Even a strategy with
36:33an edge can begin with an unfavorable
36:36set sequence.
36:38Um
36:39This analysis can help us compare
36:43different risk levels without changing
36:46the strategy itself. Maybe 1% risk gives
36:50us 38% probability of reaching the
36:52funded account. Maybe 0.5%
36:56um increases the probability to 55%. In
37:00that case, reducing the risk makes the
37:03process slower, but improves the chance
37:06of survival.
37:09So
37:12that information is more valuable than
37:15simply saying
37:17my backtest made 18% so I should pass.
37:22We now have an estimate of the journey,
37:25not only the destination.
37:29So
37:33what do I do once Codex identifies the
37:36most reasonable risk levels that we set
37:390.75? I return to TradingView.
37:43I enter that risk value into the
37:46strategy panel.
37:48Right here.
37:50I assume this not
37:52Okay, this also on MNQ. I we don't
37:55we we just need to say we have a
37:57$100,000 account. We're going to risk
37:590.75%
38:01per trade. This is not the calculation
38:04model. This is just for sending the
38:07signals
38:09to the master copier that going to
38:11replicate the the trades into our
38:16um prop account.
38:18Right?
38:24So before
38:27before
38:29we
38:31we are going
38:33before we are going to deploy
38:36the actual strategy into
38:41um
38:44into our
38:47challenge account
38:49we want to
38:51forward test the strategy
38:55inside a demo account.
38:57So, get a demo account, we connect the
39:00strategy with alerts, we add an alert
39:04with the orb.
39:05We included everything, function call,
39:08alerts only, and we're going to call it
39:12whatever, orb X funder pro demo
39:18forward
39:20test.
39:21We're going to use
39:22the we're going to create the webhook
39:26with Meta Copier. This is what I use,
39:29but you can find your own. There are
39:32thousands of available.
39:34Where do you set up your your account?
39:36So, just a minute to to make it simple
39:39for you to get for you guys to
39:40understand, you have TradingView right
39:43here.
39:45Sorry, let me do this.
39:46Going to be much easier.
39:48You have TradingView right here,
39:51TradingView.
39:53TradingView is going to send a buy.
39:57Right? With a fixed take profit
40:01and stop loss. Okay? Then, it's going to
40:04go to the cloud copier.
40:14The cloud copier
40:16is where you want to put your account
40:20password and login.
40:22Let's say you have MT5,
40:24right? You're going to put your MT5
40:27login and password, and the cloud is
40:29going to send and replicate the same
40:32exact trades in your
40:35actual Funder Pro
40:39MT5
40:41account.
40:43Right?
40:44So, we want to test this, and we want to
40:46test it on a first of all on a demo
40:50account for two reason. One,
40:54we want to be sure the connection works
40:57as we intended.
40:59And the second
41:00is
41:03demo.
41:04Demo. And the second is we want to
41:07forward test.
41:10Means that we want to run this strategy
41:13for, let's say, 1 week, couple of weeks,
41:16and we want to see that the results
41:18aligns with what we had
41:22in our back test.
41:24So, we can collect the actual real
41:26trades taken on a demo account, on a
41:28paper trading account,
41:30give them back to Codex and say, "Hey
41:33dude,
41:34I got this trade on the on a forward
41:37test.
41:39Do you see similarities or are we doing
41:42something completely different?"
41:45If it says, "You're good to go, man."
41:48Then you can connect the account to the
41:51actual
41:53uh
41:53MT5
41:55of Funder Pro,
41:57right? And begin your journey.
42:00Funder Pro.
42:03Okay?
42:05So, this is basically it.
42:09Um
42:12Let me just clarify
42:16um
42:17one important thing.
42:20So,
42:21about this area right here.
42:25If Codex estimates a 50 60 70%
42:29probability of passing, that is not a
42:32promise.
42:33The estimate is based on the historical
42:36trades we supply.
42:39Future market conditions can be totally
42:42different. Slippage can be worse. The
42:45strategy can enter a market regime that
42:48was not represented in our sample. The
42:51simulation does not see the future,
42:54okay? It helps us make a more informed
42:58decision using the evidence we currently
43:01have. Imagine
43:03since yesterday you were going to your
43:07favorite gurus
43:09and he tells you, "Oh, when you see a
43:11drop, then you find a liquidity sweep,
43:15then you find a a fair value gap, retest
43:17of the fair value gap, put your stop
43:19loss right here, and put your big profit
43:21right there. Yo, put the dubs in the
43:22chat." Right.
43:26Okay.
43:27I do that.
43:29I like to trade like this way.
43:31It's a lot of fun.
43:35But
43:36I code. I also code all the strategy.
43:40All my strategy that I use and that I
43:42teach are coded, are validated. You can
43:48back test them.
43:50All of them.
43:52And you can automate them.
43:54Right? So,
43:56can you explain the question when you go
43:59to your next favorite guru?
44:02Ask a question to yourself and then to
44:04him and see if you get kicked out from
44:07the server or whatever.
44:10Can you
44:12teach
44:14the strategy?
44:20I believe the answer is going to be yes.
44:24Next question is going to be
44:27for yourself.
44:30The strategy
44:32is
44:34Can I enunciate the strategy? Can I
44:38create a list of if these then that or
44:42is just So, this is the strategy, but
44:45then comes to the comes to the
44:48experience. Then if these then that, if
44:51these then that, but then you have to
44:54feel it in your gut. That That is not a
44:58strategy.
45:00That is not codable.
45:03The butterfly in your chest, in your
45:05stomach is not
45:08Do you want to base and put your money
45:11in the feeling in your gut?
45:14I don't think so. I don't want to.
45:17But if the strategy
45:19is
45:20is explainable,
45:24okay, then it's you can code it. And if
45:28you can code it, then that The next
45:30question to ask your favorite guru is
45:34why you're not selling me and helping me
45:38or helping me to develop
45:41a
45:43fully workable bot?
45:47Maybe they're selling you a TradingView
45:50indicator
45:52that does not automatically backtest the
45:55strategy. They're selling you an
45:58indicator. They have this
46:00>> [snorts]
46:01>> great new idea
46:03to make money for them.
46:05Why not to if you can code a an
46:08indicator, you can code a bot. If you
46:11can code a bot, you can backtest a bot.
46:14So, you don't have to pass hours and
46:16hours and hours going back with the
46:19replay mode and write it down every
46:22trade you take and then you you're not
46:24sure you did it correctly. Maybe you
46:26fake yourself by because you know how
46:29the price is going to react. Maybe
46:30you're saying, "Yeah, maybe I'm going to
46:31close this here because I see a candle
46:34and blah blah blah." You already passed
46:36through the space. If you didn't, you
46:38will.
46:39Um so,
46:43take care.
46:44Be careful.
46:46Understand this.
46:49Okay?
46:51Uh
46:58That is
46:59what we did is far better than
47:04buying a challenge because
47:06one equity curve looks attractive or
47:09just because you started studying with
47:11your next guru.
47:13Because this way, we know
47:17approximately
47:19how sensitive the strategy is to risk,
47:22how frequently it may fail, how long
47:26passing may take, and what kind of
47:28payout outcome is plausible.
47:32Okay?
47:33Right. So, this bring us to the end.
47:35Across these four lessons, we begin with
47:37nothing more than idea. We transform
47:40that idea into precise rules. We ask
47:42Codex to create the strategy. We tested
47:45it on TradingView. We optimized the
47:47parameters without changing everything
47:49randomly.
47:51Um
47:52what we did? We We included realistic
47:54execution costs. We exported and
47:56validated the trades. Then today we
47:59transformed the validated results into a
48:02practical prop firm plan.
48:04We calculated the estimated probability
48:07of passing
48:09phase one, phase two, the overall
48:12probability of reaching a funded
48:14account, and the probability of
48:16receiving a first payout.
48:18Finally, we prepared the connection
48:21between TradingView with the alerts and
48:25Funded Pro account through a cloud copy.
48:28That is the complete journey
48:30from an idea to a bot, from a bot to
48:35evidence. We're going to see it.
48:37Because I'm going to run this this very
48:40same strategy. I'm I might probably give
48:43it a little more of of test. And I'm
48:46going to deploy it on a Funded Pro
48:48two-phase
48:50challenge. And I'm going to show you
48:52guys next week how it's going.
48:56Right? Once again, thank you to Funded
48:58Pro for supporting these live sessions
49:00and for allowing algorithm trading. You
49:03will find the Funded Pro link in the
49:04description on the screen or down below.
49:07Use the code live to receive the best
49:09discount currently available. It's 20%
49:12and if you want to learn how to develop
49:14your own trading bot from zero, follow
49:17me on Instagram michelerossi_official
49:20and send me a direct message. Tell me
49:22your experience level, the market you
49:25trade, the platform you use, and the
49:26idea you want to automate. I provide
49:29personalized learning paths to help you
49:32move from your first concept to a tested
49:36and deployable trading system. If you
49:38enjoyed this series, subscribe to to the
49:41channel and leave a comment down below
49:43and tell me something.
49:45Now,
49:46would you buy the challenge if the
49:48simulation give you
49:50a 50% probability of reaching the funded
49:53account or would you continue improving
49:56the strategy? I'm
49:58genuinely curious to read your answer.
50:02Thank you for being here. Test
50:04everything, control your risk, and I
50:05will see you in the next video. Bye.

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