Transcription
In this video, I'm going to show you exactly how to build your own crypto trading bot in Python without writing a single line of code. Most traders already have strategies they believe in, but struggle to turn them into something that actually trades for them. I'll also show you how to find proven working strategies completely for free, and then how to turn them into a live automated trading bot using a powerful custom GPT. And yes, by the end of this video, I'll share the exact prompt that makes it all happen. So, make sure you watch till the end.
Here's what we're going to cover in this tutorial. How to find ready-to-use profitable strategies online completely free. How to take that strategy and give it to ChatGpt to convert into real Python code automatically. How to run the bot on your system, connect it to your exchange and watch it trade live.
Now, here's how the whole process looks in simple terms. You take a strategy from somewhere and then you give it to ChatGpt in one click. It converts that strategy into a fully automated trading bot written in Python. You then take that bot, plug in your exchange details and run it. That's it. No coding, no debugging, no confusing setup. Just copy, paste, and trade.
All right, now let's talk about where we actually get these strategies from because this is the foundation of the whole process. You can't build a good bot without a good strategy behind it. The code and automation part might sound fancy, but remember the bot can only follow the logic you feed it. So before we even start, let's understand where most traders in the world test and share their ideas.
The website we are going to look into is Trading View. If you've never used it before, Trading View is basically the YouTube of trading strategies. People from all around the world share indicators, scripts, and complete strategies written in something called Pine Script. It's the scripting language built right into Trading View. Now, here's the beautiful part. A huge number of those scripts are completely free and open-source, which means you can see how they work, copy their code, and even modify it if you want.
Let's go step by step so you can follow along with me. First, open tradingview.com and log in to your account. The free plan works fine for this. Once you're on the homepage, go to the top panel and click on community. This is where the gold lives. It's basically a huge public library of indicators and strategies shared by traders and developers over the years.
Now, within this community section, you'll see a few options. We are interested in indicators and strategies. We're interested in the strategies section because those are complete trading systems. They already contain buy and sell conditions, stop losses, take profits, and everything that a bot needs to trade automatically. Scroll through the list and you'll notice every strategy has a title, a short description, and the author's name.
Now, this is the part where you'll actually have to spend a bit of time. And I can't stress this enough. See, building the bot itself is the easy part. the coding, the automation, all of that will literally take less than a minute, as you'll see later in the video. But finding the right strategy here, that's where your success really comes from. You need to look for a strategy that fits your trading style, one that looks logical and performs well on the chart.
Take your time scrolling through different options. Test them visually. See how often they trade, how consistent they look. This part might take you an hour or even more, but trust me, the more time you spend here choosing a strong open-source strategy, the better your results will be once the bot goes live. So, take this step seriously. Don't just pick the first shiny one with lots of arrows or a fancy name. Go for something that actually makes sense to you because the coding will be done in seconds. But a good strategy is what makes that code profitable.
Now, I'm going to select this strategy for the sake of this video, but trust me, I don't take this step lightly. I spend a lot of time here because this is where most of the real work happens. I actually have a working strategy that took me over a month to build and fine-tune, but for this tutorial, we'll use one that's publicly available, so you can follow along easily. The one I'm choosing is called Deepseek Multi-time Frame EMA Strategy by Benjamin. You can see its preview card here. It shows a sample chart, the title, a short description, and details like how long ago it was published, how many likes or comments it has, and the author's name. These little details are helpful because they give you a quick sense of how active or reliable the script might be.
Once you find one that looks interesting, click on it to open its full page. Inside the page, you'll notice at the top that it's marked as an open-source script. That's really important because it means you can see and use the code freely. Below the title, you'll find three main tabs: chart, strategy report, and source code. The chart tab lets you see how the strategy performs visually. The report gives you statistics and back testing data. And the source code tab is where we'll eventually copy the logic from.
When you're on the chart view, you'll see the strategy plotted directly on a Bitcoin 1-hour chart from Binance. You can see the purple line here. That's the higher time frame EMA acting as a trend filter. Then there are orange or smaller EMAs that work as the faster signals. The green triangles represent long entries, while the red ones indicate exits or short positions. Labels like close entry order long show exactly where positions were closed. This gives you a quick visual idea of how the strategy behaves before you even look at the code.
If you scroll down a bit, you'll see the full strategy description written by the creator. It explains that the idea is based on aligning two different EMAs across multiple time frames. A slower one on a higher time frame, which is one day that defines the trend, and a faster one on the lower time frame, that's 1 hour, for entry and exit triggers. It even lists all the trading conditions. For example, it only goes long when the fast EMA is above the slow one and price crosses above it, confirming the trend.
Further down, you'll find the key features and configuration. This section shows the parameters the author used for testing, like an initial capital of $1,000, 100% equity per trade, no pyramiding, which means only one position at a time can be opened, and a small 0.1% commission for realism. It also mentions how orders are executed at the close of each 1-hour candle and explains how the visualization is done with color-coded EMA and entry exit markers. At the very bottom, the summary explains the logic in plain language. The strategy tries to buy the dip within a broader uptrend by waiting for the higher time frame to confirm a bullish move, then entering when the faster EMA catches a short-term pullback. It exits when that short-term trend weakens. In short, it's a clean and logical trend following system.
Once you've reviewed everything and you're happy with how it looks, go up to the top and click the source code button. This opens the full Pine script code in the Trading View editor. Simply click on this icon, which will copy the entire code.
Now that we've got our strategy fully reviewed and copied, we're ready for the next big step, turning it into an actual Python trading bot. Well, we're going to give this Pinecript code to ChatGpt. But here's the thing. ChatGpt doesn't automatically know what to do with it. If you just paste the code as is, it'll stare at it like, "Okay, what now?" That's where the template prompt comes in. I've already prepared one for you. And this single prompt basically does all the heavy lifting. It tells chat GPT exactly who it needs to be, what role to take, how to read the strategy, and what kind of output to produce. Think of it as the brain behind the conversion. It's the set of instructions that makes Chat GPT behave like a professional quant engineer who builds real trading bots.
Here's what's inside the prompt. It starts by defining a clear role for chat GPT. It tells it to act as a senior quant engineer and code generator. That means the chat GPT will think and work like a professional developer who builds live trading bots for a living. CCXT, by the way, is the library that acts as the bridge between your bot and the exchanges. It's what allows your code to fetch live prices, place and manage orders, handle stop-losses, and basically trade for you on platforms like Binance, Buybit, Coin, OKX, and Bitjet.
After that, the prompt sets some very specific rules. And this is exactly why it works so reliably. It tells chat GPT to focus on live trading only, meaning no test net, no paper trading, no sandbox environments. We're going straight to live execution. It also limits the bot to futures contracts only. So it won't touch spot trading. Then it instructs chat GPT to replicate your Pine script strategy exactly as it is using Python libraries like pandas and numpy to calculate the same signals, entries, and exits. And finally, it defines how the final bot should be structured. Everything should be built cleanly into just three files. Config.py, bot.py, and main.py. Each file has its own role. The config for your settings and API keys, the bot file for all the trading logic, and the main file to run it.
So, in short, this part of the template makes sure that the output you get isn't just random code. It's a professional, modular, and fully functional live trading bot that's ready to use right away. That means when chat GPT generates your bot, it will always give you a clean, professional looking project. Something that actually feels like a real trading system, not a messy script. You'll see all the right parts in place. A configuration file where you control your settings, a main logic file that handles your signals and trades, and a runner file that ties it all together. It's structured, modular, and easy to work with. exactly how a proper trading bot should look.
Now, the prompt also includes something called the user input section. And this is where you'll actually paste your strategy code and set your exchange. You'll see two markers in the template, and that's where your Pine script goes. Just paste it right in between those lines. And then at the bottom where it says exchange, Binance, simply replace Binance with whatever exchange you're using, maybe Bybit, OKX, or Coin. And that's it. You don't have to edit anything else. As long as your strategy is between the markers and your exchange is correctly mentioned, the prompt knows exactly what to do.
What you have now is your ready prompt template, a complete blueprint for your trading bot. It already contains all the rules, logic, and structure for how the bot should behave once it's converted into Python code. Every line inside it serves a specific purpose. It defines the role chat GPT will take, what kind of output to generate, which files to include, and even how the bot should operate once it's live. The best part, you can reuse this template again and again for any strategy you like.
All right, so now you've got your strategy pasted in, your exchange selected, and your full prompt template ready to go. What's next? Now it's time to give the prompt to chat GPT. But here's the thing. If you just paste this into the regular chat GPT, it won't give you the same results that I get. It might still generate some code, but it won't be the clean, fully working production-ready bot that you actually need. You'll probably end up spending hours fixing small errors, missing imports, broken logic, or exchange API issues that just don't make sense. Or worse, it might start asking you a bunch of technical questions that you probably have no idea how to answer. That's because the normal chat GPT isn't built for this kind of thing. It doesn't really understand the technical side of trading. It doesn't know how futures markets work. It doesn't properly handle exchange APIs, and it has no idea how to structure a live trading bot the way a real system should be built. So, even though it looks like it's doing the job, it keeps making tiny mistakes that add up quickly.
That's why we're going to use something far more powerful. A custom GPT that's been specifically trained for this exact task. This GPT already knows what to do. It understands what CCXT is, how to structure the bot files, and how to generate proper trading logic that perfectly matches your Pinescript strategy. The one we'll be using is called Pinescript to Python, and it's built by Tom Payne. It's a relatively new custom GPT made exactly for what we're trying to do. Taking any Trading View strategy and turning it into a complete live production-ready Python bot. And since it's still new in the market, not a lot of people know about it yet, which means it's still super affordable.
To find it, open Chat GPT. On the left-hand side, you'll see an option called Explore GPTs. It has a small compass icon next to it. Click that and a new page will open. At the top, there's a search bar. Just type Pinescript to Python and you'll see it appear with the creator's name, Tom Payne. That's the one you want to open.
Once you're on the Pinescript to Python page, you'll see a button that says let's start. Go ahead and click that. It will ask to connect through GPTools.co, which is just the secure platform that powers this custom GPT and gives it access to extra trading functionalities. Now, when you click sign in with gpttools.co, you'll be redirected to a new page where you'll need to enter your email address. Once you do that, a verification code will be sent to your inbox. Just open your email, copy that code, and paste it back into the page to continue.
Once verified, you'll be taken straight to the payment page. The subscription costs about $12 per month. Build monthly. And honestly, that's a fantastic deal. Think about it. Hiring a freelancer to build even a basic trading bot can cost anywhere between $50 to $1,000. And that's for just one bot. But with this custom GPT, you can build unlimited bots in minutes without needing to write a single line of code. If you've ever tried buying bots online, you already know the deal. Most don't work as advertised. Many are overpriced, and some are straight up scams. But here, you're completely in control. You can see exactly what code is being generated, understand how it works, and modify it however you want.
Once you've completed your payment, you'll be redirected back to chat GPT where the Pinescript to Python GPT will now appear in your sidebar just like any other chat. Open it up and you're ready to start using it. I already have an active subscription so I won't go through the payment process again. But once you're done, you'll be exactly where I am right now, all set up and ready to go.
And now that you've got access to the custom GPT, this is where the fun begins. We'll paste our full prompt template into it and watch as it builds a complete ready to run Python trading bot for you in just one click.
Now, when you're pasting this into the custom GPT, there's one little thing you need to be careful about. Don't copy the very top line that says prompt template. Always start copying from the line that begins with you are a senior quant engineer and code generator. That's really important because some custom GPTs, including this one, can sometimes get confused if the word template appears before the main instructions. So, just to be safe, when you're pasting, select everything starting from you are a senior quant engineer all the way to the end of the document, including your strategy and the exchange line at the bottom. Also, make sure that the strategy you copied from Trading View is pasted right between those markers. Don't paste it above or below those lines. Those markers are what help the GPT understand exactly where your strategy begins and ends. If you paste it outside that section, it might not read the Pine script correctly, and you could end up with errors or incomplete code. So, just double check that your entire strategy is neatly sitting between those markers before you hit enter.
All right, now let's paste the prompt to our GPT. After you've pasted the full prompt, the custom GPT will take over. First, it'll quickly check whether you're a paid subscriber of this custom GPT or not. Basically, it verifies your access using the email linked to your chat GPT account. So, just make sure you're logged in with the same email address you used when you subscribed. That way, it can confirm your access instantly without any issues. It usually takes a few minutes.
So, while it's writing the code, let's talk about what's actually happening behind the scenes. This strategy that we picked earlier is a really clean trend-based setup. It's using a combination of EMAs to identify direction and trigger entries. Nothing too complicated, just smart and logical. And that's exactly the kind of strategy that works best for automation. Simple rules, clear structure, and consistency. You don't want 50 different indicators fighting with each other. You want something that executes cleanly, exactly the same way every single time.
Now, while the GPT is generating, this is a good moment to understand why using a custom GPT like this makes such a big difference. It's not like the normal chat GPT that needs you to explain every single detail or fix errors later. This one already knows what to do. It's been trained specifically for trading. So, it understands PineScript. It understands CCXT. And it knows exactly how to build a production-ready bot. It's precise, fast, and reliable.
And before you actually go live with this, a quick word of advice. Always start small. Even though this bot is designed for live trading, don't rush in with big capital right away. Test it on smaller amounts first. Get a feel for how it behaves, how the orders execute, how your exchange responds. Once you're comfortable, then slowly scale up. Also, if you ever get stuck, maybe you want to build a new bot, fix an error, or just understand how to modify your strategy. Feel free to reach out to me personally on Telegram. My handle is displayed on the screen now. It's at the rate of symbol then, sedp, but please make sure you're messaging the real one. There are always scammers pretending to be me. I'll never ask for money, API keys, or anything private. Just text me directly if you need genuine help.
All right, looks like the GPT is done generating our bot. It's created the three files: config.py, bot.py, and main.py, plus the requirements and readme. Now, it's time to take this code and run it. I use PyCharm as my IDE, but honestly, if you're using VS Code or anything else, that's totally fine. Just create a new project, make three new files with the same names, and paste the code exactly where it belongs.
All right, so before we actually run the bot, there are a couple of really important things I want to walk you through. Starting with a small fix that almost everyone needs to do the first time they use this custom GPT. When the GPT generates the files config.py, bot.py, and main.py, you'll notice that at the very top of each file, it adds a line that literally says something like /config.py. This happens because the GPT includes the file name in the output. But Python doesn't understand that. If you try running it as is, it'll immediately throw a syntax error. So just open each file, delete that very first line, the one that looks like /config.py/bot.py or/main.py. Save your changes, and you're good to go. Hopefully the creator fixes that soon, but for now, that's the quick and easy fix.
Now, let's talk about the config file because this is where everything begins. Think of config.py as your control center. This is where all your exchange details, risk settings, and strategy parameters live. The exact variables you see here will depend on the strategy you pasted earlier. Since our strategy is based on EMAs, you'll probably see variables like EMA_LTF, EMA_HTF, and maybe some time frame settings. But if you use a different strategy later, the variable names might change a little. Don't worry about that. The structure of the file always stays pretty much the same.
At the top, you'll see your exchange settings. Things like exchange ID, which should be the lowercase name of your exchange, like Binance, Bybit, or OKX. Below that, you'll have your API key and secret key. These are the keys you generate from your exchange account. And it's really important that they're from your futures trading API, not spot. Some exchanges like Bybit or Bitjet might also ask for an extra field like API password or UID. If you see those, just fill them in too.
Next comes the market and time frame section. Here you'll see the variable symbol, which is the trading pair your bot will use. After the symbol, you'll see your time frame, usually something like 1 hour or 15 minutes. If your strategy uses two time frames, you might also see another line for the higher one, like 1 day.
Then there's the strategy parameters like EMA lengths, stop-loss and take-profit percentages, leverage, position size, and a few safety or cool-down settings. For example, take profit percentage might be 0.02 for 2% or stop-loss percentage might be one for 1%. These define how your bot manages trades once they're live. You'll also see a cool-down period, which tells the bot to pause trading for a few bars after a trade closes. This helps avoid overtrading in choppy markets. One thing I really like about this setup is that it's very readable. You don't have to search through hundreds of lines of code. Everything important is right there at the top of config.py. If you ever want to tweak your bot later, this is the only file you'll need to touch. The rest bot.py and main.py handle the logic and execution automatically.
All right, before we actually run the main file, there's one last thing we need to make sure of, and that's installing all the required packages. This step is super important because without the dependencies, the bot simply won't start. So, open your terminal right here inside PyCharm or your code editor, whichever you're using, and type this command pip install-r requirements.txt. It will be shown in the screen. Now, what this does is it reads through the requirements.txt file that the gpt generated for us and installs all the necessary Python libraries your bot needs to run. This usually includes things like cext, pandas, and numpy. These are what handle the Exchange connection, data fetching, and calculations behind the scenes. It'll take a few seconds to install depending on your internet speed. Once you see that it's done without any red error messages, you're all set up.
Now we're ready to go live. Before you hit run, make sure you've pasted your API key and API secret from your Binance Futures account into the config file. Just double check those two lines and save the file.
All right, now that everything's in place, let's run the main file. Go ahead and click the run button on top. Let me do that. And there we go. As you can see, the bot is running successfully. It's initialized, detected the exchange, and started scanning the market on the selected time frame. The bot has started up successfully. You can see it's connected to Binance, loaded the exchange data, and is now checking the market in real time. It'll start scanning the charts, comparing the EMAs, and waiting for a valid trade setup.
If you look at the console logs, you'll notice it's saying things like checking for new signals and conditions not met. That just means the strategy rules aren't being triggered right now. The market doesn't currently fit the entry criteria. And that's a good thing. It shows the bot is behaving exactly as it should. It's not forcing trades or guessing. It's patiently waiting for the perfect setup, just like the strategy was designed to do. So yeah, the bot's alive, connected, and monitoring everything automatically. From here on, whenever the conditions line up, it'll execute trades on its own, completely hands-free.
All right, so that's it for today's video. We've officially gone from finding a strategy to converting it into a Python bot to actually running it live, all without writing a single line of code. I'll drop the prompt template link and all the other important links down below in the description and also in my Telegram group. Feel free to join the group if you want to discuss algo trading, share strategies, or if you want me to build a custom trading bot for you. You can contact me directly there. Also, make sure to join my Telegram channel to stay updated with new tutorials, strategies, and trading bot releases. If you found this video helpful, make sure to like the video, subscribe to the channel, and turn on the notifications so you don't miss what's coming next. I'll see you soon in the next video where we'll take this even further.