This ChatGPT Trick Will Transform Your Crypto Portfolio Management Forever

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How to build a personalized crypto portfolio tracker using ChatGPT

Key takeaways

  • AI tools such as ChatGPT offer a convenient solution for both seasoned and novice cryptocurrency investors, enabling them to effortlessly monitor their investments. This leaves ample room for engagement in other financial endeavors while simplifying the overall experience of managing portfolios.

  • To create a personalized investment portfolio tracker that suits your objectives, it’s crucial to outline the particular digital currencies you want to monitor and select the relevant data points of interest.

  • Using ChatGPT in conjunction with real-time data from APIs such as CoinMarketCap allows for the creation of insightful market commentary and analysis, enhancing your understanding of your portfolio’s performance. Enhancing this tool with features like price alerts, performance analysis, and an intuitive interface will make it more useful, empowering you to keep pace with market trends and efficiently manage your cryptocurrency investments.

If you’re into investing in cryptocurrencies, it’s clear that you have a high tolerance for risk! Navigating the world of cryptocurrency requires various steps, such as conducting thorough research on potential profits, actively trading digital currencies, and keeping tabs on regulations. Even experienced investors may find managing a cryptocurrency portfolio challenging due to its complexity and time demands.

On the other hand, if you’re just starting out in the realm of cryptocurrencies and aim for prosperity, you might find the intricacy overwhelming.

A great advantage is that Artificial Intelligence (AI) provides useful resources for the cryptocurrency sector, making it easier for you to manage your portfolio and conduct detailed analyses, as long as it’s used correctly.

For seasoned crypto investors, utilizing AI could allow for the valuable time spent managing investments to be redirected towards other aspects of your investment journey. On the other hand, if you’re just starting out as an investor, AI can offer a helpful first step. Discover how AI, particularly ChatGPT, can assist in creating a tailored portfolio tracker for you – keep reading to find out more!

To begin with, what is it? 

Let’s find out.

What is ChatGPT?

ChatGPT is an artificial intelligence system designed for conversation, capable of carrying out numerous tasks based on user instructions such as gathering information, processing data, and creating visual representations.

The acronym GPT, or Generative Pre-trained Transformer, signifies a sophisticated language model comprehensively educated on extensive text collections from various online resources. Its purpose is to grasp context and generate helpful outcomes for users.

Utilizing the advanced intelligence of ChatGMT, you can construct an effective cryptocurrency portfolio tailored to your unique investment strategy and preferences.

Let’s learn how to build a custom portfolio tracker with ChatGPT.

Step 1: Define your requirements

Before diving into the technical aspects, it’s essential to clarify your expectations for your cryptocurrency portfolio tracker. For instance, you might want to ponder over these questions:

1. What specific data about each cryptocurrency should the tracker display? (e.g., current price, market cap, percentage change, etc.)
2. How do you prefer to view this information? (e.g., in a table format, graphically, etc.)
3. Do you want real-time updates or are updates at specific intervals sufficient?
4. Are there any additional features you would like the tracker to have, such as alerts for significant price movements or portfolio performance analysis tools?
5. Is it important that the tracker integrates with other financial platforms or wallets you use?

  • What cryptocurrencies will you track? 

  • Could you share your investment strategy with me? Do you prefer an aggressive approach that involves frequent trading of cryptocurrencies throughout the day, or do you lean more towards a passive approach, where you buy and keep these assets for extended periods of time?

  • Could you please list the pieces of information required for our tracking system? This might encompass items like current price, total market capitalization, trading volume, as well as summarized news articles from the internet that could potentially impact your investment choices significantly.

  • Could you clarify specifically what kind of real-time updates, periodic summaries, or a mix of both functionalities you’d like the tracker to provide you with?

  • Could you please specify what kind of result you’re expecting? This could be alerts, analysis for performance, historical data, or any other type of information.

After you’ve thoroughly grasped what you need, you’re ready to proceed with the subsequent actions. For optimal results, it’s advisable to jot down your needs in a unified specifications document. This way, you can make adjustments as needed at a later time.

Step 2: Set up a ChatGPT instance

This part is quite exciting! It will be enjoyable for those who delight in coding. Just keep in mind that ChatGPT is a sophisticated language model, packed with a tremendous amount of intelligence.

To make the most out of ChatGPT, it’s important to have the ability to interact with its underlying model directly. This can be achieved using an Application Programming Interface (API) for easier access.

1. First, acquire the necessary API keys from OpenAI.
2. Next, integrate these keys within your project to access and connect with the ChatGPT platform.
3. Lastly, customize and configure the ChatGPT instance as per your requirements.

  1. Navigate to OpenAI and sign up for an API key.

  2. To create a suitable setup for making API calls, Python is a recommended solution, though other options like Node.js also work effectively. In essence, you need to establish a setting that facilitates the use of APIs, and Python or Node.js can both serve this purpose well.

  3. import os
    from openai import ChatCompletion

    # Set your API key here
    api_key = “YOUR_API_KEY”
    os.environ[“OPENAI_API_KEY”] = api_key

    def get_chat_completion(prompt):
    messages = [{“role”: “user”, “content”: prompt}]
    response = ChatCompletion.create(model=”model_name”, messages=messages)
    return response.choices[0].message[“content”]

    # Example usage
    print(get_chat_completion(“What is the current market price of Bitcoin?”))

Step 3: Integrate a cryptocurrency data source

After you’ve successfully installed ChatGPT, let’s move on to configuring the remaining piece of the puzzle – your cryptocurrency data provider. You have numerous options to choose from, and various APIs are available to assist in gathering the necessary data for this task.

Consider exploring various cryptocurrency data platforms such as CoinGecko, CoinMarketCap, or CryptoCompare. After researching their features to find one suitable for your needs, integrate that platform with the ChatGPT instance you set up in Step 2. This will allow ChatGPT to provide more accurate and updated information about cryptocurrencies.

1. Investigate different crypto data resources like CoinGecko, CoinMarketCap, or CryptoCompare to discover the one that aligns with your preferences.
2. Once you’ve chosen a platform, make it compatible with the ChatGPT instance from Step 2 for more precise and current cryptocurrency information within your chatbot.

To illustrate, should you opt for the CoinMarketCap API, the ensuing code snippet can help you fetch the current cost of Bitcoin, a component in your digital currency portfolio that you might be actively trading.

Step 4: Combine ChatGPT and crypto data

After completing the challenging part, since you now possess an AI tool (like ChatGPT) and a source for cryptocurrency information (such as CoinMarketCap in this case), you are all set to construct a crypto portfolio tracker. To accomplish this, you can utilize prompt engineering to take advantage of ChatGPT’s intelligence by asking for data and generating insights.

Here’s an example that fetches Bitcoin, Ethereum, and Litecoin price data and displays the result as a data frame:
import pandas as pd
import requests
from datetime import datetime

def get_crypto_prices(symbols):
url = “https://min-api.cryptocompare.com/data/pricemultifull?fsyms={}&tsym=USD”

df[col] = pd.to_numeric(df[col])

return df

def main():
symbols = [‘BTC‘, ‘ETH‘, ‘LTC‘]
timepoint = datetime.now() # Use your desired time here

crypto_prices = get_crypto_prices(symbols)
print(crypto_prices[crypto_prices.datetime > timepoint])

if __name__ “__main__”:
main()

Adjust the ‘timepoint’ variable to the desired time you want the summary of cryptocurrency prices to be fetched, and update the ‘symbols’ list with any other cryptocurrencies you’d like to track.

“`python

    # Set your OpenAI API key

    client = OpenAI(api_key=openai_api_key)

    messages = [

You possess a deep understanding of the dynamics within the cryptocurrency market, acting as a seasoned analyst.

Request for a succinct analysis of the market condition based on the current price of {symbol}, which is ${price:.2f} as of {date}. Include a brief summary and potential investment advice in your response.

    ]

    try:

        response = client.chat.completions.create(

            model=”gpt-4o-mini”,

            messages=messages,

            max_tokens=100,

            temperature=0.7

        )

        commentary = response.choices[0].message.content

        return commentary

    except Exception as e:

        print(f”Error obtaining commentary for {symbol}: {e}”)

        return “No commentary available.”

Function named `create_crypto_datatable` that takes in a `cmc_api_key`, an `openai_api_key` (note: this seems unlikely for a crypto dataframe as OpenAI is not related to cryptocurrency), a list of `symbols`, and an optional parameter `convert` with default value “USD”. Returns a pandas DataFrame.
def create_crypto_datatable(api_key_cmc, api_key_openai=None, symbol_list, currency=”USD”) -> pd.DataFrame:
# Function to build a DataFrame containing crypto data using the provided API keys and symbols

    records = []

    # Capture the current datetime once for consistency across all queries.

    current_timestamp = datetime.now().strftime(“%Y-%m-%d %H:%M:%S”)

    for symbol in symbols:

        price = get_crypto_price(cmc_api_key, symbol, convert)

        if price is None:

            commentary = “No commentary available due to error retrieving price.”

        else:

            commentary = get_openai_commentary(openai_api_key, symbol, price, current_timestamp)

        records.append({

            “Symbol”: symbol,

            “Price”: price,

            “Date”: current_timestamp,

            “Market Commentary”: commentary

        })

    df = pd.DataFrame(records)

    return df

# Example usage:

if __name__ == ‘__main__’:

    # Replace with your actual API keys.

    cmc_api_key = ‘YOUR_API_KEY’

    openai_api_key = ‘YOUR_API_KEY’

    # Specify the cryptocurrencies of interest.

    crypto_symbols = [“BTC”, “ETH”, “XRP“]

    # Build the data frame containing price and commentary.

    crypto_df = build_crypto_dataframe(cmc_api_key, openai_api_key, crypto_symbols)

    # Print the resulting dataframe.

    print(crypto_df)

“`

====================================================================

As a researcher, I’ve developed a tool that analyzes the performance of three cryptocurrencies in my investment portfolio – Bitcoin (BTC), Ether (ETH), and XRP (XRP). This tool leverages the ChatGPT API to fetch real-time market prices from CoinMarketCap as its data source. The results are then presented in an easy-to-understand table format, complete with AI-generated insights about the current market conditions. This allows me to effortlessly monitor my portfolio and make informed decisions based on the latest market trends.

Step 5: Develop additional features

You’ve got the opportunity to boost your tracker! You can do this by incorporating additional features or stunning graphics. As an illustration, think about:

  • Alerts: Set up email or SMS alerts for significant price changes.

  • Performance analysis: Track portfolio performance over time and provide insights. 

  • Visual representations: Incorporate past data to depict patterns in pricing. This could assist astute investors in predicting future significant market changes.

Step 6: Create a user interface

To ensure your cryptocurrency portfolio tracker is easy for users to navigate, it’s recommended that you create a user-friendly interface, either on the web or through a mobile app. For web applications, Python frameworks like Flask, Streamlit, or Django can be useful in building straightforward yet intuitive interfaces. Alternatively, if you prefer developing a mobile app, consider using React Native or Flutter for an efficient and simple user experience. Ultimately, simplicity should remain the focus of your design decisions.

Have you heard that Flask, Streamlit, and Django each offer unique benefits? Flask is known for its lightweight flexibility, Streamlit makes data visualization a breeze, while Django provides robust, secure backends. These tools are great for creating tools to monitor prices and market trends!

Step 7: Test and deploy

Verify that your tracker is fully tested for precision and dependability. After testing, consider deploying it onto a server or cloud service such as Amazon Web Services (AWS) or Heroku. Over time, keep an eye on its effectiveness and make adjustments to its features as needed.

Utilizing Artificial Intelligence (AI) in managing cryptocurrencies allows you to create a personalized portfolio tracker with valuable market insights. This integration helps monitor your crypto investments more effectively. Yet, remember that AI predictions aren’t always spot-on, data from APIs might not be up-to-date, and over-relying on it could potentially distort decisions. So, use this tool thoughtfully and consider the potential risks involved.

Happy AI-powered trading! 

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2025-04-10 15:47