Leveraging Jupyter AI for Traders and Investors – Python Tutorial

Rajandran R
Telecom Engineer turned Full-time Derivative Trader. Mostly Trading Nifty, Banknifty, USDINR and High Liquid Stock Derivatives. Trading the Markets Since 2006 onwards. Using Market Profile and Orderflow for greater than a decade. Designed and printed 100+ open supply buying and selling programs on varied buying and selling instruments. Strongly imagine that market understanding and sturdy buying and selling frameworks are the important thing to the buying and selling success. Writing about Markets, Trading System Design, Market Sentiment, Trading Softwares & Trading Nuances since 2007 onwards. Author of Marketcalls.in)

January 31, 2024

2 minutes learn

Jupyter AI gives a state-of-the-art useful resource for knowledge scientists, knowledge analysts, and merchants/traders, boosting their Python programming productiveness and effectivity. This device considerably enhances productiveness by enabling the speedy execution of your Python codes and techniques inside a Jupyter pocket book. With this device, you now have the power to work together by chat with main Large Language Models (LLMs) reminiscent of AI21, Anthropic, Cohere, Hugging Face, OpenAI, and SageMaker, amongst others.

Leveraging Jupyter AI for Traders and Investors – Python Tutorial
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JupyterAI runs on most working programs and integrates with varied platforms like Google Colab and VSCode.

How Traders/Investors can make the most of JupyterAI

  1. Enhanced Analysis: Traders can make the most of Jupyter AI to investigate advanced monetary knowledge, generate predictive fashions, and even simulate market situations. The skill to rapidly generate and take a look at hypotheses can considerably enhance decision-making.
  2. Automated Research: Investors can leverage Jupyter AI to automate elements of their analysis. By feeding prompts into the system, they’ll generate complete market studies, summaries, and even predictive insights about market traits.
  3. Code Generation and Error Fixing: Jupyter AI’s skill to generate code snippets and repair errors is invaluable. Traders can use this characteristic to develop customized algorithms, back-test buying and selling methods, and even automate elements of their buying and selling programs.
  4. Interactive Learning: The platform can act as an academic device, serving to customers perceive advanced monetary ideas and algorithms by interactive examples and explanations.

Prerequisites

Jupyter AI is suitable with any system able to operating Python variations starting from 3.8 to three.11.

Install VS Code with Python preferably less than 3.11 with Jupyter Extensions (bear in mind on the time of writing the newest model is 3.12)

set up

Install jupyterAI utilizing the pip command

pip set up jupyter_ai

Get the API Key from OpenAI

To combine OpenAI with PandasAI, an API token is important. Follow the simple steps outlined under to create your API_TOKEN with OpenAI.

  1. go to https://platform.openai.com/apps and signup along with your electronic mail tackle or join your Google Account.
  2. Go to View API Keys on the left aspect of your Personal Account Settings
  3. Select Create New Secret key
Leveraging Jupyter AI for Traders and Investors – Python Tutorial
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The API entry to openai is a paid service. You should arrange billing. Read the Pricing info earlier than experimenting.

Load the JupyterAI extension

  1. Launch Visual Studio Code and Open a Jupyter Notebook
  2. Activate the Extension Using This Command in a Jupyter Cell:
%load_ext jupyter_ai

Set the Environmental Variable

import os
os.environ['OPENAI_API_KEY'] = 'sk-your-openai-api-key'

List of Supported AI LLM Models

Leveraging Jupyter AI for Traders and Investors – Python Tutorial
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The %%ai Magic Command

The %%ai cell magic permits the invocation of a selected mannequin with a immediate. This flexibility lets customers tailor their expertise, whether or not they require advanced knowledge evaluation, pure language processing, and even picture era fashions.

%%ai chatgpt --format code
Write a Python Code to Fetch the information from yfinance and plot the road charts utilizing plotly for the ticker HDFCBANK.NS
Leveraging Jupyter AI for Traders and Investors – Python Tutorial
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Get the Latex Math Formulas

%%ai chatgpt --format math
Write the Black Sholes Formula for Computing implied volatility
Leveraging Jupyter AI for Traders and Investors – Python Tutorial
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Create Automated Markdown with Brief Instructions

%%ai chatgpt --format markdown 
Explain Pandas Dataframe
Leveraging Jupyter AI for Traders and Investors – Python Tutorial
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List of Supported Format Types

Jupyter AI is programmed to anticipate markdown because the default output format from a mannequin. Consequently, the outcomes of an %%ai instructions are usually introduced in markdown. However, this may be altered with the -f or --format possibility in your magic command, permitting for quite a lot of output codecs. These codecs embrace:

  • code:For output that’s primarily code-centric.
  • picture: This is unique to text-to-image fashions from Hugging Face Hub.
  • markdown: The default format, appropriate for normal textual content and formatting.
  • math: Ideal for mathematical expressions and equations.
  • html: Useful for outputs that must be in HTML format.
  • json: For outputs which might be finest represented in JSON format.
  • textual content:A easy, unformatted textual content output.

This flexibility ensures that the output is in probably the most applicable format to your particular wants.

Jupyter AI is greater than only a device; it is a complete resolution for merchants and traders looking for to harness the ability of AI of their decision-making course of. Its versatility, ease of use, and highly effective options make it an indispensable asset on the earth of finance. As the world of buying and selling and investing continues to evolve, Jupyter AI stands out as a beacon of innovation, driving effectivity and perception in market evaluation.

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