Prosperity_year2

If you push new code, please notify in the Discord first.

Installing the Pre-Push Hook

We use a custom Git pre-push hook in our project to ensure code pushed to the main branch has been properly updated and rebased. This section guides you through setting up this hook.

1 - Pull the Latest Changes

Make sure you have the latest version of the repository:

git pull origin main

2 - Run the Setup Script

Execute the setup_hooks.sh script to install the pre-push hook:

sh git_hooks/setup_hooks.sh

3 - Run the Algo

Do inspec on your IMC prosperity page, and check for CognitoIdentityServiceProvider...idToken. Copy to your clipboard and then execute the following command

pbpaste | poetry run prosperity2submit Tutorial/Trader.py

Algorithmic Trading Challenge: SeaShells Trader

Introduction

Welcome to the SeaShells Trader Challenge! In this competition, you'll develop a Python-based trading algorithm to compete against bots in a simulated island exchange environment. The aim is to accrue as many SeaShells, the island's virtual currency, as you can through strategic trading.

How It Works

Your task is to create a Trader class that contains your trading logic. This class interacts with a variety of other classes provided within the simulation environment, which together facilitate your interaction with the market.

1. Trader Class

Trader is your main class where the algorithm resides.

run: The heart of your strategy, which processes the TradingState to make trading decisions.
result: A dictionary output of your orders, keyed by product.
traderData: A string to maintain state across the algorithm's execution calls.

2. TradingState Class

Provides a snapshot of the current market situation.

Attributes: Includes trader data, timestamp, listings, order depths, trades, position data, and observations.

3. Order and Execution Mechanics

Describes how orders are placed and executed within the simulation.

4. OrderDepth Class

Details outstanding market orders, influencing trading decisions.

5. Trade Class

Represents an individual trade, providing insights into market activities.

6. Order Class

Defines a trading order's structure.

7. Listing Class

Contains metadata for tradable products.

8. Observation Class

Encapsulates market insights and conditions impacting trading decisions.

9. ConversionObservation Class

Offers data relevant to product conversions, essential for strategies involving asset conversion.

10. Placing Orders

Describes how the algorithm should place orders using the Order class.

Strategy Tips

Understanding Position Limits: Manage your exposure to products, and strategize within the set position limits.
Enhancing Trading Strategies: Utilize the provided data classes to tailor strategies, exploit opportunities, and adapt to market conditions.

Getting Started

Clone this repository.
Navigate to the cloned directory.
Implement your Trader class logic.
Test your algorithm using the simulation environment.
Submit your Trader class as instructed within the challenge platform.

Skyngexe/Prosperity-2024