Quant coder-code support for trading strategies.

Example

Generating Python code for a fixed distance market-making model, complete with explanations for each step of the code.

Scenario

A user wants to implement a market-making strategy. Quant Coder provides a code snippet that simulates placing long and short limit orders at a fixed distance from the midprice, updating orders based on price movements, and managing inventory. The code also includes comments explaining how each part of the strategy works, helping the user understand the mechanics behind it.

Example

Analyzing and visualizing the distribution of trade sizes and order book imbalances using historical market data.

Scenario

A user needs to analyze the order book data for a particular trading pair to understand liquidity patterns. Quant Coder can generate code to load the data, calculate key metrics like order arrival rates, and create visualizations that highlight significant patterns, such as the correlation between order size and market movements.

Example

Developing and backtesting a momentum-based trading strategy using historical price data.

Scenario

A user is interested in testing a momentum trading strategy. Quant Coder helps by providing a code framework that loads historical data, applies the momentum logic, and backtests the strategy to evaluate its performance over different time periods. This allows the user to refine the strategy before deploying it in a live trading environment.