Group Number: OL2
Problem Assigned: B
Group Members: Jack Inwood, Felix Mayo, Samantha Starling, Adam Rapley
This repository contains the implementation of data-analytics techniques for identifying trading signals ("buy" or "sell") in Level-2 financial market data. The goal of this project is to explore advanced analytics methods to predict near-term movements in price and evaluate the profitability of automated trading strategies based on these signals.
The global financial markets generate vast amounts of data, especially in the form of Level-2 data, which summarizes all bids and asks currently resting at the exchange for a tradable asset. This data includes price and quantity information for buy and sell orders, resulting in large and complex datasets with significant potential for advanced data analysis. The challenge is to implement and evaluate data-analytics techniques to extract meaningful trading signals from this data, ultimately aiming to develop profitable automated trading strategies.