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Analyzing latency's impact on HFT strategies: Investigating how varying latency levels affect HFT algorithm performance metrics like fill rates, slippage, profitability & more.

Python 100.00%

hft-latency-research-project's Introduction

Impact of Latency on High Frequency Trading

This repository contains code and resources for analyzing the impact of latency on High-Frequency Trading (HFT) strategies. The project aims to investigate how varying levels of latency affect the performance metrics of HFT algorithms, including fill rates, slippage, and profitability.

Overview

High-Frequency Trading (HFT) relies heavily on low-latency infrastructure to execute trades rapidly in financial markets. This project explores the relationship between latency and trading outcomes, providing insights into the effectiveness of HFT strategies under different latency conditions.

Features

  • Simulation Framework: Implemented a simulation framework for generating random market data, simulating trade execution, and calculating performance metrics.

  • Latency Levels: Evaluated the impact of different latency levels (e.g., low latency, moderate latency) on HFT strategy performance.

  • Performance Metrics: Calculated key performance metrics such as fill rates, slippage, and profitability to assess the effectiveness of HFT strategies.

  • Analysis and Visualization: Analyzed simulation results and visualized findings to gain insights into the impact of latency on trading outcomes.

hft-latency-research-project's People

Contributors

shaikhmubin02 avatar

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