Statistical Tick Data Metrics of 100 Scandinavian Blue-Chip Stocks Across 4 Days

A Comprehensive Analysis of Tick Data for Market Insights

Quantitative Analysis of High-Frequency Trading Data

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Project Overview

This report presents a detailed analytical study of statistical metrics derived from a dataset containing four days of tick data for 100 Scandinavian blue-chip stocks. The dataset, sourced from https://itarle.com/data-set-tests/, is structured as a large CSV file and processed using C++ for efficient computation and metric extraction.

Key Objectives

1. Analyze inter-trade times and tick changes to identify market patterns
2. Measure bid-ask spreads to assess market liquidity
3. Investigate the round number effect in stock prices
4. Provide insights for algorithmic trading strategies and market efficiency studies

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Dataset Description

• Source: AWS-hosted dataset
• Format: Large CSV file
• Scope: 100 Scandinavian blue-chip stocks
• Timeframe: 4 consecutive trading days
• Data Points: High-frequency tick data (price, volume, bid-ask spreads, etc.)

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Methodology

Metrics Extracted

1. Inter-Trade Times: Time intervals between consecutive trades
2. Tick Changes: Price movements between trades
3. Bid-Ask Spreads: Difference between bid and ask prices
4. Round Number Effect: Frequency of trades occurring at round price levels (e.g., $10.00, $15.00)

Tools and Technologies

• Programming Language: C++
• Libraries: Standard Template Library (STL) for data structures and algorithms
• Data Processing: Custom-built C++ scripts for efficient handling of large datasets

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