2025

Financial Market Pattern Detection and Trend Analysis

Developed a comprehensive program to analyze stock market data, applying statistical methods, time-series analysis, and pattern detection to identify market trends and anomalies for 10+ financial instruments. Built with Python and Streamlit for interactive visualization.

PythonStreamlitRefinitiv LSEGTime SeriesStatistical Analysis
View on GitHub
Project Objectives
  • Analyze stock market data for multiple financial instruments
  • Identify patterns and trends in market behavior
  • Apply statistical methods for anomaly detection
  • Create interactive dashboards for data visualization
Methodology
  1. 1

    Data acquisition from Refinitiv LSEG WorkSpace

  2. 2

    Time-series decomposition and trend analysis

  3. 3

    Statistical pattern recognition algorithms

  4. 4

    Anomaly detection using statistical thresholds

  5. 5

    Interactive dashboard development with Streamlit

  6. 6

    Backtesting and validation of identified patterns

Key Results

Successfully analyzed 10+ financial instruments

Identified key market trends and patterns

Built interactive visualization dashboard

Academic recognition for methodology and results

Technologies Used
PythonStreamlitPandasNumPyMatplotlibRefinitiv LSEG WorkSpaceStatistical Analysis

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