Stock Market Anomaly Detection

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Overview

The stock market is dynamic, with prices influenced by various factors including economic indicators, company performance, and market sentiment. Anomalies in stock prices or trading volumes can indicate significant events or changes in the market environment. Identifying and analyzing these anomalies is crucial for investors, traders, and financial analysts to make informed decisions and manage risk effectively.

The given dataset contains the following features:

• Date: The date of the stock data entry.
• Ticker: The stock ticker symbol.
• Adj Close: The adjusted closing price of the stock, which accounts for any corporate actions like splits or dividends.
• Close: The closing price of the stock.
• High: The highest price of the stock during the trading day.
• Low: The lowest price of the stock during the trading day.
• Open: The opening price of the stock.
• Volume: The number of shares traded during the day.

Objectives

Your task is to develop a robust data-driven approach to detect anomalies in stock market data (specifically, adjusted close prices and trading volumes) and assess the risk level of investing in different stocks based on the frequency and magnitude of these anomalies.