Financial-market-trend-recovery

This dataset simulates financial market trends and recovery patterns over a period of time. It contains 3000 records that represent daily financial market activities, focusing on key metrics that impact market stability, price trends, trading volume, and regulatory changes. This data is generated to provide insights into how markets behave during periods of recovery, particularly after economic downturns or volatility spikes.

Features:
Date: The specific date on which the market data was recorded.
Market Price ($): The simulated price of financial assets (such as stocks or commodities) on a given day. It ranges from $100 to $1500.
Recovery Index: An index that tracks the market’s recovery performance, with values closer to 1 indicating stability. The range is 0.5 to 1.5.
Trading Volume: Simulated daily trading volume of assets in the market, ranging from 100,000 to 10,000,000.
Volatility Index: A measure of market volatility on a given day, where higher values indicate more uncertainty. The range is 0.1 to 1.0.
Interest Rate (%): The interest rate during the recorded day, ranging from 0.5% to 5%, which can influence market movements and investor decisions.
Regulatory Change (Binary): A binary feature (0 or 1) indicating if a regulatory change occurred on that day, with a 5% chance of occurrence.
Market Recovery (Binary): A binary feature (0 or 1) showing whether the market showed signs of recovery, with a 30% chance of recovery.
Use Cases:
Market Analysis: Use this dataset to identify patterns of market recovery during volatile periods.
Machine Learning Models: Train models for financial forecasting, risk assessment, and regulatory impact analysis.
Trend Analysis: Evaluate how different factors (e.g., market price, trading volume, interest rates) influence the recovery process in financial markets.