BTC Minute Market Data 2 Million CANDLES

Data Pre-Processing Notebook:**

• Notebook: Pre-Prep & Technical Indicators Bitcoin Market Data

Main Datasets:

• power_data.csv: ready to load, already pre-processed with all features, technical indicators.
• Shape: 1,997,210 rows, 27 columns
• Misc: 774MB
• Time Period: From 2020-01-01 00:01:00 to 2023-10-22 23:59:00
• Misc: If you want raw data files, please see version 3

Description:

This dataset provides a view of Bitcoin (BTC) market data by the minute, spanning from 2020 to the current date of October 24, 2023. It provided a wealth of valuable information (pure gold) for those interested in analyzing and understanding the minute-by-minute dynamics of the BTC market. Suitable for Algorithmic Trading, Neural Network, Reinforcement Learning, Machine Learning, Statistical Analysis and any kind of predictive analysis.

Key Features:

• OHLCV Data: The dataset includes Open, High, Low, Close, and Volume (OHLCV) information, which are essential components for charting and analyzing price movements in the BTC market.
• Trade Count: The number of trades that occurred within each minute, offering insights into trading activity and market participation.
• Date Data: day (object) & hour (int) features

Technical Indicators:

• Multiple EMAs (Exponential Moving Averages): These moving averages provide a dynamic view of the market by giving more weight to recent data points, making them particularly responsive to current price movements.
• WMA (Weighted Moving Average): A 14-period WMA offers a moving average that assigns varying weights to each data point in the series, thus providing a different perspective on price trends.
• MACD (Moving Average Convergence Divergence): MACD, Signal Line, and Histogram are included, offering a comprehensive view of this trend-following momentum indicator, which highlights the relationship between two moving averages.
• ATR (Average True Range): ATR measures market volatility by calculating the average range between high and low prices, making it a valuable tool for assessing price volatility.
• HMA (Hull Moving Average): This weighted moving average is designed to reduce lag and increase responsiveness to price changes, allowing for more timely analysis.
• KAMA (Kaufman's Adaptive Moving Average): KAMA is an adaptive moving average that adjusts its speed based on market conditions, providing a more dynamic view of price trends.
• CMO (Chande Momentum Oscillator): The Chande Momentum Oscillator measures price changes relative to the total range of prices over a specified period, facilitating insights into market momentum.
• Z-Score: The Z-Score measures how far a data point is from the mean in terms of standard deviations, helping to identify extreme deviations from the norm.
• QStick: QStick measures momentum based on the difference between the opening and closing prices, allowing for a deeper understanding of price movements within each minute.