BTC Trading Bot Dataset With Advanced Indicators
Predict BTC Trends with Advanced Indicators
@kaggle.emirhanai_btc_trading_bot_dataset_with_advanced_indicators
About this Dataset
BTC Trading Bot Dataset With Advanced Indicators
BTC Trading Bot Dataset with Advanced Indicators - Predict $100,000 Breakthrough
Description:
This dataset is designed to power innovative machine learning and LLM-based trading bots focused on Bitcoin (BTC) trading strategies. It combines historical BTC price data with advanced custom indicators, offering valuable insights for predicting key market trends, including the potential breakthrough of BTC exceeding $100,000.
The dataset contains enriched features, meticulously crafted to serve as the foundation for predictive models and algorithmic trading strategies. Each indicator has been optimized for capturing both macro and micro trends in BTC's volatile market.
Dataset Features
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Date and Time: Timestamp of the price data in UTC.
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Open, High, Low, Close (OHLC): Standard candlestick charting data.
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Volume: Total trading volume in BTC during the respective time period.
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Custom Indicators (Synthetic):
- Momentum Signal (MOM_S): Measures the velocity of price movements over a custom period.
- Volatility Tracker (VOL_T): Captures the price range fluctuations with a proprietary algorithm.
- Trend Oscillator (T_OSC): Detects market trends by analyzing price shifts and crossovers.
- Buy Pressure Index (BPI): Highlights potential buy zones based on unique volume-weighted formulas.
- Breakthrough Indicator (BRI): Focused on identifying signals for major price thresholds like $100,000.
- Sentiment Score (SENT_S): Derived from on-chain data and social sentiment.
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Derived Metrics:
- Moving Averages (MA10, MA50, MA200): Commonly used technical indicators.
- RSI (Relative Strength Index): Measures the magnitude of recent price changes to evaluate overbought/oversold conditions.
Target Audience
This dataset is ideal for:
- Quantitative Analysts: Exploring BTC trends and creating trading signals.
- Data Scientists: Building LLMs for price prediction and risk analysis.
- Financial Enthusiasts: Experimenting with algorithmic trading strategies.
Usage Scenarios
- Predicting Market Movements: Utilize the synthetic indicators and historical data to train models for identifying price spikes or drops.
- Developing Trading Bots: Fine-tune machine learning-based trading bots, focusing on the $100,000 BTC price breakthrough.
- Backtesting Strategies: Validate trading algorithms and measure performance against historical data.
Additional Notes
This dataset is tailored for Bitcoin trading and does not include unrelated financial instruments. The provided indicators were designed for educational and research purposes but align with real-world trading practices for improved predictive accuracy. Dive into the data and start creating your trading bot today!