hypertrial 0.1.0

Bitcoin Dollar-Cost Averaging (DCA) Backtest Framework

Hypertrial: Bitcoin DCA Strategy Framework

A Bitcoin Dollar-Cost Averaging (DCA) framework for evaluating and comparing algorithmic trading strategies.

Installation

pip install hypertrial

Quick Start

import pandas as pd
from hypertrial import backtest_dynamic_dca, load_data, register_strategy

# Load Bitcoin data (included with the package)
btc_df = load_data()

# Create a simple custom strategy
@register_strategy("my_custom_strategy")
def custom_dca_strategy(df):
    # Strategy logic goes here
    # Return purchase weights for each day
    return weights_df

# Run backtest with your strategy
results = backtest_dynamic_dca(btc_df, strategy_name="my_custom_strategy")

Key Features

• DCA Strategy Testing: Evaluate Bitcoin dollar-cost averaging strategies
• Performance Metrics: Analyze strategies using Sats Per Dollar (SPD)
• Cross-Cycle Analysis: Test strategies across multiple Bitcoin market cycles
• Visualization Tools: Plot performance metrics and strategy behaviors
• Security Verification: Security scanning for submitted strategies

Command Line Interface

Hypertrial comes with a built-in CLI:

# List available strategies
hypertrial --list

# Run backtest with a specific strategy
hypertrial --strategy dynamic_dca

# Run backtest for all strategies
hypertrial --backtest-all --output-dir results

Contributing

We welcome contributions! Please visit our GitHub repository for more information.

License

This project is available under the MIT License.