finance-core 0.1.8

No project description provided

Finance core

Financial indicators implemented in Rust with a Python interface.

Install

pip install finance_core

Example usage

import finance_core as fc


max_three_days = fc.Maximum(3)

print(max_three_days.next(1)) # >> 1
print(max_three_days.next(4)) # >> 4
print(max_three_days.next(2)) # >> 4
print(max_three_days.next(5)) # >> 5


min_three_days = fc.Minimum(3)

print(min_three_days.next(1)) # >> 1
print(min_three_days.next(4)) # >> 1
print(min_three_days.next(2)) # >> 1
print(min_three_days.next(5)) # >> 2


sma_three_days = fc.SimpleMovingAverage(3)

print(sma_three_days.next(1)) # >> 1
print(sma_three_days.next(4)) # >> 2.5
print(sma_three_days.next(2)) # >> 2.33
print(sma_three_days.next(5)) # >> 3.66

Indicators

• Averge true range (ATR)
• Exponential moving average (EMA)
• Maximum
• Minimum
• Moving average convergence/divergence (MACD)
• Rate of change (ROC)
• Relative strength index (RSI)
• Sharpe ratio (SR)
• Simple moving average (SMA)
• Standard deviation, population (SD)
• True range (TR)

Strategies

• Exponential moving average crossover
• Simple moving average crossover

Data classes

• Bar (open, high, low, close, volume)
• Signal (BUY, SELL, HOLD)

Contribute

Install Docker and open this repo in DevContainer.

# create virtual environment
python -m venv .venv

# activate virtual environment
source .venv/bin/activate

# install dependencies
pip install -r requirements.txt

Useful commands:

• make build-dev to build the package during development
• make build-prod to perform an optimised build for benchmarking