A comprehensive library for financial analysis
Project description
StockDataManager
This Python library offers a comprehensive suite of tools for technical and fundamental analysis, along with options analysis capabilities. Utilizing the yfinance library, it facilitates access to historical stock data, financial statements, and key financial metrics from Yahoo Finance. It includes over 30 technical indicators and options analysis tools.
Features
- Technical Analysis (
IndicatorCalculator
Class): Offers over 30 technical indicators like Moving Averages, MACD, Bollinger Bands, RSI, Ichimoku Cloud, etc., for analyzing market trends and volatility. - Fundamental Analysis (
Fetcher
Class): Retrieve historical stock data, income statements, balance sheets, cash flows, and key financial ratios (e.g., P/E, ROE, current ratio). - Options Analysis (
Greeks
andOptionPricing
Classes): tools to calculate options greeks and simulate option prices using various models, with enhanced methods to estimate risk-free rates and volatility.
Installation
pip install stockdatamanager
Quick Start
from stockdatamanager import Fetcher, IndicatorCalculator
from stockdatamanager.options import Greeks, OptionPricing
# Fetching stock data and financial statements
fetcher = Fetcher(ticker='AAPL')
print(fetcher.get_pe_ratio())
# Applying technical analysis
indicators = IndicatorCalculator(dataframe=fetcher.df)
df_with_rsi = indicators.calculate_RSI()
# Calculating options Greeks
greeks = Greeks(ticker = 'AAPL', call = True, identification = 0)
delta = greeks.calculate_delta()
# Pricing an American-style option using the binomial tree method
option_pricing = OptionPricing(ticker='MSFT', call=False, american=True, risk_free_rate='13 weeks', identification=0, use_yfinance_volatility=True)
option_price = option_pricing.calculate_option_price(method='binomial', describe=False)
print(f"Option Price: {option_price}")
Usage
Fetching Data
fetcher = Fetcher(ticker='AAPL')
income_statement = fetcher.get_income_statement()
Calculating Technical Indicators
transform = Transform(ticker='AAPL')
df_with_macd = transform.calculate_MACD()
Option Analysis
Calculate the Delta of an option:
greeks = Greeks(ticker='AAPL', call=True, identification='AAPL220121C00100000')
print(greeks.calculate_delta())
Simulate option pricing using the Crank-Nicholson method:
option_pricing = OptionPricing(ticker='MSFT', call=False, american=True, risk_free_rate='13 weeks', identification='AAPL220121C00100000', use_yfinance_volatility=True)
option_price = option_pricing.calculate_option_price(method='crank-nicolson', describe=False)
print(f"Crank-Nicolson Method Option Price: {option_price}")
Contributions
Contributions are welcome! Feel free to open an issue or submit a pull request for improvements or new features.
License
stockdatamanager is made available under the MIT License. See the LICENSE file for more details.
Contacts
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Hashes for stockdatamanager-1.1.2-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 0f0856b85d93fa688a344c84063712dfe527bab8340efc58ded671affb90e0bc |
|
MD5 | 703ccd009d8a253e7ff5a0e09d44fb20 |
|
BLAKE2b-256 | bd33a37ebff7bb9bfcfeede278f24ff419cde416adb6a85d85d2f90670a2ce5a |