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Project description
- Stylized name, shortened spelling of stepping stone;
- A Python framework for ingesting and interpreting structured and unstructured financial data, designed to optimize quantitative methods in financial markets.
Key Features
- Data Extraction: Retrieve market data from various sources such as B3, CVM, and BACEN (Olinda);
- Quantitative Methods: Supports a range of quantitative techniques, including portfolio optimization, risk management, and financial modeling;
- Derivatives Pricing: Implements both closed-form solutions (e.g., Black-Scholes model) and open-form, iterative methods (e.g., Binomial Tree model) for pricing derivatives;
- Data Treatment: Tools for cleaning, structuring, and transforming raw financial data into usable formats for analysis;
- Data Loading: Seamlessly integrates with databases such as PostgreSQL, MySQL, and SQLite.
Project Structure
stpstone
├── airflow
│ └── plugins.py
├── cals
│ ├── br_bzdays.py
│ ├── handling_dates.py
│ └── usa_bzdays.py
├── charts
│ ├── general_funcs.py
│ ├── prob_and_stats.py
│ ├── risk_management.py
│ ├── stock_market.py
│ └── tsir.py
├── cloud_clients
│ └── aws_s3.py
├── document_numbers
│ └── br.py
├── dsa
│ └── trees
│ └── b_tree.py
├── equity_consolidation
│ └── banks.py
├── finance
│ ├── anbima
│ │ ├── abimadata_api.py
│ │ ├── anbima_mtm.py
│ │ ├── anbima_stats.py
│ │ └── anbimadev.py
│ ├── auditing
│ │ └── earnings_manipulation.py
│ ├── b3
│ │ ├── cei.py
│ │ ├── core.py
│ │ ├── inoa.py
│ │ ├── line.py
│ │ ├── margin_simulator.py
│ │ ├── market_data.py
│ │ ├── search_by_trading.py
│ │ └── up2data_web.py
│ ├── comdinheiro
│ │ └── api_request.py
│ ├── cvm
│ │ ├── cvm_data.py
│ │ └── cvm_web.py
│ ├── dadosdemercado_site
│ │ └── api_request.py
│ ├── debentures
│ │ └── pricing.py
│ ├── derivatives
│ │ ├── forward.py
│ │ ├── futures.py
│ │ └── options
│ │ ├── american.py
│ │ └── european.py
│ ├── financial_risk
│ │ ├── capital_risk.py
│ │ ├── liquidity_risk.py
│ │ ├── market_risk.py
│ │ └── yield_risk.py
│ ├── macroeconomics
│ │ ├── br_macro.py
│ │ ├── global_rates.py
│ │ ├── usa_macro.py
│ │ └── world_gov_bonds.py
│ ├── performance_apprraisal
│ │ ├── company_return.py
│ │ └── financial_math.py
│ ├── reuters
│ │ └── api_request.py
│ ├── spot
│ │ └── stocks.py
│ └── tesouro_direto
│ ├── calculadora.py
│ └── consulta_dados.py
├── geography
│ └── br.py
├── handling_data
│ ├── dicts.py
│ ├── folders.py
│ ├── html.py
│ ├── img.py
│ ├── json.py
│ ├── lists.py
│ ├── lxml.py
│ ├── numbers.py
│ ├── object.py
│ ├── pd.py
│ ├── pdf.py
│ ├── pickle.py
│ ├── str.py
│ ├── tgz.py
│ ├── txt.py
│ └── xml.py
├── llms
│ └── gpt.py
├── loggs
│ ├── create_logs.py
│ └── db_logs.py
├── meta
│ └── validate_pm.py
├── microsoft_apps
│ ├── cmd.py
│ ├── excel.py
│ ├── onedrive.py
│ ├── outlook.py
│ └── windows_os.py
├── multithreading
│ └── mp_helper.py
├── opening_config
│ └── setup.py
├── pool_conn
│ ├── dabricksCLI.py
│ ├── databricks.py
│ ├── generic.py
│ ├── mongodb.py
│ ├── mysql.py
│ ├── postgresql.py
│ ├── redis.py
│ ├── session.py
│ ├── sqlite.py
│ └── sqlserver.py
├── quantitative_methods
│ ├── calculus.py
│ ├── classification.py
│ ├── data_cleaning.py
│ ├── eda.py
│ ├── features_selecting.py
│ ├── fit_assessment.py
│ ├── interpolation.py
│ ├── linear_algebra.py
│ ├── prob_distributions.py
│ ├── regression.py
│ ├── root.py
│ ├── sequences.py
│ ├── statistical_description.py
│ └── statistical_inference.py
├── sendgrid
│ └── handling_sendgrid.py
├── settings
│ ├── _global_slots.py
│ ├── anbima.yaml
│ ├── b3.yaml
│ ├── br_macro.yaml
│ ├── br_treasury.yaml
│ ├── comdinheiro.yaml
│ ├── generic.yaml
│ ├── global_rates.yaml
│ ├── inoa.yaml
│ ├── llms.yaml
│ ├── microsoft_apps.yaml
│ ├── session.yaml
│ ├── usa_macro.yaml
│ └── world_gov_bonds.yaml
├── trading_platforms
│ └── mt5.py
├── typeform_sdk_master
│ ├── CHANGELOG.md
│ ├── CONTRIBUTING.md
│ ├── LICENSE
│ ├── MANIFEST.in
│ ├── README.md
│ ├── requirements-dev.txt
│ ├── setup.cfg
│ ├── setup.py
│ └── typeform
│ ├── __init__.py
│ ├── client.py
│ ├── constants.py
│ ├── dealing_tf.py
│ ├── forms.py
│ ├── responses.py
│ ├── test
│ │ ├── __init__.py
│ │ ├── fixtures.py
│ │ ├── suite.py
│ │ ├── test_client.py
│ │ ├── test_forms.py
│ │ └── test_responses.py
│ └── utils.py
└── webhooks
├── slack.py
└── teams.py
Getting Started
These instructions will get you a copy of the project running on your local machine for development and testing purposes.
Prerequisites
- Python ^3.12
Installing
PyPi.org
(bash)
# latest version
pip install stpstone
# optional: versioning
pip install stpstone==0.1.0
- Available at: https://pypi.org/project/stpstone/0.1.0/
Local Machine Version
-
Git clone
-
Pyenv for Python ^3.12.8 local installation:
(PowerShell)
Invoke-WebRequest -UseBasicParsing -Uri "https://raw.githubusercontent.com/pyenv-win/pyenv-win/master/pyenv-win/install-pyenv-win.ps1" -OutFile "./install-pyenv-win.ps1"; &"./install-pyenv-win.ps1"
(bash)
echo installing local version of python within project
cd "complete/path/to/project"
pyenv install 3.12.8
pyenv versions
pyenv global 3.12.8
pyenv local 3.12.8
- Activate poetry .venv
(bash)
echo defining local pyenv version
pyenv global 3.12.8
pyenv which python
poetry env use "COMPLETE_PATH_PY_3.12.8"
echo check python version running locally
poetry run py --version
echo installing poetry .venv
poetry init
poery install --no-root
echo running current .venv
poetry shell
poetry add <package name, optionally version>
poetry run <module.py>
Running the Tests
- EDA - Exploratory Data Analysis:
(bash)
cd "complete/path/to/project"
poetry run python stpstone.tests.eda.py
- European / American Options:
(bash)
cd "complete/path/to/project"
poetry run python tests.european-american-options.py
- Markowitz Portfolios:
(bash)
cd "complete/path/to/project"
poetry run python tests.markowitz-portfolios.py
Authors
Guilherme Rodrigues
License
Acknowledgments
- Hat tip to anyone whose code was used
- Inspiration
- etc
Inspirations
Project details
Release history Release notifications | RSS feed
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