A collection of IPython notebooks for scraping and cleaning publically available U.S. government data
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Updated
Feb 20, 2017 - Jupyter Notebook
A collection of IPython notebooks for scraping and cleaning publically available U.S. government data
Computational data tools for financial economics. Keywords: Jupyter notebook pandas Federal Reserve FRED Ferbus GDP CPI PCE inflation unemployment wage income debt Case-Shiller housing asset portfolio equities SPX bonds TIPS rates currency FX euro EUR USD JPY yen XAU gold Brent WTI oil Holt-Winters time-series forecasting statistics econometrics
Presentation and notebook for the lightning talk A Quick Intro to Hidden Markov Models Applied to Stock Volatility presented in R/Finance 2017.
Executable notebooks of market analysis.
iPython notebook which allows the calculation of historical VaR for a variable range of user defined US equities. The lookback period is manually user defined.
This project contains codes and notebooks related to various use cases for banking.
Study notebooks made for learning machine learning for the Hawk team
Python class and jupyter iPython notebook for pricing a fixed coupon bond
Detecting critical transitions in financial networks with topological data analysis.
Tools for financial economics. Curated wrapper over Python ecosystem. Source code for fecon235 Jupyter notebooks.
Implementation with a Jupyter Notebook of the VIX index modelization provided in its CBOE white paper.
Jupyter Notebooks Collection for Learning Time Series Models
notebooks created on pluto
Notebooks for fine-tuning a BERT model and training a LSTM model for financial QA
FinMan is an educational suite of tools that can be used to conduct an analysis of financial instruments and their performance. It is comprised of notebooks that will aid in financial analysis and data collection. The goal of the project is to provide a simple UI and automate the process of analyzing data using machine learning
Finance related Jupyter notebooks
This is a python program for finance. It shows how to commpute portfolio simple returns, get daily returns and volatility etc. The graphs are also present in the notebook.
Be systematically sort out my relevant knowledge of Matlab
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