Educational notebooks on quantitative finance, algorithmic trading, financial modelling and investment strategy
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Updated
Jul 2, 2020 - Jupyter Notebook
Educational notebooks on quantitative finance, algorithmic trading, financial modelling and investment strategy
Notebooks based on financial machine learning.
Two Jupyter Notebooks written in Python, treating of time series analysis with ARIMA and its seasonal counterpart.
notebooks created on pluto
zipline-broker Examples. Full notebooks plus python code for long term investment strategies using zipline based tools.
Used SQL in Jupyter Notebooks to analyze and explore data on international debts and codes.
Colaboratory notebook that implements several strategic indicators that are commonly used in the financial ecosystem. Enter a ticker symbol for an equity (ETF, cryptocurrency, et. al.), a start date, and an end date for the analysis. Run all and let the analysis begin. Note: This is not financial advise, use at your own risk.
An example of working with financial data in elixir livebook (similar to jupyter notebooks).
Notebooks y entregables de proyecto de las tareas de laboratorio realizadas en la asignatura Métodos Estadísticos para Finanzas y Seguros del Grado en Ciencia e Ingeniería de Datos. 📈
Examines trade data and finds the day trades that occurred within a given time period in a Jupyter Notebook hosted on a Docker container.
EDA on Bank Loan Case Study
2022년 1학기 금융시장빅데이터분석 강의자료 및 jupyter notebook 실습 파일
2022학년도 2학기 금융시장계량분석 수업자료 및 Jupyter Notebook 실습 파일
This repository contains solution notebooks for CL Financial Analysis internship. Certificate here :
Exercises and notes completed in the Jupyter Notebook while completing the Udemy course, "Python for Data Analysis and Machine Learning
Here you can find jupyter notebooks to visualiza data related to financial markets, such as equity returns, volatilities, payoffs, etc
I’ll be creating two financial analysis tools with a single Jupyter notebook: A financial planner for emergencies and retirement.
Analyze 40 S&P 500 sector-weighted stocks, evaluating portfolio strategies for return, risk, and the Sharpe ratio with Python (Pandas, NumPy, Matplotlib) in a Jupyter Notebook.
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