Name		Name	Last commit message	Last commit date
Latest commit History 29 Commits
.gitignore		.gitignore
ACF_PACF_with_stock_returns.ipynb		ACF_PACF_with_stock_returns.ipynb
ARIMA.ipynb		ARIMA.ipynb
ARIMA_continued.ipynb		ARIMA_continued.ipynb
PACF_and_ACF.ipynb		PACF_and_ACF.ipynb
README.md		README.md
SimpleMovingAverage.ipynb		SimpleMovingAverage.ipynb
Warmup.ipynb		Warmup.ipynb
adjusted_close.ipynb		adjusted_close.ipynb
alpha_and_beta.ipynb		alpha_and_beta.ipynb
arima.ipynb		arima.ipynb
ewma_holtwinters.ipynb		ewma_holtwinters.ipynb
fin_data_stats.ipynb		fin_data_stats.ipynb
financial_basics_getdata.ipynb		financial_basics_getdata.ipynb
financial_basics_understanding.ipynb		financial_basics_understanding.ipynb
requirements.txt		requirements.txt
stationarity.ipynb		stationarity.ipynb

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financial_engineering

This repo includes the files I used for the Financial Engineering and Artificial Intelligence in Python course from Lazy Programmer.

Introduction and Basics

Warmup.ipynb: notebook with basic warmup exercises
financial_basics_getdata.ipynb: collect needed data for this course
financial_basics_understanding.ipynb: basic manipulations of stock data
adjusted_close.ipynb: review of close vs adjusted close prices
fin_data_stats.ipynb: main notebook for section 2 on financial data statistics
alpha_and_beta.ipynb: how to calculate alpha and beta in a simple model

Time Series Analysis

SimpleMovingAverage.ipynb: how to calculate simple moving averages using a rolling window
ewma_holtwinters.ipynb: how to use EWMA and Holt-Winters models
arima.ipynb: how to use ARIMA models
stationarity.ipynb: how to run tests for stationarity of a time series