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benfords_law

This repository contains lecture slides and Python code examining Benford's Law and when one should or should not expect Benford's Law to hold. The lecture slides also cover techniques from data science applied to financial statement auditing.

chess_app

Chess.com Historical Games Data Analyses

cramer_reddit_analysis

Data re-examining a Reddit thread about Jim Cramer's stock selections.

earnings_and_returns

A replication and extension of MacKinlay's "Event Studies in Economics and Finance" Journal of Economic Literature (1997).

final-grades

Python code to calculate final grades after dropping the lowest quiz score and replacing missing midterms with the final exam score

garmin

Python code to analyze Garmin Connect fitness data

git_example

going_concern

Python code to identify going concern audit report modifications from Audit Analytics data

listener

Automated "listener" or "polling" program connected to an ETL project I worked on for an oil and gas company.

machine_learning_introduction

Lecture slides, Excel files, and a Jupyter Notebook for an introduction to machine learning talk.

p_value_monte_carlo

See this blog post https://robsonglasscock.wordpress.com/2020/11/13/p-values-monte-carlos-and-classical-hypothesis-testing/ for the background of this code.

pandas-workshop

An introductory workshop on pandas with notebooks and exercises for following along.

ploomber

The fastest ⚡️ way to build data pipelines. Develop iteratively, deploy anywhere. ☁️

plotly-dash

pycon_debug

PyCon tutorial on debugging

python-object-oriented-programming---4th-edition

Code Repository for Python Object-Oriented Programming - 4th edition, Published by Packt

python_pandas_primer

Python code and stock market data used as a gentle introduction to Python and pandas for graduate students in ACC 5200.

returns_earnings_announcements

Python code to merge financial data from earnings announcements with stock price data. Both datasets are from Sharadar and obtained via Quandl's API. The code considers earnings announced on non-trading days prior to the merge and includes a function that takes a reserarcher-specified number of days for the event window to calculate the returns.

scaling-bias

Mathematical proofs and Monte Carlo simulations which show that popular forms of scaling/deflating induce bias

sjr_revenue_analysis

This repository contains anlayses related to SJR's average revenue per customer in the Wireless and Wireline segments. It also contains data visualizations of revenue, segmented revenue, and customer groups over time. The analyses use time-series data (quarterly frequency) to forecast forward revenue. A training set and test set are used for forecasting model selection where the test set includes the four most recent quarters as of 3/3/21. A .py and .ipynb are provided as well as hand collected data from 10-Q's and 10-K's.

sp500_vs_all

This respository contains Python code to calculate how often publicly traded firms have stock prices appreciate year over year.

wash_park

Analysis of Washington Park home sales in Denver, CO to homeowners vs. developers 2020- 2023.

wash_park_scrape

Web scraper for the Denver Property Taxation and Assessment System

web_scraping_sec_edgar

Python code to web scrape a Balance Sheet from EDGAR and convert into a pandas DataFrame

web_scraping_sec_edgar_part_2

Web scraping 10-K's exploiting the fact that the financial statements are after the audit opinion and before the notes to the financial statements.

web_scraping_sec_edgar_part_3

The Jupyter Notebook contains an example of scraping SEC EDGAR annual reports (i.e., 10-K's) to pull Net Income from the Income Statement of each company.