RobsonGlasscock
Quantitative Analyst @ Federal Reserve Bank of Richmond
Federal Reserve Bank of RichmondCharlotte, NC
Pinned Repositories
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.
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).
Going_Concern
Python code to identify going concern audit report modifications from Audit Analytics data
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
SP500_vs_All
This respository contains Python code to calculate how often publicly traded firms have stock prices appreciate year over year.
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.
RobsonGlasscock's Repositories
RobsonGlasscock/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.
RobsonGlasscock/Python_pandas_Primer
Python code and stock market data used as a gentle introduction to Python and pandas for graduate students in ACC 5200.
RobsonGlasscock/Earnings_And_Returns
A replication and extension of MacKinlay's "Event Studies in Economics and Finance" Journal of Economic Literature (1997).
RobsonGlasscock/Going_Concern
Python code to identify going concern audit report modifications from Audit Analytics data
RobsonGlasscock/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.
RobsonGlasscock/Cramer_Reddit_Analysis
Data re-examining a Reddit thread about Jim Cramer's stock selections.
RobsonGlasscock/Scaling-Bias
Mathematical proofs and Monte Carlo simulations which show that popular forms of scaling/deflating induce bias
RobsonGlasscock/SP500_vs_All
This respository contains Python code to calculate how often publicly traded firms have stock prices appreciate year over year.
RobsonGlasscock/Web_Scraping_SEC_EDGAR
Python code to web scrape a Balance Sheet from EDGAR and convert into a pandas DataFrame
RobsonGlasscock/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.
RobsonGlasscock/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.
RobsonGlasscock/chess_app
Chess.com Historical Games Data Analyses
RobsonGlasscock/Final-Grades
Python code to calculate final grades after dropping the lowest quiz score and replacing missing midterms with the final exam score
RobsonGlasscock/Garmin
Python code to analyze Garmin Connect fitness data
RobsonGlasscock/git_example
Examples of various merge conflicts and a fast forward merge.
RobsonGlasscock/Listener
Automated "listener" or "polling" program connected to an ETL project I worked on for an oil and gas company.
RobsonGlasscock/Machine_Learning_Introduction
Lecture slides, Excel files, and a Jupyter Notebook for an introduction to machine learning talk.
RobsonGlasscock/marisi_practice
RobsonGlasscock/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.
RobsonGlasscock/pandas-workshop
An introductory workshop on pandas with notebooks and exercises for following along.
RobsonGlasscock/ploomber
The fastest ⚡️ way to build data pipelines. Develop iteratively, deploy anywhere. ☁️
RobsonGlasscock/Plotly-Dash
RobsonGlasscock/pycon_debug
PyCon tutorial on debugging
RobsonGlasscock/Python-Object-Oriented-Programming---4th-edition
Code Repository for Python Object-Oriented Programming - 4th edition, Published by Packt
RobsonGlasscock/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.
RobsonGlasscock/wash_park
Analysis of Washington Park home sales in Denver, CO to homeowners vs. developers 2020- 2023.
RobsonGlasscock/wash_park_scrape
Web scraper for the Denver Property Taxation and Assessment System