michaelrdionne / fintech-workspace

UC Berkeley Extension - Fintech

Module-1 Financial Programming with Python

Module 2- Financial Programming with Python

Helpful ZSH commands

cd = changes directory
ls = lists files in directory
mkdir <foldername> = make directory
touch <filename> = creates a file
rm = removes a file
rm -rf = removes a directory
mv = moves a file
cp = copies a file
pwd = prints working directory
cat = prints contents of a file
open . = opens the current folder
code . = opens the current folder in VSC
cd ~ = changes to home directory
cd .. = changes to parent directory

Module-1

Variables (assign data, formatting as strings)

Hello Variable World

Using lists (data structures, containers,indexing & slicing, add to, operations)

Listing assets

Using dictionaries (key-value pairs, create & delete items )

401k shuffle

Conditional Logic & truth testing in Python (booleans & if-else, comparison & logical operators)

Conditional Statement

Complex conditionals (if-else-elif, nested)

nested_conditionals

Data Driven Decisions (present & future value)

Split-Second Home buying,part 1

Python Functions (body, definition, calling)

Function Definition

A Definitive Buy

Making Functions Dynamic (function parameters, function arguments, return values from functions)

Function Arguments vs parameters

Returned Goods

Split-Second Home Buying,Part 2

Automation with Python (Iterators ("for" loops))

Racking up the Profits

Iterating Nested Data structures (nested containers, list of lists, CSV files)

1.6.5 Iterating Nested Data structures

1.6.6 Iterating CSV Files

Pathways to Success

Read & Write to CSV files

1.6.8 Read and Write to CSV files

Code for a loop (gif)

Pathways to Success 2

Write CSV Files

1.6.9 Write CSV Files

Automated equity Rounds

Module-1 Challenge (Valuing loans) Analyze loan data, financial calculations, filter lists of loans

Module-1 Challenge

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Module-2 Financial Applications with Python

Write Financial Calculations for a Loan qualifier (user stories)

Loan Qualifier Financial Calculations

Loan Qualifier Filtering Data

Functions (Importing, modular coding)

Loan Qualifier Modular Coding

Intro to Python Fire

CLI Random Clothes picker

Adding Fire to the loan qualifier app

Add questionary to the loan qualifier app

Add questionary to the loan app

Creating the loan qualifier README

loan qualifier README

Module-2 Challenge

Module-2 Challenge

Pseudocoding

''' def count_the_vowels(str): # initialize a counter variable to 0 # loop through each character in the string # if the char matches one of the vowels in uppercase or lowercase # increment counter by one # return the counter '''

Pseudocoding

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Module-3 Financial Applications with Pandas

Series & Dataframes in Pandas (Import data, relative path)

Relative Paths JPG

Import Data

Importing the Vix

Fix Column Headers (add column headers & names, rename columns)

3.1.7 Fix column headers

Headerless Horseman

Fix Rows (set_index function)

3.1.9 Fix Rows

Set index function png

Auto set index function by pandas png

Read data from csv file & declare a Datetimeindex

Intro to Data Preparation (Dirty data, missing data, isnull (mean, percentage)

3.2.2 Missing data

Handle missing data (dropna, fillna)

3.2.3 Handle missing data

Missing Money

Handle Duplicated Data

3.2.5 Handle duplicated data

3.2.6 Handle Additional Dirty Data (dtypes, str.replace, loc/iloc, astype (convert strings to numbers), duplicated, drop_duplicates)

3.2.6 Handle additional dirty data

Dollars & Change

Big Picture Analysis (generate summary statistics, describe function, Matplotlib, simple plot, line plot of behavior over time (NumPy "random" function), box plot, )

Pandas "Describe" function PNG

3.3.2 Summary Statistics

Visualize the VIX

Targeted Analysis (location functions (iloc/loc), integer based location, select rows from a huge dataframe, histogram)

3.3.4 Do a targeted analysis

Rowing for Yield

3.3.6 Select Columns (select rows ([row,column]), )

3.3.6 Select Columns

Rowing for Yields Redux

3.3.8 Use Conditional Selection (boolean expression/filters, conditional statements (keep positive and drop negative numbers), comparison operators, logical operators )

Boolean Filter png

3.3.8 Use Conditional Selection

Python comparison operators png

Python logical operators png

Banking Bonanza

3.4.1 Time series analysis (index_col, Parse_date, )

Collect the Bitcoin Data

3.4.4 Prepare the BTC Data (handle missing values, duplicated, describe function, summary stats, )

3.4.7 Analyze the BTC Data via Plot Visualizations (overlay plots, 'loc' function

Bitcoin Summary_Statistics

3.4.7 Analyze the BTC Data via Plot Visualizations (overlay plots, 'loc' function)

BTC Activity: Month Week Day

3.4.12 Arbitrage Analysis (measure the spread, cover the trading costs, calculate profit in dollars and drop null values, profit sum, plot the profit, cumsum)

3.4.12 Arbitrage Analysis

Module 3 Challenge (Arbitrage Opportunities Bitstamp Vs Coinbase)

Module 3 Challenge (Arbitrage Opportunities Bitstamp Vs Coinbase)

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Module-4 Quantitative Analysis with Pandas

Calculating Return on Investment (ROI, )

Relat