Welcome to my project: Financial Analyzer

Hosted on AWS EC2: View Live Server

1/ Robo-advisor

Built a robo-advisor to recommend top 5 portfolios with the lowest risk & highest return based on users' input (initial investment, duration, target return).
Leveraged yfinance API to fetch and analyze historical stock prices for S&P 500 companies.
Calculated annual returns, annual risks, covariance matrix to measure stock correlations. and an efficient frontier.
Applied Modern Portfolio Theory (MPT) to simulate 10,000+ random portfolios
Identified top-performing portfolios based on Sharpe Ratios using Numpy for matrix operations.

2/ Credit Risk Analysis

Trained K-Nearest Neighbors, Decision Tree, Random Forest models using Python and Scikit-learn with accuracy ~ 74% to predict loan risk based on loan duration, age, installment percentage, and customers' existing credit.

3/ General back-end technologies

Name		Name	Last commit message	Last commit date
Latest commit History 39 Commits
models		models
static		static
templates		templates
LICENSE		LICENSE
README.md		README.md
annual_returns.csv		annual_returns.csv
app.py		app.py
company_tickers.csv		company_tickers.csv
cov_matrix.csv		cov_matrix.csv
credit-risk-dataset.csv		credit-risk-dataset.csv
decision_tree_model.pkl		decision_tree_model.pkl
decisiontree.ipynb		decisiontree.ipynb
knn.ipynb		knn.ipynb
knn_model.pkl		knn_model.pkl
modern_portfolio_theory.ipynb		modern_portfolio_theory.ipynb
mpt.py		mpt.py
random_forest_model.pkl		random_forest_model.pkl
randomforest.ipynb		randomforest.ipynb
requirements.txt		requirements.txt
robo.js		robo.js
s&p500.csv		s&p500.csv
scrape.ipynb		scrape.ipynb
stock_prices.csv		stock_prices.csv