Introduction to Data Science in Finance
- Capital Markets: Participants, Asset Classes
- Financial Math: Compounding, AAR (Accounting Rate of Return), Present Value, Bond Math
- Stock returns (In connection to Random Distributions): Mean, Standard Deviation, Probability, Gaussian distributions, Z-scores etc
- Lab: Download Prices, Price adjustments, Connection to Gaussian
Fundamentals of Valuation
- Financial Statement Analysis
- Risk, Return, and Portfolio Theory
- Equity Valuation
- Bond Markets, Valuation, and Risk Management
Introduction to Machine Learning
- Mutual Funds & Performance Attribution: Linear Regression, Understanding Beta, CAPM (Capital Asset Pricing Model)
- Introduction Classification: Logistic Regression (Bankruptcy prediction, Loan defaults)
- Feature Engineering, Outliers & Regularization
- Index Tracking Mutual Fund – Regularization
Unsupervised Learning and Optimization
- Unsupervised Learning – Portfolio Selection: PCA, Clustering
- Optimization: Markowitz Allocation
Advanced Machine Learning Methods
- Other ML algorithms: KNN (K-Nearest Neighbors), Recommendation Engine, Decision Trees, Association Rules, Ensemble Algorithms
- Text & Sentiment Analytics: Twitter sentiment, News Sentiments
- Visualization
- Neural Networks
Understanding Market Behavior: Market Microstructure, Behavioral Finance & Derivatives
- Options, Futures, and Other Derivatives
- Derivatives Strategies and Valuation
- Efficient Markets and Behavioral Finance
- Market Microstructure
- Technical Analysis
Algorithmic Trading
- Algorithmic Trading: Indicators, Backtesting, Position sizing, Stops, ML in Algorithmic Trading
- Options Strategies
Time Series and Forecasting Methods
- Forecasting: Macroeconomic Variables, Arima, FB (Facebook) Prophet, VAR (Vector Autoregression), LSTM (Long Short-Term Memory) & CNN (Convolutional Neural Network)
Blockchain and Big Data Engineering
- Introduction to Blockchain
- Big Data Engineering
Capstone Projects
- Stock Selection Algorithm using Fundamental Data
- Adjusting Leverage in a Portfolio using AI based methods
- Smart Portfolio Allocation Strategy
- Stock Price Prediction using ML methods
- Build Volatility Forecasting Algorithm using Time Series methods
- Automated Stock Trading Using ML Algorithms
- NSE Stock Market Prediction Using Deep-Learning Models
- Time Series Forecasting of a company’s Stock Prices Using LSTM
- And more…
Case studies and Hands-on Labs
- Creation of Index Tracking Funds
- Anti-money Laundering
- Robo-advisors
- Risk Monitoring in Hedge Funds
- Forecasting of Economic Series