SAS for Finance

Table of Contents

1. Introduction to Time Series modelling in financial industry
2. Forecasting stock prices and portfolio decisions using Time Series data (Stocks Forecasting)
3. Build Probability of Default (PD) model to adhere to BASEL norms (Risk Management)
4. Revenue forecasting to manage budgets/operational strategies (Budget and Demand Forecasting)
5. Inflation forecasting for financial planning (Econometric Modelling)
6. Manage customer loyalty using Time Series data (Customer Loyalty)
7. Pattern Discovery in Product Purchases (Segmentation)