Update README.md

README.md

@@ -25,15 +25,17 @@ This repository includes the following:
   Techniques for visualizing, decomposing, and understanding temporal structures in financial time series.
 
 - **Classical Forecasting Methods**  
-  Models such as:
+ 
   - ARIMA / SARIMA  
   - Facebook Prophet
   - Vector Auto Regression
   - Arch/Garch for volatility modeling
+  - Single and Double Exponential Smoothing
+  - Holt Winters Exponential Smoothing
   
 
 - **Machine Learning Approaches**  
-  Implementation of:
+
   - Random Forests
   - XGBoost
   - Long Short Term Memory
@@ -42,7 +44,11 @@ This repository includes the following:
   Lag features, rolling statistics, seasonal indicators, and date-based encodings.
 
 - **Model Optimization and Evaluation**  
-  Grid-search-cv , Randomized-search-cv, cross-validation for time series, and performance metrics (MAE, RMSE, MAPE).
+  Grid-search-cv , Randomized-search-cv, Training with cross-validation, and performance metrics (MAE, RMSE, MAPE).
+
+
+- **Additional concpets covered**
+  Grangers causality test, Parameter selection with AIC , BIC 
 
 ---
 
@@ -55,4 +61,4 @@ The notebooks primarily work with **financial datasets**, such as:
 - Foreign Exchnage rates.
 - Inflation rates.
 - Cryptocurrency price histories.
-- Sales datasets
+- Sales and Revenue datasets