Brief Overview of the Programme

Time series analysis is a powerful tool for understanding patterns in data that evolve over time. In today’s business environment, decision-making often depends on interpreting such temporal data—whether it is stock prices, sales forecasts, demand planning, or economic indicators. This FDP/MDP aims to bridge the gap between theoretical knowledge and practical applications, enabling participants to apply modern time series techniques to real-world business problems using industry-relevant tools.

Programme Objectives :

• To provide participants with foundational and advanced knowledge of time series data and models.
• To introduce statistical and econometric techniques for forecasting and decision-making.
• To demonstrate the application of time series methods in finance, operations, and business analytics.
• To equip participants with practical skills in software tools such as Gretl and Python for Time Series Analysis.
• To enable participants to interpret results effectively and translate them into actionable business insights.

Contents of the Programme :

• Introduction to Time Series Data and its Characteristics.
• Stationarity, Trend, and Seasonality.
• Autoregressive (AR), Moving Average (MA), and ARIMA Models.
• Vector Autoregression (VAR) and Cointegration.
• Volatility Modelling: ARCH & GARCH Models.
• Forecasting Methods and Accuracy Measures.
• Applications in Financial Markets, Macroeconomics, and Business Forecasting.
• Hands-on Practice using GRETL and Python.