Price (from): €100 / dayShare Share
I have eight years of comprehensive experience in compiling, analyzing, and modeling economic and financial data to guide policy decision-making. In the past, I had the opportunity to be a team leader and member of several modeling projects in a different organization such as Asian Development Bank, World Bank, Ministry of Economic Development and Ministry of Finance of Azerbaijan, as well as in private firms and banks. Currently, I work in Modelling and forecasting division at the Central Bank of Azerbaijan. I am responsible for developing and upgrading modeling techniques to improve forecast projections, supervising statistical accuracy of the database, and making regular updates. I received my M.A. degree in Economics at Williams College (U.S.A). Besides my master studies, I also attended several forecasting courses held by the IMF.
About the training
#very practical #real world problems #user-friendly software
In this course, you will learn to predict a firm-level (as well as macro, financial) variables such as sales, revenues, liabilities, and assets, and to create statistical models and use them to estimate responses to marketing campaigns, economic policies, and other similar events. This course gives a rigorous foundation in the estimation of econometric models and their application for forecasting and event analysis in banks, firms, ministries, and other public and private organizations. You will learn from hands-on demonstrations of model-building, forecasting, and event analysis, using data sets from a wide variety of sources. Practical exercises and applications will be conducted using EViews—a popular software for estimating and simulating forecasting models on Windows. The training is based on five major aspects of empirical modeling and forecasting. Initially, the statistical characteristics of economic indicators are analyzed. Then the methodology is selected and compiled according to the nature of the indicators. Using the chosen method we will evaluate the model and carry our scenario analyzes. Finally, we will discuss the results and examine the forecasting error. The acquired knowledge will help you to answer the following questions:
• What are the sales projections for next month?
• What are the factors that influence the effectiveness of employees?
• How do marketing or advertising campaigns affect the company's profitability?
• Credit risk stress testing: How will the bank credit portfolio behave to unexpected exchange rate shock? What are the factors affecting the probability of default?
• How will sales and revenues change if prices increase by one percentage point?
• Which of the two financial assets is more profitable?
• Which factors determine the demand for real estate?
Evaluation of properties of time series data
Evaluation of econometric models
Ex-ante and ex-post forecasting techniques
Comparison of models based on forecasting performance
Review of statistics
An overview of econometric modeling and prediction
Single variable regression models
Multivariable regression models
Discrete models: Probit and Logit
Properties of time series variables
Modeling uncertainty: ARCH and GARCH models
Vector Autoregression Models (VAR)
Forecast uncertainty analysis and forecasting
More trainings of the trainer
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