Dear All,
Indepth Research Services would like to invite you to take a course in Time Series Data Analysis and Modelling using Stata. The course will show how economic and financial time series can be modeled and analyzed. The aim is to provide understanding and insight into the methods used, as well as explaining the technical details. Statistical modeling will be demonstrated using the Stata Software and participants will be given the opportunity to use Stata in class. Statistical modeling will be demonstrated using Stata Software.
OBJECTIVES
- Understand the definitions, features and objectives of time series modeling.
- Understand descriptive analysis of time series, plots, aggregation, smoothing and regression techniques.
- Understand and conduct periodic regression and ARIMA modeling using stationary time series.
- Using ARIMA modeling (Box & Jenkins), understand and use auto-correlation functions and partial auto-correlation functions to study how much an observation at a given time is related to observation at previous lags.
TOPICS TO BE COVERED
- Introduction
- Stationary time series
- Unobserved components and signal extraction.
- Time Series Models
- ARIMA models
- Structural time series models
- Explanatory variables and intervention analysis
- State space models and the Kalman filter.
- Signal extraction.
- Missing observations and other data irregularities
- Spectral analysis
- Spectra of ARMA processes; stochastic cycles; linear filters; estimation of spectrum
- Trends and cycles
- Analysis of the effects of moving average and differencing operations
- Hodrick-Prescott and band-pass filters. Seasonality
- Multivariate time series models
- Common trends and co-integration; control groups
- Nonlinear models. Financial econometrics; distributions of returns, stochastic volatility and GARCH
- Dynamic conditional score models
- Multivariate volatility models.
Register now
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For any enquiries, feel free to engage us at [email protected] or contact us on (+254) 715 077 817 or +250 789 621 067
Best regards,
Indepth Research Services