Time Series Analysis and Modelling Course

7 years ago Posted By : User Ref No: WURUR14383 0
  • Image
  • TypeTraining or Development Class
  • Image
  • Location Nairobi, Kenya
  • Price
  • Date 23-10-2017 - 27-10-2017
Training or Development Class Title
Time Series Analysis and Modelling Course
Event Type
Training or Development Class
Training or Development Class Date
23-10-2017 to 27-10-2017
Location
Nairobi, Kenya
Organization Name / Organize By
Indepth Research Services
Organizing/Related Departments
Research
Organization Type
Organization
Training or Development ClassCategory
Both (Technical & Non Technical)
Training or Development ClassLevel
International
Related Industries

Education/Teaching/Training/Development

Research/Science

Business Development

Economics

OTHERS

Location
Nairobi, Kenya

Event: Time Series Analysis and Modelling Course

Venue: Indepth Research Services, Nairobi, Kenya.

Event Date: 23rd – 27th October, 2017.

NITA CERTIFIED

INTRODUCTION

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 the Stata Software.

DURATION

5 Days

WHO SHOULD ATTEND?

Participants are expected to have attended the previous course on Data Management, Graphics and Statistical analysis using Stata or to be familiar with 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.

Tailor-Made Training

This training can also be customized for your institution upon request to a minimum of 4 participants. You can have it delivered in our training centre or at a convenient location.

How to participate

  • Tailors make your course.
  • Register individual.
  • Register as a group.
  • Become one of our partners.
  • Purchase software’s
  • Frequently asked Questions (FAQ’s)

View related courses

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For further inquiries, please contact us on Tel: +254 715 077 817, +254 (020) 211 3814, +254 731240802, +254 735331020.

Others Details

Accommodation is arranged upon request. For reservations contact the Training Officer.

Registration Fees
Available
Registration Fees Details
USD 1100
Registration Ways
Email
Phone
Website
Address/Venue
  Nairobi , Kenya. 
Official Email ID