Quasi Score-Driven Models Course


Quasi Score-driven models course designed to cater to the needs of individuals who want to enhance their knowledge and skills in score-driven modeling. Prior knowledge of statistical modeling and programming is beneficial for attendees to fully grasp the concepts covered in the course.


10 Days

Who Should Attend?

  • Researchers and analysts.
  • Policy analysts and policymakers.
  • Econometricians and statisticians.
  • Financial Analysts.

Course Objectives

  • Understand the fundamentals of score-driven models: The course will provide a comprehensive overview of the basic principles and concepts underlying score-driven models.
  • Explore the applications of score-driven models: Participants will learn about the diverse applications of score-driven models in various fields, such as finance, economics, and time series analysis.
  • Develop practical skills in implementing score-driven models: The course will focus on hands-on learning, equipping attendees with the necessary tools and techniques to effectively implement score-driven models in real-world scenarios.
  • Gain insights into model estimation and inference: Participants will learn about the estimation methods and statistical inference techniques associated with score-driven models, enabling them to interpret and evaluate model results.
  • Analyze and interpret model outputs: The course will emphasize the interpretation and analysis of model outputs, helping attendees derive meaningful insights and make informed decisions based on the results obtained from score-driven models.
  • Stay updated with the latest advancements: Participants will be exposed to recent developments and advancements in score-driven models, ensuring they stay up-to-date with the latest trends and techniques in this field.

Course outline

Module 1: Introduction To Quasi Score-Driven Models

  • Overview of score-driven models
  • Understanding the motivation behind quasi score-driven models
  • Applications and advantages of quasi score-driven models

Module 2: Time Series Analysis And Modelling

  • Review of time series analysis concepts
  • Introduction to time series models
  • ARIMA models and their limitations

Module 3: Introduction To Score-Driven Models

  • Understanding the concept of score-driven models
  • Score-driven models for time series forecasting
  • Implementation of score-driven models in practice

Module 4: Quasi Score-Driven Models Framework

  • Introduction to the quasi score-driven models framework
  • Advantages and limitations of the quasi score-driven approach
  • Modelling techniques and algorithms for quasi score-driven models

Module 5: Estimation And Inference

  • Estimating parameters in quasi score-driven models
  • Inference procedures for model evaluation
  • Hypothesis testing and model selection in the quasi score-driven framework

Module 6: Advanced Topics And Applications

  • Advanced topics in quasi score-driven models
  • Applications of quasi score-driven models in various fields
  • Case studies and real-world examples


Enroll for this Course

We are proud to offer this course in a variety of training formats to suit your needs.


Enroll for a Face-to-Face (In-Person) Class

We use the highest quality learning facilities to make sure your experience is as comfortable as possible.

Register Here

Enroll for a Virtual (Zoom) Class

Join a scheduled class with a live instructor and other delegates.

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Enroll for an Online Self-Paced Class

Keep track of your own progression throughout your course and ensure continuous improvement.

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Benefits of Taking a Course at IRES


Our courses are carefully curated to keep you abreast of latest industry trends, technological advancements, and best practices. We employ a variety of teaching methodologies, including hands-on workshops, case studies, and interactive sessions, all aimed at fostering an engaging and effective learning environment. Our expert instructors bring a wealth of knowledge and real-world experience, providing our clients with insights that can be immediately applied in their professional lives.


Our courses serve as a vibrant platform for professionals to connect and engage with a diverse community of peers, industry leaders, and experts. By participating in our programs, you gain access to an invaluable network that spans across various sectors and geographical boundaries. This networking aspect is not just about forming professional relationships; it's about creating a supportive ecosystem where ideas, opportunities, and collaborations can flourish.


Our courses are designed to challenge and inspire professionals to step out of their comfort zones and explore new horizons. Through a combination of theoretical knowledge and practical application, our programs help professionals refine their existing skills and acquire new ones, making them more versatile and competitive.

FAQs & Course Administration Details:

This training can also be customized to suit the needs of your institution upon request. You can have it delivered in our IRES Training Centre or at a convenient location. For further inquiries, please contact us on Phone: +254 715 077 817 or Email: [email protected].
The instructor led trainings are delivered using a blended learning approach and comprise of presentations, guided sessions of practical exercise, web-based tutorials and group work. Our facilitators are seasoned industry experts with years of experience, working as professional and trainers in these fields. All facilitation and course materials will be offered in English. The participants should be reasonably proficient in English.
Upon successful completion of this training, participants will be issued with an Indepth Research Institute (IRES) certificate certified by the National Industrial Training Authority (NITA).
Payment should be transferred to IRES account through bank on or before start of the course. Send proof of payment to [email protected].
Accommodation and airport pickup are arranged upon request. For reservations contact the Training Officer. Email: [email protected] Phone: +254 715 077 817.