AF7005 - Financial Econometrics and Forecasting II

What will I learn on this module?

This module will enhance your knowledge and skills of empirical finance that you will have gained in the first semester module “Financial Econometrics and Forecasting I”. You will be able to understand and apply both contemporary and traditional econometric methods at an advanced level. You will appreciate and understand other econometric techniques based on the violations of classical OLS assumptions. For this the module consists of areas where you will be taught advanced regressions and ARCH models (Nobel Prize was awarded in 2003 to Robert F. Engle for his contribution and research in this area) that are very useful in forecasting returns in financial markets. Compared to the module “Financial Econometrics and Forecasting I”, this module will be more empirically rigorous. This module will involve a large analytical project that uses real world financial data and estimation of various econometric models, which you will conduct in the computer lab.

The content of the module that you will study comprises four key blocks which are listed below.
Block 1- Violation of classical assumptions of OLS method: Autocorrelation, Heteroscedasticity and Multicollinearity.
Autoregressive Conditional Heteroscedasticity (ARCH) models and other volatility models.
Block 2- Introduction to multivariate models, modelling long-run relationships and models involving limited dependent variables.
Block 3 - Models involving limited dependent variables (special cases) and event study approaches
Block 4 – Introduction to advanced topics in econometrics such regime switching models. Applying the research methods learned in Financial Econometrics 1 and 2 to conduct empirical research in Finance and Economics (Preparing for final Dissertation)

How will I learn on this module?

The module is supported by a teaching and learning plan which outlines the formal sessions, workshops in IT lab, together with tutor-directed study and independent reading. The emphasis will be on you having high levels of engagement in understanding theory, collecting and analysing real world data and interpreting results for forecasting financial markets. Independent learning will use both theory in finance and application of statistical software. You can therefore expect the reflective-practitioner approaches to learning that are both knowledge and skills based which are embedded in all delivery sessions.

The assessment requirements will engage you with a wide range of scholarly sources to evaluate your effectiveness and currency and subsequently communicate them in exam and assignment.

Your directed learning will centre upon a range of activities including pre-reading, preparation for interactive activities, practice in IT lab and use of the discussion board to learn and share knowledge.

Your independent learning will centre upon you identifying and pursuing areas of interest in relation to econometrics and financial forecasting and by providing deeper/broader knowledge and understanding of the subject through a range of learning activities that will include extended reading, reflection, research, statistical calculations etc.

Critical reflection on knowledge, experience and practice underpins the learning and teaching philosophy that you will be exposed to along with the explicit development of competence.

How will I be supported academically on this module?

The module will comprise lectures and IT lab based workshop activities where you will have access to real world financial data. IT lab workshops will teach you the use of the econometric package (EViews) in which you will be provided the data and information on key financial forecasting exercises.

You will also have access to Northumbria University’s library and databases. Academic content and delivery will be enhanced through opportunity for guest practitioner expert input. In addition, there will be an induction programme to introduce you to the university and the course. You will also be assigned a personal tutor to provide pastoral support and guidance throughout the course. Additionally, you will be supported by Academic Skills Unit (ASK), the feedback process of summative and formative assessments. At the start of the module, you will also be provided the module teaching and learning plan which details the delivery structure and activities.

The eLP will house lecture and workshop materials relating to the module. Additionally, you will find recorded lecture videos after each class that would be uploaded in the eLP to support you in your independent study. Where available you will also be given individual login access to use Bloomberg and training will be provided to learn various Bloomberg commands. Moreover, the use of Bloomberg is fully supported by a comprehensive range of materials which are housed on the eLP for your independent learning.

You will be provided with a wide-ranging electronic reading list that comprises of academic journal articles, web pages and youtube videos that showcase the application of various quantitative techniques presented in the module.

What will I be expected to read on this module?

All modules at Northumbria include a range of reading materials that students are expected to engage with. The reading list for this module can be found at:
(Reading List service online guide for academic staff this containing contact details for the Reading List team –

What will I be expected to achieve?

Knowledge & Understanding:
• To be able to evidence advanced knowledge of the theories and methods of modern financial econometrics. [MLO1]
• To be able to make forecast based on informed and critical judgment that are supported by application of valid econometric models. [MLO2]
• To be able to critically apply both emerging and more traditional forecasting methodologies to real world financial problems. [MLO3]

Intellectual / Professional skills & abilities:
• To be able to choose between alternative forecasting techniques. [MLO4]
• To be able to advance use of econometric software for the statistical analysis of data. [MLO5]

Personal Values Attributes (Global / Cultural awareness, Ethics, Curiosity) (PVA):

How will I be assessed?

The module will be assessed by one summative assessment of 3000 words which will have 100% weightage.
(MLOs 1-5).
The assignment needs to be submitted electronically via electronic learning platform.
In this summative assignment there will be three sections. Each section will assess different topics within the module, which will require you to collect and clean data, perform preliminary data analysis, perform necessary econometric analysis, present results of the econometric models and discuss them critically within the context of existing literature.
Summative feedback mechanism will ensure that you obtain timely and adequate feedback on their works. In the case coursework, feedback will be provided in writing for each section of the questions.





Module abstract

You will develop the knowledge and skills of empirical finance which will enable you to understand and apply both contemporary and traditional econometric methods at an advanced level. The module consists of advanced topics useful in forecasting prices of financial markets such as linear regression and ARCH models (Nobel Prize was awarded in 2003 to Robert F. Engle for his contribution and research in this area). In addition to time series techniques, you will also learn on panel data regression method which is important to study different complicated behavioural models in finance. As such you will learn and master various empirical approaches in finance used by practitioners, alongside important skills of using econometric software. You will work in the IT lab each week making extensive use of Bloomberg terminals, Microsoft Excel and econometric software (Eviews) where you will be guided by qualified tutors.

Course info

Credits 20

Level of Study Postgraduate

Mode of Study 2 years full-time (with advanced practice in second year)
2 other options available

Department Newcastle Business School

Location City Campus, Northumbria University

City Newcastle

Fee Information

Module Information

All information is accurate at the time of sharing.

Full time Courses starting in 2023 are primarily delivered via on-campus face to face learning but may include elements of online learning. We continue to monitor government and local authority guidance in relation to Covid-19 and we are ready and able to flex accordingly to ensure the health and safety of our students and staff.

Contact time is subject to increase or decrease in line with additional restrictions imposed by the government or the University in the interest of maintaining the health and safety and wellbeing of students, staff, and visitors, potentially to a full online offer, should further restrictions be deemed necessary in future. Our online activity will be delivered through Blackboard Ultra, enabling collaboration, connection and engagement with materials and people.


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