ICM283-Economic Modelling and Analysis of Shipping Markets

Module Provider: ICMA Centre
Number of credits: 10 [5 ECTS credits]
Terms in which taught: Spring term module
Non-modular pre-requisites:
Modules excluded:
Current from: 2020/1

Module Convenor: Dr Satya Sahoo

Email: satya.sahoo@reading.ac.uk

Type of module:

Summary module description:

Following the Introduction to Quantitative Methods for Finance module in the previous term, the primary objective of this module is to provide an application to the most common empirical methods used in the economic modelling and analysis of shipping markets. The module provides the students with the business modeling tools and skills necessary to conduct empirical analysis in shipping. Emphasis is placed on practical applications of the research techniques used in international shipping markets


It aims to learn students to use real shipping market data and dedicated software and apply the empirical assessment methods through case studies.

Assessable learning outcomes:

By the end of the module, it is expected that the student will be able to:

  • Understand the risk-return trade-offs and evaluate the sources of business risks in shipping.

  • Evaluate all available derivatives products and markets as well as the various underlying assets

  • Implement different hedging strategies with the use of derivatives products in shipping

  • Manage shipping related risk exposures

  • Develop , appraise and implement shipping related risk management strategies.

  • Price shipping derivatives and estimate optimal hedge ratios

  • Apply advanced option trading strategies in shipping

Additional outcomes:

The module also aims to encourage the development of IT skills and in particular the employment of data using statistical software packages (i.e. Eviews). Students will also improve their ability to translate abstract theoretical concepts into practical solutions to maritime economics problems.

Outline content:

1. Linear Regression Modelling and Applications in Shipping 

  • Simple linear regression 

  • The assumptions of the Ordinary Least Squares

  • Properties of OLS

  • Precision and standard errors

  • Hypothesis testing

  • Normal and Student-t probability distributions

  • Confidence intervals

  • Modelling Seasonality in Shipping Markets

  • Estimating Simpl e Piecewise Linear Functions

  • Markov Switching Models

  • Example of Markov Switching Models

2. Modelling Shipping Firms’ Stock Returns and Risk Factors

  • Generalizing the simple OLS model

  • How the parameters are calculated

  • Testing single hypothesis: the t-test

  • Testing multiple hypotheses: the F-test

  • The relationship between the t- and F-distributions

  • Goodness of fit statistics

3. The Information Efficiency of Shipping Markets 

  • Violations of the OLS assumptions 

  • Multicollinearity

  • Adopting the wrong functional form

  • Omission of an important variable

  • Inclusion of an irrelevant variable

  • Parameter stability tests

  • Stationari ty and Unit Root testing (DF, ADF, PP and KPSS tests)

  • Error-Correction Models (ECM)

  • Engle and Granger and Johansen cointegration tests

  • Vector Error Correction Models (VECM)

4. Modelling and Forecasting Shipping Factors

  • Strictly and weakly stationary process

  • White noise process

  • Moving Average (MA) processes

  • Autoregressive (A R) processes

  • Autoregressive Moving Average (ARMA) processes

  • The Box-Jenkins ARMA model

  • Information criteria for ARMA model selection

5. Economic Modelling and Cross-Effects between Freight and Commodity Markets

  • Simultaneous equations 

  • Exogeneity principal and Tests

  • Introduction to Vector Autoregressive (VAR) models

  • Cau sality tests

  • ARCH and GARCH Processes

  • Estimation of ARCH/GARCH Models

  • Extensions to the basic GARCH Model

  • Asymetric GARCH models (GJR and EGARCH)

  • Tests of asymmetries in Volatility

Brief description of teaching and learning methods:
Lectures will be used for the exposition of theory. Classes will be used to discuss non-assessed problem sets and case studies. There will be 5 2-hour lectures and 5 1-hour seminars. The techniques used to achieve the stated module objectives will consist of a combination of active teaching, question-answer sessions, class examinations, assignments and class discussions.

Contact hours:
  Autumn Spring Summer
Lectures 10
Seminars 5
Guided independent study:      
    Wider reading (independent) 10
    Wider reading (directed) 5
    Exam revision/preparation 10
    Preparation for tutorials 10
    Preparation for seminars 5
    Preparation for performance 5
    Preparation of practical report 10
    Group study tasks 30
Total hours by term 0 100 0
Total hours for module 100

Summative Assessment Methods:
Method Percentage
Written assignment including essay 70
Class test administered by School 30

Summative assessment- Examinations:

Summative assessment- Coursework and in-class tests:

Group assignment based on a research project. 3,000 words maximum. Assignment is given at the start of the term and its deadline is near the end of the term.

The in-class mid-term test takes place in the middle of the term and its duration is one hour long. It involves short essay questions.

Formative assessment methods:

Penalties for late submission:
Penalties for late submission on this module are in accordance with the University policy. Please refer to page 5 of the Postgraduate Guide to Assessment for further information: http://www.reading.ac.uk/internal/exams/student/exa-guidePG.aspx

Assessment requirements for a pass:
50% weighted average mark

Reassessment arrangements:

Reassessment by assignment 

Additional Costs (specified where applicable):
1) Required text books:
2) Specialist equipment or materials:
3) Specialist clothing, footwear or headgear:
4) Printing and binding:
5) Computers and devices with a particular specification:
6) Travel, accommodation and subsistence:

Last updated: 27 August 2020


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