Behavioural Finance

The details
Essex Business School
Colchester Campus
Postgraduate: Level 7
Sunday 17 January 2021
Friday 26 March 2021
25 June 2020


Requisites for this module



Key module for

MSC N39012 Finance and Investment,
MSC N39024 Finance and Investment

Module description

Behavioural finance has since the 1980s emerged as a new paradigm within finance. On the one hand, it rejects crucial tenets of mainstream finance such as the Efficient Market Hypothesis (EMH) on the basis that agents are less than fully rational and that arbitrage fails to eliminate mispricing.

It posits that people misapply Bayes' law and deviate from the traditional expected utility (EU) framework. It proposes e.g. a prospect theory framework as an alternative to model investor preferences.

On the other hand, it identifies market anomalies or regularities that are at odds with the EMH. These include profitability of momentum, reversals, and value strategies, stock market bubbles and crashes, abnormal returns to non-risk factors, delayed reaction to financial news such as earnings announcements, and overreaction and eventual corrections to measures of media tone and attention amongst others.

Behavioural finance uses ideas from psychology and aspects of limits to arbitrage to explain these. In this module, we will discuss psychological concepts and ideas most relevant to financial applications while at the same time emphasising the deviations from rational beliefs and rational preferences, and show how allowing for common human traits such as overconfidence, loss aversion, conservatism, anchoring, framing, mental accounting, representativeness, emotions, etc., and limits to arbitrage give us a better understanding of financial markets and the trading strategies of investors. We will consider applications in the context of the aggregate stock market, the cross-section of average returns, investor trading behaviour, financing and investment decisions of firms, savings behaviour, and behavioural investing amongst others.

Module aims

This module aims:
1. To provide alternative advanced theoretical models to neoclassical financial model that are based on the efficient market hypothesis
2. To understand how key cognitive biases and limits to arbitrage are introduced in advanced behavioural models of investment behaviour and asset prices
3. To examine the application of advanced concepts in behavioural finance to real world issues such as mergers and acquisitions and investment strategies
4. To present some latest research relating to both the theoretical developments in the field of behavioural finance along with the related empirical evidence
5. To build a bridge between academic research and investment practice

Module learning outcomes

On successful completion of the module, students will be able to:
1. Understand the implications of psychological biases and of limits to arbitrage for financial markets and asset prices
2. Understand the differences between behavioural and traditional explanations of anomalies in financial markets
3. Be familiar with the literatures in both empirical and theoretical developments of behavioural finance
4. Evaluate the theoretical and empirical evidence for behavioural models and hypotheses.

Module information

No additional information available.

Learning and teaching methods

This Module is normally delivered through: 2-hour lecture each week in the Spring term In academic year 2020-2021 the delivery is likely to be different and involve online learning.


  • Barberis, Nicholas; Thaler, Richard. (2003-2013) A survey of behavioural finance, Amsterdam: Elsevier/North-Holland. vol. 1B
  • Benartzi, Shlomo. (no date) 'Heuristics and Biases in Retirement Savings Behavior', in Journal of Economic Perspectives. vol. 21 (3) , pp.81-104
  • Barberis, Nicholas C. (no date) 'Thirty Years of Prospect Theory in Economics: A Review and Assessment', in Journal of Economic Perspectives. vol. 27 (1) , pp.173-96
  • Nicholas Barberis, Ming Huang and Tano Santos. (no date) 'Prospect Theory and Asset Prices', in The Quarterly Journal of Economics: Oxford University Press.
  • Barberis, Nicholas; Shleifer, Andrei; Vishny, Robert. (1998-9) 'A model of investor sentiment', in Journal of Financial Economics. vol. 49 (3) , pp.307-343
  • K. BRUNNERMEIER, MARKUS; NAGEL, STEFAN. (2004-10) 'Hedge Funds and the Technology Bubble', in The Journal of Finance. vol. 59 (5) , pp.2013-2040
  • Shleifer, Andrei; Vishny, Robert W. (1997-03) 'The Limits of Arbitrage', in The Journal of Finance. vol. 52 (1) , pp.35-55
  • Baker, Malcolm. (no date) 'Investor Sentiment in the Stock Market', in Journal of Economic Perspectives. vol. 21 (2) , pp.129-152
  • Baker, H. Kent; Nofsinger, John. R. (2002) 'Psychological Biases of Investors.', in Financial Services Review.
  • Barberis, Nicholas; Greenwood, Robin; Jin, Lawrence; Shleifer, Andrei. (2018-08) 'Extrapolation and bubbles', in Journal of Financial Economics. vol. 129 (2) , pp.203-227
  • J. Bradford De Long, Andrei Shleifer, Lawrence H. Summers and Robert J. Waldmann. (no date) 'Noise Trader Risk in Financial Markets', in Journal of Political Economy: The University of Chicago Press.
  • Hirshleifer, David. (August 2001) 'Investor Psychology and Asset Pricing', in The Journal of Finance. vol. 56 (4)
  • Ackert, Lucy F.; Deaves, Richard. (2010) Behavioral finance: psychology, decision-making, and markets, Mason, OH: South-Western/Cengage Learning.
  • Baker, Malcolm; Wurgler, Jeffrey. (2003-2013) 'Behavioural Corporate Finance: An Updated Survey', in Handbook of the economics of finance, Amsterdam: Elsevier/North-Holland. vol. 21
  • Barberis, Nicholas; Greenwood, Robin; Jin, Lawrence; Shleifer, Andrei. (2015-01) 'X-CAPM: An extrapolative capital asset pricing model', in Journal of Financial Economics. vol. 115 (1) , pp.1-24
  • Daniel, Kent; Hirshleifer, David; Subrahmanyam, Avanidhar. (1998-12) 'Investor Psychology and Security Market Under- and Overreactions', in The Journal of Finance. vol. 53 (6) , pp.1839-1885

The above list is indicative of the essential reading for the course. The library makes provision for all reading list items, with digital provision where possible, and these resources are shared between students. Further reading can be obtained from this module's reading list.

Assessment items, weightings and deadlines

Coursework / exam Description Deadline Weighting
Written Exam  In-class Test     100% 
Exam  120 minutes during Summer (Main Period) (Main) 

Overall assessment

Coursework Exam
50% 50%


Coursework Exam
0% 100%
Module supervisor and teaching staff
Dr Vivek Nawosah, email:
Vivek Nawosah & Thanos Verousis



External examiner

Dr Nikolaos Papanikolaou
Bournemouth University
Senior Lecturer in Accounting & Finance
Available via Moodle
Of 24 hours, 22 (91.7%) hours available to students:
2 hours not recorded due to service coverage or fault;
0 hours not recorded due to opt-out by lecturer(s).


Further information
Essex Business School

* Please note: due to differing publication schedules, items marked with an asterisk (*) base their information upon the previous academic year.

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