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1 Cognition, Decision Making, Language Khurshid Ahmad, Chair of Computer Science Trinity College, Dublin, IRELAND 11-13 th November 2013 Being intelligent being? Knowledge Intelligence Cognition

Knowledge Intelligence Cognition...notions of bounded rationality: the need to search for decision alternatives, the replacement of optimization by targets and satisficinggoals, and

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Page 1: Knowledge Intelligence Cognition...notions of bounded rationality: the need to search for decision alternatives, the replacement of optimization by targets and satisficinggoals, and

1

Cognition, Decision Making, Language

Khurshid Ahmad,

Chair of Computer Science

Trinity College, Dublin, IRELAND

11-13th November 2013

Being intelligent being?

Knowledge

Intelligence Cognition

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Being intelligent being?

Herbert Simon in conclusion to his Nobel Lecture (1978) said

that:

“Today, we have a large mass of descriptive data, from both

laboratory and field, that show how human problem solving

and decision making actually take place in a wide variety of

situations. A number of theories have been constructed to

account for these data, and while these theories certainly do not

yet constitute a single coherent whole, there is much in common

among them. In one way or another, they incorporate the

notions of bounded rationality: the need to search for decision

alternatives, the replacement of optimization by targets and

satisficing goals, and mechanisms of learning and adaptation.”

Simon, Herbert. (1978). RATIONAL DECISION-MAKING IN BUSINESS ORGANIZATIONS. Nobel Lecture

(http://nobelprize.org/nobel_prizes/economics/laureates/1978/simon-lecture.pdf)

Being intelligent being?

Herbert Simon in characterising bounded rationality notes that:

“it is now clear that the elaborate organizations

that human beings have constructed in the modern world to carry out the work of production and government can only be understood as machinery for coping with the limits of man’s abilities to comprehend and compute in the face of complexity and uncertainty”

Simon, Herbert. (1978). RATIONAL DECISION-MAKING IN BUSINESS ORGANIZATIONS. Nobel Lecture

(http://nobelprize.org/nobel_prizes/economics/laureates/1978/simon-lecture.pdf)

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Genesis of the term ‘bounded rationality’ in Simon

Simon, Herbert. (1978). RATIONAL DECISION-MAKING IN BUSINESS ORGANIZATIONS. Nobel Lecture

(http://nobelprize.org/nobel_prizes/economics/laureates/1978/simon-lecture.pdf)

Behavioral theories of rational

choice - theories of

bounded rationality

negatively sloping demand

curves could result from a wide

range of behaviors satisfying the

assumptions of

bounded rationality rather than those of utility

maximization.

Becker indicates that he denotes

as irrational “[A]ny deviation

from utility maximization.”

Thus, what I have called

“bounded rationality” is “irrationality” in

Becker’s terminology.

strong positive case for replacing

the classical theory by a model

of

bounded rationality begins to emerge when we

examine situations

involving decision making

under uncertainty and

imperfect competition.

Genesis of the term ‘bounded rationality’ in Simon

Simon, Herbert. (1978). RATIONAL DECISION-MAKING IN BUSINESS ORGANIZATIONS. Nobel Lecture

(http://nobelprize.org/nobel_prizes/economics/laureates/1978/simon-lecture.pdf)

as theory bounded rationality must incorporate a

theory of search.

as a theory bounded rationality had been proposed as

an alternative to

classical omniscient

rationality

the general features of bounded rationality - selective search,

satisficing

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Genesis of the term ‘bounded rationality’ in Simon

http://en.wikipedia.org/wiki/Satisficing

Satisficing, a "handy blended word combining

satisfy with suffice",[1] is a decision-making

strategy that attempts to meet criteria for

adequacy, rather than to identify an optimal

solution. A satisficing strategy may often be

(near) optimal if the costs of the decision-making

process itself, such as the cost of obtaining

complete information, are considered in the

outcome calculus.

Genesis of the term ‘bounded rationality’ in Simon

http://en.wikipedia.org/wiki/Satisficing

The word satisfice was coined by Herbert Simon

in 1956. He pointed out that human beings lack

the cognitive resources to maximize: we usually

do not know the relevant probabilities of

outcomes, we can rarely evaluate all outcomes

with sufficient precision, and our memories are

weak and unreliable. A more realistic approach

to rationality takes into account these limitations:

This is called bounded rationality.

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Being intelligent being?

The foundational statement that lays the groundwork for much

of the work in behavioural finance, was made by one of the key

workers in computing (artificial intelligence), psychology

(problem solving), and economics (organisational economics) ����

Herbert Simon. For Simon, there are four main areas which

have a symbiotic relationship with behavioural finance:

1. Utility Theory and Human Choice

2. Psychology of Problem Solving

3. Organisational Decision Making

4. Theories of the Business Firm

Simon, Herbert. (1978). RATIONAL DECISION-MAKING IN BUSINESS ORGANIZATIONS. Nobel Lecture

(http://nobelprize.org/nobel_prizes/economics/laureates/1978/simon-lecture.pdf)

Being intelligent being?

For Simon, there are four main areas which have a symbiotic

relationship with behavioural finance:

Simon, Herbert. (1978). RATIONAL DECISION-MAKING IN BUSINESS ORGANIZATIONS. Nobel Lecture

(http://nobelprize.org/nobel_prizes/economics/laureates/1978/simon-lecture.pdf)

Key Symbiosis Exemplars

Utility Theory and Human Choice Framing that results in

apparently contradiction to

utility maximisation)

Psychology of Problem Solving The use of heuristics; bounded

rationality

Organisational Decision Making Decision making by collectives

Theories of the Business Firm Selective Searching, staisficing

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Being intelligent being? Cleverly searching a solution in a large space

B

A A

B

A A

C

B

A A

B

A A

C

E

F

D

Starting from a question “F”, I divide the searchspace into E and E’ ; then onto D, and onto C ...until I reach the solution ���� the colored dices.

Being intelligent being? Cleverly searching a solution in a large space

B

A A

B

A A

C

B

A A

B

A A

C

E

F

D

One can traverse all the paths, sequentially or in parallel, but a clever search strategy will be to have a good guess, based on experience, to choose a ‘plausible’ path

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Being intelligent being? with apologies to Plato

Knowledge about, knowledge by description: knowledge

of a person, thing, or perception gained through

information or facts about it rather than by direct

experience.

An impersonation of intelligence;

an intelligent or rational being;

esp. applied to one that is or may

be incorporeal; a spirit

COGNITION: The action or

faculty of knowing taken in its

widest sense, including

sensation, perception,

conception, etc., as distinguished

from feeling and volition.

Language; Images Symbols; Planning; Learning, Thinking;

Creativity

Knowledge, Cognition and Intelligence

•Knowledge is acquired and disseminated by

intelligent and cognate beings. The terms

knowledge, cognition and intelligence are used

interchangeably.

•And there is a good reason for this: Various

cognitive processes help in converting

information and stimuli into knowledge.

Knowledgeable beings then act intelligently

because of their greater awareness.

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Knowledge

Intelligence Cognition

Language; Images Symbols; Planning; Learning, Thinking;

Creativity

Information exchange, processing and decision making; Knowledge is acquired and disseminated by intelligent and cognate beings.

Knowledge, Cognition and Intelligence

Knowledge, Cognition and Intelligence

Human Information Exchange: The role of cognition, perception and movement

In everyday language cognition is used to refer to the 'higher' mental processes. In psychology cognition would generally be taken to include a variety of mental activities.

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Knowledge, Cognition and Intelligence

Human Information Exchange: The role of cognition, perception and

movement

Cognitive faculties include attention, control, categorisation, creativity, decision

making, language, learning, mental imagery, memory, problem solving, reasoning,

representation.

Perceptive capabilities enable humans to hear, see, smell, taste, and touch. These

capabilities help humans to translate a variety of environmental input, for example,

acoustic, chemical, electromagnetic, mechanical, thermal, into a language which

can be understood by the human nervous system.

Motor skills underpin the cognitive faculties and perceptive capabilities through the

complex network of muscles and nerve fibres for receiving inputs from and

providing output to the external environment.

Cognition, perception and movement helps

humans to exchange

Knowledge, Cognition and Intelligence

Kinds of Knowledge:

Cognitive psychologists have studied experts, in

the physical, medical and engineering sciences,

involved in problem solving, ranging from

diagnosis, mental calculation, design and

planning for example. The psychologists have

also observed skilled performance in taxi

driving, typing for instance. The observations

have led to six major findings (Glaser

1994:140-141):

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Cognitive Processes

• Cognition is a broad term which is

used to refer to activities like

thinking, reasoning, conceiving,

solving problems, learning,

communicating through

language and through other

symbol systems.

20

Cognitive Processes

• Cognition, or rather cognitive, is almost

invariably used whenever an agent (ANIMAL,

HUMAN or ROBOT) is

• seen to be using abstraction;

• seen to be using complex rules;

• seen to be usingmental imagery;

• said to have intended to act on his,her or its own;

• said to have used a symbol system.

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Cognitive Processes: Some Definitions

INTELLIGENCE := Perception+Cognition+Motor

Control.

Perception : Reception/analysis of sensory stimuli

Motor control: Pertaining to or characterizing that which involves the systematic use of muscles;

Cognition: Related to activities that involve abstraction, symbolization, insight, rule use, imagery, belief, internationality, problem-solving,

language-based communication

22

Percepts, Movements and Concepts?

• The sensory organs receive information about the world about us; this information is processed by the brain; and the recipient ignores/reacts to the processed information.The reception, processing and reaction involves muscular movement

• The perception of sound can relate to the cognition of speech or music; the controlled movement of limbs can relate to the cognition of dance movement.

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Cognitive Processes

• COGNITIVE PSYCHOLOGY is a branch of psychology

that emphasises internal, mental processes.

• In cognitive psychology (COG PSY) human

behaviour is discussed not in terms of its overt

properties but at an abstract level:• mental events• Mental representations• beliefs• intentions

24

Cognitive Processes: An example

~ Information Processing

• Any intended input, any idea, image, fact,

knowledge, and so on, counts as information in

COG PSY.

• Processing in COG PSY usually means moving

towards some GOAL by going through a series of

STAGES or a SEQUENCE of acts.

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Cognitive Processes: An example ~ Information Processing

• Information processing involves cognitive processes that can deal with the organization, interpretation and responding to an incoming stimulation;

PROCESSING :=ORGANISATION+INTERPRETATION+RESPONSE;

INFORMATION:=

INCOMING STIMULATION

Behaviour and Cognition

The Nature of Expertise

One view of human expertise is that some people have spent so

much time solving problems in one particular domain that they

‘know all there is to know’ (nearly) and are able to see any

problem as an instance of a class of problems with which they

have been confronted before.

Once the expert has successfully classified or recognised a new

problem as an instance of a previously experienced problem type,

all the expert has to do is apply whatever solution proved

successful in dealing with that type of problem in the past.

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Behaviour and Cognition

Cognitive psychologists have studied experts,

in the physical, medical and engineering

sciences, involved in problem solving, ranging

from diagnosis, mental calculation, design and

planning for example. The psychologists have

also observed skilled performance in taxi

driving, typing for instance. The observations

have led to six major findings (Glaser

1994:140-141):

Behaviour and Cognition

Cognitive psychologists have studied experts,

in the physical, medical and engineering

sciences, involved in problem solving, ranging

from diagnosis, mental calculation, design and

planning for example. The psychologists have

also observed skilled performance in taxi

driving, typing for instance. The observations

have led to six major findings (Glaser

1994:140-141):

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Behaviour and Cognition:A Typology of knowledge

Knowledge Type Elaboration

Structured,

Principled Knowledge

As competence is acquired, elements of knowledge become integrated and

the experts store (and retrieve) coherent chunks of knowledge

Procedural

Knowledge

The experts’ declarative knowledge appears to be bound with conditions of

applicability and procedures for use, e.g. condition-action rules.

Skilled Memory Experts and novices have similar memory storage and retrieval capacities,

but experts appear to use long-term memory in a way it resembles short-

term memory.

Automaticity Proficiency apparently requires that some competent skills must become

automatic, so that conscious processing capacity can be devoted reasoning

and decision making.

Effective Problem

Representation

Experts appear to spend time in initial analysis of a problem: they assess

the problem, build mental models to make inferences and add constraints

to reduce problem space.

Strong Self-

Regulatory Skills

Their experience helps the experts to develop a critical set of self-

regulatory or metacognitive skills. These skills are used by experts to

control their performance.

30

Knowledge Management: Key Issues•OLD VIEW:

Knowledge should ‘flow’ through an

organisation from the knowledge officers

(top executives) to the knowledge engineers

(middle management), and from the

engineers to the knowledge workers

(experts, practitioners)

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Knowledge Management: Key Issues

• POST-INDUSTRIAL VIEW:

Knowledge should ‘flow’ through an

organisation amongst the knowledge

officers (top executives), the

knowledge engineers (middle

management), and the knowledge

workers (experts, practitioners)

32

Knowledge & Change Management

Post Modern Organisation

(Pre 1950’s)

Post Industrial Organisation

(Post 1990’s)

Structure PASSIVE, STATIC REACTIVE, DYNAMIC

Products DURABLE, DULL DISPOSABLE, STYLISH

Consumer Needs

STABLE CHANGING

Markets GEOGRAPHICALLY WELL DEFINED

FUZZILY DEFINED

Competition IDENTIFIABLE RIVALS: WAR OF

POSITION

CHANGING RIVALS: WAR OF MOVEMENT

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Knowledge Spiral & Innovation

Components Technology

CMOSSemi-conductor Opto-device

CalculatorFaxVCR

Mask ROMLiquid Crystal

Display

Electronic OrganiserHome Fax

Word ProcessorLCD TV

1970’s

1980’s

1985’s

1990’s

Knowledge Spiral at SHARP

34

Knowledge Spiral & Innovation

Components Technology

CMOSSemi-conductor Opto-device

CalculatorFaxVCR

Mask ROMLiquid Crystal

Display

Electronic OrganiserHome Fax

Word ProcessorLCD TV

1970’s

1980’s

1985’s

1990’s

Knowledge Spiral at SHARP

CONCEPTS/DEVICE

PRODUCTS

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1970’s

Flash Memory;TFT;LCD; Solar Power

CMOSSemi-conductor

opto device

CalculatorFaxVCR

Mask ROMLiquid Crystal

Display

1980’s

1985’s

1990’s

1995’s

Electronic OrganiserHome Fax

Word ProcessorLCD TV

Personal Office Assistant;High Definition Television;

Multimedia Systems

2000

??

????

Knowledge Spiral & Innovation

Components Technology

36

Products/Services

Scientific Progress &

Technical Change

Social Attitudes

Knowledge Spiral & Innovation

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.Two dimensions of knowledge creation in organisation: explicit and tacit

knowledge

Explicit Knowledge(OBJECTIVE)

Knowledge of rationality (mind);

Sequential knowledge (there and then);

Digital knowledge (theory).

Tacit Knowledge(SUBJECTIVE)

Knowledge of experience (skills);Simultaneous knowledge (here and now);

Analog knowledge (practice).

Knowledge Conversion

38

.Two dimensions of knowledge creation in organisation: explicit and tacit

knowledge

Knowledge Conversion

Dimension Type

Explicit Symbolic

Implicit Embodied

Implicit/Tacit Ingrained

Tacit Culturally acquired

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Process Task

SocialisationTacit ���� Tacit

Share experience; Transfer

skills; Explain models

ExternalisationTacit ���� Explicit

Articulate knowledge; concepts,

hypotheses

InternalisationExplicit���� Tacit

Transfer or acquire knowledge:

by ‘doing’; by teaching; project

work

CombinationExplicit ���� Explicit

Systematise knowledge; Evaluation;

Testing

Nonaka & Takeuchi’s Knowledge Conversion Modes

Knowledge Conversion

Nonaka & Takeuchi’s Knowledge Conversion Modes

Socialisation

Sympathised

Knowledge

Externalisation

Conceptual

Knowledge

Internalization

Operational

Knowledge

Combination

Systemic

Knowledge

From

Tacit

Knowledge

Explicit

Knowledge

Tacit Knowledge Explicit Knowledge

To

Behaviour and Cognition: Knowledge Evolution

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Nonaka & Takeuchi’s Knowledge Conversion Modes

Linking

Explicit

Knowledge

Field

Building

Learning by Doing

Dialogue

Socialisation Externalisation

Internalisation Combination

Behaviour and Cognition: Knowledge Evolution

Nonaka & Takeuchi’s Knowledge Conversion Modes

Socialisation

Sympathised

Knowledge

Externalisation

Conceptual

Knowledge

Internalisation

Operational

Knowledge

Combination

Systemic

Knowledge

From

Tacit

Knowledge

Explicit

Knowledge

Tacit Knowledge Explicit Knowledge

To

Behaviour and Cognition: Knowledge Evolution

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Dialogue

Linking Explicit

Knowledge

Learning by doing

Field

Building

Socialization Externalisation

Internalisation Combination

Behaviour and Cognition: Knowledge Evolution

Behaviour and Cognition: The role of knowledge

Wang (2009) looked at the relationship between the ‘increasingly complex financial products in the marketplace’ and ‘investors’ financial literacy’. The author conducted a questionnaire survey to see ‘how different male and female investors’ financial knowledge and risk-taking behavior are’ (ibid:204).(Wang 2009).

Wang, Alex. (2009). Interplay of Investors’ Financial Knowledge and Risk Taking. The Journal of Behavioral Finance. Vol 10,

pp 204-213.

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Behaviour and Cognition: The role of knowledge

Wang used ‘survey data focusing on investing in mutual funds as tested

knowledge domain and measured behavior’ (ibid:208):

524 participants took part, 317 male and 207 female.

37 questions were used to measure participants’ objective knowledge

regarding investing in mutual funds; these questions were based on the

work in consumer research, especially on attention and comprehension of a

consumer (Celsi and Olson 1988), and based on work in marketing research

on the knowledge of a consumer (Moreau, Lehmann and Markman 2001).

• 10 multiple-choice questions were used to reflect participants’ objective

knowledge regarding investing in mutual funds

• 27 true-false questions were used to measure participants’ objective

knowledge about investing in mutual funds

Celsi, R. L. and J. C. Olson. “The Role of Involvement in Attention and Comprehension Processes.” Journal of Consumer Research, 15, (1988), pp. 210–224.

Moreau, C. P., D. R. Lehmann and A. B. Markman. “Entrenched Knowledge Structures and Consumer Response to New Products.” Journal of Marketing

Research, 38, (2001), pp. 14–29.

Behaviour and Cognition: The role of knowledge

Distribution of scores in an on-line questionnaire on ‘investment in mutual funds’; 37 questions on the survey

(Wang 2009).

MarksNumber of

respondents

Percentage of

respondents

Grade

<40% 9 2% Fail

≥40% & <50% 43 8% III

≥ 50% & <60% 139 27% II.2

≥ 60% & <70% 152 29% II.1

≥ 70% & <80% 155 30% I

≥80% 26 5% Distinction

Total 524 100%

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Behaviour and Cognition: The role of knowledge

Wang showed that

1. at ‘least for investors, their objective knowledge, subjective knowledge, and risk taking are highly

correlated.

2. The gender of the respondent is an important factor that differentiates investors’ levels of objective

knowledge, subjective knowledge, and risk taking.

Wang has argued that ‘it is investors’ subjective knowledge that mediates their objective knowledge on risk-taking behavior. Since male investors have higher subjective knowledge and objective knowledge than female investors, they often takemorerisks because of the mediation effect of subjective knowledge’ (2009:212) .

Wang, Alex. (2009). Interplay of Investors’ Financial Knowledge and Risk Taking. The Journal of Behavioral Finance. Vol 10,

pp 204-213.

Behaviour and Cognition: The role of knowledge

The management of financial risk depends upon an

organisation’s base of knowledge, access to capital and ICT

resources, and the accumulated experiential knowledge.

An organisation is in itself an agencement: The knowledge,

capital and technological resources, have to be seen in the

context of the manner in which individuals manage and

operate within the organisations, what is the balance of rights

and duties, rewards and punishments: in short what is the

culture of the organisation, the skills of its owners and workers,

and how is it the agencement works.

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Behaviour and Cognition: The role of knowledge

•There is a need to facilitate the communication across all the facets of the

organisation. Knowledge has to be created, shared, validated and

REGULARLY pruned. Seeding, fertilising, nourishing and pruning are

the HALLMARKS of a sustainable eco system.

•A sustainable eco-system has redundancy built into its operational

mechanisms and allows the system to take advantage of opportunities, to

weather dearth in opportunities, and to recover from disasters and

overindulgence.

•Sustainable eco-systems have well integrated components and have

contingencies to deal with failures in the various sub-systems: Each sub-

system is familiar with the operation of other proximate sub-systems.

•A sustainable eco-system is an OPEN system

Behaviour and Cognition: The role of knowledge

Post Modern

Organisation

Post Industrial

Organisation

Structure PASSIVE, STATIC REACTIVE, DYNAMIC

Products DURABLE, DULL DISPOSABLE,

STYLISH

Consumer Needs STABLE CHANGING

Markets GEOGRAPHICALLY

WELL DEFINED

FUZZILY DEFINED

Competition IDENTIFIABLE

RIVALS: WAR OF

POSITION

CHANGING RIVALS:

WAR OF MOVEMENT

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Nonaka & Takeuchi’s Knowledge Conversion Modes

Socialisation

Risk heuristics

Externalisation

Strategic Vision,

Financial Innovation

Internalisation

Back Office;

Regulatory Instruments

Combination

Financial Models;

Asset Performance;

News Management

From

Tacit

Knowledge

Explicit

Knowledge

Tacit Knowledge Explicit Knowledge

To

Behaviour and Cognition: Knowledge Evolution

Behaviour and Cognition: The role of knowledge

Three major financial risk management

disasters usually have three ingredients:

1. Dysfunctional Culture (e.g. ENRON)

2. Unmanaged Organisational Knowledge

(e.g. Barings, Kitter-Peabody, Salomon

Brothers)

3. Ineffective Controls (e.g. 2008 credit

crunch)

Marshall, Chris., Prusak, L., & Shpilberg, D. (1997). ‘Financial Risk and the Need for Superior Knowledge Management. In (Eds) Laurence

Prusak. Knowledge in Organisations: Resources for a Knowledge-Based Economy. Newton (MA, USA): Butterworths-Heinemann, Chapter 11.

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Behaviour and Cognition: The role of knowledge

Three major financial risk management

disasters: Metallgesellschaft Refining &

Marketing

Marshall, Chris., Prusak, L., & Shpilberg, D. (1997). ‘Financial Risk and the Need for Superior Knowledge Management. In (Eds) Laurence

Prusak. Knowledge in Organisations: Resources for a Knowledge-Based Economy. Newton (MA, USA): Butterworths-Heinemann, Chapter 11.

Behaviour and Cognition: The role of knowledge

Three major financial risk management

disasters: Kidder Peabody

Marshall, Chris., Prusak, L., & Shpilberg, D. (1997). ‘Financial Risk and the Need for Superior Knowledge Management. In (Eds) Laurence

Prusak. Knowledge in Organisations: Resources for a Knowledge-Based Economy. Newton (MA, USA): Butterworths-Heinemann, Chapter 11.

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Behaviour and Cognition: The role of knowledge

Three major financial risk management

disasters: Baring Securities

Marshall, Chris., Prusak, L., & Shpilberg, D. (1997). ‘Financial Risk and the Need for Superior Knowledge Management. In (Eds) Laurence

Prusak. Knowledge in Organisations: Resources for a Knowledge-Based Economy. Newton (MA, USA): Butterworths-Heinemann, Chapter 11.

Behaviour and Financial Markets

Avanidhar Subrahmanyam (2007)Behavioural Finance: A Review and Synthesis. European Financial Management, Vol. 14, No. 1, 2007, 12–29

Traditional Finance Theory

Criticism

Behavioural Finance

ResponseTheoretical behavioural models are

somewhat ad hoc and designed to explain

specific stylised facts

Behavioural models are based on how

people actually behave based on extensive

experimental evidence, and explain

evidence better than traditional ones

Empirical work is plagued by data-mining

(that is, if researchers set out to find

deviations from rational pricing by running

numerous regressions, ultimately they will

be successful).

Much empirical work has confirmed the

evidence out-of-sample, both in terms of

time-periods as well as cross-sectionally

across different countries

Behavioural finance presents no unified

theory unlike expected utility maximisation

using rational beliefs.

Traditional risk-based theories do not

appear to be strongly supported by the data.

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Neuroscience and Economics

It can be hypothesized that different criteria are applied to select one or more features of each of the interacting modalities – sometimes the features can aggregated to

achieve super-addition, such that the whole is greater than the sum of the individual features, and at other times some features can be relegated in importance such the whole is less that sum leading to sub-addition. Yet, sometimes a simple addition of the modalities suffices. The well-known cocktail party effect relies on the super-addition of low-level linguistic information with the visual information of facial changes that enables listeners to ‘listen’ in noisy environments. The

collapse of enterprises and markets on rumours, despite encouraging quantitative information about the performance their assets, is the sub-addition of linguistic information with numerical..

Processes in Prospect Theory

Multi-criteria decision making has a long history in social sciences and recently have been used in environmental sciences, images classification and financial forecasting. The different ways in which features are aggregated depends on context, data density and uncertatinity and it appears that the importance of criteria is measured by means of a capacity. In effect, it has been found out the criteria can be aggregated by means of the so-called fuzzy integrals – for cardinal evaluations it

is the Choquet integral appears to be the key and for ordinal evaluations it is the Sugeno integral.