Transcript Slide 1

BUSINESS FORECASTING AND PREDICTION MARKETS POTENTIAL ON BANKING
INDUSTRY IN KENYA
KIMANI FLORENCE WANJIRU
DR. JAMES M. NJIHIA
[email protected]
DEPARTMENT OF MANAGEMENT SCIENCE
SCHOOL OF BUSINESS
UNIVERSITY OF NAIROBI
OCTOBER 16TH 2014
Introduction:

Presently in the Banking Sector they are dependent on ERPs which have
shown dissatisfaction i.e. 88% of corporations are not satisfied especially
on cash flow forecasting.
 Lack of proper planning & control of cash resources e.g. Economic
recession as a result of poor Predictive tools.
 Experts are expected to know a variety of forecasting tools depending
on the present situation.
 According to studies done businesses cannot rely on only one method;
thus a better forecasting tool is required that cuts across all areas
without been limited by the complexity of the problem or a number of
variables.
 How can Kenyan Banks take Advantage of Prediction Markets?
Research Questions
In relation to Kenyan banks the research objectives was:
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To find out the satisfaction of the present forecasting systems in use.
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To determine awareness of prediction markets.
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Develop a prediction model for organization readiness to adopt prediction Market.
Motivation for Research
Prediction Markets in Financial Sector
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In 2007 there was a serious Economic recession where the Banking industry &
corporate companies got seriously affected; this continued to 2008-2009; A
prove that existing traditional forecasting tools did not predict correctly as
expected.
This explains further the need for better forecasting tools that capture relevant
information on ESG( Environmental, Social& Corporate governance ); this can only
be done better by prediction Markets.
If you are ignorant of information as an Entrepreneur you cannot thrive in the
Competitive Environment.
INFORMATION
is POWER!
Business Forecasting(Literature
Review)
Business Forecasting :is a planning tool that helps management in its attempts to
cope with the uncertainty of the future, relying mainly on data from the past and
present and analysis of trends e.g. Time series method, Dephi method, surveys, polls
e.t.c.
 How Well Do they Aggregate Information in the short term & long run term ?
Prediction Market
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A place where information is aggregated via market (or other) mechanisms
for the primary purpose of forecasting events, or the probability that an
event will occur.
Types of Prediction Markets
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Enterprise Prediction Markets are markets internal to an organization that
support business forecasts on sales, new product development, project
management, market and economic indicators .e.g. Siemens, Microsoft,
Google, Nokia, HP(Main memory-Constitutes 7-10% Computer Cost)this
Has greatly improved the memory price forecast by 1-2%.
Public Prediction Markets are created in the interest of the public for the
purpose of attracting enough traders.
Focus is on interesting topics that are of concern to the public. E.g : sports
events, box office, elections or any other people related news. Companies
that use: Iowa Electronic Markets, Hollywood Stock Exchange, Tradesport,
Intrade, Foresight Exchange-IEM (Presidential elections)
What makes prediction Markets
Interesting to Use
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Aggregation of information in real time.
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Change to the latest information that can help Users gather useful insights.
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Freedom, Flexibility,Moltivation & Efficiency.
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Help Participants to Proactive.
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Diverse/Dynamic information collected that gives traders insights on new
ideas.
How prediction Markets work
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Prediction markets are said to work the same way as the stock exchange or
financial markets.
Traders can be employees of the organization or individuals from the
public.
Traders participate based on their perceived understanding concerning the
future events with protection of anonymity and well defined incentive
structure
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The market price reveals the probability of an issue occurring
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Type of money used-Real money/Play money
Benefits of Prediction Markets
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Work as continuous dynamic markets that run over a relatively short or
extended period of time.
Give traders instant feedback, giving them chances to reconsider their own
information and act in response to that feedback.
Traders who are more certain in their ideas participate actively in the
market thereby influencing the market prices.
They are cheaper to use because information is gathered from different
participants thereby reducing bias.
Benefits of Prediction Markets
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Participation of employees gives them an opportunity to speak up their
mind.
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It creates incentives for information discovery.
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It does not require all traders to be informed and rational.
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Markets do not require many traders for it to be efficient.
Challenges of Prediction Markets
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Lack of access to all relevant information:-due to lack of experts and
business leaders knowledgeable in the area of interest.
Fast technology requires a great design with value proposition in mind
because prediction markets are required to be easy to use, smarter,
valuable and more popular.
A company must be well established in order to motivate employees and
other participants using incentives and other fun events.
Top managers are threatened by the hierarchical control of prediction
markets.
Challenges of Prediction Markets




Lack of access to all relevant information:-due to lack of experts and
business leaders knowledgeable in the area of interest.
Fast technology requires a great design with value proposition in mind
because prediction markets are required to be easy to use, smarter,
valuable and more popular.
A company must be well established in order to motivate employees and
other participants using incentives and other fun events.
Top managers are threatened by the hierarchical control of prediction
markets.
Theories
Why PM is closer to final results as compared to traditional methods:
 Decision theory,
 Hayek and efficient market hypothesis
 Crowd sourcing & collective intelligence
Technology used
 IS/IT theories e.g. Technology Acceptance Model(TAM), Factors that
describe the theory: Perceived ease-of use (PEOU) &Perceived
usefulness
 Innovation decision process theory: stages of diffusion process are
(Knowledge, persuasion, decision, implementation, confirmation)
 Individual innovativeness theory(Early Adopters/Risk takers)
Adoption of Prediction Markets
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Factors necessary for Adoption of Prediction markets
 Time-Research reveals that PM run over short run/long run is more
Accurate than the traditional methods
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Incentives-Play money(May yield efficient information
Aggregation).Real money(may better motivation discovery of
information)
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Participants
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Legal matters
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Management Policy
Knowledge Gap
 Based on the various theories, benefits, challenges and factors that influence
adoption of prediction markets different scholars show that there is need for
more research concerning prediction market
 Currently, in Africa there are hardly materials that discuss how receptive
people would be on prediction market as a forecasting tool thus the area
needs to be fully exploited especially by Kenyan firms; since an opportunity is
available for them to further cut down on cost.
 This therefore, represents a research gap which this study seeks to address and
also provides a basis for future studies of further exploration on prediction
markets.
Summary and Knowledge
Gap(cont’d)
 This will be the basis of change to large Kenyan firms that have
been dependent on surveys and polls that have proved to be very
costly to implement
Conceptual Framework
Research Methodology
 Research Design (Cross-sectional survey design)-provided
data,knowledge&beliefs on the entire population
 Study population: Banking Industry
 Population Size – 50
 Data collection method-Questionnaires(Semi structured)
 Target group-Managers/Executive(in 50 banks only 35 positive
responded(70%)
 Data Analysis Technique Prediction Market Awareness –Descriptive Analysis
 Satisfaction of current forecasting tools-Descriptive Analysis
 Readiness to Adopt Prediction Markets-Multiples Regression
Analysis
Prediction Market awareness
Statistics on Prediction Market Awareness
Prediction
markets are
the same as
financial
markets
Valid
Missing
Mean
Prediction Market
I Know what a I have heard of Awareness
prediction
prediction
(Average)
market is
markets
35
35
35
0
0
0
2.4286
3.2000
3.3714
3
satisfaction of current forecasting Tools
Statistics on satisfaction of current forecasting Tools
Valid
Accuracy
Cost
Time Spend
Average
Mean
Available
Expertise
35
35
35
35
0
0
0
0
Missing
Mean
3.5429
3.0286
3.1429
3.5714
3.32145
Readiness to Adopt Prediction
Markets
Coefficients
Model
(Constant)
Management
Support
Time spend
Accuracy
Legal matter
Standardize
d
Unstandardized
Coefficients
Coefficients
Std.
Error
B
Beta t
2.091
.635
3.293
95%
Confidence
Interval for B
Lower Upper
Sig. Bound Bound
.003
.794 3.388
.359
.097
.569 3.690
-.094
.647
-.102 -.146
.885 -1.416 1.227
.168
.651
.798 -1.161 1.497
-.152
.125
.182 .258
-.180 1.220-
a. Dependent Variable:
Readiness to Adopt prediction
Markets
.001
.232
.161
-.407
.558
.103
DATA ANALYSIS & DISCUSSIONS
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Having Administered questionnaires to 50 respondents only 35 responded
i.e. response rate-70%
Prediction Market Awareness –Average
Satisfaction of current forecasting tools-Average(This can be explained by
the growth, complexity and trends observed in ICT , business intelligence,
and risk management strategies )
Readiness to Adopt Prediction Markets(Used to create the PM model)
 Management Support(very Significant)
 Perception of accuracy(Not significant)
 Legal matters(Not Significant)
 Time spend(Not significant)
Why you need to get interested?
 It cuts a cross all Industries not only the Banking Sector.
 Materials on Prediction Markets in relation to Africa is rare.
Recommendation
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Prediction Markets Awareness-Creation of More Awareness.
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Satisfaction of current forecasting tools-Adopt Prediction Markets
THANK YOU
QUESTIONS?