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Prediction Markets for Business Forecasting – Results from the Lab and a

Case Study

Christian Horn, Björn Sven Ivens Otto-Friedrich-University of Bamberg, Department of Marketing and

Chair of Innovation Management, Germany

Alexander Brem University of Erlangen-Nuremberg, Germany

International Symposium on Forecasting,

Seoul, 6/25/2013

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Designed for „the primary purpose of aggregating information, so that market prices forecast future events“ (Berg, Nelson and Rietz 2003)

They bring groups of informants together and let them trade contracts whose payoff depends on the outcome of uncertain future events (Luckner 2012)

Prediction Markets work (possibly) with experts (scientists, managers, customers) and non-experts (e.g. customers)

Theoretical background

Prediction Markets (PM):

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Adidas & sporting goods characteristics

• Low to medium priced products • Short product life cycles (64 % of portfolio <4 seasons on the

market) • Extreme seasonal influence on sales • Aims for adidas:

• Production planning • Logistics planning • Price management • Sales margin forecasting

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Market Share

• Market share splits of products of one design line (t-shirt, pants, poloshirt, hodded pullover)

• Regional split of Graphic Tee sales

• Market share portfolio of product Graphic Tee

Price

• Sales optimum price of product Track Top

• Impact of own price increase on sales

• Optimal price products: replica tee, replica jersey, authentic jersey

• Price change of Jeresey: sales change

Innovation/Timing

• Ideal product launch date for product Club Track Top

• Product Jersey‘s most important features 1

• Most important fesatures 2

• Specific product version for soccer league/CL

Motivation/Benchmark

• Euro/Dollar Exchange Rate

• Sports Results of soccer matches of Euro-Championship 2012

Virtual Stocks and Contracts in PMs

Prediction Questions

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What would be the optimum sales price for the products shown below? Please invest your virtual money.

Prediction Markets: Example

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Research design

The PM experiments consisted of three steps:

Methodology

Steps for Experiment

1. Participants received an explanation of the software (Video)

2. Participants could trade for the specified trading time

3. Participants fill out questionnaire

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Find out differences of short-running markets (<2h) and long runnig scenarios (~3w) 1

Find differences of laboratory study and practical study

Identify questions/contracts applicable in a PM 3

2

Study aims

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Research design of Prediction Markets (PM)

During the PM experiments: participants had the possibility to trade 12 to18 shares and to bet on

predictions explained above Participants were could win 60 amazon.com-giftcards from 10 € up to 100 €

and 50 adidas-shirts Trading groups were set up with identical stocks for longer trading and shorter

trading time. Each group didn’t trade two stocks of the possible ones. The experiment took place in Germany at the University of Erlangen-Nuremberg and the University of Bamberg in May/June 2012

13 experimental groups with 15 to 461 persons

Methodology

Research design of Prediction Markets (PM)

Benchmark for MAPE: sales of Q3+Q4 2012 and adidas management decisions

Continous Double Auction and Simple Bet trading menachnisms

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Trading numbers (net) and sample size (net)

Groupname <1 hour transactions

~ 3 weeks transactions

participants Net

Transactions per Participant

1 Lab 1 400,00 14,00 28,6 2 Lab 2 488,00 20,00 24,4 3 Lab 3 391,00 19,00 20,6 4 Lab 4 677,00 17,00 39,8 5 Lab 5 447,00 20,00 22,4 6 Adidas Managers 1 167,00 10,00 16,7

7 Adidas Managers 2 87,00 7,00 12,4

8 B1:L 547,00 13,00 42,1

9 B2:L 868,00 20,00 43,4

10 B3:L 261,00 19,00 13,7

11 B4:L 754,00 17,00 44,4

12 B5:L 314,00 20,00 15,7 13 Public:L 13.159,00 451,00 29,2

Sum 2.657,00 15.903,00 647,00 24,6

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Example for Case Study Group „Adidas Managers 1“ (15 Adidas-Managers“) <1hour Trading Time

Stock-Question Group Subject Given Range Final Stock Price Benchmark APE Price change of product: influence sales volume

Adidas Managers

Sales Volume -2,19 -

Track Top: best retail price for sales optimum

Adidas Managers

Sales Price 75,57 65 0,16

Product feature or not: impact on sales volume

Adidas Managers

Product Managem

ent 5 5 0,00

Optimum Product Price Adidas

Managers Innovation -

Optimum Product Price Adidas

Managers Innovation

Authentic Jersey (80€ - 150€) 123,91 110 0,13

Optimum Product Price Adidas

Managers Innovation Cotton Tee (30€ - 50€) 36,28 33 0,10

Optimum Product Price Adidas

Managers Innovation Replica (70€ - 100€) 80,38 80 0,00

Optimum Product Price Adidas

Managers Innovation Replica Tee (35€ - 60€) 43,91 48 0,09

Euro-Dollar-Rate Adidas

Managers Economic 1,26 -

vorläufige Ergebnisse

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MAPE results of PMs at end of trading

Groupname MAPE < 1 hour

transactions MAPE ~ 3 weeks

transactions % improvement participants Net

1 Lab 1 0,15 14,00

2 Lab 2 0,29 20,00

3 Lab 3 0,12 19,00

4 Lab 4 0,15 17,00

5 Lab 5 0,10 20,00

6 Adidas Managers 1 0,25 10,00

7 Adidas Managers 2 0,33 7,00 % improvement MAPE

Lab1-5/ adidas1-2 -0,45

8 B1:L 0,11 0,42 14,00

9 B2:L 0,12 1,43 20,00

10 B3:L 0,15 -0,21 19,00

11 B4:L 0,13 0,11 17,00

12 B5:L 0,12 -0,17 20,00

13 Public:L 0,10 451,00

% improvement MAPE Public/MAPE Longs - - 0,28 648,00

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Conclusion

Improvement in MAPE for 3-week markets compared to <2h markets

Improvement for larger group

Experts (Adidas-employees) produced weakest results

Stocks perform differently well, some topics could not be solved

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Implications

Non-experts perform slightly better than experts, but

differences are slight.

Large numbers of participants are not necessary

Short running prediction markets can be used for

accurate forecasting in several fields.

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Limitations

motivation of Adidas-managers was lower (less trades)

sports products are low- to medium priced consumer

products

Mostly German participants

Only two expert groups

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Questions?

Christian Horn Department of Marketing Otto-Friedrich-University of Bamberg Tel. +49 951 / 863 2564 Mobile +49 176 / 20993285 Fax + 49 951 / 863 2566 Email: christian.horn@uni-bamberg.de Web: www.uni-bamberg.de/bwl-marketing