1. Spyros Alogoskoufis & Ann-RenÉe Guillemette
Experimental Economics 488
Spyros Alogoskoufis & Ann-RenÉe Guillemette

2. Commodity and Stock Markets
Initial Experiment
Age and Experience in Both Markets
Final Outcome:
Size Manipulation:
Small Markets = Commodities
Large Markets = Stocks

3. The Question
Is information incorporated faster and more equitably in a small or large market?

4. Clarification How we define “Faster”
Periods are in terms of transaction numbers and not seconds.
Justification
Excludes initial confusion
Compare similar observations - linear relationship between average transactions
Eliminates practical difficulties

5. Expected Outcomes Larger Market More Successful Than Smaller Market
Increased Competition - Breakdown of Collusion
More Information Available
By trading at a high volume, more information is discovered
Downside : Speculation of Price
Traders with information benefit
Faster Convergence Leads to Minimized Losses

6. Instructions Market Information
The experiment will consist of 16 rounds in total. One trial round will precede the experiment, in order for participants to familiarize themselves with the program
Each participant is assigned a group, A or B. In odd rounds, both groups will be in the market, whereas in even rounds, groups A and B will alternate. Groups A and B are of equal size.
In each round, certain individuals will randomly have some knowledge of the actual value of the good, and other will not.
Participants will each be given 5 shares. In order to avoid any restrictions on trading, there will be an initial endowment of 10,000 given to each trader. He or she can trade as much or as little as desired but must not have a negative holding of shares at any point during the trading round
Participants know their values for each round ahead of time. This does not affect results as each round is independent.
If information is given, the tabs will contain a random number between 100 and 1000, otherwise they will say “no information”. The “noise” of the value given will constantly be 40. This means that if the value someone is given is 800, the true value of the good is between 760 and 840.

7. Instructions Cont. Trading Program.
The trial round will allow each participant to familiarize him or herself with the computer program being used in the B74 Lab. The Z- Tree program allows us to simulate the market. The program is run by one main computer and is connected to all other sub-computers. 
Participants will open the program and be directed to a “market” screen where trading will take place.
Traders can place a bidding price to purchase shares from other traders or they can place an offering price to sell their own shares. In order to take up a trader on his “bid” or “offer” other traders have to select “sell” and “buy” respectively.
No transactions will take place when the market is closed (i.e. when the time in the upper right hand corner runs out). At the end of each round, an updated screen with ending market conditions will be posted. Participants will be able to observe their total gains from trading in each round. A time-series graph will show real-time prices.

8. Data Analysis Speed Equality
Visual - Graphic Representation of Periods
Numerical - Measure of speed of conversion and testing
Equality
Profit per transaction
Overall profit.
All these observations are comparisons between the larger (odd) and smaller (even) markets.

9. Graphs: Period 1 & 3 Actual Value: 399 Ending Value: 424

10. Graphs: Period 5 & 7 Actual Value: 648 Ending Value: 540

11. Graphs: Period 9 & 11 Actual Value: 507 Ending Value: 450

12. Graphs: Period 2 and 4 Actual Value: 694 Ending Value: 674

13. Graphs: Period 8 and 10 Actual Value: 394 Ending Value: 408

14. Graph: Period 12
Actual Value: 363
Ending Value: 450

15. Speed of Convergence Observations:
Larger markets converge faster in terms of average transactions per person
Convergence: A series of consecutive transactions exists, such that individual transactions give a price within 10% of the actual value
Large Market
Small Market
Round
Convergence
Per Participant 1 23
1.28 2 20
2.22 3 21
1.17 4
2.56 5 NA 8 12
1.33 7 13
0.72 10 9 14
0.78 11 22
1.22
Average
18.6
1.03
18.3
2.04

16. Summary of Larger Markets Equality
Large Markets
Round
Transactions
ΔTotal
StDev
Δ20
Δ10 1 70
44.9
47.5
33.65
7.1
31.7
5.6 3 74
77.5
118.9
14.4
17.8
8.9
9.2 5
192.5
104.4
28.9
110.4
19.9 7 86
36.2
60.2
8.7
5.1
11.2
5.7 9 63
104.9
154.0
25.75
31.0 12
15.8 11 98
132.5
160.1
105.1
75.9
172
0.0
Average
76.8
98.1
109.9
48.7
27.6
57.7
9.4

17. Summary of Smaller Markets Equality
Small Markets
Round
Transactions
ΔTotal
StDev
Δ10 Δ5 2 52
95.1
104.7
24.6
6.6
20.0
0.0 4 33
77.6
90.9
4.5
7.9
2.0 8 48
37.5
34.5
29.9
16.7
32.6
17.0 10 29
344.5
109.0
316.5
65.1
352.0
76.7 12 37
181.6
109.1
158.5
110.0
169.0
112.8
Average
39.8
147.3
89.6
106.8
41.3
115.1

18. Larger markets generate prices closer to the actual value

19. Equality (Overall Profits)
Observations:
Equality and Profit distribution
Faster convergence linked to fewer profits
Profits distributed more equally in larger markets
Results not significant (observations and outliers)
Large Market
Small Market
Round σ 1
148.76 2
597.60 3
107.87 4
81.17 5
257.27 8
95.39 7
37.92 10
858.78 9
509.31 12
986.84 11
868.17
Average
321.55
523.96

20. Limitations Number of Rounds Knowledge of Z-Tree Focus Issue
Time Constraint
Personal Error in Data
Knowledge of Z-Tree
Class Members versus Outside Acquaintances
Repeated usage of the program leads to better execution of its functions
Focus Issue
Participants may lose concentration after several rounds

21. Final Thoughts
Larger Markets are more equitable and converge faster than smaller markets
Possible Causes:
Increased Competition in terms of people with information
More information available (more likely to cause reactions)
Separating Equality from Speed
Though highly linked, “faster” does not guarantee “more equitably”