Spyros Alogoskoufis & Ann- RenÉe Guillemette
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Transcript of Spyros Alogoskoufis & Ann- RenÉe Guillemette
Experimental Economics 488
Commodity and Stock Markets Initial Experiment
Age and Experience in Both Markets
Final Outcome: Size Manipulation:
Small Markets = Commodities Large Markets = Stocks
The Question
Is information incorporated faster and more equitably in a small or large market?
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
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
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.
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.
Data Analysis Speed
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.
Graphs: Period 1 & 3Actual Value: 399
Ending Value: 424
Actual Value: 781
Ending Value: 780
Graphs: Period 5 & 7Actual Value: 648
Ending Value: 540
Actual Value: 484
Ending Value: 499
Graphs: Period 9 & 11Actual Value: 507
Ending Value: 450
Actual Value: 872
Ending Value: 700
Graphs: Period 2 and 4Actual Value: 694
Ending Value: 674
Actual Value: 348
Ending Value: 350
Graphs: Period 8 and 10Actual Value: 394
Ending Value: 408
Actual Value: 796
Ending Value: 360
Graph: Period 12 Actual Value: 363
Ending Value: 450
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 Round Convergence Per Participant1 23 1.28 2 20 2.223 21 1.17 4 23 2.565 NA NA 8 12 1.337 13 0.72 10 NA NA9 14 0.78 12 NA NA
11 22 1.22
Average 18.6 1.03 Average 18.3 2.04
Summary of Larger MarketsEquality
Summary of Smaller MarketsEquality
Small Markets
Round Transactions ΔTotal StDev Δ10 StDev Δ5 StDev
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 0.0
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 41.3
Larger markets generate prices closer to the actual value
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 Round σ1 148.76 2 597.603 107.87 4 81.175 257.27 8 95.397 37.92 10 858.789 509.31 12 986.84
11 868.17 Average 321.55 Average 523.96
Limitations
Number of Rounds 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
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”