'token exchange' market in Arizona

Edward Vielmetti emv at msen.com
Thu Dec 10 05:01:55 PST 1992

For you all.  Interesting because it would appear to be a real live
marketplace, with real live money, tho no crypto per se in there.


------- Forwarded Message

From: rkeca04 at uts.manchester-computing-centre.ac.uk (Thomas Krichel)
Subject: Arizona token exchange
To: cti-econ at mailbase.ac.uk
Date: Thu, 10 Dec 92 11:55:03 GMT


  this is an  item from corryfee. Apologies to those who have
  already seen it. I thought it was sufficiently interesting
  to pass it on. 

  BTW, the some of the results of the Santa Fe experiment, to which
  the text refers, will be published in a forthcomming book by 
  John Rust and Dan Friedman "Double Auction Markets: Theory, Institutions,
  Evidence". Publisher is Addison-Wesley (Santa Fe Institute series
  On Studies in the Science of Complexity).


    /   /                              Department of Economics
   /   /_  ________  __.  _            University of Keele
  /   / /_(_) / / <_(_/|_/_)           ST5 5BG                         
    _   ,                  _           Great Britain          
   ' ) /           /      //           Tel.: 44 - 782 - 714847  
    /-<  __  o _. /_  _  //            Fax:  44 - 782 - 717577
  ./   )/ (_<_(__/ /_</_</_            E-mail: Krichel at uts.mcc.ac.uk

>                             ANNOUNCING THE OPENING OF THE
>                             ARIZONA TOKEN EXCHANGE (AZTE)
>                                   January 1, 1993
> Earn cash profits by competing against computerized program traders
> Is "artificial intelligence" superior to human intelligence? In
> some domains such as chess, computer programs now outperform all
> but the very best human players.  However in other domains such as
> speech, handwriting, and other kinds of pattern recognition,
> computers lag far behind human beings.  On Wall Street computer
> "program traders" are becoming increasingly common, yet there is
> substantial controversy over their performance -- they have even
> been blamed as a factor in the October 1987 stock market crash.
> The purpose of this study, co-sponsored by the University of
> Arizona's Economic Science Laboratory and the Santa Fe Institute,
> is to compare the performance of human and program traders to see
> whether humans can learn to exploit the limitations  and
> idiosyncracies of computers in repeated interactions.
> To compare the performance of human and program traders we have
> created a computerized market, the Arizona Token Exchange (AZTE),
> in which a fictional commodity, "tokens", are traded.  The market
> is a simplified version of commodity exchanges such as the Chicago
> Board of Trade where buyers and sellers are able to call out bids
> and asks to buy or sell units of the commodity.  In each trading
> session on AZTE traders are assigned the role of buyer or seller
> and are given an allocation of tokens.  A seller's objective is to
> sell their tokens for as much as possible above the token cost and
> a buyer's objective is to buy tokens as cheaply as possible below
> their redemption value.
> By ranking the token costs and redemption values, well-defined
> supply and demand curves can be constructed.  The intersection of
> these curves defines the so-called competitive equilibrium (CE)
> price and quantity, at which neoclassical economic theory predicts
> all trading will occur.   The complication is that in the AZTE,
> each trader's token costs and redemption values are private
> information and differ from trader to trader.  Thus traders in the
> AZTE face a complex sequential decision problem: how much should
> they bid or ask for their own tokens, how soon should they place a
> bid or ask, and under what circumstances should they accept an
> outstanding bid or ask of some other trader? An additional
> complication is that each trading session runs for a fixed amount
> of time.  This creates a difficult trade-off, for if traders spend
> too much time looking for a good deal, they may find themselves
> locked out of the market without trading anything.
> In the AZTE there is a well-defined performance measure: trading
> efficiency, EFF.  This is the ratio of profits a trader actually
> earns divided by the profits it would have made if all trades took
> place at the competitive equilibrium level.  Thus, if a trader's
> EFF is greater than 100% they are earning more than their "fair"
> share of the profits.  The use of EFF is more desirable
> performance measure than simply using trading profits, since
> profits depend on the token allocations which are allocated at
> random from a known distribution.
> After each trading session, participants will earn cash profits
> equal to the following linear function of their efficiency:
>      $ payments =  a + b(EFF-100)
> The term a represents a fixed fee paid for participating in the
> trading session and the term b(EFF-100) represents a bonus
> (penalty) for trading above (or below) 100% efficiency.  Thus, it
> is possible to lose money in any particular trading session.
> Dollar earnings are cumulated over successive trading sessions and
> subjects are eligible to "cash out" at any time after participating
> in a minimum number of trading sessions (provided cumulative
> earnings are positive).
> Unlike real commodities markets where most traders are humans, in
> the AZTE all of your opponents will be computer programs.  The
> opponent programs will be selected from a field of over 30
> different trading strategies including winners of the Santa Fe
> Institute's Double Auction Tournament held in March, 1990.  The
> program traders range in sophistication from simple rules of thumb
> (such as Gode-Sunder "Zero-Intelligence" strategy) to sophisticated
> optimizing/learning algorithms (such as neural nets and genetic
> algorithms) developed from the recent literature on artificial
> intelligence.  The identities of your opponents will (usually) be
> revealed to you at the start of each trading session.  You will
> also be informed about other market characteristics such as the
> number of buyers and sellers, the number of tokens, and the joint
> distribution from which token values are drawn.
> To trade on the AZTE you will need a Unix or PC-compatible computer
> linked to the Internet computer network.  We provide the trading
> interface software that allows you to log on and trade at any time
> you like and for as long as you like (subject to general
> restrictions).  To qualify for an AZTE trading account you need to
> file an application providing information on your address, phone,
> and email address, and a release form stating whether or not you
> want to remain anonymous in published analyses of the outcome of
> this experiment.  Upon receipt of the application we will set up a
> trading account and access password.  Your dollar earnings will
> cumulate in your account until you decide to cash out, at which
> time we will close your account and mail you a check for the total
> amount of your earnings.
> The software and ASCII traders' manual (including the application
> form) is available via anonymous ftp on "fido.econ.arizona.edu", in
> the azte sub-directory.  The manual (azte.man) explains how the
> software works and what is required to use it.  We suggest you ftp
> this first and read through it, then get the appropriate trading
> interface for your system.  The DOS interface requires VGA graphics
> resolution and the use of Clarkson packet drivers for the network
> interface card.  The Clarkson drivers are also available via ftp on
> "fido.econ.arizona.edu".
> If you don't have access to anonymous ftp, we will mail you a
> diskette containing the software and trader's manual.  To cover the
> costs of a diskette and surface mail, send $5.00 to:
>        Shawn LaMaster
>        Manager, Economic Science Systems Development
>        Economic Science Laboratory
>        McClelland Hall, Room #116
>        University of Arizona
>        Tucson, Arizona  85719
>        (602) 621-6218
>        Internet: lamaster at ziggy.econ.arizona.edu
> We will assist in ftp and setting up the Clarkson packet drivers,
> just give us a call.
> The AZTE software was co-developed by:
> Sean Coates        Economic Science Laboratory, University of Arizona
> Shawn LaMaster     Economic Science Laboratory, University of Arizona
> Richard G. Palmer  Duke University
> John Rust          University of Wisconsin
> Vernon L. Smith    Economic Science Laboratory, University of
> Arizona

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