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(Un)controlled Market Experiment Mixing Natural And Artificial Agents

(Un)controlled Market Experiment Mixing Natural And Artificial Agents. Alessandro N. Cappellini University of Turin ISI Foundation cappellini@econ.unito.it Economic Science Association (ESA) - World Meeting 2007 Roma – Saturday, June 30 th , 2007. Orders. Trading Book. Prices.

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(Un)controlled Market Experiment Mixing Natural And Artificial Agents

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  1. (Un)controlled Market Experiment Mixing Natural And Artificial Agents Alessandro N. CappelliniUniversity of Turin ISI Foundation cappellini@econ.unito.it Economic Science Association (ESA) - World Meeting 2007Roma – Saturday, June 30th, 2007

  2. Orders Trading Book Prices Financial markets Enqueuing ArrangingMatching Roma - ESA World Meeting 2007

  3. Roma - ESA World Meeting 2007

  4. ABM References Financial market Agent Based Models: Santa Fe ASM (LeBaron, 2002), Genova GASM (Raberto et al., 2002; Scalas et al., 2005; Cincotti et al., 2004; Scalas, 2005)Jerusalem NATLAB (Muchnik et al., 2006; Muchnik and Solomon, 2006, 2003; Daniel et al., 2005) SUM - SumWEB(Terna 2000; Cappellini 2005), Roma - ESA World Meeting 2007

  5. Goal Participation Use of internet for subjects enrollment Mixing Artificial Agents and “Human” Control, Authority, Rules … Market Results… Roma - ESA World Meeting 2007

  6. Rules ArtificialAgents Humans ABM for Stock Markets ? Roma - ESA World Meeting 2007

  7. Roma - ESA World Meeting 2007

  8. ParticipatoryModel Roma - ESA World Meeting 2007

  9. Advantages • A bridge from pure ACE (agent-based computational economics) approach to experimental economics. • Humans can stress test model, can reveal implementation or logical error, slackness, or better can show unpredictable behaviours. • We can study humans behaviour in an artificial but adaptive controlled lab. • Avatar to de-incarnate humans among artificial agents. Roma - ESA World Meeting 2007

  10. Humans • Design and implement a web-based user friendly interface. • Explain our model and write some simple and exhaustive documentation. • Subjects: If we include traders or persons that well know the markets they can differently react. • Re-exanimate the entire model and re-design some function (wasting time in simulation). Purposes: testing the model, business simulators, find out new behaviours, research… Roma - ESA World Meeting 2007

  11. Avatar The Avatar is a religious Indian concept, that represents an incarnation of gods Shiva and Vishnu among humans. The term is used in MUD and online games and chat from ’70s. They are a virtual alter-ego. We use Avatar to de-incarnate humans among artificial agents. In our model Avatars are special agents, representations of humans into the market; using this technique we’re able to have humans operating in our model. Roma - ESA World Meeting 2007

  12. Games Winnicott’s “game” as structured game for winning (vs “play”) Callois (1981): • agon (sport and exams competition) • alea (lucky in lotteries) • mimicry (simulation of reality on the stage) • ilynx (vertigo, acrobatic sport and high risk job) Roma - ESA World Meeting 2007

  13. TheModel Roma - ESA World Meeting 2007

  14. SUM & SumWEB • SUM (Surprising (Un)realistic Market) is a Pietro Terna’s simulation • Order enqueuing rules were directly inspired by MTA (Mercato Telematico Azionario, the Italian Stock Exchange), an order driven book • Tick per tick realistic formation price mechanism • SumWEB (SUM Web Economic Behaviour) for experiment with humans • Opening and closing Auctions, multi-books, more financial instruments Roma - ESA World Meeting 2007

  15. Agents • Random They are the simplest agents, that choose randomly their actions. They represent a crowd of little investors. • Financial Technique They use schemes and rules such as traders. Eg. They can arbitrage a future or use stop-loss/take-profit strategy. • Simple Cognitive They apply simple behaviour observing the market operations. They can imitate the last movement or ask for suggestion to other agents. • Minded They have a real cognitive and adaptable structure. They are principally genetic algorithms, neural networks and classifier systems; and evolve themselves during every run. • Avatar Interface for experiments with Humans Roma - ESA World Meeting 2007

  16. Random Price Rule The prices of orders by Random Agents follow a simple rule: Where: Roma - ESA World Meeting 2007

  17. The Book Continuous Double auction implemented according to MTA (Italian Stock Exchange) rules. Opening and Closing Auction. Orders are ranked by Price, Arrival time and quantity (PQT) Roma - ESA World Meeting 2007

  18. ERA • Gilbert and Terna (2000) • Agent, RuleMaster and RuleMaker • Enviroment and informations • Cognitive Map Roma - ESA World Meeting 2007

  19. User Interface Links Day & Period Prices Wealth Form Messages and Events Portfolio Roma - ESA World Meeting 2007

  20. Trading Books: Equity Roma - ESA World Meeting 2007

  21. Trading Book: Future Roma - ESA World Meeting 2007

  22. Candlestick Roma - ESA World Meeting 2007

  23. ExperimentSetup Roma - ESA World Meeting 2007

  24. Experiments • A class game with 57 persons on 6th May 2003 for one hour. • A two weeks long online experiment, from 8th to 21th May 2003, with 152 persons over 486 agents: • 1 ArbitrageurAgent • 15 EventAgent • 200 RandomAgent • 100 WasteTimeAgent • 170 AvatarAgent • 3 Equity, 1 Index, 1 Future on Index Roma - ESA World Meeting 2007

  25. Strengths and Weaknesses • Model of “Traders” for Traders • Realism in the mechanisms (book) • Heterogeneity of Artificial Agents • More stocks, different financial instruments • “Contest”: Prizes for 15 best players • Penalty for inaction • Application of “any” market rules • Interface • No Dividends • No Interest Rates • Infinite indebtedness • No fundamental • Transaction Costs • Interface • No Free risk bond • No limit in short selling Roma - ESA World Meeting 2007

  26. Results Roma - ESA World Meeting 2007

  27. Empirical evidences Professional traders have access to (part of) the book and they use it to form trading strategies [Parlour 1998, Cao et al. 2004] Aggressive orders (market...able) [Lee et al. 2004] Traders become more aggressive when own side book is thicker [Ranaldo 2004] Roma - ESA World Meeting 2007

  28. Participation • The system accepted 273030 orders (47251 by humans) • 96939 (35%) executed (58% of humans’) Roma - ESA World Meeting 2007

  29. Results: Ranking and Wealth Wealth distribution (average 71,6, median 0) Roma - ESA World Meeting 2007

  30. Prices, Volumes and Returns End Problem Roma - ESA World Meeting 2007

  31. Human Behaviours • 7 types: Enthusiastic, Curious, Ingenuous, Expert-Frantic, Expert, Strange, Coherent • To check behaviours we act as “SumWebConsob” (such as SEC – Security Exchange Commission) • From “Expert-Frantic”: Market manipulation (scalping) Roma - ESA World Meeting 2007

  32. Price Manipulation • “transactions or orders to trade which secure a person, or persons acting in collaboration, the price of one or several financial instruments at an abnormal or artificial level.” (EU) • “to secure a dominant position over the supply of or demand for a financial instrument which has the effect of fixing, directly or indirectly, purchase or sale prices or creating other unfair trading conditions.”(EU) • Pump and dump - Transaction at successively higher prices, giving the appearance of real activity by investors, the dumping or selling at highs. • Wash Sales - Purchase and sale orders placed at same time where beneficial ownership do not change. Roma - ESA World Meeting 2007

  33. SumWebConsob Roma - ESA World Meeting 2007

  34. Effects • Lower percentage of execution (from 0.6 – 0.7 to 0.4 – 0.5) • Less orders • Penalties does not affect final ranking • Manipulator effect disappear • Moral suasion effects of “Commission” “Instuitution” Roma - ESA World Meeting 2007

  35. Strategy Example • Player # 331 • The winner • “Maximum” Buy Price • Buy and Sell periods • Group of orders • His comments about market movements and opportunities Roma - ESA World Meeting 2007

  36. Orders Manipulator Humans Roma - ESA World Meeting 2007

  37. Human Orders Price Density Roma - ESA World Meeting 2007

  38. Thanks to: • Pietro Terna (thesis supervisor and SUM author) • Paolo Mezzera and Andrea Vanara (SumWEB co-authors and experiments coordinators) • LIASES - Laboratorio di Informatica applicata alle Scienze Economiche e Sociali Giorgio Rota • Dipartimento di Scienze Economiche e Finanziarie Giuseppe Prato Roma - ESA World Meeting 2007

  39. Thank You Any questions? Roma - ESA World Meeting 2007

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