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BOOM AND MUST HERDING AND LEARNING FROM GURUs

BOOM AND MUST HERDING AND LEARNING FROM GURUs . By : Isavella Kapitani and Yuxiu Hu. What Causes Endogenous Boom and Bust in Stock Markets?. Brian Arthur from Santa Fe( 1977 ) institute stock market game.

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BOOM AND MUST HERDING AND LEARNING FROM GURUs

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  1. BOOM AND MUSTHERDING AND LEARNING FROM GURUs By : IsavellaKapitani and Yuxiu Hu

  2. What Causes Endogenous Boom and Bust in Stock Markets? • Brian Arthur from Santa Fe(1977) institute stock market game. • He says it is a contrarian or minority game for which there is NO HOMOGENOUS RATIONAL EXPECTATIONS. • SO TO WIN WHEN IN A MINORITY, AGENTS HAVE TO ENDOGENOUSLY BREAK AWAY FROM GROWING PRICE TREND. • TO TEST THIS, A SIMPLE SIMULATOR IS DONE: • PAY OFF FUNCTION PICKS WINNERS: • WHO ARE IN MINORITY • WHO ARE IN MAJORITY • WHO ARE RANDOM WHAT DO WE FIND?

  3. Win a stock game No unique algorithm/optimal strategy Reason: Price determination is Self-Reflexive, ()) ( based on believes)(based on reality) Strategies Modifying believes

  4. Then how to win a stock market game?learn from ‘Guru’ in the market. How to Learn from “Guru”? learn neighbors who have memory • In majority game, mimic from advisors who have long term memory; • In minority game, gain advices from advisors who have zero memory; • however, in random game, there is no definite rule to find the appropriate advisors.

  5. Testing and winner determination function: • Step 1: Individual forecast: • Each agent calculates its forecast based on its own past. • Mi () number of decisions and outcomes as follows: • The forecast fi,t+1 can take a value in the range [-1,+1], • where fi,t+1 >0 recommendation to buy, • fi,t+1 < 0 recommendation to sell, and • fi,t+1= 0 random recommendation. • Step 2: Decision: • The decision of an agent is based on a weighted sum of forecasts that its neighbours give it and its own. Zero-memory agents give advice based on random basis. • Majority agents win when the price is falling or increasing in a steady rate. • Minority agents win when the price if fluctuating and they represent the loop and behave differently from the majority of the agents. • Random agents win in both of the above cases.

  6. Comparison of statistics

  7. Degree of memory MAJORITY WINS: GURU IN THE CENTER OF NETWORK HAVE HIGHEST MEMORY 2) MINORITY WINS: GURU IN THE CENTER OF NETWORK HAVE ZERO MEMORY 3) RANDOM WINS: NO STRUCTURE

  8. Network Statistics 1)MAJORITY WINS: MORE AGENTS HAVE MORE MEMORY SINCE THE FOLLOW GURUS 3)RANDOM WINS: AGENTS BEHAVE RANDOMLY 2)MINORITY WINS: FAT TAIL, AGENTS HAVE ZERO MEMORY

  9. Price trend MA J O R I T Y When majority wins the price is increasing or decreasing. In this case is decreasing since everyone is buying. M I N O R I T Y When minority wins we experience boom and bust in price. The price is fluctuating but not is a stable rate as in the minority case. R A N D O M

  10. Network Statistics Minority: most of the agents are sellers. There are a few buyers as well. Majority: most of the agents are buyers. There are a few that are selling as well. = buyers =sellers Random: almost all of the agents are selling.

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