Basic2FundTypesModel

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Default-person Nam Bui (Author)

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globals [
  price-change
  bid-volume
  ask-volume
  history   ;; list of past prices
]
breed [investors investor]
breed [traders trader]
breed [equities equity]
turtles-own [money
  share
  buy?
  sell?
  wealth
  strategies    ;; list of strategies
  best-strategy ;; index of the current best strategy
  prediction    ;; prediction whether stock will go up or down based on trend
]

to setup
  clear-all

  ;; set background color
  ask patches [set pcolor yellow]

  ;; mark investors and traders with color
  create-investors investor-number [set color orange]
  create-traders trader-number [set color blue]
  create-equities 1 [set color green]

  ;; initialize the past prices randomly so that traders have a history
  set history n-values(memory-size * 2) [random 10]

    ask investors [
        set shape "circle"
        set money 100
        set share 10
        set wealth money + share * share-price
        fd 10]

  ask traders [
    set shape "square"
    set money 100
    set share 10
    set strategies n-values number-strategies [random-strategy]
    set best-strategy first strategies
    set wealth money + share * share-price
    update-strategies
    fd 15]


  ask equities [
    set shape "circle"
    set size 1.5]

  reset-ticks
end 

to go

     ask traders [
    set prediction predict-share-price best-strategy sublist history 0 memory-size
    set buy? (prediction >= share-price)
    set sell? (prediction <= share-price)
  ]

  ask investors [
    if money > share-price[
     set buy? (share-price < true-value and -10 < price-change and price-change < 10)
  ]
  ]

  ask investors[
    set sell? (price-change < -10)
  ]

    ask traders with [buy?][
      set share share + 1
      set money money - share-price
      set bid-volume bid-volume + 1
    ]
    ask traders with [sell?][
      set share share - 1
      set money money + share-price
      set ask-volume ask-volume + 1
    ]

      ask investors with [buy?][
      set share share + 1
      set money money - share-price
      set bid-volume bid-volume + 1
    ]
    ask investors with [sell?][
      set share share - 1
      set money money + share-price
      set ask-volume ask-volume + 1
    ]

 ask traders[
    set wealth share-price * share
    set color scale-color blue wealth (max[wealth] of traders + 1) 0
  ]

   ask investors[
    set wealth share-price * share
    set color scale-color orange wealth (max[wealth] of traders + 1) 0
  ]

;; update price
 set price-change bid-volume - ask-volume
 set share-price share-price + price-change

;; update share-price history
set history fput share-price but-last history

;; have the traders decide what the new best strategy is
ask traders [update-strategies]

  tick
end 

;; determine which strategy would have predicted the best results had it been used
;; the best strategy is the one that resulted in the most price-change gain

to update-strategies
  let best-score memory-size * 100 + 1
  foreach strategies [ the-strategy ->
    let score 0
    let day 1
    repeat memory-size [
      set prediction predict-share-price the-strategy sublist history day (day + memory-size)
      set score score + abs(price-change)
      set day day + 1
    ]
    if (score >= best-score)[
      set best-score score
      set best-strategy the-strategy
  ]
  ]
end 

;; reports an agent's prediction of the current price. The agent puts a set of weight for each time period
;; strategy described by formula p(t) = p(t-1) * a(t-1) + p(t-2) * a(t-2) +...+ p(t-memory-size) * a(t-memory-size) + c * 100
;; p(t) is the price at time t, a is the weight for time t, c is a constant, memory-size is how far the agents look back.

to-report predict-share-price [strategy subhistory]
  ;;the first element of the strategy is the constant c, the price prediction in the absence of any other data.
  ;; then we multiply each day in the history by its respective weight.
  report 100 * first strategy + sum(map[[weight day] -> day * weight] butfirst strategy subhistory)
end 

;; this reports a random strategy, which is a set of weights from -1.0 to 1.0.

to-report random-strategy
  report n-values (memory-size + 1)[1.0 - random-float 2.0]
end 

There is only one version of this model, created about 1 year ago by Nam Bui.

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