Artificial Financial Market (Modified)

Artificial Financial Market (Modified) preview image

1 collaborator

Tags

(This model has yet to be categorized with any tags)
Model group Risk Mathematics | Visible to everyone | Changeable by the author
Model was written in NetLogo 5.2.1 • Viewed 522 times • Downloaded 27 times • Run 0 times
Download the 'Artificial Financial Market (Modified)' modelDownload this modelEmbed this model

Do you have questions or comments about this model? Ask them here! (You'll first need to log in.)


Info tab cannot be displayed because of an encoding error

Comments and Questions

Please start the discussion about this model! (You'll first need to log in.)

Click to Run Model

patches-own [my-sentiment ;; Each trader can have a positive sentiment (+1), in which case he is 'bullish',
                          ;; that is, he beleives the market will rise or he can have a
                           ;; negative sentiment (-1) in which case he is 'bearish', that is, he beleives the market will fall.
                          ;; if the sentiment is positive the trader buys one share if it is negative he sells
                          ;; one share.
             local-field ;; local sentiment field generated by neighbors
             number-of-shares ;; Number of shares that each trader has (if negative it implies that the
                              ;; trader is 'short' (we assume that there are no limits to short selling).
             opinion-vol  ;; Volatility in a trader's own interpretation of the news.
             propensity-to-sentiment-contagion ;; Propensity to be influenced by friends sentiments
                                                ;; regarding the news qualitative nature.
             base-propensity-to-sentiment-contagion
             news-sensitivity ;; Sensitivity that the traders have to the news qualitative meaning.
             market-impact ;; Volume of shares that the trader bids
             market-order ;; Market order.
             ]

globals [log-price
         returns
         sentiment-field
         news-qualitative-meaning  ;; There is a set of news concerning the market that reaches all traders
                                   ;; these news are attributed a qualitative meaning
         number-of-traders
         volatility-indicator
         total-bullish
         total-bearish
         ]

to setup
;; (for this model to work with NetLogo's new plotting features,
  ;; __clear-all-and-reset-ticks should be replaced with clear-all at
  ;; the beginning of your setup procedure and reset-ticks at the end
  ;; of the procedure.)
ca
ask patches [
             set number-of-shares 1 ;; Each trader starts with one unit of shares
             set opinion-vol sigma + random-float 0.1
             set news-sensitivity (random-float max-news-sensitivity)
             set base-propensity-to-sentiment-contagion (random-float max-base-propensity-to-sentiment-contagion)
             set propensity-to-sentiment-contagion base-propensity-to-sentiment-contagion
             ]
set log-price random 10
set number-of-traders count patches
end 

to go
news-arrival
agent-decision
market-clearing
update-market-sentiment
compute-volatility-indicator
do-plot
end 


;;;;;;;;;;;;;;;;;;;;;;;;;;
; News Arrival mechanism ;
;;;;;;;;;;;;;;;;;;;;;;;;;;

to news-arrival
  ifelse (random-normal 0 1) > 0 [set news-qualitative-meaning 1] [set news-qualitative-meaning -1]
end 
;;;;;;;;;;;;;;;;;;;;;;;;;;
;;;;;;;;;;;;;;;;;;;;;;;;;;

;;;;;;;;;;;;;;;;;;;;;;;;;
; Agent's decision rule ;
;;;;;;;;;;;;;;;;;;;;;;;;;
; The agent's (in this case trader) sentiment is positive (+1) and he buys if
; the friends sentiment regarding the market, multiplied by the agent's propensity to be contagiated by
; the sentiment of his friends, plus the news multiplied by the agent's news sensitivity, plus a random
; term is larger than zero, otherwise, the agent's sentiment is set (-1) and the agent sells.

to agent-decision

    ask patches
    [
      set local-field sum [my-sentiment] of neighbors4
      ifelse ((propensity-to-sentiment-contagion * local-field + news-sensitivity * news-qualitative-meaning + random-normal miu opinion-vol) > 0)
      [set my-sentiment 1] [set my-sentiment -1]]
    ; If the agent's sentiment is positive the colour is set green, if he is negative it is set red.
    set total-bullish count patches with [my-sentiment = 1]
    set total-bearish count patches with [my-sentiment = -1]
    set sentiment-field mean [my-sentiment] of patches
    ask patches [
      ifelse my-sentiment = 1
      [
        set pcolor green
        set market-impact my-sentiment * total-bullish
        set number-of-shares my-sentiment * number-of-shares + market-impact
        ]
      [
        set pcolor red
        set market-impact my-sentiment * total-bearish
        set number-of-shares number-of-shares + market-impact
        ]
      ]
end 
;;;;;;;;;;;;;;;;;;;;;;;;;;
;;;;;;;;;;;;;;;;;;;;;;;;;;

;;;;;;;;;;;;;;;;;;;;;;;;;;;;;
; Market clearing mechanism ;
;;;;;;;;;;;;;;;;;;;;;;;;;;;;;

to market-clearing

  set returns mean [market-impact] of patches / market-depth
  set log-price (log-price + returns)
end 
;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;
;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;

;;;;;;;;;;;;;;;;;;;;;;;;;;
; Update market sentiment;
;;;;;;;;;;;;;;;;;;;;;;;;;;

to update-market-sentiment
  ask patches
  [; A good(bad) news confirmed by a market movement in the direction of that news
   ; leads to a greater propensity to sentiment contagion. If the good(bad) news is not
   ; confirmed by a market movement in the same direction the propensity to sentiment contagion
   ; decreases.
    if (returns > 0) and (news-qualitative-meaning > 0)
      [set propensity-to-sentiment-contagion base-propensity-to-sentiment-contagion + sentiment-field]
    if (returns > 0) and (news-qualitative-meaning < 0)
      [set propensity-to-sentiment-contagion base-propensity-to-sentiment-contagion - sentiment-field]
    if (returns < 0) and (news-qualitative-meaning < 0)
      [set propensity-to-sentiment-contagion base-propensity-to-sentiment-contagion - sentiment-field]
    if (returns < 0) and (news-qualitative-meaning > 0)
      [set propensity-to-sentiment-contagion base-propensity-to-sentiment-contagion + sentiment-field]

  ]
end 
;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;
;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;

;;;;;;;;;;;;;;;;;;;;;;;;
; Deviations to EMH ;
;;;;;;;;;;;;;;;;;;;;;;;;

to compute-volatility-indicator
  set volatility-indicator abs(returns)
end 

;;;;;;;;;;;;;;;;;;;;;;;;;;
;;;;;;;;;;;;;;;;;;;;;;;;;;

to do-plot
  set-current-plot "Log-price"
  set-current-plot-pen "log-price"
  plot log-price
  set-current-plot "Returns (%)"
  set-current-plot-pen "returns"
  plot returns * 100
  set-current-plot "Volatility (%)"
  set-current-plot-pen "volatility"
  plot volatility-indicator * 100
end 
;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;
;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;

There is only one version of this model, created about 2 years ago by Carlos Pedro S. Gonçalves.

Attached files

File Type Description Last updated
Artificial Financial Market (Modified).png preview Preview for 'Artificial Financial Market (Modified)' about 2 years ago, by Carlos Pedro S. Gonçalves Download

This model does not have any ancestors.

This model does not have any descendants.