Prospect theory to the disposition effect

Prospect theory to the disposition effect preview image

3 collaborators

Foto elder silva (Author)
Newton Da Costa Jr (Advisor)
Sergio da Silva (Advisor)

Tags

cumulative prospect theory 

Tagged by elder silva 27 days ago

disposition effect 

"Behavioral Financial"

Tagged by elder silva 27 days ago

stock market 

"Financial Agent-Based Model"

Tagged by elder silva 27 days ago

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globals[
  r         ; realized return
  D         ; demand
  I         ; indice
  p_t-1     ; price t - 1
  p_t       ; price
  buyer     ; total buyer
  seller    ; total seller
  hold      ; total hold
  t_w_DEI   ; time of hold winner shares of DEI agent
  c_w_DEI   ; count of total winner operation DEI agent
  t_l_DEI   ; time of hold loss shares of DEI agent
  c_l_DEI   ; count of total of loss operation DEI agent
  t_w_STP   ; time of hold winner shares of STOP agent
  c_w_STP   ; count of total of winner operation STOP agent
  t_l_STP   ; time of hold loss shares of STOP agent
  c_l_STP   ; count of total of loss operation STOP agent
]

patches-own[
  q            ; buy price
  B            ; information from neighbor -> buy
  S            ; information from neighbor -> sell
  H            ; information from neighbor -> hold
  xi           ; expected return
  lambda       ; Prospect theory parameter
  delta        ; Stop loss rule parameter
  beta         ; equation 4 parameter
  Pb_B         ; probability to buy - equation 9
  Pb_S         ; probability to sell - equation 9
  Pb_N         ; probability to hold - equation 9
  DEI?         ; disposition-effect investors
  STP?         ; stop-loss investors
  buyer?       ; auxiliary variable
  seller?      ; auxiliary variable
  psell        ; auxiliary variable
  transactions ; total number of transactions
  Wealth       ; wealtg of an agent
  time1        ; auxiliar variable
]

to setup
  if random? = false [random-seed 12345]     ; fixed seed of experiment
  clear-all     ; clean previous simulations
  ask patches[
    let t random-float 1                                 ; auxiliary variable distributed between zero and one
    ifelse t < STP [ set STP? true set DEI? false] [     ; handing agents among STP e DEI
      set STP? false set DEI? true ]                     ; handing agents among STP e DEI
    set buyer? false                                     ; cleaning variable
    set seller? false                                    ; cleaning variable
    set pcolor (white)                                   ; white for agents not operated in the period
    set q 0                                              ; purchase price equal to zero - initial setup
    set psell 0                                          ; selling price of zero - initial setup
    ifelse (i. = 1) or (i. = 0) [ set xi 0.01 ] [ set xi ((x_max / i.) * random i.) + 0.01]    ; create heterogeneous expectations
    set lambda LambdaTeste * xi                                 ; recording individual value
    set Wealth 100                                       ; arbitrary starting value of individual Wealth, not influence the results of experiments
    set transactions 0                                   ; resetting number of transactions the agent
    set delta random-float .02                           ; creating a particular value of the delta, used in the STOP strategy
    set beta random-float xi ]                           ; individualde beta value
  set I 0                                                ; setup indice
  set p_t P_initial                                      ; setup initial price
  set p_t-1 P_initial                                    ; setup initial price
  set t_w_DEI 0
  set c_w_DEI 0
  set t_l_DEI 0
  set c_l_DEI 0
  set t_w_STP 0
  set c_w_STP 0
  set t_l_STP 0
  set c_l_STP 0
  reset-ticks
end 

to fetch-information     ; Structure of "Equation 4"
  ifelse q != 0     [ set B omega + count neighbors with [ pcolor = blue ] ] [ set B count neighbors with [ pcolor = blue ] ]           ; value for B, adding omega own information using color to verify information from neighbors
  ifelse psell != 0 [ set S omega + count neighbors with [ pcolor = red  ] ] [ set S count neighbors with [ pcolor = red  ] ]           ; value for S, adding omega own information using color to verify information from neighbors
  ifelse (q = 0) and (psell = 0) [ set H count neighbors with [ pcolor = white ] ] [ set H count neighbors with [ pcolor = white ] ]    ; value for H, by adding omega own information using color to verify information from neighbors
  set Pb_B (B / (B + S + H)) + beta * I                                                                                                 ; probabilities buy
  set Pb_S (S / (B + S + H)) + beta * I                                                                                                 ; probabilities sell
  set Pb_N (H / (B + S + H))                                                                                                            ; probabilities hold
end 

to agent-STP   ; Structure of "Equation 9"
  let t random-float 1                                                                                 ;  auxiliary variable
  ifelse ticks < 100 [ ifelse t < (1 / 3) [ buy ] [ ifelse t > ( 2 / 3) [ sell ] [ not-operate ] ] ] [ ; first 100 simulations are used to setup the model
  ifelse q = 0 [
    ifelse (r) > (delta) [ STP-buy ] [ not-operate ]                                                   ; opening position, "equation 9" if the last return is greater than delta agent will operate.
    ] [
    ifelse p_t > q [                                                                                   ; checks if the agent closes the position or not, continuing "equation 9"
      ifelse (p_t - q) > (lambda * q) [
        if ticks > 200 [set t_w_STP (t_w_STP + (ticks - time1))]
        if ticks > 200 [set c_w_STP (c_w_STP + 1)]
        STP-sell ] [ not-operate ] ] [                                                                 ; Gain more than goal, compulsory closing the position
      ifelse (q - p_t) > (xi * q) [
        if ticks > 200 [set t_l_STP (t_l_STP + (ticks - time1))]
        if ticks > 200 [set c_l_STP (c_l_STP + 1)]
        STP-sell ] [ not-operate ] ] ] ]                                                               ; maximum loss reached, compulsory closing the position
end 

to buy ; structure for the agent to make a purchase
  set buyer? true          ; records the information that the agent made a purchase
  set seller? false        ; records that the agent not made a sale
  set pcolor (blue)        ; blue for agents who buy
  set q p_t                ; records of purchase price q
  set psell 0              ; sales price equal to zero means that the agent not made a sale
  set time1 ticks          ; counting time with posses share
end 

to sell ; structure for the agent making a sale
  set buyer? false         ; means not made a purchase
  set seller? true         ; records that held a sale
  set pcolor (red)         ; red agents to sell.
  set q 0                  ; purchase price equal to zero means that the agent not bought.
  set psell p_t            ; records sales price
  set time1 ticks          ; counting time with posses share
end 

to closing-operation-high ; agents MUST NOT use strategy STOP
  ;; p_t > q ---> GAIN
  ifelse (p_t - q) > (xi * q) [                                        ; this structure means: if (as I am earning) is greater than (My individual goal of GAIN)
    ifelse (random-float 1) < ((p_t - q - (xi * q)) / (xi * q)) [      ; if yes, verifies how much above the target ...
      set transactions transactions + 1                                ; ... and increases the probability as the gain exceeds the goal.
      set Wealth Wealth * (1 + ((p_t - q) / q))                        ; Wealth updates the agent
      set buyer? false
      set seller? true
      set pcolor (red)
      set q 0
      set psell 0
      if ticks > 200 [set t_w_DEI (t_w_DEI + (ticks - time1))]
      if ticks > 200 [set c_w_DEI (c_w_DEI + 1)]
      ] [ not-operate ]
      ] [ not-operate ]
end 

to closing-operation-falling ; agents MUST NOT use strategy STOP
  ;; p_t < q ---> LOSS
  ifelse (q - p_t) > (lambda * q) [ ; this structure means: if (as I am earning) is greater than (individual goal - bearable loss - individual LOSS)
    ifelse (random-float 1) < ((q - p_t - (q * lambda)) / (lambda * q)) [ ; probability to end position
      set transactions transactions + 1     ;
      set Wealth Wealth * (1 + ((p_t - q) / q))     ;
      set buyer? false     ;
      set seller? true     ;
      set pcolor (red)     ;
      set q 0              ;
      set psell 0          ;
      if ticks > 200 [set t_l_DEI (t_l_DEI + (ticks - time1))]
      if ticks > 200 [set c_l_DEI (c_l_DEI + 1)]
      ] [ not-operate ]    ;
      ] [ not-operate ]    ;
end 

to closing-shortposition-high ; agents MUST NOT use strategy STOP      - Agent conducted an asset sale, gain if the asset falls and loses if the asset rise
  ;; p_t > psell ---> LOSS
  ifelse (p_t - psell) > (lambda * psell) [                                           ; this structure means: if (as I am earning) is greater than (individual goal - bearable loss - individual LOSS)
    ifelse (random-float 1) < ((p_t - psell - (lambda * psell)) / (lambda * psell)) [ ; probability to end position
      set transactions transactions + 1
      set Wealth Wealth * (1 + ((psell - p_t) / psell))
      set buyer? true
      set seller? false
      set pcolor (blue)
      set q 0
      set psell 0
      if ticks > 200 [set t_l_DEI (t_l_DEI + (ticks - time1))]
      if ticks > 200 [set c_l_DEI (c_l_DEI + 1)]
      ] [ not-operate ]
      ] [ not-operate ]
end 

to closing-shortposition-falling ; agents MUST NOT use strategy STOP
  ;; psell > p_t ---> GAIN
  ifelse (psell - p_t) > (xi * psell) [                                                ; this structure means: if (as I am earning) is greater than (My individual goal of GAIN)
    ifelse (random-float 1) < ((psell - p_t - (xi * psell)) / (xi * psell)) [ ;
      set transactions transactions + 1
      set Wealth Wealth * (1 + ((psell - p_t) / psell))
      set buyer? true
      set seller? false
      set pcolor (blue)
      set q 0
      set psell 0
      if ticks > 200 [set t_w_DEI (t_w_DEI + (ticks - time1))]
      if ticks > 200 [set c_w_DEI (c_w_DEI + 1)]
      ] [ not-operate ]
    ] [ not-operate ]
end 

to STP-buy ;; agents using order STOP
  set buyer? true
  set seller? false
  set pcolor (blue)
  set q p_t
  set psell 0
  set time1 ticks
end 

to STP-sell ;; agents using order STOP
  set transactions transactions + 1
  set Wealth Wealth * (1 + ((p_t - q) / q))
  set buyer? false
  set seller? true
  set pcolor (red)
  set q 0
  set psell 0
end 

to not-operate ;; all agents
  set buyer? false
  set seller? false
  set pcolor (white)
end 

to traders    ; agents in the distribution of heterogeneity received minimum value of "x". Very active agents in the real market would be daytrader.
  let t random-float 1             ; t = auxiliary variable; first 100 simulations are used to setup the model
  ifelse ticks < 100 [ ifelse t < (1 / 3) [ buy ] [ ifelse t > ( 2 / 3) [ sell ] [ not-operate ] ] ] [ fetch-information  ifelse t < ((beta * I) + Pb_B) [ buy ] [ ifelse t > (1 - Pb_S + (beta * I)) [ sell ] [ not-operate ] ] ]
  ifelse q != 0 [ set transactions transactions + 1 set Wealth Wealth * (1 + ((p_t - q) / q)) ] [ if psell != 0 [ set Wealth Wealth * (1 + ((psell - p_t) / psell)) ]  ]
end 

to agent-DEI    ; Finishing structure operation of the agent subject to the disposition effect
  let t random-float 1                                                                                             ; auxiliary variable
  ifelse ticks < 100 [ ifelse t < (1 / 3) [ buy ] [ ifelse t > ( 2 / 3) [ sell ] [ not-operate ] ] ] [             ; first 100 simulations are used to setup the model
  ifelse q != 0 [
    ifelse p_t > q [ closing-operation-high ] [ closing-operation-falling ] ] [                                    ; checks whether the agent is winning or losing, and calls one of the functions
    ifelse psell != 0 [                                                                                            ; agent sold
      ifelse p_t > psell [ closing-shortposition-high ] [ closing-shortposition-falling ] ] [                      ; checks whether the agent is winning or losing, and calls one of the functions
      fetch-information
      ifelse t < (Pb_B) [ buy ] [                                                                                  ; uses equation 4 to verify that buys, sells, or does not operate
        ifelse t > (1 - Pb_S) [ sell ] [ not-operate ] ] ] ] ]
end 

to I-indice ; computing indice I
  ifelse (buyer + seller ) != 0 [ ifelse ISTeste = true [ if ((ticks mod 50) = 0) and (ticks > 1) [ set I ((buyer - seller) / (buyer + seller + hold)) + (I_Choque) ] ] [ set I 0 ] ] [ set I 0 ]
end 

to go ; Run
  ask patches[
    ifelse xi = 0.01 [ traders ] [
      ifelse STP? [ agent-STP ] [ agent-DEI ] ] ] ; checking which type of agent. Calls one of its functions as above.
  set buyer count patches with [buyer?]
  set seller count patches with [seller?]
  set hold (max-pycor * max-pxcor) - buyer - seller
  ifelse (buyer + seller) != 0 [ set D ((buyer - seller) / (buyer + seller + hold)) ] [ set D 0 ] ; computing demand period
  set p_t (((exp(D) - exp(- D)) / (exp(D) + exp(- D)) + 1 ) * p_t-1)                              ; computing the price period
  set r (ln(p_t) - ln(p_t-1))                                                                     ; computing the first return period
  set p_t-1 p_t                                                                                   ; updating price of the previous period
  I-indice                                                                                        ; calling function indice I
  tick ; new period
end 







There is only one version of this model, created 27 days ago by elder silva.

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