# Prospect theory to the disposition effect

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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 about 1 year ago by elder silva.

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