mhjensen
39 lines
1.3 KiB
Python
39 lines
1.3 KiB
Python
# Simulation of financial transations with or without saving/taxation on transaction
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# If lambda =0.0, no saving/taxation
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# See Patriarca et al http://www.sciencedirect.com/science/article/pii/S0378437104004327
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#!/usr/bin/env python
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import numpy as np
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import matplotlib.mlab as mlab
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import matplotlib.pyplot as plt
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import random
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# initialize the rng with a seed
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random.seed()
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# Hard coding of input parameters
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Agents = 500
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MCcounts = 1000
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Transactions = 100000
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startMoney = 1.0
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Lambda = 0.2
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FinancialAgents = startMoney*np.ones(Agents)
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for i in range (1, MCcounts, 1):
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for j in range (1, Transactions, 1):
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agent_i = int(Agents*random.random())
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agent_j = int(Agents*random.random())
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epsilon = random.random()
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if agent_i != agent_j:
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m1 = Lambda*FinancialAgents[agent_i] + (1-Lambda)*epsilon*(FinancialAgents[agent_i] + FinancialAgents[agent_j])
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m2 = Lambda*FinancialAgents[agent_j] + (1-Lambda)*(1-epsilon)*(FinancialAgents[agent_i] + FinancialAgents[agent_j])
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FinancialAgents[agent_i] = m1
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FinancialAgents[agent_j] = m2
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# the histogram of the data
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n, bins, patches = plt.hist(FinancialAgents, 50, facecolor='green')
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plt.xlabel('$x$')
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plt.ylabel('Distribution of wealth')
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plt.title(r'Money')
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plt.axis([0, 10, 0, 100])
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plt.grid(True)
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plt.show()
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