P2P

[3]:

%matplotlib inline
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import networkx as nx
import pymarket as pm

Creates new market

[4]:

r = np.random.RandomState(1234)
mar = pm.Market()

mar.accept_bid(1, 6.7, 0, True, 0)
mar.accept_bid(1, 6.6, 1, True, 0)
mar.accept_bid(1, 6.5, 2, True, 0)
mar.accept_bid(1, 6.4, 3, True, 0)
mar.accept_bid(1, 6.3, 4, True, 0)
mar.accept_bid(1, 6, 5, True, 0)

mar.accept_bid(1, 1, 6, False, 0)
mar.accept_bid(1, 2, 7, False, 0)
mar.accept_bid(2, 3, 8, False, 0)
mar.accept_bid(2, 4, 9, False, 0)
mar.accept_bid(1, 6.1, 10, False, 0)

bids = mar.bm.get_df()
transactions, extras = mar.run('p2p', r=r)
stats = mar.statistics()

[5]:

bids # bids dataframe

[5]:
quantity price user buying time divisible
0 1 6.7 0 True 0 True
1 1 6.6 1 True 0 True
2 1 6.5 2 True 0 True
3 1 6.4 3 True 0 True
4 1 6.3 4 True 0 True
5 1 6.0 5 True 0 True
6 1 1.0 6 False 0 True
7 1 2.0 7 False 0 True
8 2 3.0 8 False 0 True
9 2 4.0 9 False 0 True
10 1 6.1 10 False 0 True 
[6]:

transactions.get_df() # transactions dataframe

[6]:
bid quantity price source active
0 3 1 3.70 6 False
1 6 1 3.70 3 False
2 5 0 0.00 10 True
3 10 0 0.00 5 True
4 2 1 4.25 7 False
5 7 1 4.25 2 False
6 4 1 5.15 9 False
7 9 1 5.15 4 True
8 0 1 4.85 8 False
9 8 1 4.85 0 True
10 5 1 5.00 9 False
11 9 1 5.00 5 False
12 1 1 4.80 8 False
13 8 1 4.80 1 False 
[7]:

extras # additional information characteristic of P2P trading

[7]:

{'trading_list': [[(3, 6), (5, 10), (2, 7), (4, 9), (0, 8)], [(5, 9), (1, 8)]]}

Orignal supply and demand curves

[8]:

mar.plot()
_images/P2P_8_0.png

Trades among participants

[9]:

ax = mar.plot_method('p2p')

/home/guso/anaconda3/lib/python3.6/site-packages/networkx/drawing/nx_pylab.py:611: MatplotlibDeprecationWarning: isinstance(..., numbers.Number)
  if cb.is_numlike(alpha):
_images/P2P_10_1.png

Analysis of the results

Round 1

  • 3 trades with 6, they both trade all their quantity and are not considered for next round
  • 5 trades with 10, the asked price by 10 is to high and no trade happens, they continue in next round
  • 2 trades with 7, they both trade all their quantity and are not considered for next round
  • 4 trades with 9, they trade one unit and 9 goes to next one with one remaining unit
  • 0 trades with 8, they trade one unit and 8 goes to next one with one remaining unit
  • 1 is not paired with anyone and continues to round 2

Round 2

  • 5 trades with 9, they both trade all their remaining quantity and are not considered for the next round
  • 1 trades with 8, they both trade all their remaining quantity and are not considered for the next round
  • 10 is not paired and continues to the round 3

Round 3

  • Only 10 remains, so no trade can ocurr, the algorithm ends.

Statistics

[10]:

print('Percentage of the maximum possible traded quantity')
stats['percentage_traded']

Percentage of the maximum possible traded quantity

[10]:

0.9999999999989999

[11]:

print('Percentage of the maximum possible total welfare')
stats['percentage_welfare']

Percentage of the maximum possible total welfare

[11]:

1.0

[12]:

print('Profits per user')
for u in bids.user.unique():
    print(f'User {u:2} obtained a profit of {stats["profits"]["player_bid"][u]:0.2f}')

Profits per user
User  0 obtained a profit of 1.85
User  1 obtained a profit of 1.80
User  2 obtained a profit of 2.25
User  3 obtained a profit of 2.70
User  4 obtained a profit of 1.15
User  5 obtained a profit of 1.00
User  6 obtained a profit of 2.70
User  7 obtained a profit of 2.25
User  8 obtained a profit of 3.65
User  9 obtained a profit of 2.15
User 10 obtained a profit of 0.00

[13]:

print(f'Profit to Market Maker was {stats["profits"]["market"]:0.2f}')

Profit to Market Maker was 0.00