def test_encode_decode_network(self):
network = AssetFundsNetwork.generate_random_network(
0.5, 3, 2, [1] * 3, [2] * 3, [1] * 2, [2] * 3, [1] * 3, [1.5] * 3,
ExponentialMarketImpactCalculator(1))
network.save_to_file('../../../resources/encoding_decoding_test.json')
decoded_network = AssetFundsNetwork.load_from_file(
'../../../resources/encoding_decoding_test.json',
ExponentialMarketImpactCalculator(1))
self.assertEqual(network, decoded_network)
def test_generate_random_network(self):
num_funds = 3
num_assets = 2
assets_num_shares = [3, 4]
initial_prices = [1, 2]
volatility = [1.5, 1]
initial_capitals = [100, 200, 300]
initial_leverages = [1, 2, 3]
tolerances = [4, 5, 6]
g = AssetFundsNetwork.generate_random_network(
0.5, num_funds, num_assets, initial_capitals, initial_leverages,
initial_prices, tolerances, assets_num_shares, volatility,
ExponentialMarketImpactCalculator(1))
assets = g.assets
funds = g.funds
self.assertEqual(len(assets), num_assets)
self.assertEqual(len(funds), num_funds)
for i in range(len(assets)):
asset = assets['a' + str(i)]
self.assertEqual(initial_prices[i], asset.price)
self.assertEqual(assets_num_shares[i], asset.daily_volume)
self.assertEqual(volatility[i], asset.volatility)
for i in range(len(funds)):
fund = funds['f' + str(i)]
self.assertEqual(initial_capitals[i], fund.initial_capital)
self.assertEqual(initial_leverages[i], fund.initial_leverage)
self.assertEqual(tolerances[i], fund.tolerance)
def gen_network_nonuniform_funds(game_config, num_assets, assets_file,
dir_name, num_low_risk, num_medium_risk,
num_high_risk):
game_config.num_assets = 10
game_config.num_funds = num_low_risk + num_medium_risk + num_high_risk
initial_capitals, initial_leverages, tolerances = gen_funds_parameters(
num_low_risk, num_medium_risk, num_high_risk, game_config)
#config.initial_fund_capital = 1000000
# = [game_config.initial_fund_capital] * game_config.num_funds
#initial_leverages = [game_config.initial_leverage] * game_config.num_funds
#tolerances = [game_config.tolerance] * game_config.num_funds
network = AssetFundsNetwork.generate_random_funds_network(
density=game_config.density,
num_funds=game_config.num_funds,
initial_capitals=initial_capitals,
initial_leverages=initial_leverages,
tolerances=tolerances,
num_assets=num_assets,
assets_file=assets_file,
mi_calc=ExponentialMarketImpactCalculator(
game_config.impact_calc_constant))
network.save_to_file(dir_name + 'network.json')
return network
def test_generate_network_from_graph(self):
num_funds = 2
num_assets = 2
daily_volumes = [3, 4]
volatility = [1.5, 1, 1.1]
initial_prices = [1, 2]
initial_capitals = [100, 200]
initial_leverages = [1, 2]
tolerances = [4, 5]
investment_proportions = {'f0': [0.6, 0.4], 'f1': [1.0]}
g = nx.DiGraph()
g.add_nodes_from([0, 1, 2, 3])
g.add_edges_from([(0, 2), (0, 3), (1, 3)])
network = AssetFundsNetwork.gen_network_from_graph(
g=g,
investment_proportions=investment_proportions,
initial_capitals=initial_capitals,
initial_leverages=initial_leverages,
assets_initial_prices=initial_prices,
tolerances=tolerances,
daily_volumes=daily_volumes,
volatility=volatility,
mi_calc=ExponentialMarketImpactCalculator(1))
assets = network.assets
funds = network.funds
self.assertEqual(len(assets), num_assets)
self.assertEqual(len(funds), num_funds)
for i in range(len(assets)):
asset = assets['a' + str(i)]
self.assertEqual(initial_prices[i], asset.price)
self.assertEqual(daily_volumes[i], asset.daily_volume)
self.assertEqual(volatility[i], asset.volatility)
for i in range(len(funds)):
fund = funds['f' + str(i)]
self.assertEqual(initial_capitals[i], fund.initial_capital)
self.assertEqual(initial_leverages[i], fund.initial_leverage)
self.assertEqual(tolerances[i], fund.tolerance)
prot0 = funds['f0'].portfolio
self.assertEqual(len(prot0.items()), 2)
self.assertEqual(prot0['a0'], 120)
self.assertEqual(prot0['a1'], 40)
prot1 = funds['f1'].portfolio
self.assertEqual(len(prot1.items()), 1)
self.assertEqual(prot1['a1'], 300)
self.assertTrue('a0' not in prot1)
def main():
assets_num_shares = [5, 5]
volatility = [1.5, 1, 1.1]
initial_prices = [1, 2]
initial_capitals = [100, 200]
initial_leverages = [1, 2]
tolerances = [4, 5]
investment_proportions = {'f0': [0.6, 0.4], 'f1': [1.0]}
g = nx.DiGraph()
g.add_nodes_from([0, 1, 2, 3])
g.add_edges_from([(0, 2), (0, 3), (1, 3)])
network = AssetFundNetwork.AssetFundsNetwork.gen_network_from_graph(
g, investment_proportions, initial_capitals, initial_leverages,
initial_prices, tolerances, assets_num_shares, volatility,
ExponentialMarketImpactCalculator(1))
solver = SingleAgentDynamicProgrammingSolver(network, 10000000, 0.5)
print(solver.results.value)
print(solver.results.actions)
def test_gen_network_from_graph_with_assets(self):
num_funds = 2
assets = {
'A1': Asset(price=1, daily_volume=3, symbol='A1', volatility=1.5),
'A2': Asset(price=2, daily_volume=4, symbol='A2', volatility=1)
}
initial_capitals = [100, 200]
initial_leverages = [1, 2]
tolerances = [4, 5]
investment_proportions = {'f0': [0.6, 0.4], 'f1': [1.0]}
g = nx.DiGraph()
g.add_nodes_from([0, 1, 2, 3])
g.add_edges_from([(0, 2), (0, 3), (1, 3)])
network = AssetFundsNetwork.gen_network_from_graph_with_assets(
g=g,
investment_proportions=investment_proportions,
initial_capitals=initial_capitals,
initial_leverages=initial_leverages,
tolerances=tolerances,
assets=assets,
mi_calc=ExponentialMarketImpactCalculator(1))
assets = network.assets
funds = network.funds
self.assertEqual(len(assets), 2)
self.assertEqual(len(funds), num_funds)
self.assertTrue((network.assets, assets))
for i in range(len(funds)):
fund = funds['f' + str(i)]
self.assertEqual(initial_capitals[i], fund.initial_capital)
self.assertEqual(initial_leverages[i], fund.initial_leverage)
self.assertEqual(tolerances[i], fund.tolerance)
prot0 = funds['f0'].portfolio
self.assertEqual(len(prot0.items()), 2)
self.assertEqual(prot0['A1'], 120)
self.assertEqual(prot0['A2'], 40)
prot1 = funds['f1'].portfolio
self.assertEqual(len(prot1.items()), 1)
self.assertEqual(prot1['A2'], 300)
self.assertTrue('A1' not in prot1)
def gen_network_uniform_funds(game_config, num_assets, assets_file, dir_name):
config = GameConfig()
# config.num_assets = 10
# config.num_funds = 4
config.initial_fund_capital = 1000000
initial_capitals = [game_config.initial_fund_capital
] * game_config.num_funds
initial_leverages = [game_config.initial_leverage] * game_config.num_funds
tolerances = [game_config.tolerance] * game_config.num_funds
network = AssetFundsNetwork.generate_random_funds_network(
density=game_config.density,
num_funds=num_assets,
initial_capitals=initial_capitals,
initial_leverages=initial_leverages,
tolerances=tolerances,
num_assets=num_assets,
assets_file=assets_file,
mi_calc=ExponentialMarketImpactCalculator(config.impact_calc_constant))
network.save_to_file(dir_name + 'network.json')
return network
def test_updated_price_sell_exp(self):
calc = ExponentialMarketImpactCalculator(2)
a = Asset(price=2, daily_volume=100, volatility=1.5, symbol='a1')
mi = calc.get_updated_price(10, a, -1)
npt.assert_almost_equal(1.6374, mi, decimal=4)
def test_updated_price_buy_exp(self):
calc = ExponentialMarketImpactCalculator(2)
a = Asset(price=2, daily_volume=100, volatility=1.5, symbol='a1')
updated_price = calc.get_updated_price(10, a, 1)
npt.assert_almost_equal(2.4428, updated_price, decimal=4)
def test_market_impact_sell_order_exp(self):
calc = ExponentialMarketImpactCalculator(2)
a = Asset(price=2, daily_volume=100, volatility=1.5, symbol='a1')
order = Sell('a1', 10)
mi = calc.get_market_impact(order, a)
npt.assert_almost_equal(0.8187, mi, decimal=4)
def get_network_from_dir(dirname):
config = GameConfig()
return AssetFundsNetwork.load_from_file(
dirname + '/network.json',
ExponentialMarketImpactCalculator(config.impact_calc_constant))