def test_get_weights(self):
prices = data.read_all_files("../historical-prices", 0, 4)
risk_calculation = r.RiskCalculation(prices, 'SP500')
self.assertAlmostEqual(
1,
sum([
val.weight
for key, val in risk_calculation.risk_params.items()
]))
def main():
working_directory = "historical-prices"
date_time_index = 0
prices_index = 4
balance = get_param("Balance $")
risk = get_param("Risk %")
commission = get_param("Commission %")
prices = csv.read_all_files(working_directory, date_time_index,
prices_index)
index_symbol = get_index_code(prices)
rc = risk_calc.RiskCalculation(prices, index_symbol, r_value_min_abs=0.6)
print()
symbols = rc.risk_params.keys()
risk_params = rc.risk_params.values()
data = {
'b1': [i.b1 for i in risk_params],
'r_value': [i.r_value for i in risk_params],
'weight': [i.weight for i in risk_params],
'trade_volume': [balance * i.weight for i in risk_params],
'risk_limit': [balance * i.weight * risk / 100.0 for i in risk_params],
'commission':
[balance * i.weight * commission / 100.0 for i in risk_params]
}
df = pd.DataFrame(data, index=symbols)
cols = [
'b1', 'r_value', 'weight', 'trade_volume', 'risk_limit', 'commission'
]
df = df[cols]
print(df)
print()
input("\npush 'ENTER' to exit.")
def main():
working_directory = "historical-prices"
date_time_index = 0
prices_index = 4
balance = get_param("Balance $")
risk = get_param("Risk %")
commission = get_param("Commission %")
prices = csv.read_all_files(working_directory, date_time_index, prices_index)
index_symbol = get_index_code(prices)
rc = risk_calc.RiskCalculation(prices, index_symbol, r_value_min_abs=0.6)
print()
symbols = rc.risk_params.keys()
risk_params = rc.risk_params.values()
data = {
'b1': [i.b1 for i in risk_params],
'r_value': [i.r_value for i in risk_params],
'weight': [i.weight for i in risk_params],
'trade_volume': [balance * i.weight for i in risk_params],
'risk_limit': [balance * i.weight * risk / 100.0 for i in risk_params],
'commission': [balance * i.weight * commission / 100.0 for i in risk_params]
}
df = pd.DataFrame(data, index=symbols)
cols = ['b1', 'r_value', 'weight', 'trade_volume', 'risk_limit', 'commission']
df = df[cols]
print(df)
print()
input("\npush 'ENTER' to exit.")
def test_get_weights(self):
prices = data.read_all_files("../historical-prices", 0, 4)
risk_calculation = r.RiskCalculation(prices, 'SP500')
self.assertAlmostEqual(1, sum([val.weight for key, val in risk_calculation.risk_params.items()]))
def test_get_regressions(self):
prices = data.read_all_files("../historical-prices", 0, 4)
risk_calculation = r.RiskCalculation(prices, 'SP500')
self.assertEquals(22 - 1, len(risk_calculation.risk_params))
def test_get_historical_prices(self):
historical_prices = csv.read_all_files("../historical-prices", 0, 4)
self.assertEquals(22, len(historical_prices))
for key, value in historical_prices.items():
self.assertEquals(473, len(value))
def test_get_regressions(self):
prices = data.read_all_files("../historical-prices", 0, 4)
risk_calculation = r.RiskCalculation(prices, 'SP500')
self.assertEquals(22 - 1, len(risk_calculation.risk_params))
