stock_exchange = stock_exchange.StockExchange(10000.0)
training_trader = DeepQLearningTrader(ObscureExpert(Company.A),
ObscureExpert(Company.B), False,
True)
# Save the final portfolio values per episode
final_values_training, final_values_test = [], []
for i in range(EPISODES):
logger.info(f"DQL Trader: Starting training episode {i}")
# train the net
stock_exchange.run(training_data, [training_trader])
training_trader.save_trained_model()
final_values_training.append(
stock_exchange.get_final_portfolio_value(training_trader))
# test the trained net
testing_trader = DeepQLearningTrader(ObscureExpert(Company.A),
ObscureExpert(Company.B), True,
False)
stock_exchange.run(testing_data, [testing_trader])
final_values_test.append(
stock_exchange.get_final_portfolio_value(testing_trader))
logger.info(
f"DQL Trader: Finished training episode {i}, "
f"final portfolio value training {final_values_training[-1]} vs. "
f"final portfolio value test {final_values_test[-1]}")
from matplotlib import pyplot as plt
#print(f'training_data[Company.A].get_row_count(): {training_data[Company.A].get_row_count()}')
# Create the stock exchange and one traders to train the net
stock_exchange = stock_exchange.StockExchange(10000.0)
training_trader = DeepQLearningTrader(ObscureExpert(Company.A), ObscureExpert(Company.B), False, True)
# Save the final portfolio values per episode
final_values_training, final_values_test = [], []
for i in range(EPISODES):
logger.info(f"DQL Trader: Starting training episode {i}")
# train the net
stock_exchange.run(training_data, [training_trader])
training_trader.save_trained_model()
final_values_training.append(stock_exchange.get_final_portfolio_value(training_trader))
# test the trained net
testing_trader = DeepQLearningTrader(ObscureExpert(Company.A), ObscureExpert(Company.B), True, False)
stock_exchange.run(testing_data, [testing_trader])
final_values_test.append(stock_exchange.get_final_portfolio_value(testing_trader))
logger.info(f"DQL Trader: Finished training episode {i}, "
f"final portfolio value training {final_values_training[-1]} vs. "
f"final portfolio value test {final_values_test[-1]}")
from matplotlib import pyplot as plt
plt.figure(figsize=(7, 5))
plt.plot(final_values_training, label='training', color="black")
plt.plot(final_values_test, label='test', color="green")
