models = [
RidgeCV(alphas=[0.2, 0.3, 0.6], cv=6, fit_intercept=True)
for i in range(30)
]
for i in range(30):
models[i].fit(get_ith_col_x(x, i), get_ith_col_y(y, i))
# model = Lstm(time_steps=p, input_size=30, output_size=30)
# model.load_data(x, y, units=50, epochs=20, batch_size=50)
market.buy(P.items())
trades = []
y_preds = []
cash_y = []
cash_x = []
for prices in market.iterate(tick_names=False):
y_pred = [
m.predict(get_ith_col_x(np.array(prices).reshape((-1, p, 30)), i))
for i, m in enumerate(models)
]
y_pred = np.array(y_pred).flatten()
y_preds.append(y_pred)
returns = np.divide(
np.subtract(np.array(y_pred), np.array(prices[-1])),
np.array(prices[-1]))
returns = returns.flatten()
max_return = max(returns)
max_index = list(returns).index(max_return)
cash = market.liquidate_stocks(market.ticks)
cash_y.append(cash)
# print(f'cash: {cash}, sec: {market.get_tick_from_index(max_index)}')
