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79 lines
2.1 KiB
79 lines
2.1 KiB
8 years ago
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'''
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'''
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from data import series
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from execution.executor import Executor
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import random
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from math import inf
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import numpy
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class Solver():
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'''
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'''
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def __init__(self, series):
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'''
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Constructor
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'''
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self.series = series
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self.executor = Executor(series)
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self.generators = []
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def add_generator(self, generator):
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self.generators.append(generator)
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def solve(self):
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max_signals = 3
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max_strategies = 1000
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self.results = []
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for x in range(0, max_strategies):
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sig_num = random.randint(1, max_signals)
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strategy = []
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for i in range(0, sig_num):
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strategy.append(random.choice(self.generators).generate())
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trades = self.executor.execute(strategy)
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result = self.evaluate_trades(trades)
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result['display_name'] = ' && '.join([signal.get_text() for signal in strategy])
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self.results.append(result)
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return self.results
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def evaluate_trades(self, trades):
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result = {}
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profits = [x.pnl() for x in trades]
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result['trades_number'] = len(trades)
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result['total_pnl'] = sum(profits)
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if len(trades) > 0:
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result['avg_percentage'] = sum([trade.pnl_percentage() for trade in trades]) / len(trades)
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else:
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result['avg_percentage'] = 0
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gross_profit = sum([max(0, x.pnl()) for x in trades])
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gross_loss = sum([min(0, x.pnl()) for x in trades])
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if gross_loss != 0:
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result['profit_factor'] = gross_profit / (-gross_loss)
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else:
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result['profit_factor'] = inf
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if len(profits) > 0:
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mean = numpy.mean(profits)
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stddev = numpy.std(profits)
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if stddev != 0:
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result['sharpe'] = mean / stddev
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else:
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result['sharpe'] = 0
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else:
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result['sharpe'] = 0
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return result
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