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104 lines
3.1 KiB
104 lines
3.1 KiB
''' |
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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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from PyQt5.Qt import pyqtSignal, QObject |
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from PyQt5 import QtCore |
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import talib |
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class Solver(QObject): |
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''' |
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''' |
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progress = pyqtSignal(int, int, name='progress') |
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done = pyqtSignal(list, name='done') |
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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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super().__init__(None) |
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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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@QtCore.pyqtSlot(dict) |
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def solve(self, params): |
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max_signals = 5 |
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max_strategies = params.get('num_strategies', 1000) |
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results = [] |
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min_trades = params.get('min_trades', 0) |
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min_win_rate = params.get('min_win_rate', 0) |
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min_sharpe = params.get('min_sharpe', 0) |
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is_long = params.get('direction', 'long') == 'long' |
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print(is_long) |
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while len(results) < 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, is_long) |
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if len(trades) >= min_trades: |
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result = self.evaluate_trades(trades) |
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if result['win_percentage'] > min_win_rate and result['sharpe'] > min_sharpe: |
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result['strategy'] = strategy |
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result['display_name'] = ' && '.join([signal.get_text() for signal in strategy]) |
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result['trades'] = trades |
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results.append(result) |
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self.progress.emit(len(results), max_strategies) |
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self.done.emit(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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total_won = len(list(filter(lambda x: x.pnl() > 0, trades))) |
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if len(trades) > 0: |
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result['win_percentage'] = total_won / len(trades) * 100 |
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else: |
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result['win_percentage'] = 0 |
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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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