code stringlengths 3 6.57k |
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self.daily_results.values() |
defaultdict(list) |
self.daily_results.values() |
getattr(daily_result, key) |
append(value) |
DataFrame.from_dict(results) |
set_index("date") |
self.output("逐日盯市盈亏计算完成") |
calculate_statistics(self, df: DataFrame = None, output=True) |
self.output("开始计算策略统计指标") |
cumsum() |
np.log(df["balance"] / df["balance"].shift(1) |
fillna(0) |
len(df) |
max() |
len(df) |
len(df[df["net_pnl"] > 0]) |
len(df[df["net_pnl"] < 0]) |
min() |
min() |
idxmin() |
isinstance(max_drawdown_end, date) |
idxmax() |
sum() |
sum() |
sum() |
sum() |
sum() |
mean() |
std() |
np.sqrt(240) |
np.sqrt(240) |
self.output("-" * 30) |
self.output(f"首个交易日：\t{start_date}") |
self.output(f"最后交易日：\t{end_date}") |
self.output(f"总交易日：\t{total_days}") |
self.output(f"盈利交易日：\t{profit_days}") |
self.output(f"亏损交易日：\t{loss_days}") |
self.output(f"起始资金：\t{self.capital:,.2f}") |
self.output(f"结束资金：\t{end_balance:,.2f}") |
self.output(f"总收益率：\t{total_return:,.2f}%") |
self.output(f"年化收益：\t{annual_return:,.2f}%") |
self.output(f"最大回撤: \t{max_drawdown:,.2f}") |
self.output(f"百分比最大回撤: {max_ddpercent:,.2f}%") |
self.output(f"最长回撤天数: \t{max_drawdown_duration}") |
self.output(f"总盈亏：\t{total_net_pnl:,.2f}") |
self.output(f"总手续费：\t{total_commission:,.2f}") |
self.output(f"总滑点：\t{total_slippage:,.2f}") |
self.output(f"总成交金额：\t{total_turnover:,.2f}") |
self.output(f"总成交笔数：\t{total_trade_count}") |
self.output(f"日均盈亏：\t{daily_net_pnl:,.2f}") |
self.output(f"日均手续费：\t{daily_commission:,.2f}") |
self.output(f"日均滑点：\t{daily_slippage:,.2f}") |
self.output(f"日均成交金额：\t{daily_turnover:,.2f}") |
self.output(f"日均成交笔数：\t{daily_trade_count}") |
self.output(f"日均收益率：\t{daily_return:,.2f}%") |
self.output(f"收益标准差：\t{return_std:,.2f}%") |
self.output(f"Sharpe Ratio：\t{sharpe_ratio:,.2f}") |
self.output(f"收益回撤比：\t{return_drawdown_ratio:,.2f}") |
statistics.items() |
in (np.inf, -np.inf) |
np.nan_to_num(value) |
self.output("策略统计指标计算完成") |
show_chart(self, df: DataFrame = None) |
go.Bar(y=df["net_pnl"], name="Daily Pnl") |
go.Histogram(x=df["net_pnl"], nbinsx=100, name="Days") |
fig.add_trace(balance_line, row=1, col=1) |
fig.add_trace(drawdown_scatter, row=2, col=1) |
fig.add_trace(pnl_bar, row=3, col=1) |
fig.add_trace(pnl_histogram, row=4, col=1) |
fig.update_layout(height=1000, width=1000) |
fig.show() |
update_daily_close(self, bars: Dict[str, BarData], dt: datetime) |
dt.date() |
bars.values() |
self.daily_results.get(d, None) |
daily_result.update_close_prices(close_prices) |
PortfolioDailyResult(d, close_prices) |
new_bars(self, dt: datetime) |
self.history_data.get((dt, vt_symbol) |
self.cross_limit_order() |
self.strategy.on_bars(bars) |
self.update_daily_close(self.bars, dt) |
cross_limit_order(self) |
list(self.active_limit_orders.values() |
self.strategy.update_order(order) |
self.strategy.update_order(order) |
self.active_limit_orders.pop(order.vt_orderid) |
min(order.price, long_best_price) |
max(order.price, short_best_price) |
str(self.trade_count) |
self.strategy.update_trade(trade) |
round_to(price, self.priceticks[vt_symbol]) |
extract_vt_symbol(vt_symbol) |
str(self.limit_order_count) |
cancel_order(self, strategy: StrategyTemplate, vt_orderid: str) |
self.active_limit_orders.pop(vt_orderid) |
self.strategy.update_order(order) |
write_log(self, msg: str, strategy: StrategyTemplate = None) |
self.logs.append(msg) |
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