python版本3.6.4
catalyst版本0.5.21
运行一段双均线策略后发生致命错误
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
from catalyst import run_algorithm
from catalyst.api import record, symbol, order_target_percent
from catalyst.exchange.utils.stats_utils import extract_transactions
NAMESPACE = 'dua1_moving_average'
SIGNAL_BUY = 'buy' # 买入信号
SIGNAL_SELL = 'sell' # 卖出信号
SIGNAL_INIT = '' # 观望信号
SHORT_WIN = 5 # 短周期窗口
LONG_WIN = 20 # 长周期窗口
def initialize(context):
"""
初始化
"""
context.i = 0 # 经历的交易周期
context.asset = symbol('btc_usdt') # 交易对
context.base_price = None # 初始价格
context.signal = SIGNAL_INIT # 交易信号
context.set_commission(maker=0.001, taker=0.001) # 设置手续费
context.set_slippage(slippage=0.001) # 设置滑点
def handle_data(context, data):
"""
在每个交易周期上运行的策略
"""
context.i += 1 # 记录交易周期
if context.i < LONG_WIN + 2:
# 如果交易周期果断，无法计算均线，则跳过循环
return
# 获得历史价格
history_data = data.history(context.asset,
'close',
bar_count=LONG_WIN + 2,
frequency='1D',
)
# 获取当前的持仓数量
pos_amount = context.portfolio.positions[context.asset].amount
# 计算双均线
short_avgs = history_data.rolling(window=SHORT_WIN).mean()
long_avgs = history_data.rolling(windows=LONG_WIN).mean()
# 双均线策略
# 短期均线上穿长期均线,做多
if (short_avgs[-3] < long_avgs[-3]) and (short_avgs[-2] >= long_avgs[-2]) and pos_amount == 0:
# 开多仓
order_target_percent(asset=context.asset, target=1)
context.signal = SIGNAL_BUY
# 短期均线下穿差昂起均线，做空
if (short_avgs[-3] > long_avgs[-3]) and (short_avgs[-2] <= long_avgs[-2]) and pos_amount > 0:
# 平多仓
order_target_percent(asset=context.asset, target=0)
context.signal = SIGNAL_SELL
# 获取当前的价格
price = data.current(context.asset, 'price')
if context.base_price is None:
# 如果没有设置初始价格，将第一个周期的价格作为初始价格
context.base_price = price
# 计算价格变化百分比，作为基准
price_change = (price - context.base_price) / context.base_price
# 记录每个交易周期的信息
# 1. 价格， 2. 现金， 3. 价格变化率， 4. 快线均值， 5. 慢线均值
record(price=price,
cash=context.portfolio.cash,
price_change=price_change,
short_mavg=short_avgs[-1],
long_mavg=long_avgs[-1],
signal=context.signal)
# 输出信息
print('日期：{}， 价格：{:.4f}, 资产：{:.2f}, 持仓量：{:.8f}, {}'.format(
data.current_dt, price, context.portfolio.portfolio_value, pos_amount, context.signal))
# 进行下一次交易前重置信号
context.signal = SIGNAL_INIT
def analyze(context, perf):
# 保存交易记录
perf.to_csv('./performance.csv')
# 获取交易所得计价货币
exchange = list(context.exchange.values())[0]
quote_currency = exchange.quote_currency.upper()
# 图1：可视化资产值
ax1 = plt.subplot(411)
perf['portfolio_value'].plot(ax=ax1)
ax1.set_ylabel('Portfolio Value\n({})'.format(quote_currency))
start, end = ax1.get_ylim()
ax1.yaxis.set_ticks(np.arange(start, end, (end - start) / 5))
# 图2： 可视化货币价格，均线和买入卖出点
ax2 = plt.subplot(412, sharex=ax1)
perf[['price', 'short_mavg', 'long_mavg']].plot(ax=ax2)
ax2.set_ylabel('{asset}\n({quote})'.format(
asset=context.asset.symbol,
quote=quote_currency
))
start, end = ax2.get_ylim()
ax2.yaxis.set_ticks(np.arange(start, end, (end - start) / 5))
# 获取交易时间点
transaction_df = extract_transactions(perf)
if not transaction_df.empty:
buy_df = transaction_df[transaction_df['amount'] > 0] # 买入点
sell_df = transaction_df[transaction_df['amount'] < 0] # 卖出点
ax2.scatter(
buy_df.index.to_pydatetime(),
perf.loc[buy_df.index, 'price'],
market='买',
s=100,
c='green',
label=''
)
ax2.scatter(
sell_df.index.to_pydatetime(),
perf.loc[sell_df.index, 'price'],
market='卖',
s=100,
c='red',
label=''
)
# 图3： 比较价格变化率和资产变化率
ax3 = plt.subplot(413, sharex=ax1)
perf[['algorithm_period_return', 'price_change']].plot(ax=ax3)
ax3.set_ylabel('Percent Change')
start, end = ax3.get_ylim()
ax3.yaxis.set_ticks(np.arange(start, end, (end - start) / 5))
# 图4： 可视化现金数量
ax4 = plt.subplot(414, share=ax1)
perf['cash'].plot(ax=ax4)
ax4.set_ylabel('Cash\n({})'.format(quote_currency))
start, end = ax4.get_ylim()
ax4.yaxis.set_ticks(np.arange(0, end, end / 5))
plt.tight_layout()
plt.show()
if name == 'main':
run_algorithm(
capital_base=1000,
data_frequency='daily',
initialize=initialize,
analyze=analyze,
handle_data=handle_data,
exchange_name='binance',
algo_namespace=NAMESPACE,
quote_currency='usdt',
start=pd.to_datetime('2017-10-01', utc=True),
end=pd.to_datetime('2018-10-01', utc=True)
)
[2022-04-08 03:50:13.522477] INFO: run_algo: Catalyst version 0.5.21
[2022-04-08 03:50:13.522477] WARNING: run_algo: Catalyst is currently in ALPHA. It is going through rapid development and it is subject to errors. Please use carefully. We encourage you to report any issue on GitHub: https://github.com/enigmampc/catalyst/issues
[2022-04-08 03:50:16.530131] INFO: run_algo: running algo in backtest mode
[2022-04-08 03:50:16.924870] INFO: exchange_algorithm: initialized trading algorithm in backtest mode
Fatal Python error: Acquisition count is -1 (line 22759)
Traceback (most recent call last):
File "catalyst\gens\sim_engine.pyx", line 109, in iter
GeneratorExit
Process finished with exit code -1073740791 (0xC0000409)
希望程序能正常运行