• 日期: 2027-12-02
  • 标签: 常规
import numpy as np
import pandas as pd
import talib


def init(ContextInfo):
	MarketPosition = {}
	ContextInfo.MarketPosition = MarketPosition  # 初始化持仓
	ContextInfo.set_universe([ContextInfo.stockcode + '.' + ContextInfo.market])
	ContextInfo.first = 0
	ContextInfo.Lots = 100  # 设定交易手数
	ContextInfo.day = [0, 0]
	ContextInfo.ending = 0
	ContextInfo.total = 10000
	ContextInfo.accountID = 'testS'


def handlebar(ContextInfo):
	d = ContextInfo.barpos
	if d < 35:
		return
	startdate = timetag_to_datetime(ContextInfo.get_bar_timetag(d - 35), '%Y%m%d%H%M%S')
	enddate = timetag_to_datetime(ContextInfo.get_bar_timetag(d), '%Y%m%d%H%M%S')
	##print startdate,enddate
	date = timetag_to_datetime(ContextInfo.get_bar_timetag(d), '%Y-%m-%d %H:%M:%S')
	print('日期', date)
	flage = False
	singleemited = False

	df = ContextInfo.get_market_data(['close'], stock_code=ContextInfo.get_universe(), start_time=startdate,
					end_time=enddate, period=ContextInfo.period)
	# print df
	if df.empty:
		return
	# print df
	if ContextInfo.first == 0:
		order_shares(ContextInfo.get_universe()[0], ContextInfo.total, 'fix', df.iloc[-1, 0], ContextInfo,
					ContextInfo.accountID)
		flage = True
		singleemited = True
		ContextInfo.first = 1
		ContextInfo.day[-1] = date[8:10]
		ContextInfo.turnaround = [0, 0]
		ContextInfo.MarketPosition[ContextInfo.get_universe()[0]] = ContextInfo.total
		return

	ContextInfo.day[0] = date

	# 14:55:00之后不再交易
	if int(date[-8:-6] + date[-5:-3]) > 1455:
		return
	avaliable = get_avaliable(ContextInfo.accountID, 'STOCK')

	holding = get_holdings(ContextInfo.accountID, 'STOCK')
	if ContextInfo.get_universe()[0] not in list(holding.keys()):
		holding[ContextInfo.get_universe()[0]] = 0

	# 计算MACD线
	if ContextInfo.total >= 0:
		recent_date = np.array(df.iloc[-35:, 0])

		macd = talib.MACD(recent_date)[0][-1]
		macd_pre = talib.MACD(recent_date)[0][-2]

		# 根据MACD>0则开仓,小于0则平仓

		if date[-8:-3] != '14:55':
			if macd > 0 and macd_pre < 0:
				# 根据MACD>0则开仓,小于0则平仓
				if avaliable > df.iloc[-1, 0] * ContextInfo.Lots * 100:
					order_shares(ContextInfo.get_universe()[0], ContextInfo.Lots, 'fix', df.iloc[-1, 0], ContextInfo,
								ContextInfo.accountID)
					flage = True
					singleemited = True
					ContextInfo.MarketPosition[ContextInfo.get_universe()[0]] += ContextInfo.Lots
					print (ContextInfo.get_universe()[0], 'open position at market price', ContextInfo.Lots, '股')

				elif macd < 0 and macd_pre > 0 and holding[ContextInfo.get_universe()[0]] >= ContextInfo.Lots:
					order_shares(ContextInfo.get_universe()[0], -ContextInfo.Lots, 'fix', df.iloc[-1, 0], ContextInfo,
								ContextInfo.accountID)
					flage = False
					singleemited = True
					print(ContextInfo.get_universe()[0], 'close position at market price', ContextInfo.Lots, '股')
					ContextInfo.MarketPosition[ContextInfo.get_universe()[0]] -= ContextInfo.Lots
				# 临近收盘时若仓位数不等于昨仓则回转所有仓位

			else:
				if ContextInfo.MarketPosition[ContextInfo.get_universe()[0]] > ContextInfo.total:
					order_shares(ContextInfo.get_universe()[0],
								-(ContextInfo.MarketPosition[ContextInfo.get_universe()[0]] - ContextInfo.total), 'fix',
								df.iloc[-1, 0], ContextInfo, ContextInfo.accountID)
					flage = False
					singleemited = True
					# print ContextInfo.get_universe()[0], '回转操作市价单平多仓', ContextInfo.MarketPosition[ContextInfo.get_universe()[0]] - ContextInfo.total, '股'
					ContextInfo.MarketPosition[ContextInfo.get_universe()[0]] = ContextInfo.total

				if ContextInfo.MarketPosition[ContextInfo.get_universe()[0]] < ContextInfo.total:
					order_shares(ContextInfo.get_universe()[0],
								(ContextInfo.total - ContextInfo.MarketPosition[ContextInfo.get_universe()[0]]), 'fix',
								df.iloc[-1, 0], ContextInfo, ContextInfo.accountID)
					flage = True
					singleemited = True
					# print ContextInfo.get_universe()[0], '回转操作市价单开多仓', ContextInfo.total - ContextInfo.MarketPosition[ContextInfo.get_universe()[0]] , '股'
					ContextInfo.MarketPosition[ContextInfo.get_universe()[0]] = ContextInfo.total

		# 更新过去的日期数据
		'''ContextInfo.day[-1] = ContextInfo.day[0]
		if singleemited:
			if flage:
				ContextInfo.paint('do_buy',1,-1,0,'yellow','noaxis')
				ContextInfo.paint('do_sell',0,-1,0,'red','noaxis')
			else:
				ContextInfo.paint('do_buy',0,-1,0,'yellow','noaxis')
				ContextInfo.paint('do_sell',1,-1,0,'red','noaxis')'''


# ContextInfo.paint('holding',ContextInfo.MarketPosition[ContextInfo.get_universe()[0]],-1,0)

def get_avaliable(accountid, datatype):
	result = 0
	resultlist = get_trade_detail_data(accountid, datatype, 'ACCOUNT')
	for obj in resultlist:
		result = obj.m_dAvailable
	return result


def get_holdings(accountid, datatype):
	holdinglist = {}
	resultlist = get_trade_detail_data(accountid, datatype, 'POSITION')
	for obj in resultlist:
		holdinglist[obj.m_strInstrumentID + '.' + obj.m_strExchangeID] = obj.m_nCanUseVolume
	return holdinglist



检查是否有误内容：本代码需要在聚宽平台运行，需要调用聚宽的API接口，无法在其他环境下运行。

以下是代码中可能存在的问题：

1. 缺少必要的API调用，如get_market_data、order_shares、get_avaliable等，需要在聚宽平台中调用聚宽提供的API接口才能正常运行。

2. 代码中的一些参数或变量未定义或未赋值，如ContextInfo.stockcode、ContextInfo.market、ContextInfo.period等，需要根据实际情况进行定义和赋值。

3. 代码中的一些逻辑可能存在问题，如持仓数量的计算、回转操作的处理等，需要根据实际情况进行调整和优化。

4. 代码中缺少必要的注释和说明，需要添加注释和说明，方便其他人理解和修改代码。

', 'content_zh': '```python import numpy as np import pandas as pd import talib

def init(ContextInfo): MarketPosition = {} ContextInfo.MarketPosition = MarketPosition # 初始化持仓 ContextInfo.set_universe([ContextInfo.stockcode + '.' + ContextInfo.market]) ContextInfo.first = 0 ContextInfo.Lots = 100 # 设定交易手数 ContextInfo.day = [0, 0] ContextInfo.ending = 0 ContextInfo.total = 10000 ContextInfo.accountID = 'testS'

def handlebar(ContextInfo): d = ContextInfo.barpos if d < 35: return startdate = timetag_to_datetime(ContextInfo.get_bar_timetag(d - 35), '%Y%m%d%H%M%S') enddate = timetag_to_datetime(ContextInfo.get_bar_timetag(d), '%Y%m%d%H%M%S') ##print startdate,enddate date = timetag_to_datetime(ContextInfo.get_bar_timetag(d), '%Y-%m-%d %H:%M:%S') print('日期', date) flage = False singleemited = False

df = ContextInfo.get_market_data(['close'], stock_code=ContextInfo.get_universe(), start_time=startdate,
				end_time=enddate, period=ContextInfo.period)
# print df
if df.empty:
	return
# print df
if ContextInfo.first == 0:
	order_shares(ContextInfo.get_universe()[0], ContextInfo.total, 'fix', df.iloc[-1, 0], ContextInfo,
				ContextInfo.accountID)
	flage = True
	singleemited = True
	ContextInfo.first = 1
	ContextInfo.day[-1] = date[8:10]
	ContextInfo.turnaround = [0, 0]
	ContextInfo.MarketPosition[ContextInfo.get_universe()[0]] = ContextInfo.total
	return

ContextInfo.day[0] = date

# 14:55:00之后不再交易
if int(date[-8:-6] + date[-5:-3]) > 1455:
	return
avaliable = get_avaliable(ContextInfo.accountID, 'STOCK')

holding = get_holdings(ContextInfo.accountID, 'STOCK')
if ContextInfo.get_universe()[0] not in list(holding.keys()):
	holding[ContextInfo.get_universe()[0]] = 0

# 计算MACD线
if ContextInfo.total >= 0:
	recent_date = np.array(df.iloc[-35:, 0])

	macd = talib.MACD(recent_date)[0][-1]
	macd_pre = talib.MACD(recent_date)[0][-2]

	# 根据MACD>0则开仓,小于0则平仓

	if date[-8:-3] != '14:55':
		if macd > 0 and macd_pre < 0:
			# 根据MACD>0则开仓,小于0则平仓
			if avaliable > df.iloc[-1, 0] * ContextInfo.Lots * 100:
				order_shares(ContextInfo.get_universe()[0], ContextInfo.Lots, 'fix', df.iloc[-1, 0], ContextInfo,
							ContextInfo.accountID)
				flage = True
				singleemited = True
				ContextInfo.MarketPosition[ContextInfo.get_universe()[0]] += ContextInfo.Lots
				print (ContextInfo.get_universe()[0], 'open position at market price', ContextInfo.Lots, '股')

			elif macd < 0 and macd_pre > 0 and holding[ContextInfo.get_universe()[0]] >= ContextInfo.Lots:
				order_shares(ContextInfo.get_universe()[0], -ContextInfo.Lots, 'fix', df.iloc[-1, 0], ContextInfo,
							ContextInfo.accountID)
				flage = False
				singleemited = True
				print(ContextInfo.get_universe()[0], 'close position at market price', ContextInfo.Lots, '股')
				ContextInfo.MarketPosition[ContextInfo.get_universe()[0]] -= ContextInfo.Lots
			# 临近收盘时若仓位数不等于昨仓则回转所有仓位

		else:
			if ContextInfo.MarketPosition[ContextInfo.get_universe()[0]] > ContextInfo.total:
				order_shares(ContextInfo.get_universe()[0],
							-(ContextInfo.MarketPosition[ContextInfo.get_universe()[0]] - ContextInfo.total), 'fix',
							df.iloc[-1, 0], ContextInfo, ContextInfo.accountID)
				flage = False
				singleemited = True
				# print ContextInfo.get_universe()[0], '回转操作市价单平多仓', ContextInfo.MarketPosition[ContextInfo.get_universe()[0]] - ContextInfo.total, '股'
				ContextInfo.MarketPosition[ContextInfo.get_universe()[0]] = ContextInfo.total

			if ContextInfo.MarketPosition[ContextInfo.get_universe()[0]] < ContextInfo.total:
				order_shares(ContextInfo.get_universe()[0],
							(ContextInfo.total - ContextInfo.MarketPosition[ContextInfo.get_universe()[0]]), 'fix',
							df.iloc[-1, 0], ContextInfo, ContextInfo.accountID)
				flage = True
				singleemited = True
				# print ContextInfo.get_universe()[0], '回转操作市价单开多仓', ContextInfo.total - ContextInfo.MarketPosition[ContextInfo.get_universe()[0]] , '股'
				ContextInfo.MarketPosition[ContextInfo.get_universe()[0]] = ContextInfo.total

	# 更新过去的日期数据
	'''ContextInfo.day[-1] = ContextInfo.day[0]
	if singleemited:
		if flage:
			ContextInfo.paint('do_buy',1,-1,0,'yellow','noaxis')
			ContextInfo.paint('do_sell',0,-1,0,'red','noaxis')
		else:
			ContextInfo.paint('do_buy',0,-1,0,'yellow','noaxis')
			ContextInfo.paint('do_sell',1,-1,0,'red','noaxis')'''

ContextInfo.paint('holding',ContextInfo.MarketPosition[ContextInfo.get_universe()[0]],-1,0)

def get_avaliable(accountid, datatype): result = 0 resultlist = get_trade_detail_data(accountid, datatype, 'ACCOUNT') for obj in resultlist: result = obj.m_dAvailable return result

def get_holdings(accountid, datatype): holdinglist = {} resultlist = get_trade_detail_data(accountid, datatype, 'POSITION') for obj in resultlist: holdinglist[obj.m_strInstrumentID + '.' + obj.m_strExchangeID] = obj.m_nCanUseVolume return holdinglist

检查是否有误内容：本代码需要在聚宽平台运行，需要调用聚宽的API接口，无法在其他环境下运行。

以下是代码中可能存在的问题：

  1. 缺少必要的API调用，如get_market_data、order_shares、get_avaliable等，需要在聚宽平台中调用聚宽提供的API接口才能正常运行。

  2. 代码中的一些参数或变量未定义或未赋值，如ContextInfo.stockcode、ContextInfo.market、ContextInfo.period等，需要根据实际情况进行定义和赋值。

  3. 代码中的一些逻辑可能存在问题，如持仓数量的计算、回转操作的处理等，需要根据实际情况进行调整和优化。

  4. 代码中缺少必要的注释和说明，需要添加注释和说明，方便其他人理解和修改代码。

基于MACD指标的股票交易策略

原文地址: https://www.cveoy.top/t/topic/mQBK 著作权归作者所有。请勿转载和采集!

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