设置股票池，每天9:23分运行集合竞价处理函数：如果最新价不小于涨停价则买入
def initialize(context):
# 初始化此策略
# 设置股票池, 这里我们只操作一支股票
g.security = '600570.SS'
set_universe(g.security)
#每天9:23分运行集合竞价处理函数
run_daily(context, aggregate_auction_func, time='9:23')
def aggregate_auction_func(context):
stock = g.security
# 获取最新价
snapshot = get_snapshot(stock)
price = snapshot[stock]['last_px']
# 获取涨停价
up_limit = snapshot[stock]['up_px']
# 如果最新价不小于涨停价则买入
if float(price) >= float(up_limit):
order(g.security, 100, limit_price=up_limit)
def handle_data(context, data):
pass
设置股票池，盘前准备历史数据，每3秒钟触发一次：首先用最新的tick行情数据计算五日均线和十日均线，然后进行比较：当五日均线高于十日均线时买入，当五日均线低于十日均线时卖出
def initialize(context):
# 初始化此策略
# 设置股票池, 这里我们只操作一支股票
g.security = '600570.SS'
set_universe(g.security)
# 每3秒运行一次主函数
run_interval(context, func, seconds=3)
# 盘前准备历史数据
def before_trading_start(context, data):
history = get_history(10, '1d', 'close', g.security, fq='pre', include=False)
g.close_array = history['close'].values
# 当五日均线高于十日均线时买入，当五日均线低于十日均线时卖出
def func(context):
stock = g.security
# 获取最新价
snapshot = get_snapshot(stock)
price = snapshot[stock]['last_px']
# 获取五日均线价格
days = 5
ma5 = get_MA_day(stock, days, g.close_array[-4:], price)
# 获取十日均线价格
days = 10
ma10 = get_MA_day(stock, days, g.close_array[-9:], price)
# 获取当前资金余额
cash = context.portfolio.cash
# 如果当前有余额，并且五日均线大于十日均线则买入
if ma5 > ma10:
# 用所有 cash 买入股票
order_value(stock, cash)
# 记录这次买入
log.info("Buying %s" % (stock))
# 如果五日均线小于十日均线，并且目前有头寸，则全部卖出
elif ma5 < ma10 and get_position(stock).amount > 0:
# 全部卖出
order_target(stock, 0)
# 记录这次卖出
log.info("Selling %s" % (stock))
# 计算实时均线函数
def get_MA_day(stock,days,close_array,current_price):
close_sum = close_array[-(days-1):].sum()
MA = (current_price + close_sum)/days
return MA
def handle_data(context, data):
pass
设置股票池，每个handle_data周期进行如下判断处理：当五日均线高于十日均线时买入，当五日均线低于十日均线时卖出
def initialize(context):
# 初始化此策略
# 设置股票池, 这里我们只操作一支股票
g.security = '600570.SS'
set_universe(g.security)
# 当五日均线高于十日均线时买入，当五日均线低于十日均线时卖出
def handle_data(context, data):
security = g.security
# 获取十日历史价格
df = get_history(10, '1d', 'close', security, fq=None, include=False)
# 获取五日均线价格
ma5 = round(df['close'][-5:].mean(), 3)
# 获取十日均线价格
ma10 = round(df['close'][-10:].mean(), 3)
# 获取昨天收盘价
price = data[security]['close']
# 获取当前资金余额
cash = context.portfolio.cash
# 如果当前有余额，并且五日均线大于十日均线
if ma5 > ma10:
# 用所有 cash 买入股票
order_value(security, cash)
# 记录这次买入
log.info("Buying %s" % (security))
# 如果五日均线小于十日均线，并且目前有头寸
elif ma5 < ma10 and get_position(security).amount > 0:
# 全部卖出
order_target(security, 0)
# 记录这次卖出
log.info("Selling %s" % (security))
用历史日K线数据计算MACD指标，以计算结果进行买入卖出交易。
"""
macd强势金叉买入、macd弱势死叉卖出
"""
def initialize(context):
g.hold_num = 10
def before_trading_start(context, data):
# 获取沪深300股票
g.security_list = get_index_stocks('000300.SS')
g.close_data_dict = {}
# 获取K线数据
history = get_history(100, frequency='1d', field=["close"], security_list=g.security_list, fq='dypre',
include=False, is_dict=True)
for stock in g.security_list:
close_data = history[stock]['close']
g.close_data_dict[stock] = close_data
g.every_value = context.portfolio.portfolio_value / g.hold_num
def handle_data(context, data):
for security in g.security_list:
close_data = g.close_data_dict[security]
macdDIF_data, macdDEA_data, macd_data = get_MACD(close_data, 12, 26, 9)
DIF = macdDIF_data[-1]
DEA = macdDEA_data[-1]
macd_current = macd_data[-1]
macd_pre = macd_data[-2]
# 获取当前价格
current_price = data[security].price
# 获取当前的现金
position = context.portfolio.positions
# DIF、DEA均为正，macd金叉，买入信号参考
if position[security].amount == 0:
if DIF > 0 and DEA > 0 and macd_pre < 0 and macd_current >= 0:
if context.portfolio.cash < g.every_value*0.8:
continue
# 以市单价买入股票，日回测时即是开盘价
order_target_value(security, g.every_value)
# 记录这次买入
log.info("Buying %s" % (security))
else:
# DIF、DEA均为负，macd死叉，卖出信号参考
if DIF < 0 and DEA < 0 and macd_pre >= 0 and macd_current < 0:
# 卖出所有股票,使这只股票的最终持有量为0
order_target(security, 0)
# 记录这次卖出
log.info("Selling %s" % (security))设置标的池，每个handle_data周期进行如下判断处理：当五日均线高于十日均线时买入，当五日均线低于十日均线时卖出。其中买入卖出所调用的API为融资融券业务专用API。
def initialize(context):
# 初始化策略
# 设置股票池, 这里我们只操作一支股票
g.security = "600570.SS"
set_universe(g.security)
def before_trading_start(context, data):
# 买入标识
g.order_buy_flag = False
# 卖出标识
g.order_sell_flag = False
# 当五日均线高于十日均线时买入，当五日均线低于十日均线时卖出
def handle_data(context, data):
# 获取十日历史价格
df = get_history(10, "1d", "close", g.security, fq=None, include=False)
# 获取五日均线价格
ma5 = round(df["close"][-5:].mean(), 3)
# 获取十日均线价格
ma10 = round(df["close"][-10:].mean(), 3)
# 获取昨天收盘价
price = data[g.security]["close"]
# 如果五日均线大于十日均线
if ma5 > ma10:
if not g.order_buy_flag:
# 获取最大可融资数量
amount = get_margincash_open_amount(g.security).get(g.security)
# 进行融资买入操作
margincash_open(g.security, amount)
# 记录这次操作
log.info("Buying %s Amount %s" % (g.security, amount))
# 当日已融资买入
g.order_buy_flag = True
# 如果五日均线小于十日均线，并且目前有头寸
elif ma5 < ma10 and get_position(g.security).amount > 0:
if not g.order_sell_flag:
# 获取标的卖券还款最大可卖数量
amount = get_margincash_close_amount(g.security).get(g.security)
# 进行卖券还款操作
margincash_close(g.security, -amount)
# 记录这次操作
log.info("Selling %s Amount %s" % (g.security, amount))
# 当日已卖券还款
g.order_sell_flag = True