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# 用5日均线和10日均线进行判断 --- 改进版 > 来源:https://uqer.io/community/share/561e3a65f9f06c4ca82fb5ec ## 1、 修改Adobe同学的代码 ```py data=DataAPI.MktEqudGet(ticker="600030",beginDate="20131001") #选取600030股票 a = data.closePrice B = [] n = len(a) for i in range(10, n): x5 = a[i-5:i].mean() #5日均线值 x10 = a[i-10:i].mean() #10日均线值 B.append(x5 > x10) ``` ```py import matplotlib.pyplot as plt o = data.openPrice m = len(B) w = 0 #利润 cash = 1000000 #操作金额1亿,但考虑买的份额为100的整数,取1百万 amount = 0 PL = [] #利润w的数组 for i in range(1, m): k = i + 10 if B[i-1] == 0 and B[i] == 1 and not amount: amount = cash // o[k] #买入份额 cash -= o[k] * amount elif B[i-1] == 1 and B[i]==0 and amount: cash += o[k] * amount #卖出的金额 amount = 0 # print cash, amount PL.append(cash + o[k] * amount) print("利润:{}".format(PL[-1])) plt.plot(PL,color="green",label="Profit and Loss") plt.xlabel("Date") plt.ylabel("Price") plt.show() plt.plot(a[10:], color="red",label="Profit and Loss") plt.show() 利润:1559132.78 ``` ![](https://box.kancloud.cn/2016-07-30_579cbb01c8f63.png) ![](https://box.kancloud.cn/2016-07-30_579cbb01dc6ef.png) ## 2、 Uqer框架相同策略 ```py import numpy as np start = '2013-10-01' # 回测起始时间 end = '2015-10-13' # 回测结束时间 benchmark = 'SH50' # 策略参考标准 universe = ['600030.XSHG'] # 股票池 中信证券 capital_base = 100000 # 起始资金 commission = Commission(0.0,0.0) window_short = 5 # 短均线周期 window_long = 10 # 长均线周期 def initialize(account): # 初始化虚拟账户状态 account.fund = universe[0] def handle_data(account): # 每个交易日的买入卖出指令 cp_hist = account.get_attribute_history('closePrice', window_long)[account.fund] short_mean = np.mean(cp_hist[-window_short:]) # 计算短均线值 long_mean = np.mean(cp_hist[-window_long:]) #计算长均线值 # 计算买入卖出信号 if short_mean - long_mean > 0: if account.fund not in account.valid_secpos: # 空仓时全仓买入,买入股数为100的整数倍 approximationAmount = int(account.cash / account.referencePrice[account.fund] / 100) * 100 order(account.fund, approximationAmount) else: # 卖出时,全仓清空 if account.fund in account.valid_secpos: order_to(account.fund, 0) ``` ![](https://box.kancloud.cn/2016-07-30_579cbb01f01db.jpg)