Delete stock_date_from_tushare.py
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"""
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This code is supported by the website: https://www.guanjihuan.com
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The newest version of this code is on the web page: https://www.guanjihuan.com/archives/706
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"""
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import numpy as np
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import time
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import matplotlib.pyplot as plt
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import tushare as ts
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def main():
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start_clock = time.perf_counter()
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pro = ts.pro_api('到官网上注册，寻找Token填在这里!')
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print('\n我的策略：见好就收，遇低抄底。\n'
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' 【卖出】买入后涨了5%就卖出\n'
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' 【买入】卖出后跌了5%就买入\n'
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'注：第一天必须买进，最后一天前必须卖出(为了与不操作的做对比)\n')
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number = 1
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for i in range(number):
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data = pro.stock_basic(exchange='', list_status='L', fields='ts_code,symbol,name,area,industry,list_date') # 所有股票列表
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# print(data.columns) # 查看该数据的表头
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# print(data) # 3688多行的股票数据
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i = 1 # 查看第二行数据“万科A”股
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ts_code = data.values[i, 0] # 股票代码
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stock = data.values[i, 2] # 股票名称
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industry = data.values[i, 4] # 属于哪个行业
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start_date = '20110101' # 开始时间
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end_date = '20191027' # 结束时间
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df = pro.daily(ts_code=ts_code, start_date=start_date, end_date=end_date) # 查看该股票的日线数据
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# print(df.columns) # 查看该数据的表头
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# print(df) # 查看该股票的日线数据
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close = np.array(list(reversed(df.values[:, 5]))) # 提取出收盘价，并按时间顺序排列，从过去到现在
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pct_chg = np.array(list(reversed(df.values[:, 8]))) # 提取出涨跌幅，并按时间顺序排列，从过去到现在
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# print(df.columns[5], '=', close, '\n') # 查看收盘价
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# print(df.columns[8], '=', pct_chg, '\n') # 查看涨跌幅
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profit, profit_no_operation, times, invest_money, buy_time_all, sell_time_all = back_test(close.shape[0], close, pct_chg)
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# 调用回测函数，返回了“利润，未操作的利润， 按该策略操作了几次， 总投资金额， 按该策略买的时间， 按该策略卖的时间”的值
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print('\n------股票：', stock, ts_code, industry, '[买入市值=%7.2f' % invest_money, ']------')
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print('回测时间段：', start_date, '-', end_date)
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print('操作后利润= %6.2f' % profit, ' 买入（卖出）次数=', times, ' ')
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print('不操作利润= %6.2f' % profit_no_operation, '（第一天买入，最后一天卖出，中间未操作）')
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end_clock = time.perf_counter()
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print('CPU执行时间=', end_clock - start_clock, 's')
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plt.figure(1)
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plt.title('Stock Code: '+ts_code+' (red point: buy, green point: sell)')
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plt.grid()
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plt.plot(range(close.shape[0]), close, '-')
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for i in buy_time_all:
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plt.plot(i, close[int(i)], 'or', markersize=13) # 红色是买进的点
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for i in sell_time_all:
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plt.plot(i, close[int(i)], 'dg', markersize=13) # 绿色是卖出的点
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plt.show()
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def back_test(days, close, pct_chg, money_in=10000): # 定义该策略的回测效果（按旧数据检查该策略是否有效）
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money_in_amount = int(money_in/close[0]) # 投资金额换算成股票股数
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invest_money = close[0]*money_in_amount # 实际买了股票的金额
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profit_no_operation = (close[close.shape[0]-1]-close[0])*money_in_amount # 不操作的利润
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position = -1 # 买入还是卖出的状态，默认卖出
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total_profit = 0
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times = 0
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current_buy_pct = -999
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current_sell_pct = 999
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buy_time_all = np.array([])
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sell_time_all = np.array([])
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for i in range(days): # 总天数
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if i == 0: # 第一天，满仓买买买！为了和不操作的对比，第一天就要买入。
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buy_time = i # 买入时间
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buy_time_all = np.append(buy_time_all, [buy_time], axis=0) # 买入时间存档
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position = 1 # 标记为买入状态
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print('------------------第', buy_time, '天买进-------------')
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else:
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profit = 0
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if position == 1: # 买入状态
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current_buy_pct = (close[i]-close[buy_time])/close[buy_time]*100 # 买入后的涨跌情况
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# print('当前买进后的涨跌情况：第', i, '天=', current_buy_pct)
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if position == 0: # 卖出状态
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current_sell_pct = (close[i]-close[sell_time])/close[sell_time]*100 # 卖出后的涨跌情况
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if current_sell_pct < -5 and position == 0: # 卖出状态，且卖出后跌了有3%，这时候买入
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buy_time = i # 买入时间
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buy_time_all = np.append(buy_time_all, [buy_time], axis=0) # 买入时间存档
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print('------------------第', buy_time, '天买进-------------')
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position = 1 # 标记为买入状态
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continue
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if current_buy_pct > 5 and position == 1: # 买入状态，且买入后涨了有3%，这时候卖出
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sell_time = i # 卖出时间
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sell_time_all = np.append(sell_time_all, [sell_time], axis=0) # 卖出时间存档
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print('----------第', sell_time, '天卖出，持有天数：', sell_time-buy_time, '--------------\n')
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position = 0 # 标记为卖出状态
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profit = close[sell_time]-close[buy_time] # 赚取利润
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times = times + 1 # 买入（卖出）次数加1
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total_profit = total_profit + profit*money_in_amount # 计算总利润
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if position == 1: # 最后一天如果是买入状态，则卖出
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profit = close[i]-close[buy_time] # 赚取利润
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total_profit = total_profit + profit # 计算总利润
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times = times + 1 # 买入（卖出）次数加1
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print('--------------第', i, '天（最后一天）卖出，持有天数：', sell_time-buy_time, '--------------\n')
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sell_time_all = np.append(sell_time_all, [i], axis=0) # 卖出时间存档
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return total_profit, profit_no_operation, times, invest_money, buy_time_all, sell_time_all
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if __name__ == '__main__':
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main()
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