def sample_821_1():
"""
8.2.1_1 选股使用示例
:return:
"""
# 选股条件threshold_ang_min=0.0, 即要求股票走势为向上上升趋势
stock_pickers = [{'class': AbuPickRegressAngMinMax,
'threshold_ang_min': 0.0, 'reversed': False}]
# 从这几个股票里进行选股，只是为了演示方便
# 一般的选股都会是数量比较多的情况比如全市场股票
choice_symbols = ['usNOAH', 'usSFUN', 'usBIDU', 'usAAPL', 'usGOOG',
'usTSLA', 'usWUBA', 'usVIPS']
benchmark = AbuBenchmark()
capital = AbuCapital(1000000, benchmark)
kl_pd_manager = AbuKLManager(benchmark, capital)
stock_pick = AbuPickStockWorker(capital, benchmark, kl_pd_manager,
choice_symbols=choice_symbols,
stock_pickers=stock_pickers)
stock_pick.fit()
# 打印最后的选股结果
print('stock_pick.choice_symbols:', stock_pick.choice_symbols)
# 从kl_pd_manager缓存中获取选股走势数据，注意get_pick_stock_kl_pd为选股数据，get_pick_time_kl_pd为择时
kl_pd_noah = kl_pd_manager.get_pick_stock_kl_pd('usNOAH')
# 绘制并计算角度
deg = ABuRegUtil.calc_regress_deg(kl_pd_noah.close)
print('noah 选股周期内角度={}'.format(round(deg, 3)))
def sample_811():
"""
8.1.1 买入因子的实现
:return:
"""
# buy_factors 60日向上突破，42日向上突破两个因子
buy_factors = [{
'xd': 60,
'class': AbuFactorBuyBreak
}, {
'xd': 42,
'class': AbuFactorBuyBreak
}]
benchmark = AbuBenchmark()
capital = AbuCapital(1000000, benchmark)
kl_pd_manager = AbuKLManager(benchmark, capital)
# 获取TSLA的交易数据
kl_pd = kl_pd_manager.get_pick_time_kl_pd('usTSLA')
abu_worker = AbuPickTimeWorker(capital, kl_pd, benchmark, buy_factors,
None)
abu_worker.fit()
orders_pd, action_pd, _ = ABuTradeProxy.trade_summary(abu_worker.orders,
kl_pd,
draw=True)
ABuTradeExecute.apply_action_to_capital(capital, action_pd, kl_pd_manager)
capital.capital_pd.capital_blance.plot()
plt.show()
def sample_821_2():
"""
8.2.1_2 ABuPickStockExecute
:return:
"""
stock_pickers = [{
'class': AbuPickRegressAngMinMax,
'threshold_ang_min': 0.0,
'threshold_ang_max': 10.0,
'reversed': False
}]
choice_symbols = [
'601398', '601988', '601939', '603993', '600999', '300059', '600900',
'601328', '601288', '600887', '600029', '000002'
]
benchmark = AbuBenchmark()
capital = AbuCapital(1000000, benchmark)
kl_pd_manager = AbuKLManager(benchmark, capital)
print(
'ABuPickStockExecute.do_pick_stock_work:\n',
ABuPickStockExecute.do_pick_stock_work(choice_symbols, benchmark,
capital, stock_pickers))
kl_pd_sfun = kl_pd_manager.get_pick_stock_kl_pd('601398')
print('sfun 选股周期内角度={}'.format(
round(ABuRegUtil.calc_regress_deg(kl_pd_sfun.close), 3)))
def sample_821_2():
"""
8.2.1_2 ABuPickStockExecute
:return:
"""
stock_pickers = [{
'class': AbuPickRegressAngMinMax,
'threshold_ang_min': 0.0,
'threshold_ang_max': 10.0,
'reversed': False
}]
choice_symbols = [
'usNOAH', 'usSFUN', 'usBIDU', 'usAAPL', 'usGOOG', 'usTSLA', 'usWUBA',
'usVIPS'
]
benchmark = AbuBenchmark()
capital = AbuCapital(1000000, benchmark)
kl_pd_manager = AbuKLManager(benchmark, capital)
print(
'ABuPickStockExecute.do_pick_stock_work:\n',
ABuPickStockExecute.do_pick_stock_work(choice_symbols, benchmark,
capital, stock_pickers))
kl_pd_sfun = kl_pd_manager.get_pick_stock_kl_pd('usSFUN')
print('sfun 选股周期内角度={}'.format(
round(ABuRegUtil.calc_regress_deg(kl_pd_sfun.close), 3)))
def sample_b3_4():
"""
【示例4】abu量化系统选股结合相关性，编写相关性选股策略
AbuPickSimilarNTop源代码请自行阅读，只简单示例使用。
:return:
"""
from abupy import AbuPickSimilarNTop
from abupy import AbuPickStockWorker
from abupy import AbuBenchmark, AbuCapital, AbuKLManager
benchmark = AbuBenchmark()
# 选股因子AbuPickSimilarNTop， 寻找与usTSLA相关性不低于0.95的股票
# 这里内部使用以整个市场作为观察者方式计算，即取值范围0-1
stock_pickers = [{
'class': AbuPickSimilarNTop,
'similar_stock': 'usTSLA',
'threshold_similar_min': 0.95
}]
# 从这几个股票里进行选股，只是为了演示方便，一般的选股都会是数量比较多的情况比如全市场股票
choice_symbols = [
'usNOAH', 'usSFUN', 'usBIDU', 'usAAPL', 'usGOOG', 'usTSLA', 'usWUBA',
'usVIPS'
]
capital = AbuCapital(1000000, benchmark)
kl_pd_manager = AbuKLManager(benchmark, capital)
stock_pick = AbuPickStockWorker(capital,
benchmark,
kl_pd_manager,
choice_symbols=choice_symbols,
stock_pickers=stock_pickers)
stock_pick.fit()
print('stock_pick.choice_symbols:\n', stock_pick.choice_symbols)
"""
通过选股因子first_choice属性执行批量优先选股操作，具体阅读源代码
"""
# 选股因子AbuPickSimilarNTop， 寻找与usTSLA相关性不低于0.95的股票
# 通过设置'first_choice':True，进行优先批量操作，默认从对应市场选股
stock_pickers = [{
'class': AbuPickSimilarNTop,
'first_choice': True,
'similar_stock': 'usTSLA',
'threshold_similar_min': 0.95
}]
benchmark = AbuBenchmark()
capital = AbuCapital(1000000, benchmark)
kl_pd_manager = AbuKLManager(benchmark, capital)
stock_pick = AbuPickStockWorker(capital,
benchmark,
kl_pd_manager,
choice_symbols=None,
stock_pickers=stock_pickers)
stock_pick.fit()
print('stock_pick.choice_symbols:\n', stock_pick.choice_symbols)
def sample_821_2():
"""
8.2.1_2 ABuPickStockExecute
:return:
"""
stock_pickers = [{'class': AbuPickRegressAngMinMax,
'threshold_ang_min': 0.0, 'threshold_ang_max': 10.0,
'reversed': False}]
choice_symbols = ['usNOAH', 'usSFUN', 'usBIDU', 'usAAPL', 'usGOOG',
'usTSLA', 'usWUBA', 'usVIPS']
benchmark = AbuBenchmark()
capital = AbuCapital(1000000, benchmark)
kl_pd_manager = AbuKLManager(benchmark, capital)
print('ABuPickStockExecute.do_pick_stock_work:\n', ABuPickStockExecute.do_pick_stock_work(choice_symbols, benchmark,
capital, stock_pickers))
kl_pd_sfun = kl_pd_manager.get_pick_stock_kl_pd('usSFUN')
print('sfun 选股周期内角度={}'.format(round(ABuRegUtil.calc_regress_deg(kl_pd_sfun.close), 3)))
def sample_811():
"""
8.1.1 买入因子的实现
:return:
"""
# buy_factors 60日向上突破，42日向上突破两个因子
buy_factors = [{'xd': 60, 'class': AbuFactorBuyBreak},
{'xd': 42, 'class': AbuFactorBuyBreak}]
benchmark = AbuBenchmark()
capital = AbuCapital(1000000, benchmark)
kl_pd_manager = AbuKLManager(benchmark, capital)
# 获取TSLA的交易数据
kl_pd = kl_pd_manager.get_pick_time_kl_pd('usTSLA')
abu_worker = AbuPickTimeWorker(capital, kl_pd, benchmark, buy_factors, None)
abu_worker.fit()
orders_pd, action_pd, _ = ABuTradeProxy.trade_summary(abu_worker.orders, kl_pd, draw=True)
ABuTradeExecute.apply_action_to_capital(capital, action_pd, kl_pd_manager)
capital.capital_pd.capital_blance.plot()
plt.show()
# 1、这里是买入突破
# 创建60日向上突破，42日向上突破两个因子
buy_factors = [{
'xd': 60,
'class': AbuFactorBuyBreak
}, {
'xd': 42,
'class': AbuFactorBuyBreak
}]
# 基准利润
benchmark = AbuBenchmark()
# 现金和基准利润
capital = AbuCapital(1000000, benchmark)
# 多线程管理类
kl_pd_manager = AbuKLManager(benchmark, capital)
# 获取TSLA的股票信息
kl_pd = kl_pd_manager.get_pick_time_kl_pd('usTSLA')
# 准备开始工作
abu_worker = AbuPickTimeWorker(capital, kl_pd, benchmark, buy_factors,
None)
abu_worker.fit()
# 画出哪几个点可以买入，以及最终的收益情况
# orders_pd,action_pd,_=ABuTradeProxy.trade_summary(abu_worker.orders,kl_pd,draw=True)
orders_pd, action_pd, _ = ABuTradeProxy.trade_summary(abu_worker.orders,
kl_pd,
draw=False)
# 上面是从股价角度，下面从我们的资金来看
# ABuTradeExecute.apply_action_to_capital(capital, action_pd, kl_pd_manager)
# print(capital.capital_pd.head())
def sample_821_3():
"""
8.2.1_2 ABuPickStockExecute
:return:
"""
stock_pickers = [{
'class': abupy.FuWeekVolumeBoll,
'threshold_ang_min': 0.0,
'threshold_ang_max': 10.0,
'reversed': False
}]
choice_symbols = [
'601398', '601988', '601939', '603993', '600999', '300059', '600900',
'601328', '601288', '600887', '600029', '000002'
]
choice_symbols = [
'sz000983', 'sh600338', 'sh600511', 'sh600196', 'sh600423', 'sz399136',
'sz002044', 'sh601800', 'sz300132', 'sz300133', 'sh000821', 'sz300003',
'sz300009', 'sz200045', 'sh600998', 'sz300313', 'sh601607', 'sz002644',
'sh600697', 'sz000627', 'sh000003', 'sz399302', 'sh600984', 'sz399301',
'sz000916', 'sz000911', 'sz000912', 'sz000688', 'sh600079', 'sh601101',
'sz000861', 'sz000736', 'sz002053', 'sz000048', 'sh600703', 'sh000814',
'sz300015', 'sh000818', 'sz399352', 'sz399356', 'sh900911', 'sh600395',
'sh000075', 'sz002323', 'sh000101', 'sh600285', 'sh600882', 'sz000789',
'sh601398', 'sz000898', 'sh601390', 'sh601009', 'sh601001', 'sz000525',
'sh600713', 'sh601628', 'sz399299', 'sz399298', 'sh600800', 'sh000808',
'sh900909', 'sh900908', 'sh000061', 'sh000068', 'sh000116', 'sz000617',
'sh600535', 'sz000792', 'sz000889', 'sz000065', 'sh601015', 'sz000089',
'sh600871', 'sz002412', 'sz399400', 'sz399402', 'sz399404', 'sh000057',
'sh900930', 'sh900936', 'sh900934', 'sh900935', 'sh600267', 'sz000650',
'sz399978', 'sh600485', 'sh601021', 'sh601601', 'sh600208', 'sh601288',
'sh600062', 'sh600015', 'sh600016', 'sz300197', 'sz300199', 'sz399413',
'sz399411', 'sz399416', 'sh000134', 'sh000136', 'sh000139', 'sz002007',
'sh600258', 'sh600123', 'sz000511', 'sh601618', 'sh600745', 'sz399170',
'sh000923', 'sz399319', 'sz399554', 'sz399555', 'sz002530', 'sh000145',
'sz002070', 'sh000149', 'sz399220', 'sh601998', 'sh600111', 'sh600023',
'sz000560', 'sh601699', 'sz399305', 'sz399431', 'sz000766', 'sz399436',
'sz399230', 'sz399237', 'sz002661', 'sz002599', 'sh000155', 'sh000152',
'sh000151', 'sh600806', 'sh601988', 'sh600693', 'sh600699', 'sh600582',
'sz000995', 'sh600566', 'sh601318', 'sz399150', 'sz399441', 'sz399200',
'sh000841', 'sh600917', 'sz002128', 'sh600176', 'sz000968', 'sh600771',
'sh600579', 'sh600578', 'sh600572', 'sh600681', 'sh600680', 'sz399140',
'sz000540', 'sz000545', 'sz200022', 'sz200026', 'sz200025', 'sz399210',
'sz200029', 'sz002601', 'sz002656', 'sz002204', 'sz002737', 'sz000748',
'sh600965', 'sz002135', 'sh000934', 'sh601169', 'sh601899', 'sh601898',
'sh600549', 'sh600546', 'sh600545', 'sz000778', 'sh600141', 'sh600145',
'sh601231', 'sz399139', 'sz000630', 'sz000613', 'sz399137', 'sz399130',
'sz399131', 'sz399132', 'sz399133', 'sz200019', 'sz300146', 'sz300144',
'sz399661', 'sz002701', 'sh600971', 'sz002382', 'sz002385', 'sh600085',
'sh603158', 'sz002602', 'sh601939', 'sh600007', 'sz399645', 'sh600000',
'sh601339', 'sh601336', 'sh000125', 'sz399674', 'sh000974', 'sz399160',
'sz002653', 'sz002717', 'sz200726', 'sz399647', 'sz300294', 'sh000100',
'sz300347', 'sh600348', 'sh000933', 'sh600401', 'sh000109', 'sz000034',
'sh600623', 'sz000581', 'sz000672', 'sz300028', 'sh603368', 'sh000023',
'sh000021', 'sz002198', 'sh600432', 'sh603989', 'sz000937', 'sh600508',
'sh600500', 'sh000159', 'sz000732', 'sh600188', 'sz000598', 'sz000029',
'sz000028', 'sz399394', 'sh000832', 'sz300036', 'sz200053', 'sz300326',
'sz002742', 'sz300253', 'sh000013', 'sh000011'
]
# choice_symbols = ['002656', '000903']
benchmark = AbuBenchmark(n_folds=15)
capital = AbuCapital(1000000, benchmark)
kl_pd_manager = AbuKLManager(benchmark, capital)
stock_pickers = ABuPickStockExecute.do_pick_stock_work(
None,
benchmark,
# stock_pickers = ABuPickStockExecute.do_pick_stock_work(choice_symbols, benchmark,
capital,
stock_pickers)
print('ABuPickvStockExecute.do_pick_stock_work:\n', stock_pickers)
for stock_symbol in stock_pickers:
if ~fetch_stock_base_info(stock_symbol):
continue
draw_candle(stock_symbol, 15)
# stock_kd = pd.getByName(stock)
ABuEnv.g_cpu_cnt = 4#并发运行线程数
ABuEnv.draw_order_num = 0 #要绘制的订单数
ABuEnv.g_data_fetch_mode = EMarketDataFetchMode.E_DATA_FETCH_FORCE_NET #强制从网络获取
#ABuEnv.g_data_fetch_mode = EMarketDataFetchMode.E_DATA_FETCH_FORCE_LOCAL #强制本地，可多线程
ABuEnv.g_market_source = EMarketSourceType.E_MARKET_SOURCE_tx #作用同上点击效果。腾讯数据源(美股，A股，港股)
ABuEnv.g_market_target = EMarketTargetType.E_MARKET_TARGET_CN
benchmark = AbuBenchmark(n_folds=1, start=None, end=None)
# 资金类初始化
capital = AbuCapital(1000000, benchmark, user_commission_dict=None)
# kl数据管理类初始化
kl_pd_manager = AbuKLManager(benchmark, capital)
# 批量获取择时kl数据
industryPchangeAllDaetDic = dict()
if __name__ == '__main__':
kl_pd_manager.batch_get_pick_time_kl_pd(choice_symbols, n_process=4)
kl_pd_dick = kl_pd_manager.pick_kl_pd_dict['pick_time']
for stockCode, stockData in kl_pd_dick.items():
if stockData is None:
continue
pd_data = stockData.p_change
stockIndustryNames = industry_data['c_name'][industry_data.code == stockCode]
for _, stockIndustryName in stockIndustryNames.items():
if stockIndustryName in industryPchangeAllDaetDic.keys():
left = industryPchangeAllDaetDic[stockIndustryName]
right = pd.DataFrame({'date': stockData.date, stockCode: stockData.p_change})
industryPchangeAllDaetDic[stockIndustryName] = pd.merge(left, right, on='date', how='outer')
stock_pickers = [{
'class': AbuPickRegressAngMinMax,
'threshold_ang_min': 0.0,
'received': False
}]
# 一般而言，我们是遍历整个股市来选股，这里我们就选择以下几个股票来做演示
choice_symbols = [
'usNOAH', 'usSFUN', 'usBIDU', 'usAAPL', 'usGOOG', 'usTSLA', 'usWUBA',
'usVIPS'
]
# 开始执行
benchmark = AbuBenchmark()
capital = AbuCapital(1000000, benchmark)
kl_pd_manager = AbuKLManager(benchmark, capital)
stock_pick = AbuPickStockWorker(capital,
benchmark,
kl_pd_manager,
choice_symbols=choice_symbols,
stock_pickers=stock_pickers)
stock_pick.fit()
print(stock_pick.choice_symbols)
# 绘图
kl_pd_SFUN = kl_pd_manager.get_pick_stock_kl_pd('usNOAH')
deg = ABuRegUtil.calc_regress_deg(kl_pd_SFUN.close)
print(deg)
# 上面使用worker的操作太麻烦，下面可以直接使用executer
#设置暴跌止损因子
sell_factor3 = {'pre_atr_n':1.0, 'class':AbuFactorPreAtrNStop}
#设置保护止盈因子组成dict
sell_factor4 = {'close_atr_n':1.5,'class': AbuFactorCloseAtrNStop}
sell_factors = [sell_factor1, sell_factor2, sell_factor3,sell_factor4]
benchmark = AbuBenchmark()
choice_symbols = ['usTSLA', 'usNOAH', 'usSFUN', 'usBIDU', 'usAAPL', 'usGOOG', 'usWUBA', 'usVIPS']
capital = AbuCapital(1000000, benchmark)
kl_pd_manager = AbuKLManager(benchmark,capital)
#orders_pd, action_pd, _ = ABuTradeProxy.trade_summary(abu_worker.orders, kl_pd, draw=True)
#orders_pd, action_pd, all_fit_symbols_cnt = ABuPickTimeExecute.do_symbols_with_same_factors(choice_symbols, benchmark, buy_factors, sell_factors, capital, show=False)
orders_pd, action_pd, _ = ABuPickTimeExecute.do_symbols_with_same_factors(['usAAPL'],
benchmark,
buy_factors,
sell_factors,
capital, show=True)
orders_pd[:10].filter(['symbol', 'buy_price', 'buy_cnt', 'buy_factor', 'buy_pos',
'sell_date', 'sell_type_extra', 'sell_type', 'profit'])
print(action_pd[:10])
stock_pickers = [{
'threshold_ang_min': 0.0,
'threshold_ang_max': 10.0,
'reversed': False,
'class': AbuPickRegressAngMinMax
}, {
'threshold_price_min': 50.0,
'threshold_price_max': 100.0,
'reserved': False,
'class': AbuPickStockPriceMinMax
}]
symbols = ABuSymbol.search_to_symbol_dict('黄金')
benchmark = AbuBenchmark()
capital = AbuCapital(1000000, benchmark)
# assign money
kl_pd_manager = AbuKLManager(benchmark, capital)
'''
# tedious way
from abupy import AbuPickStockWorker;
stock_pick = AbuPickStockWorker(capital, benchmark, kl_pd_manager, choice_symbols = list(symbols.keys()), stock_pickers = stock_pickers);
stock_pick.fit();
print('candidates:', list(symbols.keys()));
print('picked:', stock_pick.choice_symbols);
'''
# simple way
from abupy import ABuPickStockExecute
from abupy import ABuRegUtil
picked_stocks = ABuPickStockExecute.do_pick_stock_work(
list(symbols.keys()), benchmark, capital, stock_pickers)
print('candidates:', list(symbols.keys()))
for stock in picked_stocks: