mirror of
https://github.com/awwesomeman/vectorbt-visualization.git
synced 2026-07-27 18:57:46 +00:00
tsunglin
112 lines
4.2 KiB
Python
112 lines
4.2 KiB
Python
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from plot import Plot
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class My_Strategy(Plot):
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def __init__(self,api):
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super().__init__(api)
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def KDJMA(self, time_period = 10,oversell = 20,overbuy = 80, ma1 = 5,ma2 = 20,trading_type='standard'):
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#-------------------------------------------------
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# calculate k, d , j
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#-------------------------------------------------
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data = self.kbars_df
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ini_k = 50
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ini_d = 50
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k=[]
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d=[]
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rsv = (data['Close'].rolling(time_period).apply(lambda x:x[-1]) - data["Low"].rolling(time_period).min() ) / ( data["High"].rolling(time_period).max() - data["Low"].rolling(time_period).min() ) *100
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rsv = rsv.dropna()
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for _ in rsv:
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ini_k = 2/3 * ini_k + 1/3 * _
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k.append(ini_k)
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for _ in k:
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ini_d = 2/3 * ini_d + 1/3 * _
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d.append(ini_d)
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k = pd.Series(k,index = rsv.index)
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d = pd.Series(d,index = rsv.index)
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j = 3 * k - 2 * d
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ma1 = data['Close'].rolling(ma1).mean()
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ma2 = data['Close'].rolling(ma2).mean()
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#-------------------------------------------------
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# make strategy signals
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#-------------------------------------------------
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init_buy_sig = ( j>oversell ) & ( j.shift()<oversell ) & (ma1>ma2)
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init_sell_sig = ( j<overbuy ) & ( j.shift()>overbuy ) & (ma1<ma2)
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indicators = [('sub',{"K":k,"D":d,"J":j}),('main',{"ma1":ma1,"ma2":ma2})] # [('sub', {indicators1}), ('main'{indicators2})......]
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self.init_buy_sig = init_buy_sig
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self.init_sell_sig = init_sell_sig
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self.indicators = indicators
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self.trading_type = trading_type
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def MA(self, ma1 = 5,ma2 = 20,trading_type='standard'):
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#-------------------------------------------------
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# calculate ma
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#-------------------------------------------------
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data = self.kbars_df
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ma1 = data['Close'].rolling(ma1).mean()
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ma2 = data['Close'].rolling(ma2).mean()
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#-------------------------------------------------
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# make strategy signals
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#-------------------------------------------------
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init_buy_sig = ( ma1>ma2 ) & ( ma1.shift()<ma2 )
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init_sell_sig = ( ma1<ma2 ) & ( ma1.shift()>ma2 )
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indicators = [('main',{"ma1":ma1,"ma2":ma2})] # [('sub', {indicators1}), ('main'{indicators2})......]
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self.init_buy_sig = init_buy_sig
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self.init_sell_sig = init_sell_sig
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self.indicators = indicators
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self.trading_type = trading_type
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def KDJ(self, time_period = 10,oversell = 20,overbuy = 80,trading_type='standard'):
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#-------------------------------------------------
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# calculate k, d , j
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#-------------------------------------------------
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data = self.kbars_df
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ini_k = 50
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ini_d = 50
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k=[]
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d=[]
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rsv = (data['Close'].rolling(time_period).apply(lambda x:x[-1]) - data["Low"].rolling(time_period).min() ) / ( data["High"].rolling(time_period).max() - data["Low"].rolling(time_period).min() ) *100
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rsv = rsv.dropna()
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for _ in rsv:
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ini_k = 2/3 * ini_k + 1/3 * _
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k.append(ini_k)
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for _ in k:
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ini_d = 2/3 * ini_d + 1/3 * _
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d.append(ini_d)
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k = pd.Series(k,index = rsv.index)
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d = pd.Series(d,index = rsv.index)
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j = 3 * k - 2 * d
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#-------------------------------------------------
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# make strategy signals
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#-------------------------------------------------
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init_buy_sig = ( j>oversell ) & ( j.shift()<oversell )
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init_sell_sig = ( j<overbuy ) & ( j.shift()>overbuy )
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# 模擬真實交易狀況，在訊號出現的下一個交易機會買入
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init_buy_sig = init_buy_sig.shift().dropna()
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init_sell_sig = init_sell_sig.shift().dropna()
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indicators = [('sub',{"K":k,"D":d,"J":j})] # [('sub', {indicators1}), ('main'{indicators2})......]
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self.init_buy_sig = init_buy_sig
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self.init_sell_sig = init_sell_sig
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self.indicators = indicators
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self.trading_type = trading_type
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