94 lines
3.4 KiB
Python
94 lines
3.4 KiB
Python
import pandas as pd
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import numpy as np
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from pandas_datareader import data
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start_date = '2014-01-01'
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end_date = '2018-01-01'
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SRC_DATA_FILENAME = 'goog_data.pkl'
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try:
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goog_data = pd.read_pickle(SRC_DATA_FILENAME)
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print('File data found...reading GOOG data')
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except FileNotFoundError:
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print('File not found...downloading the GOOG data')
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goog_data = data.DataReader('GOOG', 'yahoo', start_date, end_date)
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goog_data.to_pickle(SRC_DATA_FILENAME)
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goog_data_signal = pd.DataFrame(index=goog_data.index)
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goog_data_signal['price'] = goog_data['Adj Close']
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import numpy as np
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def trading_support_resistance(data, bin_width=20):
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data['sup_tolerance'] = pd.Series(np.zeros(len(data))) # tolerance of support line
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data['res_tolerance'] = pd.Series(np.zeros(len(data))) # tolerance of resistance line
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data['sup_count'] = pd.Series(np.zeros(len(data))) # number of hitting support line
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data['res_count'] = pd.Series(np.zeros(len(data)))
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data['sup'] = pd.Series(np.zeros(len(data))) # support line value (constant)
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data['res'] = pd.Series(np.zeros(len(data)))
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data['position'] = pd.Series(np.zeros(len(data)))
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data['signal'] = pd.Series(np.zeros(len(data)))
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in_support = 0
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in_resistance = 0
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for x in range((bin_width-1) + bin_width, len(data)):
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data_section = data[x-bin_width : x+1] # get data within rolling window
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support_level = min(data_section['price'])
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resistance_level = max(data_section['price'])
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range_level = resistance_level - support_level
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data['res'][x] = resistance_level
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data['sup'][x] = support_level
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data['sup_tolerance'][x] = support_level + 0.2*range_level # 20% tolorance
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data['res_tolerance'][x] = resistance_level - 0.2*range_level
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if (data['price'][x] >= data['res_tolerance'][x]) and (data['price'][x] <= data['res'][x]):
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# if price is within resistance tolerance region
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in_resistance += 1
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data['res_count'][x] = in_resistance
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elif (data['price'][x] <= data['sup_tolerance'][x]) and (data['price'][x] >= data['sup'][x]):
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# price is within support tolerance region
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in_support += 1
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data['sup_count'][x] = in_support
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else:
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# if not within any region, clear count
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in_support = 0
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in_resistance = 0
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if in_resistance > 2:
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# If enter resistance region twice
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data['signal'][x] = 1
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elif in_support > 2:
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data['signal'][x] = 0
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else:
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data['signal'][x] = data['signal'][x-1]
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data['position'] = data['signal'].diff()
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trading_support_resistance(goog_data_signal)
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print(goog_data_signal)
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import matplotlib.pyplot as plt
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fig = plt.figure()
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ax1 = fig.add_subplot(111, ylabel='Google price in $')
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goog_data_signal['sup'].plot(ax=ax1, color='g', lw=2.)
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goog_data_signal['res'].plot(ax=ax1, color='b', lw=2.)
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goog_data_signal['price'].plot(ax=ax1, color='r', lw=2.)
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ax1.plot(goog_data_signal.loc[goog_data_signal.position == 1.0].index,
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goog_data_signal.price[goog_data_signal.position == 1.0], '^', markersize=7, color='k', label='buy')
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ax1.plot(goog_data_signal.loc[goog_data_signal.position == -1.0].index,
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goog_data_signal.price[goog_data_signal.position == -1.0], 'v', markersize=7, color='k', label='sell')
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plt.legend()
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plt.savefig("supportresistanceline_improved")
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plt.show() |