jens
7fdef39c3f
git-svn-id: http://moon:8086/svn/projects/Stock@295 fda53097-d464-4ada-af97-ba876c37ca34
64 lines
1.4 KiB
Python
64 lines
1.4 KiB
Python
import pandas as pd
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import pandas_datareader.data as web
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import numpy as np
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import math
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import matplotlib.pyplot as plt
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import datetime
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# Stock Investors Financial Math
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# https://www.fmlabs.com/reference/default.htm?url=SimpleMA.htm
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# Alpha Vantage
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# https://www.alphavantage.co/documentation/
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# Pandas
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# https://pandas.pydata.org/pandas-docs/stable/index.html
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# Knowledge
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# https://www.investopedia.com/articles/technical/02/050602.asp
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# https://ntguardian.wordpress.com/2016/09/19/introduction-stock-market-data-python-1
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key = '0UO7Z2MVZ2YSQSVE'
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def sin(f, a, N):
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result = np.empty(0)
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for n in range(0, N):
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v = a*math.sin(2*math.pi*f*n/N)
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result = np.append(result, v)
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return result
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def ema(data, alpha=0.75):
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result = np.empty(0)
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r = data[0]
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for v in data:
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r = alpha*r + (1-alpha)*v
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result = np.append(result, r)
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return result
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def macd(data):
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ema_short = ema(data, alpha=0.85)
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ema_long = ema(data, alpha=0.925)
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return ema_short - ema_long
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if 0:
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# Get stock price via data reader
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start = datetime.datetime(2016,1,1)
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end = datetime.date.today()
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apple = web.DataReader("AAPL", "av-monthly", start, end, api_key=key)
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type(apple)
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pd_data = pd.read_csv("aapl.csv", names=['Dates', 'Price'])
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np_data = np.flip(pd_data['Price'].to_numpy())
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plt.plot(np_data, label='Price')
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plt.plot(ema(np_data), label='EMA')
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plt.plot(macd(np_data), label='MACD')
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plt.legend()
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plt.grid()
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plt.show()
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