#for ticker in tickers: # fed = DataReader(ticker,data_source,start,end) # print(fed.tail(10)) # fed.plot(title = ticker,figsize = (15,5)) # plt.show() sp = DataReader(tickers[7],data_source,start,end) print(sp.tail(10)) sp.plot(title = tickers[7],figsize = (15,5)) plt.show() num = 233 risk_num = 60 sp1 = sp.copy() sample = sp1.dropna() ret_cum = sample / sample.iloc[0,:] ret_per = sample / sample.shift(1) - 1 print(ret_cum.tail()) print(ret_per.tail()) ret_cum.plot(title = "cumulative return") mn = ret_per.rolling(window = num).mean() #(rolling_mean(ret_per,window = num) stdev = ret_per.rolling(window = num).std() mn.plot(title = "rolling mean") stdev.plot(title = "rolling std") sharp_roll = 252 ** 0.5 * (mn / stdev) sharp_roll.plot(title = "rolling sharp") plt.show()
df['maPos'].iloc[row] = -1
if (df['OBV'].iloc[row] > 0):
df['obvPos'].iloc[row] = 1
else:
df['obvPos'].iloc[row] = -1
if (df['CCI'].iloc[row] > 0):
df['cciPos'].iloc[row] = 1
else:
df['cciPos'].iloc[row] = -1
# Clean up dataframe
frame = pd.DataFrame()
frame['PC'] = df['Adj Close'].pct_change()
db = df.copy()
df = df.drop(columns=[
'Open', 'High', 'Low', 'Close', 'Adj Close', 'Volume',
'upper_band', 'lower_band', 'middle_band', 'lower_band', 'macd',
'macdsignal', 'macdhist', 'RSI', 'Momentum', 'Z-Score', 'SMA',
'EMA', 'OBV', 'CCI'
])
df['pos'] = df.mean(axis=1)
df['PC'] = frame['PC']
db = db.reset_index()
db['Buy'] = np.where((df['pos'] < 0.7), 1, 0)
db['Sell'] = np.where((df['pos'] < -0.3), 1, 0)
db['Buy_ind'] = np.where((db['Buy'] > db['Buy'].shift(1)), 1, 0)
db['Sell_ind'] = np.where((db['Sell'] > db['Sell'].shift(1)), 1, 0)
