def __init__(self, ticker, json):
self.ticker = ticker
self.df = da.dataframe(ticker)
self.df_spy = da.dataframe('SPY')
self.price_csv = da.csv(self.df['Adj_Close'], json)
pnl = self.df['Adj_Close'].diff()
pnl[0] = 0
self.pnl_csv = da.csv(pnl, json)
self.json = json
def __init__(self, ticker, json):
self.ticker = ticker
self.df = da.dataframe(ticker)
self.df_spy = da.dataframe('SPY')
self.price_csv = da.csv(self.df['Adj_Close'], json)
pnl = self.df['Adj_Close'].diff()
pnl[0] = 0
self.pnl_csv = da.csv(pnl, json)
self.json = json
def __init__(self, ticker1, ticker2, json):
self.df1 = da.dataframe(ticker1)
self.df2 = da.dataframe(ticker2)
self.ticker1 = ticker1
self.ticker2 = ticker2
self.price_csv1 = da.csv(self.df1['Adj_Close'], json)
self.price_csv2 = da.csv(self.df2['Adj_Close'], json)
pnl1 = self.df1['Adj_Close'].diff()
pnl1[0] = 0
pnl2 = self.df2['Adj_Close'].diff()
pnl2[0] = 0
self.pnl_csv1 = da.csv(pnl1, json)
self.pnl_csv2 = da.csv(pnl2, json)
self.json = json
self.flip = 'False'
if self.df2.index[0] > self.df1.index[0]:
self.flip = 'True'
def __init__(self, ticker1, ticker2, json):
self.df1 = da.dataframe(ticker1)
self.df2 = da.dataframe(ticker2)
self.ticker1 = ticker1
self.ticker2 = ticker2
self.price_csv1 = da.csv(self.df1["Adj_Close"], json)
self.price_csv2 = da.csv(self.df2["Adj_Close"], json)
pnl1 = self.df1["Adj_Close"].diff()
pnl1[0] = 0
pnl2 = self.df2["Adj_Close"].diff()
pnl2[0] = 0
self.pnl_csv1 = da.csv(pnl1, json)
self.pnl_csv2 = da.csv(pnl2, json)
self.json = json
self.flip = "False"
if self.df2.index[0] > self.df1.index[0]:
self.flip = "True"
def __init__(self, strategy, ticker, start, end):
prices = da.dataframe(ticker)['Adj_Close']
prices = da.selection(prices, start, end)
self.signals = strategy(prices)
self.pnl = pd.Series(np.zeros(len(prices)), index=prices.index)
shares = 0
for i in xrange(len(self.pnl)):
self.pnl[i] = (prices[i] - prices[i - 1]) * shares
shares += self.signals[i]
def __init__(self, strategy, ticker, start, end):
prices = da.dataframe(ticker)['Adj_Close']
prices = da.selection(prices, start, end)
self.signals = strategy(prices)
self.pnl = pd.Series(np.zeros(len(prices)), index=prices.index)
shares = 0
for i in xrange(len(self.pnl)):
self.pnl[i] = (prices[i]-prices[i-1])*shares
shares += self.signals[i]
def function(tickers, start, end):
start = dt.datetime(start)
end = dt.datetime(end)
all_price_data = {}
for ticker in tickers:
p = da.dataframe(ticker)['Adj_Close']
all_price_data[ticker] = p[np.logical_and(p.index>start, p.index<end)]
price = pd.DataFrame(all_price_data)
returns_meandev = price.pct_change()
for col in returns_meandev:
returns_meandev[col] = returns_meandev[col] - returns_meandev[col].mean()
def function(tickers, start, end):
start = dt.datetime(start)
end = dt.datetime(end)
all_price_data = {}
for ticker in tickers:
p = da.dataframe(ticker)['Adj_Close']
all_price_data[ticker] = p[np.logical_and(p.index > start,
p.index < end)]
price = pd.DataFrame(all_price_data)
returns_meandev = price.pct_change()
for col in returns_meandev:
returns_meandev[
col] = returns_meandev[col] - returns_meandev[col].mean()
