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()