quantitative-finance

I am having an issue with a script that was functioning prior to an upgrade of Anaconda (thus an upgrade of pandas and numpy) I have a DataFrame that I would like to use one column from and multiply by the values in a column of another DataFrame, outputting the final value to a column in a new DataFrame. As I said this code was working until I upgraded to pandas 0.17. class MarketOnClosePortfolio(Portfolio): def __init__(self, symbol, bars, signals, initial_capital=10000.0): self.symbol = symbol self.bars = bars self.signals = signals self.initial_capital = float(initial_capital) self

I would like to compute the RSI function, which is given as follows: RSI = 100 * RS / ( 1 + RS ), where RS = n_up / n_down and n_up( t ) = ( 1 - b ) * n_up( t - 1 ) + b * U( t ), and n_down( t ) = ( 1 - b ) * n_down( t - 1 ) + b * D( t ). where U( t ) = 1 for P( t ) > P( t - 1 ) and 0 otherwise; and D( t ) = 1 for P( t ) < P( t - 1 ) and 0 otherwise. So here is my code: p <- data[,6] rsi <- function(P,t,n) { U <- function(P,t) { if (diff(P)[t] > 0) { return(1) } else { return(0) } } D <- function(P,t) { if (diff(P)[t] < 0) { return(1) } else { return(0) } } recursive.n_up <- function(P,t,b) {

I am researching/backtesting a trading system. I have a Pandas dataframe containing OHLC data and have added several calculated columns which identify price patterns that I will use as signals to initiate positions. I would now like to add a further column that will keep track of the current net position. I have tried using df.apply(), but passing the dataframe itself as the argument instead of the row object, as with the latter I seem to be unable to look back at previous rows to determine whether they resulted in any price patterns: open_campaigns = [] Campaign = namedtuple('Campaign', 'open