Hi all,

I have been enjoying testing out and playing with the existing framework in Quantopian. It seems to suit my needs well, but I am having some difficulties implementing simple tasks (adjusting to the source code is a bit tricky).

Anyway, I have a day trading algorithm that allows me to read in from a properly formatted csv file and execute trades. The algorithm was working very well for me, except recently I changed how I populate my backlog of stocks. Now there is infrequent spacing between listed stocks (I.E. there might only be a stock every 3 days). I do not want to hold my last stock until the next trade, but I could not find a way access dates outside of this list of stocks that corresponds to my universe.

How can the code be tweaked such that I may read in from a properly formatted CSV, buy the stock at the following days opening price (as I am currently doing) and sell at that days close?

Thanks!

import pandas as pd

def initialize(context):  
    # import the custom CSV data file  
    fetch_csv("ProperlyFormatted.csv",  
              pre_func=preview,  
              post_func=preview,  
              date_column='date',  
              universe_func=my_universe)  
        # Create a variable to track the date change  
    context.yesterday = None  
    context.holdingStock = None

# my_universe returns a set of securities that define your universe.  
def my_universe(context, fetcher_data):  
    my_stocks = set(fetcher_data['sid'])  
    context.count = len(my_stocks)  
    return my_stocks

# see a snapshot of your CSV for debugging  
def preview(df):  
    log.info(' %s ' % df.head())  
    return df

def handle_data(context,data):  
    # bam. copied someone else's code and it uses closing price  
    # out of the box!  
    if get_datetime().date() == context.yesterday: return  
    context.yesterday = get_datetime().date()  
    # basic idea, for each day, find out which stock we need to buy from the csv, then buy it. on the next day, sell everything we have and try to buy that day's stock. in this way, we only hold on to a stock for a day at most  
    print "Holding %s" % context.holdingStock  
    # if we're holding something, try to sell all of it  
    if(context.holdingStock is not None):  
        try:  
            # sell 100% of this stock  
            order_target_percent(context.holdingStock, 0)  
            print "Sold %s" % context.holdingStock.symbol  
        except:  
            pass  
    for stock in data:  
        print "%s %s" % (str(data[stock]['day']), str(get_datetime().date()))  
        # if the stock in the loop isn't to be traded for the day, skip  
        if str(data[stock]['day']) != str(get_datetime().date()):  
            continue  
        try:  
            # use 100% of our money to buy the stock  
            order_target_percent(stock, 1)  
            context.holdingStock = stock  
            print "Bought %s" % stock.symbol  
            break # ordered one for today, that's enough  
        except:  
            print "Couldn't order %s" % stock.symbol  

P.S. ~~ ProperlyFormatted is a csv containing a list of stock names and dates.