Problem with fetch_csv when loading multiple signals.

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edited

I'm new to this community and I'm having trouble using the fetcher to import multiple signals from one single csv file.
My data are located at :
https://dl.dropboxusercontent.com/u/503052837/FinalDataFrame.csv
or:
https://copy.com/0F3y2N9kfaatlyzY
They are the same so you can use either one.

I have several columns signals for each of Dow Jones Stocks
And I seem to getting this error every time i run this.
Can someone please explain for this?

def initialize(context):

    fetch_csv("https://copy.com/0F3y2N9kfaatlyzY",date_column ='date', date_format = '%m-%d-%Y')

    set_symbol_lookup_date('2015-11-01')  
    context.stocks = symbols('MMM', 'DIS', 'NKE', 'GE', 'AAPL', 'GS', 'MSFT', 'PFE', 'UTX',  
       'INTC', 'HD', 'PG', 'JPM', 'V', 'TRV', 'DD', 'CSCO', 'BA', 'AXP',  
       'CVX', 'IBM', 'MRK', 'MCD', 'UNH', 'WMT', 'XOM', 'CAT', 'VZ', 'KO',  
       'JNJ')  
def handle_data(context, data):  
    for stock in data:  
        if ("rate" and "retweet") in data[stock]:  
            indicator1 = data[stock]["rate"]  
            indicator2 = data[stock]["retweet"]  
        try:  
            current_price = data[stock].price  
            current_position = context.portfolio.positions[stock].amount  
            #cash = context.portfolio.cash  
            if (indicator1 < -1) and (indicator2 > 10) and (current_position == 0):  
                number_of_shares = int((33000 - current_position*current_price)/current_price)  
                order(stock, number_of_shares)  
                log.info("Buying shares")

            elif  (indicator1 > 5) and (indicator2 > 10) and (current_position != 0):  
                order_target(stock, 0)  
                log.info("Selling share")  
        except:  
            pass

KeyError: 'symbol'  
There was a runtime error on line 2.

Thank you very much!

11 responses

Alisa Deychman

I cloned your code and the algorithm runs using the dropbox link. Perhaps the CSV changed since you tried running the code?

Cheers,
Alisa

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chan john

Hi.. Zhuite Si is this leverage?

Blue Seahawk

It is, yes, in the sense that leverage is very low, so the profit vs. dollars put into play are lower than what you see on the chart, in fact, lower than the benchmark. Thank you chan john for sniffing out another one. Explanation.

Hover over the custom chart and compare PvR (Profit vs. Risk) to Algorithm and Benchmark values.

chan john

how to take out this leverage effect...? so that I can see... whether.. his algo really.. bet the index... without the leverage anyone..? thanks...

Zhuite Si

Hey guys, Merry Christmas! Thank you for all the explanations. I fixed it by changing column name from "tickers"to "symbol", then everything works fine.

chan john

pls, post your corrected algo. thanks ;)

Zhuite Si

Hi, chan. I mean the code itself is correct, problem is about the CSV file that I need to fetch, the column name that contains the tickers must be "symbol", not others. Previously the column in my CSV was called "tickers". The code above was just a scratch, I was learning to use the fetcher method.

chan john

@ Zhuite Si whats the logic.. behind your algo...? and why is it returning 900 percent... in short amount of time...aside from leverage...? is it base on retweet?

Blue Seahawk

I would change that original error message to -- Expected csv header 'symbol' not found.

Clarifying, Chan John ran the identical code as above, extending the algo's date range.
The CSV includes data from 2014-01-02 (where it starts trading) to 2015-12-04.
Headers ... date,symbol,rate,rate_tfidf,follower,retweet,follower_per_tweet,5rate,5rate_tfidf,5follower,5retweet,5follower_per_tweet,20rate, 20rate_tfidf,20follower,20retweet,20follower_per_tweet,60rate,60rate_tfidf,60follower,60retweet,60follower_per_tweet

The custom chart shows leverage over 6000%, negative cash (margin) over $800K. No shorting.
PvR (Profit vs. Risk), the amount of profit for each dollar put into play (including negative cash) is about 11 cents.
One of the advantages of PvR is that no matter how much leverage it still measures actual profitability.

Below, I added a line, the second line here, keeping the code from doubling up on orders:

    for stock in data:  
        if get_open_orders(stock): continue

Max leverage is now .86 and an extra penny PvR, well over half of the benchmark.
A starting point. Now it is something a software developer can sink their teeth into.

Zhuite Si

The basic idea is to construct some signals by using NLP stuff on twits, very basic sentiment analysis actually(buy if the sentiment is positive, sell if the sentiment is negative). So far the signals are poor as you can see, if you set a limit on the leverage.

Blue Seahawk

Have you normalized the data? 200 tweets for AAPL might be small compared to usual and extraordinary for ACME.
Also attention can drop off the next day or two and I don't think you really want to sell immediately just because things are quiet, it could be rising.

This is some simple code anyone can use to see what a value tends to be doing. Here, it was run twice, once for indicator1, another time for indicator2, and the results added as comments. c = context ... set elsewhere.

        indicator1 = data[stock]['rate']  
        indicator2 = data[stock]['retweet']  
        #track_val(c, indicator1)  # now 0.00  avg  0.18  lo -31.00  hi    70.00  
        #track_val(c, indicator2)  # now 0.00  avg 48.15  lo   0.00  hi 12895.00

def track_val(c, var):    # Value diagnostics  
    if 'val' not in c:  
        c.val = {  
            'hi' : var,  
            'lo' : var,  
            'avg': [0, 0],  
        }  
    avg, num     = c.val['avg']  
    avg_new      = ((avg * num) + var) / (num + 1)  
    c.val['avg'] = [avg_new, num + 1]  
    if var > c.val['hi']: c.val['hi'] = var  
    if var < c.val['lo']: c.val['lo'] = var  
    log.info('now {}  avg {}  lo {}  hi {} '.format(  
        '%.2f' % var, '%.2f' % avg_new, '%.2f' % c.val['lo'], '%.2f' % c.val['hi']))

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