How to code for yesterday's value?

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How to code for yesterday's value?

posted Dec 13, 2016

Hi,
I'm new so please go easy :) I've copied this code from the sample talib alogs using the stochastic indicator:

 # Iterate over our list of stocks  
    for stock in context.stocks:  
        current_position = context.portfolio.positions[stock].amount  
        slowk, slowd = talib.STOCH(hist['high'][stock],  
                                   hist['low'][stock],  
                                   hist['close'][stock],  
                                   fastk_period=5,  
                                   slowk_period=3,  
                                   slowk_matype=0,  
                                   slowd_period=3,  
                                   slowd_matype=0)

        # get most recent SSI value  
        slowk = slowk[-1]  
        slowd = slowd[-1]  

        # If either the slowk or slowd are less than 20, the stock is  
        # 'oversold,' a long position is opened if there are no shares  
        # in the portfolio.  
        if slowk < 20 and current_position <= 0 and data.can_trade(stock):  
            order_target_percent(stock, context.long_pct_per_stock)

However, how can I call a previous day's value to compare to the current value? Thanks in advance!

7 responses

 slowk_yest = slowk[-2]  
 slowd_yest = slowd[-2]

Thank you Vladimir. I did try that previously, but I got this error: IndexError: invalid index to scalar variable. I'm not sure how to fix it.

Santiago,

You may do this way.

Thank you once again. Any idea on why that error occurred when I tried your previous, simpler suggestion?

Just out of curiosity, for a leaner code, could I use something like this?

hist = data.history(context.spy, 'price', 20, '1d')

Of course it would be for the stochasitcs indicator instead of price. But then could I call previous day's data like this?
slowk_yest = slowk[-2] slowd_yest = slowd[-2] I just don't know how to put it all together to ensure the syntax is correct.

Santiago,

You may use fast stochastic, it is working that way.

Or slow stochastic.

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The material on this website is provided for informational purposes only and does not constitute an offer to sell, a solicitation to buy, or a recommendation or endorsement for any security or strategy, nor does it constitute an offer to provide investment advisory services by Quantopian.

In addition, the material offers no opinion with respect to the suitability of any security or specific investment. No information contained herein should be regarded as a suggestion to engage in or refrain from any investment-related course of action as none of Quantopian nor any of its affiliates is undertaking to provide investment advice, act as an adviser to any plan or entity subject to the Employee Retirement Income Security Act of 1974, as amended, individual retirement account or individual retirement annuity, or give advice in a fiduciary capacity with respect to the materials presented herein. If you are an individual retirement or other investor, contact your financial advisor or other fiduciary unrelated to Quantopian about whether any given investment idea, strategy, product or service described herein may be appropriate for your circumstances. All investments involve risk, including loss of principal. Quantopian makes no guarantees as to the accuracy or completeness of the views expressed in the website. The views are subject to change, and may have become unreliable for various reasons, including changes in market conditions or economic circumstances.