My first attempt at a dollar neutral portfolio. Algo scans 500 stocks and ranks them into top and bottom 10%. Then using CVXOPT it minimizes variance of portfolio.
My current implementation uses a crude technique (return / vol) to rank stocks. Anyone has better ideas? I know people rank stocks based on technical, fundamental and statistical indicators. Please suggest if you can improve it.
Best regards,
Beginner
Hi,
I took a quick look at your ranking function, and was wonder if you may have accidentally forgotten to apply pct_change() in the denominator of the ranking statement:
stocks[sid] = prices[sid].pct_change(15).dropna()[-1] / np.std(prices[sid].values)
In this case since its just taking the np.std() of the price series, with the numerator being in percentage terms, the ranking function will most likely be driven by the actual stock price rather than the volatility. (e.g. since the np.std() of lower priced stocks will simply always be smaller than np.std() of a high priced stock). In order to rank the stock on a more apples-to-apples basis, apply pct_change() to the prices in the denominator as well when computing the std(). Perhaps try:
stocks[sid] = prices[sid].pct_change(15).dropna()[-1] / (np.std(prices[sid].pct_change().dropna()[-15:].values) * np.sqrt(15))
As well in the revised statement above I transform the standard dev of the daily pct_change returns into a 15-day standard dev by multiplying by sqrt(15). This is because volatility scales at the sqrt of time. Though this scaling by sqrt(15) isn't absolutely necessary I suppose, since I imagine if you just use the basic daily return standard deviation for all the stocks and then you rank them, it should rank in the same order I imagine.
Apologies if perhaps I missed if in the code you already normalized all the stock prices to a standard basis and these it's possible doing it the way you have it will work just fine.
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Thanks Justin for taking a look at the Algo. You are right, I should scale by std dev of returns.
Best regards,
Pravin
Hi Pravin,
The pipeline API was launched today and should help both make the coding of this strategy easier, and will also allow you to scan the entire universe of 8000+ securities instead of just the 500 securities you specified. You can read all about it here.
I've also attached an example that calculates two factors (one momentum based, the other liquidity) and then ranks the universe by those factors. It longs and shorts 5% of the resulting universe respectively. Hopefully this is helpful.
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.
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.
