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Net Money - feeding on overreaction
Jiri Miklosy
posted Feb 26, 2017
Finance Theory Seeking Help Getting Started Collaboration Request Value

This algo is very simple. It is based on theory that there may occur an event when company’s net cash position (cash - total liabilities) is higher than market cap. That means that you are buying all the cash and all the remaining assets are free of charge.
Of course this does not guarantee a profit, as the company may go through some expensive restructuralization - which can eat the cash in the future.

btw: I could not figure out why the algo is so slow after 2010, maybe somebody can have a look. Thanks

3 responses
Blue Seahawk
Feb 26, 2017

To find the slowdown, try https://www.quantopian.com/posts/timing-code

By the way returns on amount invested are 100 percentage points higher than shown due to unfilled orders and not using all available cash, maybe filter out a percentile of low-volume stocks to see how much difference that makes in speed, for fewer unfilled orders. Consider data.current(stock, 'price') instead of history(), and stock.last_sale_price and context.portfolio.positions[stock].cost_basis. Fundamentals query can just be query(), empty, because that populates the dataframe values and they are unused, although that one can help with speed yet not to the degree we're talking here. Even though it runs every day, give pipeline a whirl and see if it resolves the problem if timing() doesn't find the issue.

Blue Seahawk
Feb 26, 2017

Less starting cash results in fewer unfilleds here.

Jiri Miklosy
Feb 27, 2017

hi @Blue , yes partially filled orders are a problem. Realistically I would not invest more than 10000$ as an initial capital. Thanks for the tips!

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