2016-06-09 19:27:36 -04:00
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2016-10-22 22:29:18 -04:00
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2016-06-09 19:27:36 -04:00
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< h1 class = "header-title" > Event Studies and Earnings Releases< / h1 >
< p class = "header-date" > < a href = "https://bspeice.github.io/author/bradlee-speice.html" > Bradlee Speice< / a > , Wed 08 June 2016, < a href = "https://bspeice.github.io/category/blog.html" > Blog< / a > < / p >
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< a href = "https://bspeice.github.io/tag/earnings.html" > earnings< / a > , < a href = "https://bspeice.github.io/tag/event-study.html" > event study< / a > < / p >
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< p > Or, being suspicious of market insiders.< / p >
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< p > Use the button below to show the code I've used to generate this article. Because there is a significant amount more code involved than most other posts I've written, it's hidden by default to allow people to concentrate on the important bits.< / p >
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< h1 id = "The-Market-Just-Knew" > The Market Just Knew< a class = "anchor-link" href = "#The-Market-Just-Knew" > ¶ < / a > < / h1 > < p > I recently saw two examples of stock charts that have kept me thinking for a while. And now that the semester is complete, I finally have enough time to really look at them and give them the treatment they deserve. The first is good old Apple:< / p >
< / div >
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< div class = " highlight hl-ipython3" > < pre > < span class = "kn" > from< / span > < span class = "nn" > secrets< / span > < span class = "k" > import< / span > < span class = "n" > QUANDL_KEY< / span >
< span class = "kn" > import< / span > < span class = "nn" > matplotlib.pyplot< / span > < span class = "k" > as< / span > < span class = "nn" > plt< / span >
< span class = "kn" > from< / span > < span class = "nn" > matplotlib.dates< / span > < span class = "k" > import< / span > < span class = "n" > date2num< / span >
< span class = "kn" > from< / span > < span class = "nn" > matplotlib.finance< / span > < span class = "k" > import< / span > < span class = "n" > candlestick_ohlc< / span >
< span class = "kn" > from< / span > < span class = "nn" > matplotlib.dates< / span > < span class = "k" > import< / span > < span class = "n" > DateFormatter< / span > < span class = "p" > ,< / span > < span class = "n" > WeekdayLocator< / span > < span class = "p" > ,< / span > \
< span class = "n" > DayLocator< / span > < span class = "p" > ,< / span > < span class = "n" > MONDAY< / span >
< span class = "kn" > import< / span > < span class = "nn" > quandl< / span >
< span class = "kn" > from< / span > < span class = "nn" > datetime< / span > < span class = "k" > import< / span > < span class = "n" > datetime< / span >
< span class = "kn" > import< / span > < span class = "nn" > pandas< / span > < span class = "k" > as< / span > < span class = "nn" > pd< / span >
< span class = "o" > %< / span > < span class = "k" > matplotlib< / span > inline
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< span class = "c1" > # Quandl is currently giving me issues with returning< / span >
< span class = "c1" > # the entire dataset and not slicing server-side.< / span >
< span class = "c1" > # So instead, we' ll do it client-side!< / span >
< span class = "n" > q_format< / span > < span class = "o" > =< / span > < span class = "s1" > ' %Y-%m-< / span > < span class = "si" > %d< / span > < span class = "s1" > ' < / span >
< span class = "n" > ticker_data< / span > < span class = "o" > =< / span > < span class = "n" > quandl< / span > < span class = "o" > .< / span > < span class = "n" > get< / span > < span class = "p" > (< / span > < span class = "s1" > ' YAHOO/' < / span > < span class = "o" > +< / span > < span class = "n" > ticker< / span > < span class = "p" > ,< / span >
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< span class = "n" > start_date< / span > < span class = "o" > =< / span > < span class = "n" > start< / span > < span class = "o" > .< / span > < span class = "n" > strftime< / span > < span class = "p" > (< / span > < span class = "n" > q_format< / span > < span class = "p" > ),< / span >
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< span class = "n" > authtoken< / span > < span class = "o" > =< / span > < span class = "n" > QUANDL_KEY< / span > < span class = "p" > )< / span >
< span class = "k" > return< / span > < span class = "n" > ticker_data< / span >
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< span class = "k" > def< / span > < span class = "nf" > ohlc_dataframe< / span > < span class = "p" > (< / span > < span class = "n" > data< / span > < span class = "p" > ,< / span > < span class = "n" > ax< / span > < span class = "o" > =< / span > < span class = "kc" > None< / span > < span class = "p" > ):< / span >
< span class = "c1" > # Much of this code re-used from:< / span >
< span class = "c1" > # http://matplotlib.org/examples/pylab_examples/finance_demo.html< / span >
< span class = "k" > if< / span > < span class = "n" > ax< / span > < span class = "ow" > is< / span > < span class = "kc" > None< / span > < span class = "p" > :< / span >
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< span class = "n" > mondays< / span > < span class = "o" > =< / span > < span class = "n" > WeekdayLocator< / span > < span class = "p" > (< / span > < span class = "n" > MONDAY< / span > < span class = "p" > )< / span >
< span class = "n" > alldays< / span > < span class = "o" > =< / span > < span class = "n" > DayLocator< / span > < span class = "p" > ()< / span >
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< span class = "n" > weekFormatter< / span > < span class = "o" > =< / span > < span class = "n" > DateFormatter< / span > < span class = "p" > (< / span > < span class = "s1" > ' %b < / span > < span class = "si" > %d< / span > < span class = "s1" > ' < / span > < span class = "p" > )< / span >
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< span class = "n" > ax< / span > < span class = "o" > .< / span > < span class = "n" > xaxis< / span > < span class = "o" > .< / span > < span class = "n" > set_major_locator< / span > < span class = "p" > (< / span > < span class = "n" > mondays< / span > < span class = "p" > )< / span >
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< span class = "n" > ax< / span > < span class = "o" > .< / span > < span class = "n" > xaxis< / span > < span class = "o" > .< / span > < span class = "n" > set_major_formatter< / span > < span class = "p" > (< / span > < span class = "n" > weekFormatter< / span > < span class = "p" > )< / span >
< span class = "k" > return< / span > < span class = "n" > ax< / span >
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< span class = "n" > AAPL< / span > < span class = "o" > =< / span > < span class = "n" > fetch_ticker< / span > < span class = "p" > (< / span > < span class = "s1" > ' AAPL' < / span > < span class = "p" > ,< / span > < span class = "n" > datetime< / span > < span class = "p" > (< / span > < span class = "mi" > 2016< / span > < span class = "p" > ,< / span > < span class = "mi" > 3< / span > < span class = "p" > ,< / span > < span class = "mi" > 1< / span > < span class = "p" > ),< / span > < span class = "n" > datetime< / span > < span class = "p" > (< / span > < span class = "mi" > 2016< / span > < span class = "p" > ,< / span > < span class = "mi" > 5< / span > < span class = "p" > ,< / span > < span class = "mi" > 1< / span > < span class = "p" > ))< / span >
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< span class = "n" > ax< / span > < span class = "o" > =< / span > < span class = "n" > ohlc_dataframe< / span > < span class = "p" > (< / span > < span class = "n" > AAPL< / span > < span class = "p" > )< / span >
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< span class = "n" > ax< / span > < span class = "o" > .< / span > < span class = "n" > get_ylim< / span > < span class = "p" > ()[< / span > < span class = "mi" > 0< / span > < span class = "p" > ],< / span > < span class = "n" > ax< / span > < span class = "o" > .< / span > < span class = "n" > get_ylim< / span > < span class = "p" > ()[< / span > < span class = "mi" > 1< / span > < span class = "p" > ],< / span >
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< span class = "n" > color< / span > < span class = "o" > =< / span > < span class = "s1" > ' b' < / span > < span class = "p" > ,< / span >
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< span class = "n" > plt< / span > < span class = "o" > .< / span > < span class = "n" > legend< / span > < span class = "p" > (< / span > < span class = "n" > loc< / span > < span class = "o" > =< / span > < span class = "mi" > 3< / span > < span class = "p" > )< / span >
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< span class = "n" > plt< / span > < span class = "o" > .< / span > < span class = "n" > title< / span > < span class = "p" > (< / span > < span class = "s2" > " Apple Price 3/1/2016 - 5/1/2016" < / span > < span class = "p" > );< / span >
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< p > The second chart is from Facebook:< / p >
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2016-10-22 22:29:18 -04:00
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2016-06-09 19:27:36 -04:00
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2016-06-09 19:27:36 -04:00
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< p > These two charts demonstrate two very specific phonomena: how the market prepares for earnings releases. Let's look at those charts again, but with some extra information. As we're about the see, the market "knew" in advance that Apple was going to perform poorly. The market expected that Facebook was going to perform poorly, and instead shot the lights out. Let's see that trend in action:< / p >
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< div class = "input" >
< div class = "prompt input_prompt" > In [4]:< / div >
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< div class = " highlight hl-ipython3" > < pre > < span class = "k" > def< / span > < span class = "nf" > plot_hilo< / span > < span class = "p" > (< / span > < span class = "n" > ax< / span > < span class = "p" > ,< / span > < span class = "n" > start< / span > < span class = "p" > ,< / span > < span class = "n" > end< / span > < span class = "p" > ,< / span > < span class = "n" > data< / span > < span class = "p" > ):< / span >
< span class = "n" > ax< / span > < span class = "o" > .< / span > < span class = "n" > plot< / span > < span class = "p" > ([< / span > < span class = "n" > date2num< / span > < span class = "p" > (< / span > < span class = "n" > start< / span > < span class = "p" > ),< / span > < span class = "n" > date2num< / span > < span class = "p" > (< / span > < span class = "n" > end< / span > < span class = "p" > )],< / span >
2016-10-22 22:29:18 -04:00
< span class = "p" > [< / span > < span class = "n" > data< / span > < span class = "o" > .< / span > < span class = "n" > loc< / span > < span class = "p" > [< / span > < span class = "n" > start< / span > < span class = "p" > ][< / span > < span class = "s1" > ' High' < / span > < span class = "p" > ],< / span > < span class = "n" > data< / span > < span class = "o" > .< / span > < span class = "n" > loc< / span > < span class = "p" > [< / span > < span class = "n" > end< / span > < span class = "p" > ][< / span > < span class = "s1" > ' High' < / span > < span class = "p" > ]],< / span >
< span class = "n" > color< / span > < span class = "o" > =< / span > < span class = "s1" > ' b' < / span > < span class = "p" > )< / span >
2016-06-09 19:27:36 -04:00
< span class = "n" > ax< / span > < span class = "o" > .< / span > < span class = "n" > plot< / span > < span class = "p" > ([< / span > < span class = "n" > date2num< / span > < span class = "p" > (< / span > < span class = "n" > start< / span > < span class = "p" > ),< / span > < span class = "n" > date2num< / span > < span class = "p" > (< / span > < span class = "n" > end< / span > < span class = "p" > )],< / span >
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< span class = "p" > [< / span > < span class = "n" > data< / span > < span class = "o" > .< / span > < span class = "n" > loc< / span > < span class = "p" > [< / span > < span class = "n" > start< / span > < span class = "p" > ][< / span > < span class = "s1" > ' Low' < / span > < span class = "p" > ],< / span > < span class = "n" > data< / span > < span class = "o" > .< / span > < span class = "n" > loc< / span > < span class = "p" > [< / span > < span class = "n" > end< / span > < span class = "p" > ][< / span > < span class = "s1" > ' Low' < / span > < span class = "p" > ]],< / span >
< span class = "n" > color< / span > < span class = "o" > =< / span > < span class = "s1" > ' b' < / span > < span class = "p" > )< / span >
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< span class = "n" > f< / span > < span class = "p" > ,< / span > < span class = "n" > axarr< / span > < span class = "o" > =< / span > < span class = "n" > plt< / span > < span class = "o" > .< / span > < span class = "n" > subplots< / span > < span class = "p" > (< / span > < span class = "mi" > 1< / span > < span class = "p" > ,< / span > < span class = "mi" > 2< / span > < span class = "p" > )< / span >
< span class = "n" > ax_aapl< / span > < span class = "o" > =< / span > < span class = "n" > axarr< / span > < span class = "p" > [< / span > < span class = "mi" > 0< / span > < span class = "p" > ]< / span >
< span class = "n" > ax_fb< / span > < span class = "o" > =< / span > < span class = "n" > axarr< / span > < span class = "p" > [< / span > < span class = "mi" > 1< / span > < span class = "p" > ]< / span >
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< span class = "c1" > # Plot the AAPL trend up and down< / span >
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< span class = "n" > ohlc_dataframe< / span > < span class = "p" > (< / span > < span class = "n" > AAPL< / span > < span class = "p" > ,< / span > < span class = "n" > ax< / span > < span class = "o" > =< / span > < span class = "n" > ax_aapl< / span > < span class = "p" > )< / span >
< span class = "n" > plot_hilo< / span > < span class = "p" > (< / span > < span class = "n" > ax_aapl< / span > < span class = "p" > ,< / span > < span class = "n" > datetime< / span > < span class = "p" > (< / span > < span class = "mi" > 2016< / span > < span class = "p" > ,< / span > < span class = "mi" > 3< / span > < span class = "p" > ,< / span > < span class = "mi" > 1< / span > < span class = "p" > ),< / span > < span class = "n" > datetime< / span > < span class = "p" > (< / span > < span class = "mi" > 2016< / span > < span class = "p" > ,< / span > < span class = "mi" > 4< / span > < span class = "p" > ,< / span > < span class = "mi" > 15< / span > < span class = "p" > ),< / span > < span class = "n" > AAPL< / span > < span class = "p" > )< / span >
< span class = "n" > plot_hilo< / span > < span class = "p" > (< / span > < span class = "n" > ax_aapl< / span > < span class = "p" > ,< / span > < span class = "n" > datetime< / span > < span class = "p" > (< / span > < span class = "mi" > 2016< / span > < span class = "p" > ,< / span > < span class = "mi" > 4< / span > < span class = "p" > ,< / span > < span class = "mi" > 18< / span > < span class = "p" > ),< / span > < span class = "n" > datetime< / span > < span class = "p" > (< / span > < span class = "mi" > 2016< / span > < span class = "p" > ,< / span > < span class = "mi" > 4< / span > < span class = "p" > ,< / span > < span class = "mi" > 26< / span > < span class = "p" > ),< / span > < span class = "n" > AAPL< / span > < span class = "p" > )< / span >
< span class = "n" > ax_aapl< / span > < span class = "o" > .< / span > < span class = "n" > vlines< / span > < span class = "p" > (< / span > < span class = "n" > date2num< / span > < span class = "p" > (< / span > < span class = "n" > datetime< / span > < span class = "p" > (< / span > < span class = "mi" > 2016< / span > < span class = "p" > ,< / span > < span class = "mi" > 4< / span > < span class = "p" > ,< / span > < span class = "mi" > 26< / span > < span class = "p" > ,< / span > < span class = "mi" > 12< / span > < span class = "p" > )),< / span >
< span class = "n" > ax_aapl< / span > < span class = "o" > .< / span > < span class = "n" > get_ylim< / span > < span class = "p" > ()[< / span > < span class = "mi" > 0< / span > < span class = "p" > ],< / span > < span class = "n" > ax_aapl< / span > < span class = "o" > .< / span > < span class = "n" > get_ylim< / span > < span class = "p" > ()[< / span > < span class = "mi" > 1< / span > < span class = "p" > ],< / span >
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< span class = "n" > color< / span > < span class = "o" > =< / span > < span class = "s1" > ' g' < / span > < span class = "p" > ,< / span > < span class = "n" > label< / span > < span class = "o" > =< / span > < span class = "s1" > ' Earnings Release' < / span > < span class = "p" > )< / span >
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< span class = "n" > ax_aapl< / span > < span class = "o" > .< / span > < span class = "n" > legend< / span > < span class = "p" > (< / span > < span class = "n" > loc< / span > < span class = "o" > =< / span > < span class = "mi" > 2< / span > < span class = "p" > )< / span >
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< span class = "n" > ax_aapl< / span > < span class = "o" > .< / span > < span class = "n" > set_title< / span > < span class = "p" > (< / span > < span class = "s1" > ' AAPL Price History' < / span > < span class = "p" > )< / span >
2016-06-09 19:27:36 -04:00
2016-10-22 22:29:18 -04:00
< span class = "c1" > # Plot the FB trend down and up< / span >
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< span class = "n" > ohlc_dataframe< / span > < span class = "p" > (< / span > < span class = "n" > FB< / span > < span class = "p" > ,< / span > < span class = "n" > ax< / span > < span class = "o" > =< / span > < span class = "n" > ax_fb< / span > < span class = "p" > )< / span >
< span class = "n" > plot_hilo< / span > < span class = "p" > (< / span > < span class = "n" > ax_fb< / span > < span class = "p" > ,< / span > < span class = "n" > datetime< / span > < span class = "p" > (< / span > < span class = "mi" > 2016< / span > < span class = "p" > ,< / span > < span class = "mi" > 3< / span > < span class = "p" > ,< / span > < span class = "mi" > 30< / span > < span class = "p" > ),< / span > < span class = "n" > datetime< / span > < span class = "p" > (< / span > < span class = "mi" > 2016< / span > < span class = "p" > ,< / span > < span class = "mi" > 4< / span > < span class = "p" > ,< / span > < span class = "mi" > 27< / span > < span class = "p" > ),< / span > < span class = "n" > FB< / span > < span class = "p" > )< / span >
< span class = "n" > plot_hilo< / span > < span class = "p" > (< / span > < span class = "n" > ax_fb< / span > < span class = "p" > ,< / span > < span class = "n" > datetime< / span > < span class = "p" > (< / span > < span class = "mi" > 2016< / span > < span class = "p" > ,< / span > < span class = "mi" > 4< / span > < span class = "p" > ,< / span > < span class = "mi" > 28< / span > < span class = "p" > ),< / span > < span class = "n" > datetime< / span > < span class = "p" > (< / span > < span class = "mi" > 2016< / span > < span class = "p" > ,< / span > < span class = "mi" > 5< / span > < span class = "p" > ,< / span > < span class = "mi" > 5< / span > < span class = "p" > ),< / span > < span class = "n" > FB< / span > < span class = "p" > )< / span >
< span class = "n" > ax_fb< / span > < span class = "o" > .< / span > < span class = "n" > vlines< / span > < span class = "p" > (< / span > < span class = "n" > date2num< / span > < span class = "p" > (< / span > < span class = "n" > datetime< / span > < span class = "p" > (< / span > < span class = "mi" > 2016< / span > < span class = "p" > ,< / span > < span class = "mi" > 4< / span > < span class = "p" > ,< / span > < span class = "mi" > 27< / span > < span class = "p" > ,< / span > < span class = "mi" > 12< / span > < span class = "p" > )),< / span >
< span class = "n" > ax_fb< / span > < span class = "o" > .< / span > < span class = "n" > get_ylim< / span > < span class = "p" > ()[< / span > < span class = "mi" > 0< / span > < span class = "p" > ],< / span > < span class = "n" > ax_fb< / span > < span class = "o" > .< / span > < span class = "n" > get_ylim< / span > < span class = "p" > ()[< / span > < span class = "mi" > 1< / span > < span class = "p" > ],< / span >
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< span class = "n" > color< / span > < span class = "o" > =< / span > < span class = "s1" > ' g' < / span > < span class = "p" > ,< / span > < span class = "n" > label< / span > < span class = "o" > =< / span > < span class = "s1" > ' Earnings Release' < / span > < span class = "p" > )< / span >
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< span class = "n" > ax_fb< / span > < span class = "o" > .< / span > < span class = "n" > legend< / span > < span class = "p" > (< / span > < span class = "n" > loc< / span > < span class = "o" > =< / span > < span class = "mi" > 2< / span > < span class = "p" > )< / span >
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< span class = "n" > ax_fb< / span > < span class = "o" > .< / span > < span class = "n" > set_title< / span > < span class = "p" > (< / span > < span class = "s1" > ' FB Price History' < / span > < span class = "p" > )< / span >
2016-06-09 19:27:36 -04:00
< span class = "n" > f< / span > < span class = "o" > .< / span > < span class = "n" > set_size_inches< / span > < span class = "p" > (< / span > < span class = "mi" > 18< / span > < span class = "p" > ,< / span > < span class = "mi" > 6< / span > < span class = "p" > )< / span >
< / pre > < / div >
< / div >
< / div >
< / div >
< div class = "output_wrapper" >
< div class = "output" >
< div class = "output_area" > < div class = "prompt" > < / div >
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< p > As we can see above, the market broke a prevailing trend on Apple in order to go down, and ultimately predict the earnings release. For Facebook, the opposite happened. While the trend was down, the earnings were fantastic and the market corrected itself much higher.< / p >
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< h1 id = "Formulating-the-Question" > Formulating the Question< a class = "anchor-link" href = "#Formulating-the-Question" > ¶ < / a > < / h1 > < p > While these are two specific examples, there are plenty of other examples you could cite one way or another. Even if the preponderance of evidence shows that the market correctly predicts earnings releases, we need not accuse people of collusion; for a company like Apple with many suppliers we can generally forecast how Apple has done based on those same suppliers.< / p >
< p > The question then, is this: < strong > how well does the market predict the earnings releases?< / strong > It's an incredibly broad question that I want to disect in a couple of different ways:< / p >
< ol >
< li > Given a stock that has been trending down over the past N days before an earnings release, how likely does it continue downward after the release?< / li >
< li > Given a stock trending up, how likely does it continue up?< / li >
< li > Is there a difference in accuracy between large- and small-cap stocks?< / li >
< li > How often, and for how long, do markets trend before an earnings release?< / li >
< / ol >
< p > < strong > I want to especially thank Alejandro Saltiel for helping me retrieve the data.< / strong > He's great. And now for all of the interesting bits.< / p >
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< h1 id = "Event-Studies" > Event Studies< a class = "anchor-link" href = "#Event-Studies" > ¶ < / a > < / h1 > < p > Before we go too much further, I want to introduce the actual event study. Each chart intends to capture a lot of information and present an easy-to-understand pattern:< / p >
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< div class = "prompt input_prompt" > In [5]:< / div >
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< div class = " highlight hl-ipython3" > < pre > < span class = "kn" > import< / span > < span class = "nn" > numpy< / span > < span class = "k" > as< / span > < span class = "nn" > np< / span >
< span class = "kn" > import< / span > < span class = "nn" > pandas< / span > < span class = "k" > as< / span > < span class = "nn" > pd< / span >
< span class = "kn" > from< / span > < span class = "nn" > pandas.tseries.holiday< / span > < span class = "k" > import< / span > < span class = "n" > USFederalHolidayCalendar< / span >
< span class = "kn" > from< / span > < span class = "nn" > pandas.tseries.offsets< / span > < span class = "k" > import< / span > < span class = "n" > CustomBusinessDay< / span >
< span class = "kn" > from< / span > < span class = "nn" > datetime< / span > < span class = "k" > import< / span > < span class = "n" > datetime< / span > < span class = "p" > ,< / span > < span class = "n" > timedelta< / span >
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< span class = "c1" > # If you remove rules, it removes them from *all* calendars< / span >
< span class = "c1" > # To ensure we don' t pop rules we don' t want to, first make< / span >
< span class = "c1" > # sure to fully copy the object< / span >
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< span class = "n" > trade_calendar< / span > < span class = "o" > =< / span > < span class = "n" > USFederalHolidayCalendar< / span > < span class = "p" > ()< / span >
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< span class = "n" > trade_calendar< / span > < span class = "o" > .< / span > < span class = "n" > rules< / span > < span class = "o" > .< / span > < span class = "n" > pop< / span > < span class = "p" > (< / span > < span class = "mi" > 6< / span > < span class = "p" > )< / span > < span class = "c1" > # Remove Columbus day< / span >
< span class = "n" > trade_calendar< / span > < span class = "o" > .< / span > < span class = "n" > rules< / span > < span class = "o" > .< / span > < span class = "n" > pop< / span > < span class = "p" > (< / span > < span class = "mi" > 7< / span > < span class = "p" > )< / span > < span class = "c1" > # Remove Veteran' s day< / span >
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< span class = "n" > TradeDay< / span > < span class = "o" > =< / span > < span class = "k" > lambda< / span > < span class = "n" > days< / span > < span class = "p" > :< / span > < span class = "n" > CustomBusinessDay< / span > < span class = "p" > (< / span > < span class = "n" > days< / span > < span class = "p" > ,< / span > < span class = "n" > calendar< / span > < span class = "o" > =< / span > < span class = "n" > trade_calendar< / span > < span class = "p" > )< / span >
< span class = "k" > def< / span > < span class = "nf" > plot_study< / span > < span class = "p" > (< / span > < span class = "n" > array< / span > < span class = "p" > ):< / span >
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< span class = "c1" > # Given a 2-d array, we assume the event happens at index `lookback`,< / span >
< span class = "c1" > # and create all of our summary statistics from there.< / span >
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< span class = "n" > lookback< / span > < span class = "o" > =< / span > < span class = "nb" > int< / span > < span class = "p" > ((< / span > < span class = "n" > array< / span > < span class = "o" > .< / span > < span class = "n" > shape< / span > < span class = "p" > [< / span > < span class = "mi" > 1< / span > < span class = "p" > ]< / span > < span class = "o" > -< / span > < span class = "mi" > 1< / span > < span class = "p" > )< / span > < span class = "o" > /< / span > < span class = "mi" > 2< / span > < span class = "p" > )< / span >
< span class = "n" > norm_factor< / span > < span class = "o" > =< / span > < span class = "n" > np< / span > < span class = "o" > .< / span > < span class = "n" > repeat< / span > < span class = "p" > (< / span > < span class = "n" > array< / span > < span class = "p" > [:,< / span > < span class = "n" > lookback< / span > < span class = "p" > ]< / span > < span class = "o" > .< / span > < span class = "n" > reshape< / span > < span class = "p" > (< / span > < span class = "o" > -< / span > < span class = "mi" > 1< / span > < span class = "p" > ,< / span > < span class = "mi" > 1< / span > < span class = "p" > ),< / span > < span class = "n" > array< / span > < span class = "o" > .< / span > < span class = "n" > shape< / span > < span class = "p" > [< / span > < span class = "mi" > 1< / span > < span class = "p" > ],< / span > < span class = "n" > axis< / span > < span class = "o" > =< / span > < span class = "mi" > 1< / span > < span class = "p" > )< / span >
< span class = "n" > centered_data< / span > < span class = "o" > =< / span > < span class = "n" > array< / span > < span class = "o" > /< / span > < span class = "n" > norm_factor< / span > < span class = "o" > -< / span > < span class = "mi" > 1< / span >
< span class = "n" > lookforward< / span > < span class = "o" > =< / span > < span class = "n" > centered_data< / span > < span class = "o" > .< / span > < span class = "n" > shape< / span > < span class = "p" > [< / span > < span class = "mi" > 1< / span > < span class = "p" > ]< / span > < span class = "o" > -< / span > < span class = "n" > lookback< / span >
< span class = "n" > means< / span > < span class = "o" > =< / span > < span class = "n" > centered_data< / span > < span class = "o" > .< / span > < span class = "n" > mean< / span > < span class = "p" > (< / span > < span class = "n" > axis< / span > < span class = "o" > =< / span > < span class = "mi" > 0< / span > < span class = "p" > )< / span >
< span class = "n" > lookforward_data< / span > < span class = "o" > =< / span > < span class = "n" > centered_data< / span > < span class = "p" > [:,< / span > < span class = "n" > lookforward< / span > < span class = "p" > :]< / span >
< span class = "n" > std_dev< / span > < span class = "o" > =< / span > < span class = "n" > np< / span > < span class = "o" > .< / span > < span class = "n" > hstack< / span > < span class = "p" > ([< / span > < span class = "mi" > 0< / span > < span class = "p" > ,< / span > < span class = "n" > lookforward_data< / span > < span class = "o" > .< / span > < span class = "n" > std< / span > < span class = "p" > (< / span > < span class = "n" > axis< / span > < span class = "o" > =< / span > < span class = "mi" > 0< / span > < span class = "p" > )])< / span >
< span class = "n" > maxes< / span > < span class = "o" > =< / span > < span class = "n" > lookforward_data< / span > < span class = "o" > .< / span > < span class = "n" > max< / span > < span class = "p" > (< / span > < span class = "n" > axis< / span > < span class = "o" > =< / span > < span class = "mi" > 0< / span > < span class = "p" > )< / span >
< span class = "n" > mins< / span > < span class = "o" > =< / span > < span class = "n" > lookforward_data< / span > < span class = "o" > .< / span > < span class = "n" > min< / span > < span class = "p" > (< / span > < span class = "n" > axis< / span > < span class = "o" > =< / span > < span class = "mi" > 0< / span > < span class = "p" > )< / span >
< span class = "n" > f< / span > < span class = "p" > ,< / span > < span class = "n" > axarr< / span > < span class = "o" > =< / span > < span class = "n" > plt< / span > < span class = "o" > .< / span > < span class = "n" > subplots< / span > < span class = "p" > (< / span > < span class = "mi" > 1< / span > < span class = "p" > ,< / span > < span class = "mi" > 2< / span > < span class = "p" > )< / span >
< span class = "n" > range_begin< / span > < span class = "o" > =< / span > < span class = "o" > -< / span > < span class = "n" > lookback< / span >
< span class = "n" > range_end< / span > < span class = "o" > =< / span > < span class = "n" > lookforward< / span >
< span class = "n" > axarr< / span > < span class = "p" > [< / span > < span class = "mi" > 0< / span > < span class = "p" > ]< / span > < span class = "o" > .< / span > < span class = "n" > plot< / span > < span class = "p" > (< / span > < span class = "nb" > range< / span > < span class = "p" > (< / span > < span class = "n" > range_begin< / span > < span class = "p" > ,< / span > < span class = "n" > range_end< / span > < span class = "p" > ),< / span > < span class = "n" > means< / span > < span class = "p" > )< / span >
< span class = "n" > axarr< / span > < span class = "p" > [< / span > < span class = "mi" > 1< / span > < span class = "p" > ]< / span > < span class = "o" > .< / span > < span class = "n" > plot< / span > < span class = "p" > (< / span > < span class = "nb" > range< / span > < span class = "p" > (< / span > < span class = "n" > range_begin< / span > < span class = "p" > ,< / span > < span class = "n" > range_end< / span > < span class = "p" > ),< / span > < span class = "n" > means< / span > < span class = "p" > )< / span >
< span class = "n" > axarr< / span > < span class = "p" > [< / span > < span class = "mi" > 0< / span > < span class = "p" > ]< / span > < span class = "o" > .< / span > < span class = "n" > fill_between< / span > < span class = "p" > (< / span > < span class = "nb" > range< / span > < span class = "p" > (< / span > < span class = "mi" > 0< / span > < span class = "p" > ,< / span > < span class = "n" > range_end< / span > < span class = "p" > ),< / span >
< span class = "n" > means< / span > < span class = "p" > [< / span > < span class = "o" > -< / span > < span class = "n" > lookforward< / span > < span class = "p" > :]< / span > < span class = "o" > +< / span > < span class = "n" > std_dev< / span > < span class = "p" > ,< / span >
< span class = "n" > means< / span > < span class = "p" > [< / span > < span class = "o" > -< / span > < span class = "n" > lookforward< / span > < span class = "p" > :]< / span > < span class = "o" > -< / span > < span class = "n" > std_dev< / span > < span class = "p" > ,< / span >
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< span class = "n" > alpha< / span > < span class = "o" > =.< / span > < span class = "mi" > 5< / span > < span class = "p" > ,< / span > < span class = "n" > label< / span > < span class = "o" > =< / span > < span class = "s2" > " $\pm$ 1 s.d." < / span > < span class = "p" > )< / span >
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< span class = "n" > axarr< / span > < span class = "p" > [< / span > < span class = "mi" > 1< / span > < span class = "p" > ]< / span > < span class = "o" > .< / span > < span class = "n" > fill_between< / span > < span class = "p" > (< / span > < span class = "nb" > range< / span > < span class = "p" > (< / span > < span class = "mi" > 0< / span > < span class = "p" > ,< / span > < span class = "n" > range_end< / span > < span class = "p" > ),< / span >
< span class = "n" > means< / span > < span class = "p" > [< / span > < span class = "o" > -< / span > < span class = "n" > lookforward< / span > < span class = "p" > :]< / span > < span class = "o" > +< / span > < span class = "n" > std_dev< / span > < span class = "p" > ,< / span >
< span class = "n" > means< / span > < span class = "p" > [< / span > < span class = "o" > -< / span > < span class = "n" > lookforward< / span > < span class = "p" > :]< / span > < span class = "o" > -< / span > < span class = "n" > std_dev< / span > < span class = "p" > ,< / span >
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< span class = "n" > alpha< / span > < span class = "o" > =.< / span > < span class = "mi" > 5< / span > < span class = "p" > ,< / span > < span class = "n" > label< / span > < span class = "o" > =< / span > < span class = "s2" > " $\pm$ 1 s.d." < / span > < span class = "p" > )< / span >
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< span class = "n" > max_err< / span > < span class = "o" > =< / span > < span class = "n" > maxes< / span > < span class = "o" > -< / span > < span class = "n" > means< / span > < span class = "p" > [< / span > < span class = "o" > -< / span > < span class = "n" > lookforward< / span > < span class = "o" > +< / span > < span class = "mi" > 1< / span > < span class = "p" > :]< / span >
< span class = "n" > min_err< / span > < span class = "o" > =< / span > < span class = "n" > means< / span > < span class = "p" > [< / span > < span class = "o" > -< / span > < span class = "n" > lookforward< / span > < span class = "o" > +< / span > < span class = "mi" > 1< / span > < span class = "p" > :]< / span > < span class = "o" > -< / span > < span class = "n" > mins< / span >
< span class = "n" > axarr< / span > < span class = "p" > [< / span > < span class = "mi" > 0< / span > < span class = "p" > ]< / span > < span class = "o" > .< / span > < span class = "n" > errorbar< / span > < span class = "p" > (< / span > < span class = "nb" > range< / span > < span class = "p" > (< / span > < span class = "mi" > 1< / span > < span class = "p" > ,< / span > < span class = "n" > range_end< / span > < span class = "p" > ),< / span >
< span class = "n" > means< / span > < span class = "p" > [< / span > < span class = "o" > -< / span > < span class = "n" > lookforward< / span > < span class = "o" > +< / span > < span class = "mi" > 1< / span > < span class = "p" > :],< / span >
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< span class = "n" > yerr< / span > < span class = "o" > =< / span > < span class = "p" > [< / span > < span class = "n" > min_err< / span > < span class = "p" > ,< / span > < span class = "n" > max_err< / span > < span class = "p" > ],< / span > < span class = "n" > label< / span > < span class = "o" > =< / span > < span class = "s1" > ' Max & Min' < / span > < span class = "p" > )< / span >
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< span class = "n" > axarr< / span > < span class = "p" > [< / span > < span class = "mi" > 0< / span > < span class = "p" > ]< / span > < span class = "o" > .< / span > < span class = "n" > legend< / span > < span class = "p" > (< / span > < span class = "n" > loc< / span > < span class = "o" > =< / span > < span class = "mi" > 2< / span > < span class = "p" > )< / span >
< span class = "n" > axarr< / span > < span class = "p" > [< / span > < span class = "mi" > 1< / span > < span class = "p" > ]< / span > < span class = "o" > .< / span > < span class = "n" > legend< / span > < span class = "p" > (< / span > < span class = "n" > loc< / span > < span class = "o" > =< / span > < span class = "mi" > 2< / span > < span class = "p" > )< / span >
< span class = "n" > axarr< / span > < span class = "p" > [< / span > < span class = "mi" > 0< / span > < span class = "p" > ]< / span > < span class = "o" > .< / span > < span class = "n" > set_xlim< / span > < span class = "p" > ((< / span > < span class = "o" > -< / span > < span class = "n" > lookback< / span > < span class = "o" > -< / span > < span class = "mi" > 1< / span > < span class = "p" > ,< / span > < span class = "n" > lookback< / span > < span class = "o" > +< / span > < span class = "mi" > 1< / span > < span class = "p" > ))< / span >
< span class = "n" > axarr< / span > < span class = "p" > [< / span > < span class = "mi" > 1< / span > < span class = "p" > ]< / span > < span class = "o" > .< / span > < span class = "n" > set_xlim< / span > < span class = "p" > ((< / span > < span class = "o" > -< / span > < span class = "n" > lookback< / span > < span class = "o" > -< / span > < span class = "mi" > 1< / span > < span class = "p" > ,< / span > < span class = "n" > lookback< / span > < span class = "o" > +< / span > < span class = "mi" > 1< / span > < span class = "p" > ))< / span >
< span class = "k" > def< / span > < span class = "nf" > plot_study_small< / span > < span class = "p" > (< / span > < span class = "n" > array< / span > < span class = "p" > ):< / span >
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< span class = "c1" > # Given a 2-d array, we assume the event happens at index `lookback`,< / span >
< span class = "c1" > # and create all of our summary statistics from there.< / span >
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< span class = "n" > lookback< / span > < span class = "o" > =< / span > < span class = "nb" > int< / span > < span class = "p" > ((< / span > < span class = "n" > array< / span > < span class = "o" > .< / span > < span class = "n" > shape< / span > < span class = "p" > [< / span > < span class = "mi" > 1< / span > < span class = "p" > ]< / span > < span class = "o" > -< / span > < span class = "mi" > 1< / span > < span class = "p" > )< / span > < span class = "o" > /< / span > < span class = "mi" > 2< / span > < span class = "p" > )< / span >
< span class = "n" > norm_factor< / span > < span class = "o" > =< / span > < span class = "n" > np< / span > < span class = "o" > .< / span > < span class = "n" > repeat< / span > < span class = "p" > (< / span > < span class = "n" > array< / span > < span class = "p" > [:,< / span > < span class = "n" > lookback< / span > < span class = "p" > ]< / span > < span class = "o" > .< / span > < span class = "n" > reshape< / span > < span class = "p" > (< / span > < span class = "o" > -< / span > < span class = "mi" > 1< / span > < span class = "p" > ,< / span > < span class = "mi" > 1< / span > < span class = "p" > ),< / span > < span class = "n" > array< / span > < span class = "o" > .< / span > < span class = "n" > shape< / span > < span class = "p" > [< / span > < span class = "mi" > 1< / span > < span class = "p" > ],< / span > < span class = "n" > axis< / span > < span class = "o" > =< / span > < span class = "mi" > 1< / span > < span class = "p" > )< / span >
< span class = "n" > centered_data< / span > < span class = "o" > =< / span > < span class = "n" > array< / span > < span class = "o" > /< / span > < span class = "n" > norm_factor< / span > < span class = "o" > -< / span > < span class = "mi" > 1< / span >
< span class = "n" > lookforward< / span > < span class = "o" > =< / span > < span class = "n" > centered_data< / span > < span class = "o" > .< / span > < span class = "n" > shape< / span > < span class = "p" > [< / span > < span class = "mi" > 1< / span > < span class = "p" > ]< / span > < span class = "o" > -< / span > < span class = "n" > lookback< / span >
< span class = "n" > means< / span > < span class = "o" > =< / span > < span class = "n" > centered_data< / span > < span class = "o" > .< / span > < span class = "n" > mean< / span > < span class = "p" > (< / span > < span class = "n" > axis< / span > < span class = "o" > =< / span > < span class = "mi" > 0< / span > < span class = "p" > )< / span >
< span class = "n" > lookforward_data< / span > < span class = "o" > =< / span > < span class = "n" > centered_data< / span > < span class = "p" > [:,< / span > < span class = "n" > lookforward< / span > < span class = "p" > :]< / span >
< span class = "n" > std_dev< / span > < span class = "o" > =< / span > < span class = "n" > np< / span > < span class = "o" > .< / span > < span class = "n" > hstack< / span > < span class = "p" > ([< / span > < span class = "mi" > 0< / span > < span class = "p" > ,< / span > < span class = "n" > lookforward_data< / span > < span class = "o" > .< / span > < span class = "n" > std< / span > < span class = "p" > (< / span > < span class = "n" > axis< / span > < span class = "o" > =< / span > < span class = "mi" > 0< / span > < span class = "p" > )])< / span >
< span class = "n" > maxes< / span > < span class = "o" > =< / span > < span class = "n" > lookforward_data< / span > < span class = "o" > .< / span > < span class = "n" > max< / span > < span class = "p" > (< / span > < span class = "n" > axis< / span > < span class = "o" > =< / span > < span class = "mi" > 0< / span > < span class = "p" > )< / span >
< span class = "n" > mins< / span > < span class = "o" > =< / span > < span class = "n" > lookforward_data< / span > < span class = "o" > .< / span > < span class = "n" > min< / span > < span class = "p" > (< / span > < span class = "n" > axis< / span > < span class = "o" > =< / span > < span class = "mi" > 0< / span > < span class = "p" > )< / span >
< span class = "n" > range_begin< / span > < span class = "o" > =< / span > < span class = "o" > -< / span > < span class = "n" > lookback< / span >
< span class = "n" > range_end< / span > < span class = "o" > =< / span > < span class = "n" > lookforward< / span >
< span class = "n" > plt< / span > < span class = "o" > .< / span > < span class = "n" > plot< / span > < span class = "p" > (< / span > < span class = "nb" > range< / span > < span class = "p" > (< / span > < span class = "n" > range_begin< / span > < span class = "p" > ,< / span > < span class = "n" > range_end< / span > < span class = "p" > ),< / span > < span class = "n" > means< / span > < span class = "p" > )< / span >
< span class = "n" > plt< / span > < span class = "o" > .< / span > < span class = "n" > fill_between< / span > < span class = "p" > (< / span > < span class = "nb" > range< / span > < span class = "p" > (< / span > < span class = "mi" > 0< / span > < span class = "p" > ,< / span > < span class = "n" > range_end< / span > < span class = "p" > ),< / span >
< span class = "n" > means< / span > < span class = "p" > [< / span > < span class = "o" > -< / span > < span class = "n" > lookforward< / span > < span class = "p" > :]< / span > < span class = "o" > +< / span > < span class = "n" > std_dev< / span > < span class = "p" > ,< / span >
< span class = "n" > means< / span > < span class = "p" > [< / span > < span class = "o" > -< / span > < span class = "n" > lookforward< / span > < span class = "p" > :]< / span > < span class = "o" > -< / span > < span class = "n" > std_dev< / span > < span class = "p" > ,< / span >
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< span class = "n" > alpha< / span > < span class = "o" > =.< / span > < span class = "mi" > 5< / span > < span class = "p" > ,< / span > < span class = "n" > label< / span > < span class = "o" > =< / span > < span class = "s2" > " $\pm$ 1 s.d." < / span > < span class = "p" > )< / span >
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< span class = "n" > max_err< / span > < span class = "o" > =< / span > < span class = "n" > maxes< / span > < span class = "o" > -< / span > < span class = "n" > means< / span > < span class = "p" > [< / span > < span class = "o" > -< / span > < span class = "n" > lookforward< / span > < span class = "o" > +< / span > < span class = "mi" > 1< / span > < span class = "p" > :]< / span >
< span class = "n" > min_err< / span > < span class = "o" > =< / span > < span class = "n" > means< / span > < span class = "p" > [< / span > < span class = "o" > -< / span > < span class = "n" > lookforward< / span > < span class = "o" > +< / span > < span class = "mi" > 1< / span > < span class = "p" > :]< / span > < span class = "o" > -< / span > < span class = "n" > mins< / span >
< span class = "n" > plt< / span > < span class = "o" > .< / span > < span class = "n" > errorbar< / span > < span class = "p" > (< / span > < span class = "nb" > range< / span > < span class = "p" > (< / span > < span class = "mi" > 1< / span > < span class = "p" > ,< / span > < span class = "n" > range_end< / span > < span class = "p" > ),< / span >
< span class = "n" > means< / span > < span class = "p" > [< / span > < span class = "o" > -< / span > < span class = "n" > lookforward< / span > < span class = "o" > +< / span > < span class = "mi" > 1< / span > < span class = "p" > :],< / span >
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< span class = "n" > yerr< / span > < span class = "o" > =< / span > < span class = "p" > [< / span > < span class = "n" > min_err< / span > < span class = "p" > ,< / span > < span class = "n" > max_err< / span > < span class = "p" > ],< / span > < span class = "n" > label< / span > < span class = "o" > =< / span > < span class = "s1" > ' Max & Min' < / span > < span class = "p" > )< / span >
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< span class = "n" > plt< / span > < span class = "o" > .< / span > < span class = "n" > legend< / span > < span class = "p" > (< / span > < span class = "n" > loc< / span > < span class = "o" > =< / span > < span class = "mi" > 2< / span > < span class = "p" > )< / span >
< span class = "n" > plt< / span > < span class = "o" > .< / span > < span class = "n" > xlim< / span > < span class = "p" > ((< / span > < span class = "o" > -< / span > < span class = "n" > lookback< / span > < span class = "o" > -< / span > < span class = "mi" > 1< / span > < span class = "p" > ,< / span > < span class = "n" > lookback< / span > < span class = "o" > +< / span > < span class = "mi" > 1< / span > < span class = "p" > ))< / span >
< span class = "k" > def< / span > < span class = "nf" > fetch_event_data< / span > < span class = "p" > (< / span > < span class = "n" > ticker< / span > < span class = "p" > ,< / span > < span class = "n" > events< / span > < span class = "p" > ,< / span > < span class = "n" > horizon< / span > < span class = "o" > =< / span > < span class = "mi" > 5< / span > < span class = "p" > ):< / span >
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< span class = "c1" > # Use horizon+1 to account for including the day of the event,< / span >
< span class = "c1" > # and half-open interval - that is, for a horizon of 5,< / span >
< span class = "c1" > # we should be including 11 events. Additionally, using the< / span >
< span class = "c1" > # CustomBusinessDay means we automatically handle issues if< / span >
< span class = "c1" > # for example a company reports Friday afternoon - the date< / span >
< span class = "c1" > # calculator will turn this into a " Saturday" release, but< / span >
< span class = "c1" > # we effectively shift that to Monday with the logic below.< / span >
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< span class = "n" > td_back< / span > < span class = "o" > =< / span > < span class = "n" > TradeDay< / span > < span class = "p" > (< / span > < span class = "n" > horizon< / span > < span class = "o" > +< / span > < span class = "mi" > 1< / span > < span class = "p" > )< / span >
< span class = "n" > td_forward< / span > < span class = "o" > =< / span > < span class = "n" > TradeDay< / span > < span class = "p" > (< / span > < span class = "n" > horizon< / span > < span class = "o" > +< / span > < span class = "mi" > 1< / span > < span class = "p" > )< / span >
< span class = "n" > start_date< / span > < span class = "o" > =< / span > < span class = "nb" > min< / span > < span class = "p" > (< / span > < span class = "n" > events< / span > < span class = "p" > )< / span > < span class = "o" > -< / span > < span class = "n" > td_back< / span >
< span class = "n" > end_date< / span > < span class = "o" > =< / span > < span class = "nb" > max< / span > < span class = "p" > (< / span > < span class = "n" > events< / span > < span class = "p" > )< / span > < span class = "o" > +< / span > < span class = "n" > td_forward< / span >
< span class = "n" > total_data< / span > < span class = "o" > =< / span > < span class = "n" > fetch_ticker< / span > < span class = "p" > (< / span > < span class = "n" > ticker< / span > < span class = "p" > ,< / span > < span class = "n" > start_date< / span > < span class = "p" > ,< / span > < span class = "n" > end_date< / span > < span class = "p" > )< / span >
< span class = "n" > event_data< / span > < span class = "o" > =< / span > < span class = "p" > [< / span > < span class = "n" > total_data< / span > < span class = "o" > .< / span > < span class = "n" > ix< / span > < span class = "p" > [< / span > < span class = "n" > event< / span > < span class = "o" > -< / span > < span class = "n" > td_back< / span > < span class = "p" > :< / span > < span class = "n" > event< / span > < span class = "o" > +< / span > < span class = "n" > td_forward< / span > < span class = "p" > ]< / span > \
< span class = "p" > [< / span > < span class = "mi" > 0< / span > < span class = "p" > :< / span > < span class = "n" > horizon< / span > < span class = "o" > *< / span > < span class = "mi" > 2< / span > < span class = "o" > +< / span > < span class = "mi" > 1< / span > < span class = "p" > ]< / span > \
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< span class = "p" > [< / span > < span class = "s1" > ' Adjusted Close' < / span > < span class = "p" > ]< / span >
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< span class = "k" > for< / span > < span class = "n" > event< / span > < span class = "ow" > in< / span > < span class = "n" > events< / span > < span class = "p" > ]< / span >
< span class = "k" > return< / span > < span class = "n" > np< / span > < span class = "o" > .< / span > < span class = "n" > array< / span > < span class = "p" > (< / span > < span class = "n" > event_data< / span > < span class = "p" > )< / span >
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< span class = "c1" > # Generate a couple of random events< / span >
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< span class = "n" > event_dates< / span > < span class = "o" > =< / span > < span class = "p" > [< / span > < span class = "n" > datetime< / span > < span class = "p" > (< / span > < span class = "mi" > 2016< / span > < span class = "p" > ,< / span > < span class = "mi" > 5< / span > < span class = "p" > ,< / span > < span class = "mi" > 27< / span > < span class = "p" > )< / span > < span class = "o" > -< / span > < span class = "n" > timedelta< / span > < span class = "p" > (< / span > < span class = "n" > days< / span > < span class = "o" > =< / span > < span class = "mi" > 1< / span > < span class = "p" > )< / span > < span class = "o" > -< / span > < span class = "n" > TradeDay< / span > < span class = "p" > (< / span > < span class = "n" > x< / span > < span class = "o" > *< / span > < span class = "mi" > 20< / span > < span class = "p" > )< / span > < span class = "k" > for< / span > < span class = "n" > x< / span > < span class = "ow" > in< / span > < span class = "nb" > range< / span > < span class = "p" > (< / span > < span class = "mi" > 1< / span > < span class = "p" > ,< / span > < span class = "mi" > 40< / span > < span class = "p" > )]< / span >
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< span class = "n" > data< / span > < span class = "o" > =< / span > < span class = "n" > fetch_event_data< / span > < span class = "p" > (< / span > < span class = "s1" > ' CELG' < / span > < span class = "p" > ,< / span > < span class = "n" > event_dates< / span > < span class = "p" > )< / span >
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< span class = "n" > plot_study_small< / span > < span class = "p" > (< / span > < span class = "n" > data< / span > < span class = "p" > )< / span >
< span class = "n" > plt< / span > < span class = "o" > .< / span > < span class = "n" > legend< / span > < span class = "p" > (< / span > < span class = "n" > loc< / span > < span class = "o" > =< / span > < span class = "mi" > 3< / span > < span class = "p" > )< / span >
< span class = "n" > plt< / span > < span class = "o" > .< / span > < span class = "n" > gcf< / span > < span class = "p" > ()< / span > < span class = "o" > .< / span > < span class = "n" > set_size_inches< / span > < span class = "p" > (< / span > < span class = "mi" > 12< / span > < span class = "p" > ,< / span > < span class = "mi" > 6< / span > < span class = "p" > );< / span >
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< span class = "n" > plt< / span > < span class = "o" > .< / span > < span class = "n" > annotate< / span > < span class = "p" > (< / span > < span class = "s1" > ' Mean price for days leading up to each event' < / span > < span class = "p" > ,< / span >
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< span class = "p" > (< / span > < span class = "o" > -< / span > < span class = "mi" > 5< / span > < span class = "p" > ,< / span > < span class = "o" > -.< / span > < span class = "mi" > 01< / span > < span class = "p" > ),< / span > < span class = "p" > (< / span > < span class = "o" > -< / span > < span class = "mf" > 4.5< / span > < span class = "p" > ,< / span > < span class = "o" > .< / span > < span class = "mi" > 025< / span > < span class = "p" > ),< / span >
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< span class = "n" > arrowprops< / span > < span class = "o" > =< / span > < span class = "nb" > dict< / span > < span class = "p" > (< / span > < span class = "n" > facecolor< / span > < span class = "o" > =< / span > < span class = "s1" > ' black' < / span > < span class = "p" > ,< / span > < span class = "n" > shrink< / span > < span class = "o" > =< / span > < span class = "mf" > 0.05< / span > < span class = "p" > ))< / span >
< span class = "n" > plt< / span > < span class = "o" > .< / span > < span class = "n" > annotate< / span > < span class = "p" > (< / span > < span class = "s1" > ' ' < / span > < span class = "p" > ,< / span > < span class = "p" > (< / span > < span class = "o" > -.< / span > < span class = "mi" > 1< / span > < span class = "p" > ,< / span > < span class = "o" > .< / span > < span class = "mi" > 005< / span > < span class = "p" > ),< / span > < span class = "p" > (< / span > < span class = "o" > -.< / span > < span class = "mi" > 5< / span > < span class = "p" > ,< / span > < span class = "o" > .< / span > < span class = "mi" > 02< / span > < span class = "p" > ),< / span >
< span class = "n" > arrowprops< / span > < span class = "o" > =< / span > < span class = "p" > {< / span > < span class = "s1" > ' facecolor' < / span > < span class = "p" > :< / span > < span class = "s1" > ' black' < / span > < span class = "p" > ,< / span > < span class = "s1" > ' shrink' < / span > < span class = "p" > :< / span > < span class = "o" > .< / span > < span class = "mi" > 05< / span > < span class = "p" > })< / span >
< span class = "n" > plt< / span > < span class = "o" > .< / span > < span class = "n" > annotate< / span > < span class = "p" > (< / span > < span class = "s1" > ' $\pm$ 1 std. dev. each day' < / span > < span class = "p" > ,< / span > < span class = "p" > (< / span > < span class = "mi" > 5< / span > < span class = "p" > ,< / span > < span class = "o" > .< / span > < span class = "mi" > 055< / span > < span class = "p" > ),< / span > < span class = "p" > (< / span > < span class = "mf" > 2.5< / span > < span class = "p" > ,< / span > < span class = "o" > .< / span > < span class = "mi" > 085< / span > < span class = "p" > ),< / span >
< span class = "n" > arrowprops< / span > < span class = "o" > =< / span > < span class = "p" > {< / span > < span class = "s1" > ' facecolor' < / span > < span class = "p" > :< / span > < span class = "s1" > ' black' < / span > < span class = "p" > ,< / span > < span class = "s1" > ' shrink' < / span > < span class = "p" > :< / span > < span class = "o" > .< / span > < span class = "mi" > 05< / span > < span class = "p" > })< / span >
< span class = "n" > plt< / span > < span class = "o" > .< / span > < span class = "n" > annotate< / span > < span class = "p" > (< / span > < span class = "s1" > ' Min/Max each day' < / span > < span class = "p" > ,< / span > < span class = "p" > (< / span > < span class = "o" > .< / span > < span class = "mi" > 9< / span > < span class = "p" > ,< / span > < span class = "o" > -.< / span > < span class = "mi" > 07< / span > < span class = "p" > ),< / span > < span class = "p" > (< / span > < span class = "o" > -< / span > < span class = "mi" > 1< / span > < span class = "p" > ,< / span > < span class = "o" > -.< / span > < span class = "mi" > 1< / span > < span class = "p" > ),< / span >
< span class = "n" > arrowprops< / span > < span class = "o" > =< / span > < span class = "p" > {< / span > < span class = "s1" > ' facecolor' < / span > < span class = "p" > :< / span > < span class = "s1" > ' black' < / span > < span class = "p" > ,< / span > < span class = "s1" > ' shrink' < / span > < span class = "p" > :< / span > < span class = "o" > .< / span > < span class = "mi" > 05< / span > < span class = "p" > });< / span >
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< / pre > < / div >
< / div >
< / div >
< / div >
< div class = "output_wrapper" >
< div class = "output" >
< div class = "output_area" > < div class = "prompt" > < / div >
< div class = "output_png output_subarea " >
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< p > And as a quick textual explanation as well:< / p >
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< li > < p > The blue line represents the mean price for each day, represented as a percentage of the price on the '0-day'. For example, if we defined an 'event' as whenever the stock price dropped for three days, we would see a decreasing blue line to the left of the 0-day.< / p >
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< li > < p > The blue shaded area represents one standard deviation above and below the mean price for each day following an event. This is intended to give us an idea of what the stock price does in general following an event.< / p >
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< li > < p > The green bars are the minimum and maximum price for each day following an event. This instructs us as to how much it's possible for the stock to move.< / p >
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< h1 id = "Event-Type-1:-Trending-down-over-the-past-N-days" > Event Type 1: Trending down over the past N days< a class = "anchor-link" href = "#Event-Type-1:-Trending-down-over-the-past-N-days" > ¶ < / a > < / h1 > < p > The first type of event I want to study is how stocks perform when they've been trending down over the past couple of days prior to a release. However, we need to clarify what exactly is meant by "trending down." To do so, we'll use the following metric: < strong > the midpoint between each day's opening and closing price goes down over a period of N days< / strong > .< / p >
< p > It's probably helpful to have an example:< / p >
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< div class = "prompt input_prompt" > In [6]:< / div >
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< p > Given these charts, we can see that FB was trending down for the four days preceding the earnings release, and AAPL was trending down for a whopping 8 days (we don't count the peak day). This will define the methodology that we will use for the study.< / p >
< p > So what are the results? For a given horizon, how well does the market actually perform?< / p >
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< div class = "prompt input_prompt" > In [7]:< / div >
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< div class = " highlight hl-ipython3" > < pre > < span class = "c1" > # Read in the events for each stock;< / span >
< span class = "c1" > # The file was created using the first code block in the Appendix< / span >
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< span class = "kn" > import< / span > < span class = "nn" > yaml< / span >
< span class = "kn" > from< / span > < span class = "nn" > dateutil.parser< / span > < span class = "k" > import< / span > < span class = "n" > parse< / span >
< span class = "kn" > from< / span > < span class = "nn" > progressbar< / span > < span class = "k" > import< / span > < span class = "n" > ProgressBar< / span >
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< span class = "n" > data_str< / span > < span class = "o" > =< / span > < span class = "nb" > open< / span > < span class = "p" > (< / span > < span class = "s1" > ' earnings_dates.yaml' < / span > < span class = "p" > ,< / span > < span class = "s1" > ' r' < / span > < span class = "p" > )< / span > < span class = "o" > .< / span > < span class = "n" > read< / span > < span class = "p" > ()< / span >
< span class = "c1" > # Need to remove invalid lines< / span >
< span class = "n" > filtered< / span > < span class = "o" > =< / span > < span class = "nb" > filter< / span > < span class = "p" > (< / span > < span class = "k" > lambda< / span > < span class = "n" > x< / span > < span class = "p" > :< / span > < span class = "s1" > ' {' < / span > < span class = "ow" > not< / span > < span class = "ow" > in< / span > < span class = "n" > x< / span > < span class = "p" > ,< / span > < span class = "n" > data_str< / span > < span class = "o" > .< / span > < span class = "n" > split< / span > < span class = "p" > (< / span > < span class = "s1" > ' < / span > < span class = "se" > \n< / span > < span class = "s1" > ' < / span > < span class = "p" > ))< / span >
< span class = "n" > earnings_data< / span > < span class = "o" > =< / span > < span class = "n" > yaml< / span > < span class = "o" > .< / span > < span class = "n" > load< / span > < span class = "p" > (< / span > < span class = "s1" > ' < / span > < span class = "se" > \n< / span > < span class = "s1" > ' < / span > < span class = "o" > .< / span > < span class = "n" > join< / span > < span class = "p" > (< / span > < span class = "n" > filtered< / span > < span class = "p" > ))< / span >
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< span class = "c1" > # Convert our earnings data into a list of (ticker, date) pairs< / span >
< span class = "c1" > # to make it easy to work with.< / span >
< span class = "c1" > # This is horribly inefficient, but should get us what we need< / span >
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< span class = "n" > ticker_dates< / span > < span class = "o" > =< / span > < span class = "p" > []< / span >
< span class = "k" > for< / span > < span class = "n" > ticker< / span > < span class = "p" > ,< / span > < span class = "n" > date_list< / span > < span class = "ow" > in< / span > < span class = "n" > earnings_data< / span > < span class = "o" > .< / span > < span class = "n" > items< / span > < span class = "p" > ():< / span >
< span class = "k" > for< / span > < span class = "n" > iso_str< / span > < span class = "ow" > in< / span > < span class = "n" > date_list< / span > < span class = "p" > :< / span >
< span class = "n" > ticker_dates< / span > < span class = "o" > .< / span > < span class = "n" > append< / span > < span class = "p" > ((< / span > < span class = "n" > ticker< / span > < span class = "p" > ,< / span > < span class = "n" > parse< / span > < span class = "p" > (< / span > < span class = "n" > iso_str< / span > < span class = "p" > )))< / span >
< span class = "k" > def< / span > < span class = "nf" > does_trend_down< / span > < span class = "p" > (< / span > < span class = "n" > ticker< / span > < span class = "p" > ,< / span > < span class = "n" > event< / span > < span class = "p" > ,< / span > < span class = "n" > horizon< / span > < span class = "p" > ):< / span >
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< span class = "c1" > # Figure out if the `event` has a downtrend for< / span >
< span class = "c1" > # the `horizon` days preceding it< / span >
< span class = "c1" > # As an interpretation note: it is assumed that< / span >
< span class = "c1" > # the closing price of day `event` is the reference< / span >
< span class = "c1" > # point, and we want `horizon` days before that.< / span >
< span class = "c1" > # The price_data.hdf was created in the second appendix code block< / span >
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< span class = "k" > try< / span > < span class = "p" > :< / span >
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< span class = "n" > ticker_data< / span > < span class = "o" > =< / span > < span class = "n" > pd< / span > < span class = "o" > .< / span > < span class = "n" > read_hdf< / span > < span class = "p" > (< / span > < span class = "s1" > ' price_data.hdf' < / span > < span class = "p" > ,< / span > < span class = "n" > ticker< / span > < span class = "p" > )< / span >
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< span class = "n" > data< / span > < span class = "o" > =< / span > < span class = "n" > ticker_data< / span > < span class = "p" > [< / span > < span class = "n" > event< / span > < span class = "o" > -< / span > < span class = "n" > TradeDay< / span > < span class = "p" > (< / span > < span class = "n" > horizon< / span > < span class = "p" > ):< / span > < span class = "n" > event< / span > < span class = "p" > ]< / span >
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< span class = "n" > midpoints< / span > < span class = "o" > =< / span > < span class = "n" > data< / span > < span class = "p" > [< / span > < span class = "s1" > ' Open' < / span > < span class = "p" > ]< / span > < span class = "o" > /< / span > < span class = "mi" > 2< / span > < span class = "o" > +< / span > < span class = "n" > data< / span > < span class = "p" > [< / span > < span class = "s1" > ' Close' < / span > < span class = "p" > ]< / span > < span class = "o" > /< / span > < span class = "mi" > 2< / span >
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< span class = "c1" > # Shift dates one forward into the future and subtract< / span >
< span class = "c1" > # Effectively: do we trend down over all days?< / span >
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< span class = "n" > elems< / span > < span class = "o" > =< / span > < span class = "n" > midpoints< / span > < span class = "o" > -< / span > < span class = "n" > midpoints< / span > < span class = "o" > .< / span > < span class = "n" > shift< / span > < span class = "p" > (< / span > < span class = "mi" > 1< / span > < span class = "p" > )< / span >
< span class = "k" > return< / span > < span class = "nb" > len< / span > < span class = "p" > (< / span > < span class = "n" > elems< / span > < span class = "p" > )< / span > < span class = "o" > -< / span > < span class = "mi" > 1< / span > < span class = "o" > ==< / span > < span class = "nb" > len< / span > < span class = "p" > (< / span > < span class = "n" > elems< / span > < span class = "o" > .< / span > < span class = "n" > dropna< / span > < span class = "p" > ()[< / span > < span class = "n" > elems< / span > < span class = "o" > < =< / span > < span class = "mi" > 0< / span > < span class = "p" > ])< / span >
< span class = "k" > except< / span > < span class = "ne" > KeyError< / span > < span class = "p" > :< / span >
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< span class = "c1" > # If the stock doesn' t exist, it doesn' t qualify as trending down< / span >
< span class = "c1" > # Mostly this is here to make sure the entire analysis doesn' t < / span >
< span class = "c1" > # blow up if there were issues in data retrieval< / span >
< span class = "k" > return< / span > < span class = "kc" > False< / span >
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< span class = "k" > def< / span > < span class = "nf" > study_trend< / span > < span class = "p" > (< / span > < span class = "n" > horizon< / span > < span class = "p" > ,< / span > < span class = "n" > trend_function< / span > < span class = "p" > ):< / span >
< span class = "n" > five_day_events< / span > < span class = "o" > =< / span > < span class = "n" > np< / span > < span class = "o" > .< / span > < span class = "n" > zeros< / span > < span class = "p" > ((< / span > < span class = "mi" > 1< / span > < span class = "p" > ,< / span > < span class = "n" > horizon< / span > < span class = "o" > *< / span > < span class = "mi" > 2< / span > < span class = "o" > +< / span > < span class = "mi" > 1< / span > < span class = "p" > ))< / span >
< span class = "n" > invalid_events< / span > < span class = "o" > =< / span > < span class = "p" > []< / span >
< span class = "k" > for< / span > < span class = "n" > ticker< / span > < span class = "p" > ,< / span > < span class = "n" > event< / span > < span class = "ow" > in< / span > < span class = "n" > ProgressBar< / span > < span class = "p" > ()(< / span > < span class = "n" > ticker_dates< / span > < span class = "p" > ):< / span >
< span class = "k" > if< / span > < span class = "n" > trend_function< / span > < span class = "p" > (< / span > < span class = "n" > ticker< / span > < span class = "p" > ,< / span > < span class = "n" > event< / span > < span class = "p" > ,< / span > < span class = "n" > horizon< / span > < span class = "p" > ):< / span >
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< span class = "n" > ticker_data< / span > < span class = "o" > =< / span > < span class = "n" > pd< / span > < span class = "o" > .< / span > < span class = "n" > read_hdf< / span > < span class = "p" > (< / span > < span class = "s1" > ' price_data.hdf' < / span > < span class = "p" > ,< / span > < span class = "n" > ticker< / span > < span class = "p" > )< / span >
< span class = "n" > event_data< / span > < span class = "o" > =< / span > < span class = "n" > ticker_data< / span > < span class = "p" > [< / span > < span class = "n" > event< / span > < span class = "o" > -< / span > < span class = "n" > TradeDay< / span > < span class = "p" > (< / span > < span class = "n" > horizon< / span > < span class = "p" > ):< / span > < span class = "n" > event< / span > < span class = "o" > +< / span > < span class = "n" > TradeDay< / span > < span class = "p" > (< / span > < span class = "n" > horizon< / span > < span class = "p" > )][< / span > < span class = "s1" > ' Close' < / span > < span class = "p" > ]< / span >
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< span class = "k" > try< / span > < span class = "p" > :< / span >
< span class = "n" > five_day_events< / span > < span class = "o" > =< / span > < span class = "n" > np< / span > < span class = "o" > .< / span > < span class = "n" > vstack< / span > < span class = "p" > ([< / span > < span class = "n" > five_day_events< / span > < span class = "p" > ,< / span > < span class = "n" > event_data< / span > < span class = "p" > ])< / span >
< span class = "k" > except< / span > < span class = "ne" > ValueError< / span > < span class = "p" > :< / span >
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< span class = "c1" > # Sometimes we don' t get exactly the right number of values due to calendar< / span >
< span class = "c1" > # issues. I' ve fixed most everything I can, and the few issues that are left< / span >
< span class = "c1" > # I assume don' t systemically bias the results (i.e. data could be missing< / span >
< span class = "c1" > # because it doesn' t exist, etc.). After running through, ~1% of events get< / span >
< span class = "c1" > # discarded this way< / span >
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< span class = "n" > invalid_events< / span > < span class = "o" > .< / span > < span class = "n" > append< / span > < span class = "p" > ((< / span > < span class = "n" > ticker< / span > < span class = "p" > ,< / span > < span class = "n" > event< / span > < span class = "p" > ))< / span >
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< span class = "c1" > # Remove our initial zero row< / span >
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< span class = "n" > five_day_events< / span > < span class = "o" > =< / span > < span class = "n" > five_day_events< / span > < span class = "p" > [< / span > < span class = "mi" > 1< / span > < span class = "p" > :,:]< / span >
< span class = "n" > plot_study< / span > < span class = "p" > (< / span > < span class = "n" > five_day_events< / span > < span class = "p" > )< / span >
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< span class = "n" > plt< / span > < span class = "o" > .< / span > < span class = "n" > gcf< / span > < span class = "p" > ()< / span > < span class = "o" > .< / span > < span class = "n" > suptitle< / span > < span class = "p" > (< / span > < span class = "s1" > ' Action over {} days: {} events' < / span >
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< span class = "o" > .< / span > < span class = "n" > format< / span > < span class = "p" > (< / span > < span class = "n" > horizon< / span > < span class = "p" > ,< / span > < span class = "n" > five_day_events< / span > < span class = "o" > .< / span > < span class = "n" > shape< / span > < span class = "p" > [< / span > < span class = "mi" > 0< / span > < span class = "p" > ]))< / span >
< span class = "n" > plt< / span > < span class = "o" > .< / span > < span class = "n" > gcf< / span > < span class = "p" > ()< / span > < span class = "o" > .< / span > < span class = "n" > set_size_inches< / span > < span class = "p" > (< / span > < span class = "mi" > 18< / span > < span class = "p" > ,< / span > < span class = "mi" > 6< / span > < span class = "p" > )< / span >
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< span class = "c1" > # Start with a 5 day study< / span >
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< span class = "n" > study_trend< / span > < span class = "p" > (< / span > < span class = "mi" > 5< / span > < span class = "p" > ,< / span > < span class = "n" > does_trend_down< / span > < span class = "p" > )< / span >
< / pre > < / div >
< / div >
< / div >
< / div >
< div class = "output_wrapper" >
< div class = "output" >
< div class = "output_area" > < div class = "prompt" > < / div >
< div class = "output_subarea output_stream output_stderr output_text" >
< pre > 100% (47578 of 47578) |###########################################################| Elapsed Time: 0:21:38 Time: 0:21:38
< / pre >
< / div >
< / div >
< div class = "output_area" > < div class = "prompt" > < / div >
< div class = "output_png output_subarea " >
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"
>
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< / div >
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< / div >
< div class = "cell border-box-sizing text_cell rendered" >
< div class = "prompt input_prompt" >
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< div class = "inner_cell" >
< div class = "text_cell_render border-box-sizing rendered_html" >
< p > When a stock has been trending down for 5 days, once the earnings are announced it really doesn't move on average. However, the variability is < em > incredible< / em > . This implies two important things:< / p >
< ol >
< li > The market is just as often wrong about an earnings announcement before it happens as it is correct< / li >
< li > The incredible width of the min/max bars and standard deviation area tell us that the market reacts < em > violently< / em > after the earnings are released.< / li >
< / ol >
< p > Let's repeat the same study, but over a time horizon of 8 days and 3 days. Presumably if a stock has been going down for 8 days at a time before the earnings, the market should be more accurate.< / p >
< / div >
< / div >
< / div >
< div class = "cell border-box-sizing code_cell rendered" >
< div class = "input" >
< div class = "prompt input_prompt" > In [8]:< / div >
< div class = "inner_cell" >
< div class = "input_area" >
2016-10-22 22:29:18 -04:00
< div class = " highlight hl-ipython3" > < pre > < span class = "c1" > # 8 day study next< / span >
2016-06-09 19:27:36 -04:00
< span class = "n" > study_trend< / span > < span class = "p" > (< / span > < span class = "mi" > 8< / span > < span class = "p" > ,< / span > < span class = "n" > does_trend_down< / span > < span class = "p" > )< / span >
< / pre > < / div >
< / div >
< / div >
< / div >
< div class = "output_wrapper" >
< div class = "output" >
< div class = "output_area" > < div class = "prompt" > < / div >
< div class = "output_subarea output_stream output_stderr output_text" >
< pre > 100% (47578 of 47578) |###########################################################| Elapsed Time: 0:20:29 Time: 0:20:29
< / pre >
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< p > However, looking only at stocks that trended down for 8 days prior to a release, the same pattern emerges: on average, the stock doesn't move, but the market reaction is often incredibly violent.< / p >
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< div class = "prompt input_prompt" > In [9]:< / div >
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2016-10-22 22:29:18 -04:00
< div class = " highlight hl-ipython3" > < pre > < span class = "c1" > # 3 day study after that< / span >
2016-06-09 19:27:36 -04:00
< span class = "n" > study_trend< / span > < span class = "p" > (< / span > < span class = "mi" > 3< / span > < span class = "p" > ,< / span > < span class = "n" > does_trend_down< / span > < span class = "p" > )< / span >
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< pre > 100% (47578 of 47578) |###########################################################| Elapsed Time: 0:26:26 Time: 0:26:26
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< p > Finally, when we look at a 3-day horizon, we start getting some incredible outliers. Stocks have a potential to move over ~300% up, and the standard deviation width is again, incredible. The results for a 3-day horizon follow the same pattern we've seen in the 5- and 8-day horizons.< / p >
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< h1 id = "Event-Type-2:-Trending-up-for-N-days" > Event Type 2: Trending up for N days< a class = "anchor-link" href = "#Event-Type-2:-Trending-up-for-N-days" > ¶ < / a > < / h1 > < p > We're now going to repeat the analysis, but do it for uptrends instead. That is, instead of looking at stocks that have been trending down over the past number of days, we focus only on stocks that have been trending up.< / p >
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< div class = "prompt input_prompt" > In [10]:< / div >
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< div class = " highlight hl-ipython3" > < pre > < span class = "k" > def< / span > < span class = "nf" > does_trend_up< / span > < span class = "p" > (< / span > < span class = "n" > ticker< / span > < span class = "p" > ,< / span > < span class = "n" > event< / span > < span class = "p" > ,< / span > < span class = "n" > horizon< / span > < span class = "p" > ):< / span >
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< span class = "c1" > # Figure out if the `event` has an uptrend for< / span >
< span class = "c1" > # the `horizon` days preceding it< / span >
< span class = "c1" > # As an interpretation note: it is assumed that< / span >
< span class = "c1" > # the closing price of day `event` is the reference< / span >
< span class = "c1" > # point, and we want `horizon` days before that.< / span >
< span class = "c1" > # The price_data.hdf was created in the second appendix code block< / span >
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< span class = "k" > try< / span > < span class = "p" > :< / span >
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< span class = "n" > ticker_data< / span > < span class = "o" > =< / span > < span class = "n" > pd< / span > < span class = "o" > .< / span > < span class = "n" > read_hdf< / span > < span class = "p" > (< / span > < span class = "s1" > ' price_data.hdf' < / span > < span class = "p" > ,< / span > < span class = "n" > ticker< / span > < span class = "p" > )< / span >
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< span class = "n" > data< / span > < span class = "o" > =< / span > < span class = "n" > ticker_data< / span > < span class = "p" > [< / span > < span class = "n" > event< / span > < span class = "o" > -< / span > < span class = "n" > TradeDay< / span > < span class = "p" > (< / span > < span class = "n" > horizon< / span > < span class = "p" > ):< / span > < span class = "n" > event< / span > < span class = "p" > ]< / span >
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< span class = "n" > midpoints< / span > < span class = "o" > =< / span > < span class = "n" > data< / span > < span class = "p" > [< / span > < span class = "s1" > ' Open' < / span > < span class = "p" > ]< / span > < span class = "o" > /< / span > < span class = "mi" > 2< / span > < span class = "o" > +< / span > < span class = "n" > data< / span > < span class = "p" > [< / span > < span class = "s1" > ' Close' < / span > < span class = "p" > ]< / span > < span class = "o" > /< / span > < span class = "mi" > 2< / span >
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< span class = "c1" > # Shift dates one forward into the future and subtract< / span >
< span class = "c1" > # Effectively: do we trend down over all days?< / span >
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< span class = "n" > elems< / span > < span class = "o" > =< / span > < span class = "n" > midpoints< / span > < span class = "o" > -< / span > < span class = "n" > midpoints< / span > < span class = "o" > .< / span > < span class = "n" > shift< / span > < span class = "p" > (< / span > < span class = "mi" > 1< / span > < span class = "p" > )< / span >
< span class = "k" > return< / span > < span class = "nb" > len< / span > < span class = "p" > (< / span > < span class = "n" > elems< / span > < span class = "p" > )< / span > < span class = "o" > -< / span > < span class = "mi" > 1< / span > < span class = "o" > ==< / span > < span class = "nb" > len< / span > < span class = "p" > (< / span > < span class = "n" > elems< / span > < span class = "o" > .< / span > < span class = "n" > dropna< / span > < span class = "p" > ()[< / span > < span class = "n" > elems< / span > < span class = "o" > > =< / span > < span class = "mi" > 0< / span > < span class = "p" > ])< / span >
< span class = "k" > except< / span > < span class = "ne" > KeyError< / span > < span class = "p" > :< / span >
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< span class = "c1" > # If the stock doesn' t exist, it doesn' t qualify as trending down< / span >
< span class = "c1" > # Mostly this is here to make sure the entire analysis doesn' t < / span >
< span class = "c1" > # blow up if there were issues in data retrieval< / span >
< span class = "k" > return< / span > < span class = "kc" > False< / span >
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< span class = "n" > study_trend< / span > < span class = "p" > (< / span > < span class = "mi" > 5< / span > < span class = "p" > ,< / span > < span class = "n" > does_trend_up< / span > < span class = "p" > )< / span >
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< pre > 100% (47578 of 47578) |###########################################################| Elapsed Time: 0:22:51 Time: 0:22:51
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< p > The patterns here are very similar. With the exception of noting that stocks can go to nearly 400% after an earnings announcement (most likely this included a takeover announcement, etc.), we still see large min/max bars and wide standard deviation of returns.< / p >
< p > We'll repeat the pattern for stocks going up for both 8 and 3 days straight, but at this point, the results should be very predictable:< / p >
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< div class = "prompt input_prompt" > In [11]:< / div >
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< pre > 100% (47578 of 47578) |###########################################################| Elapsed Time: 0:20:51 Time: 0:20:51
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< h1 id = "Conclusion-and-Summary" > Conclusion and Summary< a class = "anchor-link" href = "#Conclusion-and-Summary" > ¶ < / a > < / h1 > < p > I guess the most important thing to summarize with is this: < strong > looking at the entire market, stock performance prior to an earnings release has no bearing on the stock's performance.< / strong > Honestly: given the huge variability of returns after an earnings release, even when the stock has been trending for a long time, you're best off divesting before an earnings release and letting the market sort itself out.< / p >
< p > < em > However< / em > , there is a big caveat. These results are taken when we look at the entire market. So while we can say that the market as a whole knows nothing and just reacts violently, I want to take a closer look into this data. Does the market typically perform poorly on large-cap/high liquidity stocks? Do smaller companies have investors that know them better and can thus predict performance better? Are specific market sectors better at prediction? Presumably technology stocks are more volatile than the industrials.< / p >
< p > So there are some more interesting questions I still want to ask with this data. Knowing that the hard work of data processing is largely already done, it should be fairly simple to continue this analysis and get much more refined with it. Until next time.< / p >
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< h1 id = "Appendix" > Appendix< a class = "anchor-link" href = "#Appendix" > ¶ < / a > < / h1 > < p > Export event data for Russell 3000 companies:< / p >
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< span class = "k" > if< / span > < span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > store_dates< / span > < span class = "p" > :< / span >
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< span class = "n" > match< / span > < span class = "o" > =< / span > < span class = "n" > re< / span > < span class = "o" > .< / span > < span class = "n" > match< / span > < span class = "p" > (< / span > < span class = "s1" > r' \d+/\d+/\d+' < / span > < span class = "p" > ,< / span > < span class = "n" > data< / span > < span class = "p" > )< / span >
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< span class = "k" > if< / span > < span class = "n" > match< / span > < span class = "p" > :< / span >
< span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > dates< / span > < span class = "o" > .< / span > < span class = "n" > append< / span > < span class = "p" > (< / span > < span class = "n" > match< / span > < span class = "o" > .< / span > < span class = "n" > group< / span > < span class = "p" > (< / span > < span class = "mi" > 0< / span > < span class = "p" > ))< / span >
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< span class = "c1" > # If a company reports before the bell, record the earnings date< / span >
< span class = "c1" > # being at midnight the day before. Ex: WMT reports 5/19/2016,< / span >
< span class = "c1" > # but we want the reference point to be the closing price on 5/18/2016< / span >
< span class = "k" > if< / span > < span class = "s1" > ' After Close' < / span > < span class = "ow" > in< / span > < span class = "n" > data< / span > < span class = "p" > :< / span >
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< span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > earnings_offset< / span > < span class = "o" > =< / span > < span class = "n" > timedelta< / span > < span class = "p" > (< / span > < span class = "n" > days< / span > < span class = "o" > =< / span > < span class = "mi" > 0< / span > < span class = "p" > )< / span >
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< span class = "k" > elif< / span > < span class = "s1" > ' Before Open' < / span > < span class = "ow" > in< / span > < span class = "n" > data< / span > < span class = "p" > :< / span >
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< span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > earnings_offset< / span > < span class = "o" > =< / span > < span class = "n" > timedelta< / span > < span class = "p" > (< / span > < span class = "n" > days< / span > < span class = "o" > =-< / span > < span class = "mi" > 1< / span > < span class = "p" > )< / span >
< span class = "k" > def< / span > < span class = "nf" > handle_endtag< / span > < span class = "p" > (< / span > < span class = "bp" > self< / span > < span class = "p" > ,< / span > < span class = "n" > tag< / span > < span class = "p" > ):< / span >
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< span class = "k" > if< / span > < span class = "n" > tag< / span > < span class = "o" > ==< / span > < span class = "s1" > ' table' < / span > < span class = "p" > :< / span >
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< span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > store_dates< / span > < span class = "o" > =< / span > < span class = "bp" > False< / span >
< span class = "k" > def< / span > < span class = "nf" > earnings_releases< / span > < span class = "p" > (< / span > < span class = "n" > ticker< / span > < span class = "p" > ):< / span >
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< span class = "c1" > #print(" Looking up ticker {}" .format(ticker))< / span >
< span class = "n" > user_agent< / span > < span class = "o" > =< / span > < span class = "s1" > ' Mozilla/5.0 (Windows NT 10.0; WOW64; rv:46.0) ' < / span > \
< span class = "s1" > ' Gecko/20100101 Firefox/46.0' < / span >
< span class = "n" > headers< / span > < span class = "o" > =< / span > < span class = "p" > {< / span > < span class = "s1" > ' user-agent' < / span > < span class = "p" > :< / span > < span class = "n" > user_agent< / span > < span class = "p" > }< / span >
< span class = "n" > base_url< / span > < span class = "o" > =< / span > < span class = "s1" > ' http://www.streetinsider.com/ec_earnings.php?q={}' < / span > \
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< span class = "o" > .< / span > < span class = "n" > format< / span > < span class = "p" > (< / span > < span class = "n" > ticker< / span > < span class = "p" > )< / span >
< span class = "n" > e< / span > < span class = "o" > =< / span > < span class = "n" > EarningsParser< / span > < span class = "p" > ()< / span >
< span class = "n" > s< / span > < span class = "o" > =< / span > < span class = "n" > requests< / span > < span class = "o" > .< / span > < span class = "n" > Session< / span > < span class = "p" > ()< / span >
< span class = "n" > a< / span > < span class = "o" > =< / span > < span class = "n" > requests< / span > < span class = "o" > .< / span > < span class = "n" > adapters< / span > < span class = "o" > .< / span > < span class = "n" > HTTPAdapter< / span > < span class = "p" > (< / span > < span class = "n" > max_retries< / span > < span class = "o" > =< / span > < span class = "mi" > 0< / span > < span class = "p" > )< / span >
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< span class = "n" > s< / span > < span class = "o" > .< / span > < span class = "n" > mount< / span > < span class = "p" > (< / span > < span class = "s1" > ' http://' < / span > < span class = "p" > ,< / span > < span class = "n" > a< / span > < span class = "p" > )< / span >
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< span class = "n" > e< / span > < span class = "o" > .< / span > < span class = "n" > feed< / span > < span class = "p" > (< / span > < span class = "nb" > str< / span > < span class = "p" > (< / span > < span class = "n" > s< / span > < span class = "o" > .< / span > < span class = "n" > get< / span > < span class = "p" > (< / span > < span class = "n" > base_url< / span > < span class = "p" > ,< / span > < span class = "n" > headers< / span > < span class = "o" > =< / span > < span class = "n" > headers< / span > < span class = "p" > )< / span > < span class = "o" > .< / span > < span class = "n" > content< / span > < span class = "p" > ))< / span >
< span class = "k" > if< / span > < span class = "n" > e< / span > < span class = "o" > .< / span > < span class = "n" > earnings_offset< / span > < span class = "ow" > is< / span > < span class = "ow" > not< / span > < span class = "bp" > None< / span > < span class = "p" > :< / span >
< span class = "n" > dates< / span > < span class = "o" > =< / span > < span class = "nb" > map< / span > < span class = "p" > (< / span > < span class = "k" > lambda< / span > < span class = "n" > x< / span > < span class = "p" > :< / span > < span class = "n" > parser< / span > < span class = "o" > .< / span > < span class = "n" > parse< / span > < span class = "p" > (< / span > < span class = "n" > x< / span > < span class = "p" > )< / span > < span class = "o" > +< / span > < span class = "n" > e< / span > < span class = "o" > .< / span > < span class = "n" > earnings_offset< / span > < span class = "p" > ,< / span > < span class = "n" > e< / span > < span class = "o" > .< / span > < span class = "n" > dates< / span > < span class = "p" > )< / span >
< span class = "n" > past< / span > < span class = "o" > =< / span > < span class = "nb" > filter< / span > < span class = "p" > (< / span > < span class = "k" > lambda< / span > < span class = "n" > x< / span > < span class = "p" > :< / span > < span class = "n" > x< / span > < span class = "o" > < < / span > < span class = "n" > datetime< / span > < span class = "o" > .< / span > < span class = "n" > now< / span > < span class = "p" > (),< / span > < span class = "n" > dates< / span > < span class = "p" > )< / span >
< span class = "k" > return< / span > < span class = "nb" > list< / span > < span class = "p" > (< / span > < span class = "nb" > map< / span > < span class = "p" > (< / span > < span class = "k" > lambda< / span > < span class = "n" > d< / span > < span class = "p" > :< / span > < span class = "n" > d< / span > < span class = "o" > .< / span > < span class = "n" > isoformat< / span > < span class = "p" > (),< / span > < span class = "n" > past< / span > < span class = "p" > ))< / span >
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< span class = "c1" > # Use a Russell-3000 ETF tracker (ticker IWV) to get a list of holdings< / span >
< span class = "n" > r3000< / span > < span class = "o" > =< / span > < span class = "n" > pd< / span > < span class = "o" > .< / span > < span class = "n" > read_csv< / span > < span class = "p" > (< / span > < span class = "s1" > ' https://www.ishares.com/us/products/239714/' < / span >
< span class = "s1" > ' ishares-russell-3000-etf/1449138789749.ajax?' < / span >
< span class = "s1" > ' fileType=csv& fileName=IWV_holdings& dataType=fund' < / span > < span class = "p" > ,< / span >
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< span class = "n" > header< / span > < span class = "o" > =< / span > < span class = "mi" > 10< / span > < span class = "p" > )< / span >
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< span class = "n" > r3000_equities< / span > < span class = "o" > =< / span > < span class = "n" > r3000< / span > < span class = "p" > [(< / span > < span class = "n" > r3000< / span > < span class = "p" > [< / span > < span class = "s1" > ' Exchange' < / span > < span class = "p" > ]< / span > < span class = "o" > ==< / span > < span class = "s1" > ' NASDAQ' < / span > < span class = "p" > )< / span > < span class = "o" > |< / span >
< span class = "p" > (< / span > < span class = "n" > r3000< / span > < span class = "p" > [< / span > < span class = "s1" > ' Exchange' < / span > < span class = "p" > ]< / span > < span class = "o" > ==< / span > < span class = "s1" > ' New York Stock Exchange Inc.' < / span > < span class = "p" > )]< / span >
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< span class = "n" > dates_file< / span > < span class = "o" > =< / span > < span class = "nb" > open< / span > < span class = "p" > (< / span > < span class = "s1" > ' earnings_dates.yaml' < / span > < span class = "p" > ,< / span > < span class = "s1" > ' w' < / span > < span class = "p" > )< / span >
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< span class = "k" > with< / span > < span class = "n" > futures< / span > < span class = "o" > .< / span > < span class = "n" > ThreadPoolExecutor< / span > < span class = "p" > (< / span > < span class = "n" > max_workers< / span > < span class = "o" > =< / span > < span class = "mi" > 8< / span > < span class = "p" > )< / span > < span class = "k" > as< / span > < span class = "n" > pool< / span > < span class = "p" > :< / span >
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< span class = "n" > fs< / span > < span class = "o" > =< / span > < span class = "p" > {< / span > < span class = "n" > pool< / span > < span class = "o" > .< / span > < span class = "n" > submit< / span > < span class = "p" > (< / span > < span class = "n" > earnings_releases< / span > < span class = "p" > ,< / span > < span class = "n" > r3000_equities< / span > < span class = "o" > .< / span > < span class = "n" > ix< / span > < span class = "p" > [< / span > < span class = "n" > t< / span > < span class = "p" > ][< / span > < span class = "s1" > ' Ticker' < / span > < span class = "p" > ]):< / span > < span class = "n" > t< / span >
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< span class = "k" > for< / span > < span class = "n" > t< / span > < span class = "ow" > in< / span > < span class = "n" > r3000_equities< / span > < span class = "o" > .< / span > < span class = "n" > index< / span > < span class = "p" > }< / span >
< span class = "n" > pbar< / span > < span class = "o" > =< / span > < span class = "n" > progressbar< / span > < span class = "o" > .< / span > < span class = "n" > ProgressBar< / span > < span class = "p" > (< / span > < span class = "n" > term_width< / span > < span class = "o" > =< / span > < span class = "mi" > 80< / span > < span class = "p" > ,< / span >
< span class = "n" > max_value< / span > < span class = "o" > =< / span > < span class = "n" > r3000_equities< / span > < span class = "o" > .< / span > < span class = "n" > index< / span > < span class = "o" > .< / span > < span class = "n" > max< / span > < span class = "p" > ())< / span >
< span class = "k" > for< / span > < span class = "n" > future< / span > < span class = "ow" > in< / span > < span class = "n" > futures< / span > < span class = "o" > .< / span > < span class = "n" > as_completed< / span > < span class = "p" > (< / span > < span class = "n" > fs< / span > < span class = "p" > ):< / span >
< span class = "n" > i< / span > < span class = "o" > =< / span > < span class = "n" > fs< / span > < span class = "p" > [< / span > < span class = "n" > future< / span > < span class = "p" > ]< / span >
< span class = "n" > pbar< / span > < span class = "o" > .< / span > < span class = "n" > update< / span > < span class = "p" > (< / span > < span class = "n" > i< / span > < span class = "p" > )< / span >
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< span class = "n" > dates_file< / span > < span class = "o" > .< / span > < span class = "n" > write< / span > < span class = "p" > (< / span > < span class = "n" > yaml< / span > < span class = "o" > .< / span > < span class = "n" > dump< / span > < span class = "p" > ({< / span > < span class = "n" > r3000_equities< / span > < span class = "o" > .< / span > < span class = "n" > ix< / span > < span class = "p" > [< / span > < span class = "n" > i< / span > < span class = "p" > ][< / span > < span class = "s1" > ' Ticker' < / span > < span class = "p" > ]:< / span >
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< span class = "n" > future< / span > < span class = "o" > .< / span > < span class = "n" > result< / span > < span class = "p" > ()}))< / span >
< / pre > < / div >
< p > Downloading stock price data needed for the event studies:< / p >
< div class = "highlight" > < pre > < span class = "kn" > from< / span > < span class = "nn" > secrets< / span > < span class = "kn" > import< / span > < span class = "n" > QUANDL_KEY< / span >
< span class = "kn" > import< / span > < span class = "nn" > pandas< / span > < span class = "kn" > as< / span > < span class = "nn" > pd< / span >
< span class = "kn" > import< / span > < span class = "nn" > yaml< / span >
< span class = "kn" > from< / span > < span class = "nn" > dateutil.parser< / span > < span class = "kn" > import< / span > < span class = "n" > parse< / span >
< span class = "kn" > from< / span > < span class = "nn" > datetime< / span > < span class = "kn" > import< / span > < span class = "n" > timedelta< / span >
< span class = "kn" > import< / span > < span class = "nn" > quandl< / span >
< span class = "kn" > from< / span > < span class = "nn" > progressbar< / span > < span class = "kn" > import< / span > < span class = "n" > ProgressBar< / span >
< span class = "k" > def< / span > < span class = "nf" > fetch_ticker< / span > < span class = "p" > (< / span > < span class = "n" > ticker< / span > < span class = "p" > ,< / span > < span class = "n" > start< / span > < span class = "p" > ,< / span > < span class = "n" > end< / span > < span class = "p" > ):< / span >
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< span class = "c1" > # Quandl is currently giving me issues with returning< / span >
< span class = "c1" > # the entire dataset and not slicing server-side.< / span >
< span class = "c1" > # So instead, we' ll do it client-side!< / span >
< span class = "n" > q_format< / span > < span class = "o" > =< / span > < span class = "s1" > ' %Y-%m-< / span > < span class = "si" > %d< / span > < span class = "s1" > ' < / span >
< span class = "n" > ticker_data< / span > < span class = "o" > =< / span > < span class = "n" > quandl< / span > < span class = "o" > .< / span > < span class = "n" > get< / span > < span class = "p" > (< / span > < span class = "s1" > ' YAHOO/' < / span > < span class = "o" > +< / span > < span class = "n" > ticker< / span > < span class = "p" > ,< / span >
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< span class = "n" > start_date< / span > < span class = "o" > =< / span > < span class = "n" > start< / span > < span class = "o" > .< / span > < span class = "n" > strftime< / span > < span class = "p" > (< / span > < span class = "n" > q_format< / span > < span class = "p" > ),< / span >
< span class = "n" > end_date< / span > < span class = "o" > =< / span > < span class = "n" > end< / span > < span class = "o" > .< / span > < span class = "n" > strftime< / span > < span class = "p" > (< / span > < span class = "n" > q_format< / span > < span class = "p" > ),< / span >
< span class = "n" > authtoken< / span > < span class = "o" > =< / span > < span class = "n" > QUANDL_KEY< / span > < span class = "p" > )< / span >
< span class = "k" > return< / span > < span class = "n" > ticker_data< / span >
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< span class = "n" > data_str< / span > < span class = "o" > =< / span > < span class = "nb" > open< / span > < span class = "p" > (< / span > < span class = "s1" > ' earnings_dates.yaml' < / span > < span class = "p" > ,< / span > < span class = "s1" > ' r' < / span > < span class = "p" > )< / span > < span class = "o" > .< / span > < span class = "n" > read< / span > < span class = "p" > ()< / span >
< span class = "c1" > # Need to remove invalid lines< / span >
< span class = "n" > filtered< / span > < span class = "o" > =< / span > < span class = "nb" > filter< / span > < span class = "p" > (< / span > < span class = "k" > lambda< / span > < span class = "n" > x< / span > < span class = "p" > :< / span > < span class = "s1" > ' {' < / span > < span class = "ow" > not< / span > < span class = "ow" > in< / span > < span class = "n" > x< / span > < span class = "p" > ,< / span > < span class = "n" > data_str< / span > < span class = "o" > .< / span > < span class = "n" > split< / span > < span class = "p" > (< / span > < span class = "s1" > ' < / span > < span class = "se" > \n< / span > < span class = "s1" > ' < / span > < span class = "p" > ))< / span >
< span class = "n" > earnings_data< / span > < span class = "o" > =< / span > < span class = "n" > yaml< / span > < span class = "o" > .< / span > < span class = "n" > load< / span > < span class = "p" > (< / span > < span class = "s1" > ' < / span > < span class = "se" > \n< / span > < span class = "s1" > ' < / span > < span class = "o" > .< / span > < span class = "n" > join< / span > < span class = "p" > (< / span > < span class = "n" > filtered< / span > < span class = "p" > ))< / span >
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< span class = "c1" > # Get the first 1500 keys - split up into two statements< / span >
< span class = "c1" > # because of Quandl rate limits< / span >
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< span class = "n" > tickers< / span > < span class = "o" > =< / span > < span class = "nb" > list< / span > < span class = "p" > (< / span > < span class = "n" > earnings_data< / span > < span class = "o" > .< / span > < span class = "n" > keys< / span > < span class = "p" > ())< / span >
< span class = "n" > price_dict< / span > < span class = "o" > =< / span > < span class = "p" > {}< / span >
< span class = "n" > invalid_tickers< / span > < span class = "o" > =< / span > < span class = "p" > []< / span >
< span class = "k" > for< / span > < span class = "n" > ticker< / span > < span class = "ow" > in< / span > < span class = "n" > ProgressBar< / span > < span class = "p" > ()(< / span > < span class = "n" > tickers< / span > < span class = "p" > [< / span > < span class = "mi" > 0< / span > < span class = "p" > :< / span > < span class = "mi" > 1500< / span > < span class = "p" > ]):< / span >
< span class = "k" > try< / span > < span class = "p" > :< / span >
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< span class = "c1" > # Replace ' .' with ' -' in name for some tickers< / span >
< span class = "n" > fixed< / span > < span class = "o" > =< / span > < span class = "n" > ticker< / span > < span class = "o" > .< / span > < span class = "n" > replace< / span > < span class = "p" > (< / span > < span class = "s1" > ' .' < / span > < span class = "p" > ,< / span > < span class = "s1" > ' -' < / span > < span class = "p" > )< / span >
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< span class = "n" > event_strs< / span > < span class = "o" > =< / span > < span class = "n" > earnings_data< / span > < span class = "p" > [< / span > < span class = "n" > ticker< / span > < span class = "p" > ]< / span >
< span class = "n" > events< / span > < span class = "o" > =< / span > < span class = "p" > [< / span > < span class = "n" > parse< / span > < span class = "p" > (< / span > < span class = "n" > event< / span > < span class = "p" > )< / span > < span class = "k" > for< / span > < span class = "n" > event< / span > < span class = "ow" > in< / span > < span class = "n" > event_strs< / span > < span class = "p" > ]< / span >
< span class = "n" > td< / span > < span class = "o" > =< / span > < span class = "n" > timedelta< / span > < span class = "p" > (< / span > < span class = "n" > days< / span > < span class = "o" > =< / span > < span class = "mi" > 20< / span > < span class = "p" > )< / span >
< span class = "n" > price_dict< / span > < span class = "p" > [< / span > < span class = "n" > ticker< / span > < span class = "p" > ]< / span > < span class = "o" > =< / span > < span class = "n" > fetch_ticker< / span > < span class = "p" > (< / span > < span class = "n" > fixed< / span > < span class = "p" > ,< / span >
< span class = "nb" > min< / span > < span class = "p" > (< / span > < span class = "n" > events< / span > < span class = "p" > )< / span > < span class = "o" > -< / span > < span class = "n" > td< / span > < span class = "p" > ,< / span > < span class = "nb" > max< / span > < span class = "p" > (< / span > < span class = "n" > events< / span > < span class = "p" > )< / span > < span class = "o" > +< / span > < span class = "n" > td< / span > < span class = "p" > )< / span >
< span class = "k" > except< / span > < span class = "n" > quandl< / span > < span class = "o" > .< / span > < span class = "n" > NotFoundError< / span > < span class = "p" > :< / span >
< span class = "n" > invalid_tickers< / span > < span class = "o" > .< / span > < span class = "n" > append< / span > < span class = "p" > (< / span > < span class = "n" > ticker< / span > < span class = "p" > )< / span >
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< span class = "c1" > # Execute this after 10 minutes have passed< / span >
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< span class = "k" > for< / span > < span class = "n" > ticker< / span > < span class = "ow" > in< / span > < span class = "n" > ProgressBar< / span > < span class = "p" > ()(< / span > < span class = "n" > tickers< / span > < span class = "p" > [< / span > < span class = "mi" > 1500< / span > < span class = "p" > :]):< / span >
< span class = "k" > try< / span > < span class = "p" > :< / span >
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< span class = "c1" > # Replace ' .' with ' -' in name for some tickers< / span >
< span class = "n" > fixed< / span > < span class = "o" > =< / span > < span class = "n" > ticker< / span > < span class = "o" > .< / span > < span class = "n" > replace< / span > < span class = "p" > (< / span > < span class = "s1" > ' .' < / span > < span class = "p" > ,< / span > < span class = "s1" > ' -' < / span > < span class = "p" > )< / span >
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< span class = "n" > event_strs< / span > < span class = "o" > =< / span > < span class = "n" > earnings_data< / span > < span class = "p" > [< / span > < span class = "n" > ticker< / span > < span class = "p" > ]< / span >
< span class = "n" > events< / span > < span class = "o" > =< / span > < span class = "p" > [< / span > < span class = "n" > parse< / span > < span class = "p" > (< / span > < span class = "n" > event< / span > < span class = "p" > )< / span > < span class = "k" > for< / span > < span class = "n" > event< / span > < span class = "ow" > in< / span > < span class = "n" > event_strs< / span > < span class = "p" > ]< / span >
< span class = "n" > td< / span > < span class = "o" > =< / span > < span class = "n" > timedelta< / span > < span class = "p" > (< / span > < span class = "n" > days< / span > < span class = "o" > =< / span > < span class = "mi" > 20< / span > < span class = "p" > )< / span >
< span class = "n" > price_dict< / span > < span class = "p" > [< / span > < span class = "n" > ticker< / span > < span class = "p" > ]< / span > < span class = "o" > =< / span > < span class = "n" > fetch_ticker< / span > < span class = "p" > (< / span > < span class = "n" > fixed< / span > < span class = "p" > ,< / span >
< span class = "nb" > min< / span > < span class = "p" > (< / span > < span class = "n" > events< / span > < span class = "p" > )< / span > < span class = "o" > -< / span > < span class = "n" > td< / span > < span class = "p" > ,< / span > < span class = "nb" > max< / span > < span class = "p" > (< / span > < span class = "n" > events< / span > < span class = "p" > )< / span > < span class = "o" > +< / span > < span class = "n" > td< / span > < span class = "p" > )< / span >
< span class = "k" > except< / span > < span class = "n" > quandl< / span > < span class = "o" > .< / span > < span class = "n" > NotFoundError< / span > < span class = "p" > :< / span >
< span class = "n" > invalid_tickers< / span > < span class = "o" > .< / span > < span class = "n" > append< / span > < span class = "p" > (< / span > < span class = "n" > ticker< / span > < span class = "p" > )< / span >
2016-10-22 22:29:18 -04:00
< span class = "n" > prices_store< / span > < span class = "o" > =< / span > < span class = "n" > pd< / span > < span class = "o" > .< / span > < span class = "n" > HDFStore< / span > < span class = "p" > (< / span > < span class = "s1" > ' price_data.hdf' < / span > < span class = "p" > )< / span >
2016-06-09 19:27:36 -04:00
< span class = "k" > for< / span > < span class = "n" > ticker< / span > < span class = "p" > ,< / span > < span class = "n" > prices< / span > < span class = "ow" > in< / span > < span class = "n" > price_dict< / span > < span class = "o" > .< / span > < span class = "n" > items< / span > < span class = "p" > ():< / span >
< span class = "n" > prices_store< / span > < span class = "p" > [< / span > < span class = "n" > ticker< / span > < span class = "p" > ]< / span > < span class = "o" > =< / span > < span class = "n" > prices< / span >
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