HOLLYWOOD STOCK EXCHANGE
THE ENTERTAINMENT MARKET
THE ENTERTAINMENT MARKET
Building on Moviesnob's point, you may want to structure this by keeping the broad categories and then subdividing them based on results.
In. For example, you would have data on all the movies in a certain genre, and then sort them from highest delist multiplier to lowest. Look at the extreme 10% at both ends - the movies with the highest DMs and the movies with the lowest - and see what commonalities exist in those two groups. Maybe you'll see a lot of movies targeted at a particular audience (like African Americans, women over 25, conservative Christians, etc), or a particular sub-genre (like action - sci-fi, comedy - spoof, etc) or release date (build-up to Oscars, holiday weekend, etc). Then you go back and check the whole data set for other movies that fit into that category.
you don't need to shoehorn every movie into a sub-category - what you want is an average for the group and an explanation for why the outliers are so different from the average. If there's a sub-genre that performs the same as the genre average, it's not interesting
I think I'll do this (over time) with my own data - I've been meaning to do somethig like this for a long time, but relying on BOM's similar movies is too easy.
@moviesnob/rogermore - Advice requested (attempt #2) Feb 08, 16:29
I think Roger's advice about looking at the data and knowing what we know (high delist values over winter holidays) Feb 08, 20:37
Thanksgiving releases tend to have poor legs by delist, though that doesn't mean poor legs overall. Feb 09, 06:50
Building on Moviesnob's point, you may want to structure this by keeping the broad categories and then subdividing them based on results. Feb 09, 07:10
