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Exogenous event data?

I'm looking for feedback about how one would derive value from a web service that provides information about non-market/external events (holidays, weather, disease, road construction, power outages). The idea is to have each event associated with a given geography (tornado in Tulsa will have no direct impact in NYC, its level of severity/importance and time period. I suspect this will have most (all?) interest in retail equities or where geographic location matters.

Some sources already exist (GDELT, weather), but I'm proposing to aggregate and make the service technically easier to integrate.

Would it be useful to identify (say) and correlate an unexpected drop in foot traffic at retailers might be attributable to a major event (eg rock concert), is it simply nice to know but doesn't move the needle?

I have more questions and will gladly be more specific in what I'm proposing, but don't want to dump too much info up front!

Thanks for reading (and commenting!)

2 responses

For your reference, some prior (and public) work on foot traffic:

Generally, I'd say yes this type of data is very promising. However, it really depends on the details of the data and how it maps to a single stock, an industry, or something that cuts a cross section through the market. I'd love to hear more specifics!


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Yep, I'm familiar with much of the alt data world, including foot traffic. What I'm proposing could be used to identify anomalous behavior in spending patterns. When you have expected pattern of activity (foot traffic, sales by day/hour, etc....) and your plot falls outside of expected bounds, does the analyst think it's a data issue or something else? If it can be explained by (say) a snowstorm, parade, bomb threat, etc...I understand one would say "great," but does it become insight that is essential in developing a trading strategy for (in this case) retail equities?