Review historical train delay timings in a given region, and extrapolate the reasons for them against future train delays. Do so for a variety of regions and cities, to become aware of natural disasters as well as likely geopolitical actions, buildibg up a predictive model that relies on and exceeds the capabilities of this superpower. Bet on or against rideshare services active in the region as appropriate, as well as local business. Determine the likelihood of events like olympics, world cup, etc ocurring in any given city in the near and distant future based on increased service runs. Bet on or against those events ocurring in those cities, on the boom to construction and local businesses in the short term, and on the subsequent economic contraction (that likely leads a reduction in train service by some number of months–also data that can be added to the predictive model). Determine when/where train timings accelerate or appear where they hadn’t before, suggesting a technological improvement and/or an expansion in service, suggesting city growth, and bet on the economic expansion in that region.
I mean it’s a lot of guestimation for using train delays as input for weather/disaster prediction. A 3 hour delay on all lines could just be signal failure. Or Tuesday, if you use the DB
I’m thinking more catastrophic stuff, like major outages for multiple days/weeks/months like from a hurricane, earthquake, etc. That’s the unexpected stuff that throws the local economy haywire, and if you know when it will begin and when it will end, it just takes reviewing what business historically thrive vs falter in that situation in order to profit off of the human suffering.
Review historical train delay timings in a given region, and extrapolate the reasons for them against future train delays. Do so for a variety of regions and cities, to become aware of natural disasters as well as likely geopolitical actions, buildibg up a predictive model that relies on and exceeds the capabilities of this superpower. Bet on or against rideshare services active in the region as appropriate, as well as local business. Determine the likelihood of events like olympics, world cup, etc ocurring in any given city in the near and distant future based on increased service runs. Bet on or against those events ocurring in those cities, on the boom to construction and local businesses in the short term, and on the subsequent economic contraction (that likely leads a reduction in train service by some number of months–also data that can be added to the predictive model). Determine when/where train timings accelerate or appear where they hadn’t before, suggesting a technological improvement and/or an expansion in service, suggesting city growth, and bet on the economic expansion in that region.
I hate this, thanks.
I mean it’s a lot of guestimation for using train delays as input for weather/disaster prediction. A 3 hour delay on all lines could just be signal failure. Or Tuesday, if you use the DB
I’m thinking more catastrophic stuff, like major outages for multiple days/weeks/months like from a hurricane, earthquake, etc. That’s the unexpected stuff that throws the local economy haywire, and if you know when it will begin and when it will end, it just takes reviewing what business historically thrive vs falter in that situation in order to profit off of the human suffering.
True, guess you could jack up the prices on water and bandages from resale if you know in advance