Inspiration

Polymarket bets on the news. We made the city itself tradeable.

London's next 5 minutes become a live market, settled by REAL data from TFL, not opinion. AI traders read the city's live feeds; the market learns which to trust. The result is new data: a live price on what a city does next.

Marshall Wace built TOPS to learn which brokers to trust. We built it to learn which data reads a city best.

What it does

  • New markets every 5 minutes: busiest hub vs its usual day, Tube-wide busyness, the London VIX, hourly headlines.
  • Settled by sensors: only on readings TfL stamped after betting closed. Nobody knows the answer early. No reading, full refund.
  • 7 AI traders, each reading one feed: crowding, cameras (YOLO), Tube status, rain, Heathrow planes, the crowd, our simulation.
  • TOPS on a city: reality scores every call, and only proven traders move the price. No record, no say.
  • The Exchange: same markets, no house, an order book against 2,196 AI traders (market makers, funds, retail).

How we built it

  • 16 live data sources, crowding polled every 30 s, YOLO counting people on 13 cameras.
  • Prices: 50 possible futures per market, reweighted by every new reading, then an LMSR market maker.
  • AI traders: Kelly-sized bets; each one's skill is a Bayesian estimate, and the market only leans on them once their record beats our model by more than its noise.
  • Fair by construction: bets fill only after our next data poll, so nobody can trade on data we haven't seen.
  • The Exchange: real order books. On markets with a known answer, prices end 52% closer to the truth than our own model.
  • Agent simulation: 50 worlds on 1,017 real streets. It trades as one AI; it stays out of the price until it earns its place.

Challenges we ran into

  • Markets were too easy. 286 of 309 opened at 90%+. We set lines from the data so every market opens near 50/50.
  • Bots beat the house, so we let them. They found 3 leaks; we closed 2 and a timing edge (+124% → +8%).
  • Our forecast tied "nothing changes". New rule: every model must beat the old one and a coin flip out of sample, or it doesn't ship.

Accomplishments that we're proud of

  • Live on real London data, around the clock.
  • 275 markets replayed, 0 voids.
  • The market tells good data from bad: it caught our own simulation trader losing to the model over 78 markets (99.9% confidence) and gives it no say.

What we learned

  • A good market is one you only win by reading the data.
  • Beat the baseline before claiming anything.

What's next for OverWatch

  • Move live trading to the Exchange once it prices London better on recorded data.
  • Real-money licensing, business hedging, the prices as alternative data.
  • Every city: all it needs is a street graph and live feeds.

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