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How BitBanks Evidence based crypto statistics dashboard works

The overall flow of our algorithm is as follows:

  • get all the data
  • compute features in the data. Features may be something like:
    • Amount of trades in a time interval
    • Averages in the prices of trades that have gone through, weighted by trade amount
    • The best fit slope weighted by trade amount
    • Spread in the orderbook
    • Weighted orderbook midpoint (only need to consider best X amount of buy and sell orders)
    • Trends in the weighted orderbook midpoint over time
  • find evidence using a machine learning algorithm trained to optimize long term profit
  • create projections and estimated profits using the evidence using a machine learning algorithm that takes into account performance of various evidence projection strategies, how close evidence is to the current state/features, how far in the future to project, risk e.g. optimize for future average case profit instead of looking for small spikes in the future
  • concurrently saving all computed data for display in our real time dashboards, presenting the evidence so you can make informed decisions and follow along when you have a high confidence in the projections and evidence match to the current state
  • cancel all our current orders and place new real orders in the markets to validate our machine learning algorithm is actually profitable

We constantly index new data, precompute and compare predicted vs actual results and ingest our predictions so that our algorithm can adapt to changing market conditions, New data is inested after two hours when we can compare our forecast to the actual results we ingest the data to be used as evidence for new predictions so our algorithm can adapt to slow changes in the market dynamics over time, our algorithm can also not be used to predict markets when large external factors are coming into play like hardforks because we have ingested times when other large market movements have occurred and can look there for evidence.