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A trading strategy for prediction markets mediated by the logarithmic market scoring rule (LMSR) market maker

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Trading-Bot

A trading strategy for prediction markets mediated by the logarithmic market scoring rule (LMSR) market maker

To run the simulation: python my_bot.py

You can choose between plotting a single simulation and printing aggregate statistics for multiple simulations by commenting/uncommenting the appropriate lines in main().

Required Python packages:

  • numpy
  • matplotlib

In general, the line:

bots.extend(other_bots.get_bots(num_fundamentals, num_technical))

...will create a simulation with 1 + num_fundamentals + num_technical traders including your bot. You can include multiple copies of your bot or other bots in the simulation by adding them to the list with bots.append (for a single bot) or bots.extend (for a list of bots).

other_bots.py includes one type of fundamentals trader and two types of technical traders (get_bots() splits num_technical evenly between these two types). The technical traders use the price history only, and do not make money on average: they simulate noise traders which we often see in real markets.

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A trading strategy for prediction markets mediated by the logarithmic market scoring rule (LMSR) market maker

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