Algo-Trading Game: Difference between revisions
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Client: Radmilo Racic, [[IMC (Netherlands)]] <Radmilo.racic@imc.nl> | |||
Algorithmic trading is an essential part of today’s financial markets, but releasing an algorithm out in the wild certainly comes with its own hassles. One of the challenges associated with carrying a trading algorithm into production is the evaluation of its performance, preferably under different market conditions, and using different parametrizations of the algorithm. This process, called back-testing, allows one to understand the characteristics of a trading algorithm before it hits the markets. In this project, the aim is to create a game, where users will submit their algorithms to be evaluated under a back-testing framework. An algorithm will pick which products it is interested in, and the framework will supply the historical data for those products. The algorithm can then give trading decisions, which will be evaluated in order to characterize the algorithm. | Algorithmic trading is an essential part of today’s financial markets, but releasing an algorithm out in the wild certainly comes with its own hassles. One of the challenges associated with carrying a trading algorithm into production is the evaluation of its performance, preferably under different market conditions, and using different parametrizations of the algorithm. This process, called back-testing, allows one to understand the characteristics of a trading algorithm before it hits the markets. In this project, the aim is to create a game, where users will submit their algorithms to be evaluated under a back-testing framework. An algorithm will pick which products it is interested in, and the framework will supply the historical data for those products. The algorithm can then give trading decisions, which will be evaluated in order to characterize the algorithm. | ||
Latest revision as of 17:31, 22 October 2013
Client: Radmilo Racic, IMC (Netherlands) <Radmilo.racic@imc.nl>
Algorithmic trading is an essential part of today’s financial markets, but releasing an algorithm out in the wild certainly comes with its own hassles. One of the challenges associated with carrying a trading algorithm into production is the evaluation of its performance, preferably under different market conditions, and using different parametrizations of the algorithm. This process, called back-testing, allows one to understand the characteristics of a trading algorithm before it hits the markets. In this project, the aim is to create a game, where users will submit their algorithms to be evaluated under a back-testing framework. An algorithm will pick which products it is interested in, and the framework will supply the historical data for those products. The algorithm can then give trading decisions, which will be evaluated in order to characterize the algorithm.
