Trading 2.0: Learning-Adaptive Machines (Hard Cover)

Trading 2.0: Learning-Adaptive Machines (Hard Cover)This book encloses substantial financial criteria that should definitely help you enter the quantitative trading industry. The content structurally merges economics, finance, statistics and computer science along a series of experiments. These are designed to allow you understand the pros and cons of the different strategies that you may consider deploying when approaching usual trading challenges. In trading, there typically are no closed form

This book encloses substantial financial criteria that should definitely help you enter the quantitative trading industry. The content structurally merges economics, finance, statistics and computer science along a series of experiments. These are designed to allow you understand the pros and cons of the different strategies that you may consider deploying when approaching usual trading challenges. In trading, there typically are no closed-form solutions and it is the trader who ultimately needs to decide which approach can realistically fit the (ideal) solution and more importantly, why. As stressed above, the key is to account for valuable criteria and, given the range of disciplines that need to be merged in this field, not too many trading participants do have it yet. Algorithmic trading, market making and proprietary trading are comprehensively described along the book with gradually growing complexity that reaches its top at the proposed Avatar-Calibrated Trading.