Titlebook: Machine Learning in Finance; From Theory to Pract Matthew F. Dixon,Igor Halperin,Paul Bilokon Textbook 2020 Springer Nature Switzerland AG

宣誓书

Feedforward Neural Networksand statistical learning concepts and explaining how they relate to real-world examples in trading, risk management, and investment management. These applications present challenges for forecasting and model design and are presented as a reoccurring theme throughout the book. This chapter moves towa

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Interpretabilitytes techniques for interpreting a feedforward network, including how to rank the importance of the features. An example demonstrating how to apply interpretability analysis to deep learning models for factor modeling is also presented.

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细胞

Probabilistic Sequence Modelingations of the frequentist models in the previous chapters. The fitting procedure demonstrated is also different—the use of Kalman filtering algorithms for state-space models rather than maximum likelihood estimation or Bayesian inference. Simple examples of hidden Markov models and particle filters

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Advanced Neural Networks in financial econometrics. Recurrent neural networks (RNNs) are presented as non-linear time series models and generalize classical linear time series models such as .(.). They provide a powerful approach for prediction in financial time series and generalize to non-stationary data. This chapter al

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Introduction to Reinforcement Learningforcement learning and other approximate methods for solving MDPs. After describing Bellman optimality and iterative value and policy updates before moving to Q-learning, the chapter quickly advances towards a more engineering style exposition of the topic, covering key computational concepts such a

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diathermy

Terrace

Frontiers of Machine Learning and Financewe focus here on two broad themes. The first one deals with unification of supervised learning and reinforcement learning as two tasks of perception-action cycles of agents. We outline some recent research ideas in the literature including, in particular, information theory-based versions of reinfor

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This class-tested text examines each of these parameters in crucial depth and makes the argument that life forms we would recognize may be more common in our solar system than many assume. It also considers, however, exotic forms of life that would not have to rely on carbon as basic chemical eleme