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Machine Learning for Factor Investing: R Version - R Version (Hardcover)
Loot Price: R5,270
Discovery Miles 52 700
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Machine Learning for Factor Investing: R Version - R Version (Hardcover)
Series: Chapman and Hall/CRC Financial Mathematics Series
Expected to ship within 12 - 17 working days
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Machine learning (ML) is progressively reshaping the fields of
quantitative finance and algorithmic trading. ML tools are
increasingly adopted by hedge funds and asset managers, notably for
alpha signal generation and stocks selection. The technicality of
the subject can make it hard for non-specialists to join the
bandwagon, as the jargon and coding requirements may seem out of
reach. Machine Learning for Factor Investing: R Version bridges
this gap. It provides a comprehensive tour of modern ML-based
investment strategies that rely on firm characteristics. The book
covers a wide array of subjects which range from economic
rationales to rigorous portfolio back-testing and encompass both
data processing and model interpretability. Common supervised
learning algorithms such as tree models and neural networks are
explained in the context of style investing and the reader can also
dig into more complex techniques like autoencoder asset returns,
Bayesian additive trees, and causal models. All topics are
illustrated with self-contained R code samples and snippets that
are applied to a large public dataset that contains over 90
predictors. The material, along with the content of the book, is
available online so that readers can reproduce and enhance the
examples at their convenience. If you have even a basic knowledge
of quantitative finance, this combination of theoretical concepts
and practical illustrations will help you learn quickly and deepen
your financial and technical expertise.
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