Machine learning in finance and accounting

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216275%3A25410%2F21%3A39917736" target="_blank" >RIV/00216275:25410/21:39917736 - isvavai.cz</a>

Výsledek na webu

<a href="https://www.taylorfrancis.com/chapters/edit/10.4324/9781003037903-1/machine-learning-finance-accounting-mohammad-zoynul-abedin-kabir-hassan-petr-hajek-mohammed-mohi-uddin?context=ubx&refId=9d4617ee-6112-4f80-9ebf-7b200e98c97e" target="_blank" >https://www.taylorfrancis.com/chapters/edit/10.4324/9781003037903-1/machine-learning-finance-accounting-mohammad-zoynul-abedin-kabir-hassan-petr-hajek-mohammed-mohi-uddin?context=ubx&refId=9d4617ee-6112-4f80-9ebf-7b200e98c97e</a>

DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Machine learning in finance and accounting

Popis výsledku v původním jazyce

This introduction presents an overview of the key concepts discussed in the subsequent chapters of this book. The book reviews Breiman’s CART algorithm, classification features, and non-parametric methods, i.e., decision trees and random forests. It applies Machine learning (ML) to enhance longevity risk management by life insurance companies and pension fund managers. The book shows how ML can help improve mortality forecasting. It introduces kernel switching ridge regression, an ML method. The book argues that the method can make predictions from multiple “regimes of dataset” and “can overcome the unstable solution and the curse of dimensionality”. It describes sentiment analysis in predicting stock return volatilities. The book explores some important concepts and ML algorithms, and applications of machine learning techniques in the fields of economics and finance. It focuses on the use of ML and artificial intelligence (AI) in financial services industry.

Název v anglickém jazyce

Machine learning in finance and accounting

Popis výsledku anglicky

This introduction presents an overview of the key concepts discussed in the subsequent chapters of this book. The book reviews Breiman’s CART algorithm, classification features, and non-parametric methods, i.e., decision trees and random forests. It applies Machine learning (ML) to enhance longevity risk management by life insurance companies and pension fund managers. The book shows how ML can help improve mortality forecasting. It introduces kernel switching ridge regression, an ML method. The book argues that the method can make predictions from multiple “regimes of dataset” and “can overcome the unstable solution and the curse of dimensionality”. It describes sentiment analysis in predicting stock return volatilities. The book explores some important concepts and ML algorithms, and applications of machine learning techniques in the fields of economics and finance. It focuses on the use of ML and artificial intelligence (AI) in financial services industry.

Druh

C - Kapitola v odborné knize

CEP obor

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OECD FORD obor

50206 - Finance

Projekt

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Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2021

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název knihy nebo sborníku

Essentials of Machine Learning in Finance and Accounting

ISBN

978-0-367-48083-7

Počet stran výsledku

5

Strana od-do

1-5

Počet stran knihy

258

Název nakladatele

Taylor &amp; Francis Ltd.

Místo vydání

Abingdon

Kód UT WoS kapitoly

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