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AI and Financial Markets



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Autore: Hamori Shigeyuki Visualizza persona
Titolo: AI and Financial Markets Visualizza cluster
Pubblicazione: Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2020
Descrizione fisica: 1 electronic resource (230 p.)
Soggetto topico: Economics, finance, business & management
Soggetto non controllato: algorithmic trading
Stop Loss
Turtle
ATR
community finances
fiscal flexibility
individualized financial arrangements
sustainable financial services
price momentum
hidden markov model
asset allocation
blockchain
BlockCloud
Artificial Intelligence
consensus algorithms
exchange rates
fundamentals
prediction
random forest
support vector machine
neural network
deep reinforcement learning
financial market simulation
agent based simulation
artificial market
simulation
CAR regulation
portfolio
contract for difference
CfD
reinforcement learning
RL
neural networks
long short-term memory
LSTM
Q-learning
deep learning
uncertainty
economic policy
text mining
topic model
yield curve
term structure of interest rates
machine learning
autoencoder
interpretability
Persona (resp. second.): TakiguchiTetsuya
HamoriShigeyuki
Sommario/riassunto: Artificial intelligence (AI) is regarded as the science and technology for producing an intelligent machine, particularly, an intelligent computer program. Machine learning is an approach to realizing AI comprising a collection of statistical algorithms, of which deep learning is one such example. Due to the rapid development of computer technology, AI has been actively explored for a variety of academic and practical purposes in the context of financial markets. This book focuses on the broad topic of “AI and Financial Markets”, and includes novel research associated with this topic. The book includes contributions on the application of machine learning, agent-based artificial market simulation, and other related skills to the analysis of various aspects of financial markets.
Titolo autorizzato: AI and Financial Markets  Visualizza cluster
Formato: Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione: Inglese
Record Nr.: 9910557584903321
Lo trovi qui: Univ. Federico II
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