Candlestick Forecasting for Investments: Applications, Models and Properties - Brossura

Xie, Haibin; Fan, Kuikui; Wang, Shouyang

 
9780367703394: Candlestick Forecasting for Investments: Applications, Models and Properties
Brossura
ISBN 10: 0367703394 ISBN 13: 9780367703394
Casa editrice: Routledge, 2022

Sinossi

Candlestick charts are often used in speculative markets to describe and forecast asset price movements. This book is the first of its kind to investigate candlestick charts and their statistical properties. It provides an empirical evaluation of candlestick forecasting. The book proposes a novel technique to obtain the statistical properties of candlestick charts. The technique, which is known as the range decomposition technique, shows how security price is approximately logged into two ranges, i.e. technical range and Parkinson range.

Through decomposition-based modeling techniques and empirical datasets, the book investigates the power of, and establishes the statistical foundation of, candlestick forecasting.

Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.

Informazioni sull?autore

Haibin Xie is Associate Professor at the School of Banking and Finance, University of International Business and Economics.

Kuikui Fan is affiliated with the School of Statistics, Capital University of Economics and Business.

Shouyang Wang is Professor at the Academy of Mathematics and Systems Science, Chinese Academy of Sciences.

Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.

Editore
Routledge
Data di pubblicazione
2022
Lingua
Inglese
ISBN 10 
0367703394
ISBN 13 
9780367703394
Rilegatura
Copertina flessibile
Numero edizione
1
Numero di pagine
116
Contatto del produttore
non disponibile
Persona responsabile
Yeepin GmbH
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Altre edizioni note dello stesso titolo

9780367703370: Candlestick Forecasting for Investments: Applications, Models and Properties

Edizione in evidenza

ISBN 10:  0367703378 ISBN 13:  9780367703370
Casa editrice: Routledge, 2021
Rilegato