SZodixStudyAcademic Library

Shelves Open access

Study · an open academic library·Metadata from OpenAlex (CC0)·Shelves·OpenAlex metadata, de-duplicated

Noncausal Autoregressive Model in Application to Bitcoin/USD Exchange Rates · Study

ChapterShelves

ChapterNoncausal Autoregressive Model in Application to Bitcoin/USD Exchange Rates

Andrew Hencic2014

Chapter2014

Noncausal Autoregressive Model in Application to Bitcoin/USD Exchange Rates

Andrew Hencic · Christian Gouriéroux

93 citations·0/0 files stored·Studies in computational intelligence

No readable copy stored yet — this record is metadata only.

No open-access location is known for this record yet.

Literature note Cite in a project Citation map

Stock Market Forecasting Methods Financial Risk and Volatility Modeling Complex Systems and Time Series Analysis

Abstract

No abstract was published for this record.

Paper brief

Loading…

Cite this work

Citation unavailable for this work.

BibTeX RIS CSL-JSON

No public copy is stored for this record, so only the metadata is cited.

Citations in this library

Citation map →

Stored only when both papers are in the corpus — 93 citations exist upstream.

References

1961Rational Expectations and the Theory of Price Movements 1982Bubbles, Rational Expectations and Financial Markets 2009EXPLOSIVE BEHAVIOR IN THE 1990s NASDAQ: WHEN DID EXUBERANCE ESCALATE ASSET VALUES?*1991Pitfalls in Testing for Explosive Bubbles in Asset Prices 1979Speculative bubbles, crashes and rational expectations 2001Asset Pricing under Asymmetric Information 1985Limit Theory for Moving Averages of Random Variables with Regularly Varying Tail Probabilities 2011Testing for Multiple Bubbles

Cited by

2019Modelling the dynamics of Bitcoin and Litecoin: GARCH versus stochastic volatility models 2021Forecasting cryptocurrency volatility 2019Detecting bubbles in Bitcoin price dynamics via market exuberance 2021Forecasting Bitcoin with technical analysis: A not-so-random forest?2017Modelling Crypto-Currencies Financial Time-Series 2020ETH analysis and predictions utilizing deep learning

Related works

Explore the map →

Papers that cite the same references — the relational fallback while embeddings are still backfilling.

2013Detecting bubbles in Hong Kong residential property marketarticle · 5 shared references 2015Episodes of Exuberance in Housing Markets: In Search of the Smoking Gunarticle · 5 shared references 2016When Will Occur the Crude Oil Bubbles?article · 5 shared references 2020Do crude oil price bubbles occur?article · 5 shared references 2018Does Bitcoin bubble burst?article · 5 shared references 2017TESTING FOR SPECULATIVE BUBBLES USING SPOT AND FORWARD PRICESarticle · 5 shared references

Details

Year2014

Typechapter

Published2014-12-15

VenueStudies in computational intelligence

ISSN-L1860-949X

Languageen

Citations93

Files0 public / 0

ShelfStock Market Forecasting Methods

Identifiers

doi10.1007/978-3-319-13449-9_2

openalex_workW214620148

Links

Imported from OpenAlex (CC0) — nothing here is generated.

2021Forecasting the Volatility of the Cryptocurrency Market by GARCH and Stochastic Volatility

2019MIXED CAUSAL-NONCAUSAL AR PROCESSES AND THE MODELLING OF EXPLOSIVE BUBBLES