Jeffrey Chu
Economics and Econometrics · 2017–2019
A researcher in the Science corpus: 3 papers; trusts 16 researchers and is trusted by 10 researchers here, as inferred from the citation graph.
Subfields
- Economics and Econometrics — 39 citations into it; #6,568 of 23,481 by trust here, #5,178 by citations
- Finance — 27 citations into it; #7,942 of 10,518 by trust here, #6,419 by citations
- Information Systems — 19 citations into it; #2,637 of 8,771 by trust here, #1,867 by citations
Whom Jeffrey Chu trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Tim Bollerslev
- Michael Mcaleer
- Paraskevi Katsiampa
- Hirotugu Akaike
- Peter F. CHRISTOFFERSENti
- Andrew Urquhart
- Ladislav Kristoufek
- Jae Hyun Kim
- S. Ling
- Juan-Carlos Escanciano
Who trusts Jeffrey Chu overall
- Paraskevi Katsiampa
- Tony Klein
- Tetsuya Takaishi
- T. Walther
- Dehua Shen
- Andrew Urquhart
- Shaen Corbet
- Hiền Phạm Thu
- Pengfei Wang
- Brian M. Lucey
Papers from Jeffrey Chu's perspective
Ordered by how strongly the researchers Jeffrey Chu trusts endorse each paper. Same corpus, a different order for every researcher.
- Generalized autoregressive conditional heteroskedasticity
- ASYMPTOTIC THEORY FOR A VECTOR ARMA-GARCH MODEL (Econometric Theory)
- BitCoin meets Google Trends and Wikipedia: Quantifying the relationship between phenomena of the Internet era (Scientific Reports)
- Bitcoin: A Peer-to-Peer Electronic Cash System
- What Are the Main Drivers of the Bitcoin Price? Evidence from Wavelet Coherence Analysis (PLoS ONE)
- Estimating the Dimension of a Model
- Crypto-currency bubbles: an application of the Phillips–Shi–Yu (2013) methodology on Mt. Gox bitcoin prices
- Volatility estimation for Bitcoin: A comparison of GARCH models
- A test for independence based on the correlation dimension
- A new look at the statistical model identification
Their papers
- GARCH Modelling of Cryptocurrencies (2017) — 330 citations
- On the inefficiency of Bitcoin (2017) — 497 citations
- The adaptive market hypothesis in the high frequency cryptocurrency market (2019) — 121 citations