On the inefficiency of Bitcoin

By Saralees Nadarajah, Jeffrey Chu. 2017

497 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Information Systems

View Paper: https://www.semanticscholar.org/paper/c5bb74650eebdfdd8fcc52129a30afb49af4261c

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Citations in the corpus

An application of extreme value theory to cryptocurrencies (2018, unknown): “For this reason, a lot of academic research has been conducted on Bitcoin (see, e.g., Cheah and Fry, 2015; Dyhrberg, 2016; Urquhart, 2016, 2017; Bariviera, 2017; Katsiampa, 2017; Nadarajah and Chu, 2017).”
Testing for Bubbles in Cryptocurrencies with Time-Varying Volatility (2018, unknown): “, the bootstrap p-value is smaller than a nominal significance level, then it is possible to estimate the timings of the bubble and its collapse, if it occurs, following the procedure of Phillips et al.(2011). In particular, they consider the time series of sequential Dickey-Fuller statistics DFr, a”
A three-factor pricing model for cryptocurrencies (2020, result): “This finding has been supported in the literature by Nadarajah and Chu (2017), Tiwari et al (2018) amongst others.”
Does Sentiment Impact Cryptocurrency? (2021, background): “Many studies have found the cryptocurrency market to be inefficient (Urquhart 2016; Nadarajah and Chu 2017).”
Does economic policy uncertainty predict the Bitcoin returns? An empirical investigation (2018, unknown): “Using the Bitcoin returns, Nadarajah and Chu (2017) show that the efficient market hypothesis is not valid.”
Optimal vs naïve diversification in cryptocurrencies (2018, background): “…of cryptocurrencies, documenting bubbles in Bitcoin (Cheah and Fry 2015; Corbet et al 2017), the market efficiency of Bitcoin (Urquhart 2016; Nadarajah and Chu 2017; Tiwari et al 2017; Khuntia and Pattanayak 2018), the hedging and diversification benefits of Bitcoin (Bouri et al 2017a;…”
The economic value of Bitcoin: A portfolio analysis of currencies, gold, oil and stocks (2019, unknown): “, 2018; Symitsi and Chalvatzis, 2018), and market inefficiencies of cryptocurrencies (e.g., Urquhart, 2016; Nadarajah and Chu, 2017).”
Statistical properties and multifractality of Bitcoin (2017, methodology): “On the other hand, by analyzing a power transformed Bitcoin returns, Ref.[9] claims that the transformed Bitcoin returns satisfy the efficient market hypothesis.”