Peter Reinhard Hansen, Chan Kim, Wade Kimbrough
arXiv 24 Sep 2021 · Finance — Trading · publishedJournal of Financial Econometrics (2022) · 29 citations (OpenAlex)
arXiv:2109.12142 · PDF · DOI · OpenAlex · Extracted main text
We study recurrent patterns in volatility and volume for major cryptocurrencies, Bitcoin and Ether, using data from two centralized exchanges (Coinbase Pro and Binance) and a decentralized exchange (Uniswap V2). We find systematic patterns in both volatility and volume across day-of-the-week, hour-of-the-day, and within the hour. These patterns have grown stronger over the years and can be related to algorithmic trading and funding times in futures markets. We also document that price formation mainly takes place on the centralized exchanges while price adjustments on the decentralized exchanges can be sluggish.
appendix boundary found by appendix_command · 86% of the source is main text. Read the extracted text to check this.
The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | Andersen \ Bollerslev (1998) `Deutsche Mark-Dollar Volatility: Intraday Activity Patterns, Macroeconomic Announcements, and Longer Run Dependencies', Journal… | 0.644 | 2 | 2 | 100% |
| 2 | Hansen, Huang \ Shek (2012) `Realized GARCH: A joint model of returns and realized measures of volatility', Journal of Applied Econometrics 27, 877–906 | 0.644 | 2 | 2 | 100% |
| 3 | Wang, Liu \ Hsu (2020) `Time-of-day periodicities of trading volume and volatility in bitcoin exchange: Does the stock market matter?', Finance Researc… | 0.644 | 2 | 2 | 100% |
| 4 | Hansen \ Lunde (2005) `A forecast comparison of volatility models: Does anything beat a GARCH(1,1)?', Journal of Applied Econometrics 20, 873–889 | 0.585 | 3 | 1 | 100% |
| 5 | Narayanan, Bonneau, Felten, Miller \ Goldfeder (2016) Bitcoin and cryptocurrency technologies: a comprehensive introduction, Princeton University Press, New Jersey | 0.511 | 2 | 1 | 100% |
| 6 | Aleti \ Mizrach (2021) `Bitcoin spot and future market microstructure', Journal of Futures Markets 41, 194–255 | 0.405 | 1 | 1 | 100% |
| 7 | Alizadeh, Brandt \ Diebold (2002) `Range-based estimation of stochastic volatility models', Journal of Finance 57, 1047–1092 | 0.405 | 1 | 1 | 100% |
| 8 | Amihud (2002) `Illiquidity and stock returns: cross-section and time-series effects', Journal of Financial Markets 5, 31–56 | 0.405 | 1 | 1 | 100% |
| 9 | Andersen \ Bollerslev (1997) `Intraday periodicity and volatility persistence in financial markets', Journal of Empirical Finance 4(2-3), 115–158 | 0.405 | 1 | 1 | 100% |
| 10 | Andersen, Dobrev \ Schaumburg (2012) `Jump-robust volatility estimation using nearest neighbor truncation', Journal of Econometrics 169, 75–93 | 0.405 | 1 | 1 | 100% |
Showing the top 10 of 30 scored citations.
arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.
| Citing paper | Intensity | Mentions | Sections | |
|---|---|---|---|---|
| 1 | To be or not to be: Roughness or long memory in volatility? | 0.405 | 1 | 1 |
| 2 | 2607.13916 | 0.405 | 1 | 1 |