In-Sample and Out-of-Sample Predictability of Cryptocurrency Returns
| Autor: | Kyungjin Park, Hojin Lee |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2023 |
| Předmět: | |
| Zdroj: | East Asian Economic Review, Vol 27, Iss 3, Pp 213-242 (2023) |
| Druh dokumentu: | article |
| ISSN: | 2508-1640 2508-1667 |
| DOI: | 10.11644/KIEP.EAER.2023.27.3.423 |
| Popis: | This paper investigates whether the price of cryptocurrency is determined by the US dollar index, the price of investment assets such gold and oil, and the implied volatility of the KOSPI. Overall, the returns on cryptocurrencies are best predicted by the trading volume of the cryptocurrency both in-sample and out-of-sample. The estimates of gold and the dollar index are negative in the return prediction, though they are not significant. The dollar index, gold, and the cryptocurrencies seem to share characteristics which hedging instruments have in common. When investors take notice of the imminent market risks, they increase the demand for one of these assets and thereby increase the returns on the asset. The most notable result in the out-of-sample predictability is the predictability of the returns on value-weighted portfolio by gold. The empirical results show that the restricted model fails to encompass the unrestricted model. Therefore, the unrestricted model is significant in improving out-of-sample predictability of the portfolio returns using gold. From the empirical analyses, we can conclude that in-sample predictability cannot guarantee out-of-sample predictability and vice versa. This may shed light on the disparate results between in-sample and out-of-sample predictability in a large body of previous literature. |
| Databáze: | Directory of Open Access Journals |
| Externí odkaz: |
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