泡沫的局部鞅理论在加密货币中的应用

IF 0.5 Q4 BUSINESS, FINANCE

International Journal of Theoretical and Applied Finance Pub Date : 2022-04-08 DOI:10.1142/s0219024922500133

SOON HYEOK CHOI, R. Jarrow

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引用次数: 2

摘要

使用泡沫的局部鞅理论，加密货币提供了一个自然的环境来测试价格泡沫的存在，因为加密货币没有现金流。使用稳健的统计算法，我们测试了八种加密货币的价格泡沫，比特币(BTC)，莱特币(LTC)，以太坊(ETH)， Ripple (XRP)，比特币现金(BCH)， EOS (EOS)，门罗币(XMR)和Zcash (ZEC)，从2019年1月1日到2019年7月17日。统计测试首先估计加密货币的波动性作为价格水平的函数。然后，使用幂函数将这些估计值外推到正实线上。最后，这些幂函数是对价格泡沫的一系列假设检验的基础，这些假设检验控制了第一类和第二类误差。八种货币中有五种(BTC, BCH, EOS, XMR, ZEC)表现出价格泡沫，LTC没有，ETH和XRP的证据尚无定论。这篇论文为加密货币泡沫的普遍存在提供了强有力的证据。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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APPLYING THE LOCAL MARTINGALE THEORY OF BUBBLES TO CRYPTOCURRENCIES

Cryptocurrencies provide a natural setting to test for the existence of price bubbles using the local martingale theory of bubbles because cryptocurrencies have no cash flows. Using a robust statistical algorithm, we test for price bubbles in eight cryptocurrencies, Bitcoin (BTC), Litecoin (LTC), Ethereum (ETH), Ripple (XRP), Bitcoin Cash (BCH), EOS (EOS), Monero (XMR), and Zcash (ZEC), from 1 January 2019 to 17 July 2019. The statistical test first estimates the cryptocurrencies’ volatilities as a function of the price level. Then, these estimates are extrapolated over the positive real line using power functions. Finally, these power functions underly a sequence of hypothesis tests for price bubbles that control for both Type I and Type II errors. Five of the eight currencies (BTC, BCH, EOS, XMR, ZEC) exhibit price bubbles, LTC does not, and the evidence for ETH and XRP is inconclusive. The paper provides strong evidence for the prevalence of bubbles in cryptocurrencies.

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来源期刊

International Journal of Theoretical and Applied Finance BUSINESS, FINANCE-

CiteScore

1.10

自引率

20.00%

发文量

期刊介绍： The shift of the financial market towards the general use of advanced mathematical methods has led to the introduction of state-of-the-art quantitative tools into the world of finance. The International Journal of Theoretical and Applied Finance (IJTAF) brings together international experts involved in the mathematical modelling of financial instruments as well as the application of these models to global financial markets. The development of complex financial products has led to new challenges to the regulatory bodies. Financial instruments that have been designed to serve the needs of the mature capitals market need to be adapted for application in the emerging markets.