Bing Anderson
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3 publications
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658 downloads
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709 views
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Time-varying real estate prices and urban household consumption − an empirical study on selected cities in China
Investment Management and Financial Innovations Volume 10, 2013 Issue #4
Views: 502 Downloads: 143 TO CITE -
A tick-by-tick level measurement of the lead-lag duration between cryptocurrencies: The case of Bitcoin versus Cardano
Investment Management and Financial Innovations Volume 20, 2023 Issue #1 pp. 174-183
Views: 620 Downloads: 353 TO CITE АНОТАЦІЯAccording to past research utilizing Bitcoin and other cryptocurrencies, Bitcoin has been shown to lead most other cryptocurrencies in terms of price movements. However, existing studies tend to focus on the direction of the lead-lag relationship instead of the duration of the lead-lag time. Furthermore, they are handicapped by the reliance on low-frequency data such as daily prices. This paper showcases the measurement of the lead-lag duration between cryptocurrencies using ultra-high-frequency tick-by-tick data, via the pair of Bitcoin and Cardano. Tick-by-tick data bring unique challenges in terms of methodology. The vast majority of time series econometrics methods are designed for use with data collected at regularly spaced time intervals, such as every hour, every day, etc. Tick-by-tick data, on the other hand, are not synchronized in any way and do not arrive at consistently spaced time intervals. Consequently, an asynchronous data integration methodology is utilized to estimate the Bitcoin price lead over Cardano price for each month beginning in January 2019 and continuing through May 2021. The length of the lead time ranges from 16 seconds to 118 seconds, with an average of around 57 seconds. Throughout the study period, the lengths of the lead time manifest a general trend of decline, which is shown to be statistically significant via non-parametric tests. Testing of seasonal patterns turns out to be not significant. The methodology and the findings of this paper have implications for both academics and practitioners, for example, when studying and implementing statistical arbitrage with cryptocurrencies.