The witching week of herding on bitcoin exchanges

This paper analyses the herding behaviour among exchanges around the expiration of bitcoin futures traded on the Chicago Mercantile Exchange (CME). The database extends from December 2017 to October 2020, taking as a reference the main exchanges that trade bitcoin (Binance, Bitfinex, Bitstamp, Coinbase, itBit, Kraken, and Gemini) and using hourly closing prices and trading volumes in bitcoin and US dollars. Adapting the proposal of Chang, Cheng and Khorana (2000) (CCK) to test conditional herding, we obtain results that indicate that the herding effect is significant during the week before expiration. After expiration, the herding effect lasts for a few hours and disappears. Information overload originating, among other causes, from sophisticated investors’ strategies may generate this mimetic behaviour. The results show the relevance of intraday data applied to specific events such as expiration since the unconditional analysis shows, in general, anti-herding behaviour throughout the period of study

Is there an expiration effect in the bitcoin market?

This paper studies the monthly expiration effect in the bitcoin markets. The emergence of trading in bitcoin futures in regulated markets is an ideal occasion to test this effect on an asset with singular characteristics. Our results with intraday data show that around the time of maturity there are significant changes in the trading volume, volatility and return of bitcoin, an asset that is traded in many exchanges simultaneously. Therefore, there is a clear expiration effect related to bitcoin futures. The closer to the expiration time (shortly beforehand or afterwards), the more intense these effects are. However, in spite of these general results, the expiration effect is not homogeneous across exchanges and depends on the characteristics of the futures contract in question. Robustness tests are also applied to confirm the results. The increasing participation of institutional investors is consistent with our findings, particularly in relation to the expiration effects of cash-settled futures, as these contracts are more appealing for sophisticated investors who could be interested in arbitrage or speculative processes

Is there an expiration effect in the bitcoin market?

This paper studies the monthly expiration effect in the bitcoin markets. The emergence of trading in bitcoin futures in regulated markets is an ideal occasion to test this effect on an asset with singular characteristics. Our results with intraday data show that around the time of maturity there are significant changes in the trading volume, volatility and return of bitcoin, an asset that is traded in many exchanges simultaneously. Therefore, there is a clear expiration effect related to bitcoin futures. The closer to the expiration time (shortly beforehand or afterwards), the more intense these effects are. However, in spite of these general results, the expiration effect is not homogeneous across exchanges and depends on the characteristics of the futures contract in question. Robustness tests are also applied to confirm the results. The increasing participation of institutional investors is consistent with our findings, particularly in relation to the expiration effects of cash-settled futures, as these contracts are more appealing for sophisticated investors who could be interested in arbitrage or speculative processes.Grant PID2019-104304GB-I00 funded by MCIN/AEI /10.13039/501100011033 https://doi.org/10.13039/501100011033 ; Grant RTI2018-093483-B-I00 funded by MCIN/AEI /10.13039/501100011033 https://doi.org/10.13039/501100011033 and by ERDF A way of making Europe; Grant S11_20R: Cembe funded by the Government of Aragon and ERDF

The witching week of herding on bitcoin exchanges

This paper analyses the herding behaviour among exchanges around the expiration of bitcoin futures traded on the Chicago Mercantile Exchange (CME). The database extends from December 2017 to October 2020, taking as a reference the main exchanges that trade bitcoin (Binance, Bitfinex, Bitstamp, Coinbase, itBit, Kraken, and Gemini) and using hourly closing prices and trading volumes in bitcoin and US dollars. Adapting the proposal of Chang, Cheng and Khorana (2000) (CCK) to test conditional herding, we obtain results that indicate that the herding effect is significant during the week before expiration. After expiration, the herding effect lasts for a few hours and disappears. Information overload originating, among other causes, from sophisticated investors¿ strategies may generate this mimetic behaviour. The results show the relevance of intraday data applied to specific events such as expiration since the unconditional analysis shows, in general, anti-herding behaviour throughout the period of study.Grant PID2019-104304GB-I00 funded by MCIN/AEI/10.13039/501100011033 https://doi.org/10.13039/501100011033. Grant RTI2018-093483-B-I00 funded by MCIN/AEI/10.13039/501100011033 https://doi.org/10.13039/501100011033 and by ERDF A way of making Europe. Grant S11_20R: Cembe funded by the Government of Aragon and ERDF

A Biophysical Model of the Mitochondrial ATP-Mg/Pi Carrier

Mitochondrial adenine nucleotide (AdN) content is regulated through the Ca2+-activated, electroneutral ATP-Mg/Pi carrier (APC). The APC is a protein in the mitochondrial carrier super family that localizes to the inner mitochondrial membrane (IMM). It is known to modulate a number of processes that depend on mitochondrial AdN content, such as gluconeogenesis, protein synthesis, and citrulline synthesis. Despite this critical role, a kinetic model of the underlying mechanism has not been developed and validated. Here, a biophysical model of the APC is developed that is thermodynamically balanced and accurately reproduces a number of reported data sets from isolated rat liver and rat kidney mitochondria. The model is based on an ordered bi-bi mechanism for hetero-exchange of ATP and Pi and also includes homo-exchanges of ATP and Pi to explain both the initial rate and time course data on ATP and Pi transport via the APC. The model invokes seven kinetic parameters regarding the APC mechanism and three parameters related to matrix pH regulation by external Pi. These parameters are estimated based on nineteen independent data curves; the estimated parameters are validated using six additional data curves. The model takes into account the effects of pH, Mg2+ and Ca2+ on ATP and Pi transport via the APC and supports the conclusion that the pH gradient across the IMM serves as the primary driving force for AdN uptake or efflux. Moreover, computer simulations demonstrate that extra-matrix Ca2+ modulates the turnover rate of the APC and not the binding affinity of ATP, as previously suggested.Comment: This paper has been withdrawn by the author due to some incorrect presentation in the results and discussion par