چکیده:
This article, had been analyzed the persistence in cryptocurrency market. At the beginning of the process, the autocorrelation of the time series data of four cryptocurrencies Bitcoin, Light Coin, Ripple and Ethereum during the period 2017 to 2020 has been studied. The data of this research are obtained daily from the investing database showed significant autocorrelation among cryptocurrencies. Long-term memory methods such as R/S analysis and fraction integration are used for analysis of market persistence. The results of this study showed that this market is persistence. That means there is a positive correlation between past and future values, and its level and value change over time. These results provide evidence for market inefficiency. Using the pair trading algorithm and redefining it, profit has been made and the results show a return of 1463% in 2 years from 2018 to 2020. The use of trading algorithms based on market memory and cointegration has the potential to generate profits, and the development of models and algorithms can help investors to generate returns and on the other hand lead to more efficient market in the long term.
خلاصه ماشینی:
Table 6 The R/S Hurst statistic level (Source: Research findings) (Refer to page image) Following the stability function achieved in the studied cryptocurrencies and using the obtained results, a model has been designed to practically utilize the proven stability in the cryptocurrency market, employing a pairs trading algorithm based on the co-integration method.
Table 2: First-order autoregression of Bitcoin cryptocurrency (Source: Research findings) (Refer to page image) (Refer to page image) Chart 1: Pairs trading algorithm (Source: Dastouri et al.
1397) Empirical results of using the pairs trading algorithm By using the data of all cryptocurrencies considered in this research, the logarithmic price movements and the distribution of daily return data have been examined.
This reveals the necessity of testing long-term memory and subsequently the optimal use of trading tools such as trading algorithms based on co-integration, providing the possibility to develop investment tools suitable for the characteristics of the cryptocurrency market.
The use of trading algorithms based on market memory and co-integration has been able to create profit, and the development of models and algorithms can assist investors in generating returns and, on the other hand, lead to market efficiency in the long term.
Market memory, cryptocurrency, pair trading, co-integration 1-Financial Management Department, Bandar Abbas Branch, Islamic Azad University, Bandar Abbas, Iran.
In a summary of this research process, it can be stated that the use of trading algorithms based on market memory and co-integration has been able to create profit, and the development of models and algorithms can assist investors in generating returns and, on the other hand, lead to increased market efficiency in the long term.
(
, 
, 
)
