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This paper reports evidence of intraday return predictability, consisting of both intraday momentum and reversal, in the cryptocurrency market. Using high-frequency price data on Bitcoin from March 3, 2013, to May 31, 2020, it shows that the patterns of intraday return predictability change in...
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We analyze the predictability of the bitcoin market across prediction horizons ranging from 1 to 60 min. In doing so, we test various machine learning models and find that, while all models outperform a random classifier, recurrent neural networks and gradient boosting classifiers are especially...
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In recent years, Bitcoin has received substantial attention as potentially high-earning investment. However, its volatile price movement exhibits great financial risks. Therefore, how to accurately predict and capture changing trends in the Bitcoin market is of substantial importance to...
Persistent link: https://www.econbiz.de/10013170254
With the volume of activities associated with trading, it has become a very tedious task. The advent of the algorithmic trading has brought with it some positive change such as reduced latency and increase in liquidity in the Financial Market. The Algorithmic Trading also came with some high...
Persistent link: https://www.econbiz.de/10012833070
Cryptocurrencies have entered the economy as alternative money, as speculation objects, and as utility tokens for innovative service-platforms. Predictions are numerous. While some predict that their value will skyrocket, others predict their collapse. Some predict them to completely transform...
Persistent link: https://www.econbiz.de/10012907787
The following study investigates whether there exist factors that have a degree of predictability when predicting the returns of cryptocurrencies. Using a daily dataset on 11 cryptocurrencies, this paper begins with analysing the role of Momentum Value and Carry in this market. It seems that...
Persistent link: https://www.econbiz.de/10012908122
In the modern era, researchers are predicting prices of various kinds of cryptocurrency to understand their trend in the sector of finance. In this paper, we focus on price prediction of cryptocurrencies based on a period, i.e., for the year 2013 to 2018. From our research, we have identified...
Persistent link: https://www.econbiz.de/10012889320