Cryptocurrencies have quickly become an integral component of global economics. While cryptocurrencies provide numerous benefits, their price fluctuations can be unpredictable. In this article we use machine learning techniques to predict cryptocurrency prices.
Results indicate the existence of herding and recency biases in the cryptocurrency market, as well as nonlinear, environment-dependent relationships between these biases and market behavior.
Ripple
When it comes to cryptocurrency markets, the most prominent coins tend to get all the spotlight. Although this may lead investors to overlook other cryptos, Ripple could benefit.
Ripple is a network that facilitates cross-border payments and currency exchange, using its native cryptocurrency XRP for transactions. One of the oldest cryptocurrency platforms available, it has established partnerships with several large financial institutions.
At the time of Ripple’s creation, an initial set of XRP coins were pre-mined and are slowly released to the public. Unlike Bitcoin which must first be mined and distributed through complex algorithms before it can be used directly for transactions, making XRP an attractive investment choice for those wanting to avoid its volatility.
ETH
Cryptocurrency prices have experienced considerable fluctuations recently, yet some analysts expect them to stabilize and rebound by May. Others remain more wary, noting that macro conditions remain challenging.
Traders can utilize trendlines to identify support and resistance levels on charts. These lines connect a cryptocurrency’s lowest and second-lowest lows; levels that touch these lines serve as support.
Ripple markets itself as a cross-border payments solution for banks and has conducted trials with various financial institutions. Its technology aims to address high-volume, low-value transactions which are costly for banks. But Ripple CEO Brad Garlinghouse remains cautious, saying the company is more of a long-term play and projecting that XRP’s price may reach $1 by 2025.
LTC
Litecoin stands out from other cryptos by having a low transaction fee and being popular among traders, which could explain its continued expansion in the near future. Furthermore, Litecoin’s price volatility is lower than Bitcoin’s.
Gurdgiev and O’Loughlin (2020) offer evidence that cryptocurrency prices do not follow mean-reversion, yet exhibit long-range memory. Their study uses data on ten of the most popular cryptocurrencies along with proxy measures of fear and uncertainty to test this hypothesis; their analysis finds that cryptocurrency returns are significantly more persistent than equities, suggesting market inefficiency.
Crypto markets can be highly unpredictable, making it important to stay abreast of any latest developments in this space. Cryptoasset investing is highly risky and not suitable for everyone – in certain EU countries there is no regulatory oversight and consumer protection; additionally, taxes may apply on profits made.
DSH
Ripple’s XRP price has hit $1.24 before, though this amount has rarely been exceeded throughout 2018. Instead, its value has mostly stayed below this threshold for much of this year.
Many in the crypto community believe Ripple will thrive given its strong backing by banks and impressive client list. But its future ultimately hinges on its court case with SEC; should Ripple win this argument, its price may skyrocket considerably.
Ripple’s technology is more acceptable to regulators than Bitcoin’s unbridled spirit, enabling it to survive during periods of market instability more successfully. Furthermore, its instant payment processing has earned Ripple praise, making it an attractive cryptocurrency option for banks wishing to transfer funds quickly.
BCH
BCH has experienced difficulty recently. Its price has decreased over the last several months and it hasn’t received as much media coverage than Ripple due to their lawsuit with the SEC.
Bitcoin Cash, a hard fork of Bitcoin with its own mining community, has proven popular as an option for international transactions due to its low fees and fast transaction times, yet remains susceptible to scalability issues as its use becomes more widespread resulting in increased transaction numbers which in turn could increase prices over time.
Technical analysis allows traders to predict future prices for an asset by using historical data and charts as indicators of trend changes. This more logical approach to trading than fundamental analysis.
