最有看点的互联网金融门户

最有看点的互联网金融门户
全新的互联网金融模式国际资讯

耶鲁大学经济学家开发了密码价格预测系统

8月9日,耶鲁大学的研究人员提出了一个密码价格预测系统。以确定某些市值最大的加密货币的最佳买入机会。

耶鲁大学经济学教授Aleh Tsyvinski和经济学博士候选人Yukun Liu研究了比特币(BTC)、Ripple (XRP)和Ethereum (ETH)的历史价格走势。BTC数据在2011年到2018年之间进行跟踪,XRP和ETH的性能分别在2012年和2015年开始分析。这些经济学家在周一发表的题为《加密货币的风险和回报》的报告中描述了他们的发现。

Tsyvinski和Liu在论文中表示,加密货币对股票、货币和大宗商品等传统资产类别的风险敞口“很低”。该研究还对一些流行的解释提出了质疑,即供应因素(如采矿成本、市盈率或已实现的波动性)对预测加密货币回报行为有用。相反,研究人员断言“加密货币的回报可以由特定于加密货币市场的因素来预测。”

动量效应和投资者关注

经济学家们确定了两个因素来预测加密资产的未来表现。第一种被称为动量效应,这基本上意味着当一种加密货币的价值增加时,它会升得更高。这种趋势更多地适用于比特币,但对Ethereum和Ripple来说,这种趋势“在统计上仍具有重要意义”。为了利用动量效应,专家们建议,如果比特币的价格在前一周上涨超过20%,投资者应该购买它。

第二个强烈影响加密货币的因素是投资者关注的程度,这是加密价格与社交媒体和搜索引擎上加密货币的帖子和查询数量之间的关系。这篇论文解释说,投资者的高度关注预测了比特币未来1-2周的高回报,Ripple的1周的高回报,Ethereum的1- 3周和6周的高回报。

当然,人们必须记住,就像其他资产一样,过去的表现并不能保证未来的回报。也许加密货币会完全改变它的行为,但目前市场认为它不会。

每个投资组合至少应该包括6%的比特币

根据Yales金融专家的说法,比特币应该是投资者投资组合中不可或缺的一部分。对于一个人的投资组合的最优构建,经济学家们认为比特币至少应该占其中的6%。那些对最古老的加密货币不太热心的人应该持有4%的加密货币。然而,无论你在这个问题上的立场如何,BTC应至少占投资者多元化投资组合的1%。

Yale University financial experts have outlined a basic strategy for identifying the best buying opportunities for some of the largest cryptocurrencies by market capitalization.

Yale economics professor Aleh Tsyvinski and economics Ph.D. candidate Yukun Liu, have studied the historical price trends of Bitcoin (BTC), Ripple (XRP) and Ethereum (ETH). The BTC data was tracked between 2011 and 2018, while the XRP and ETH performance was analyzed since their inception in 2012 and 2015, respectively. The economists described their findings in a report titled “Risks and Returns of Cryptocurrency”, published on Monday.

Tsyvinski and Liu say in the paper that cryptocurrencies have “low exposure” to traditional asset classes, such as stock, currencies and commodities. The research also calls into question popular explanations that supply factors such as mining costs, price-to-dividend ratio, or realized volatility are useful for predicting the behavior of cryptocurrency returns. Instead, the researchers assert that “cryptocurrency returns can be predicted by factors which are specific to cryptocurrency markets.”

Momentum effect and investor attention

The economists have identified two factors to predict the crypto assets’ future performance. The first is called the momentum effect, which basically means that when a cryptocurrency increases in value, it will tend to rise even higher. This trend applies to Bitcoin more, but is “still statistically significant” for Ethereum and Ripple. To take advantage of momentum effect, the experts suggest an investor should buy Bitcoin if its value increases more than 20% in the previous week.

The second factor strongly influencing cryptocurrency is the measure of investor attention, which is a correlation between crypto prices and the number of posts and queries for cryptocurrencies on social media and in search engines. High investor attention predicts high future returns over 1-2 week horizons for Bitcoin, a 1-week horizon for Ripple, and 1-, 3-, and 6-week horizons for Ethereum, the paper explains.

“Of course, one has to remember that, as with any other assets, past performance is not a guarantee of future returns. Maybe cryptocurrency will completely change its behavior, but currently the market does not think it will,” Tsyvinski stated in an interview published on Yales’ website.

Every portfolio should include at least 6% Bitcoin

According to the Yale experts, Bitcoin is an essential part of a digital asset investor's holding. In their view, Bitcoin should normally account for at least 6% of a digital asset portfolio, but that those who are less enthusiastic about it could consider having it comprise 4% but at a minimum 1% for diversification purposes.


用微信扫描可以分享至好友和朋友圈

扫描二维码或搜索微信号“iweiyangx”
关注未央网官方微信公众号,获取互联网金融领域前沿资讯。

发表评论

发表评论

您的评论提交后会进行审核,审核通过的留言会展示在下方留言区域,请耐心等待。

评论

您的个人信息不会被公开,请放心填写! 标记为的是必填项

取消

十五国监管者就加密产业监管齐聚日本

Kevin Helm... | 巴比特资讯 7分钟前

反洗钱金融行动特别工作组修改加密货币相关标准

Ana Alexan... | 巴比特资讯 1天前

印度:持有未经政府批准的加密货币或被定为非法

Mark Emem | 巴比特资讯 10-19

全球首个加密货币相关IPO有望在日本进行

GEORGI GEO... | 巴比特资讯 10-16

万事达、VISA将加密货币与ICO纳入“高风险”类别

Helen Part... | 巴比特资讯 10-16

版权所有 © 清华大学五道口金融学院互联网金融实验室 | 京ICP备17044750号-1