There has been a prevalent belief that the value of Bitcoin is directly impacted by the performance of the U.S. dollar in relation to other major global currencies, as measured by the Dollar Strength Index (DXY). According to this belief, when the DXY index declines, Bitcoin experiences a positive effect, and vice versa. For instance, between January 2017 and August 2017, the DXY index dropped from 103.0 to a low of 92.6, while Bitcoin rallied from $1,000 to $4,930 in the same period. This has led some analysts to argue that there is enough evidence to justify a potential bull run similar to the one observed in 2016-2017. However, it is important to critically examine this claim and determine whether there is substantial evidence to support it.

Traders and influencers often caution about the negative correlation between Bitcoin and the DXY index, suggesting that a reversal in the DXY’s performance would likely push the price of Bitcoin higher. Investment research by @GameofTrades_ presented a chart showing this pattern in early 2023, with similarities to previous occurrences in May. Additionally, technical analyst el_crypto_prof highlighted a bearish “Gaussian Channel” change on the DXY chart, which matched two previous bull runs for Bitcoin and altcoins. It is true that historical data indicates an inverse relationship between Bitcoin and the DXY index, but it is crucial to note that this inverse correlation has never lasted more than 7 weeks.

Despite the seemingly strong inverse relationship between Bitcoin and the DXY index, it is important to understand the limitations of correlation analysis. The correlation indicator ranges from -100% to 100%, with -100% indicating opposite movements and 100% indicating lockstep movement. A reading close to 0% represents a lack of correlation between the two assets. While the metric has been negative for 81% of the past 670 days, indicating an inverse trend between DXY and Bitcoin, it is not statistically coherent to claim that Bitcoin has an inverse correlation to the DXY index. This is because a correlation lower than -50% has only occurred for less than a third of the days since September 2021, with the longest-ever period lasting 47 days. Therefore, it is essential to be cautious when making claims about the strength and consistency of the correlation between Bitcoin and the DXY index.

The Role of Unique Events

Furthermore, the correlation between Bitcoin and the DXY index can be influenced by unique events that are solely relevant to the cryptocurrency market. For example, the launch of the first U.S. Bitcoin futures exchange-traded fund in October 2021 could have distorted the correlation metric. However, it is crucial to remember that correlation does not imply causation. Even if there is a correlation between the DXY’s positive performance and the price of Bitcoin during a specific period, it does not necessarily mean that one directly affects the other. Other factors, such as news, macroeconomic data, and geopolitical events, can have immediate and lasting effects on the price of Bitcoin. The recent 38% loss in Bitcoin’s value in just nine days on June 8, 2022, serves as a testament to the vulnerability of the cryptocurrency market to external factors. Thus, it is essential to consider a longer time frame and a broader range of factors when assessing the potential impact of the DXY on Bitcoin’s price.

It is important to approach claims about an inverse correlation between Bitcoin and the DXY index with skepticism. While there have been instances where an inverse correlation occurred alongside a cryptocurrency bull run, it is vital to consider the multiple instances of positive correlation and gaps between the price actions of both assets. Cherry-picking a few examples of inverse correlation without taking into account the overall trend and the influence of unique events is not sufficient evidence to support the claim of a bull run similar to 2016-2017. Therefore, it is crucial to critically analyze the data and refrain from making definitive conclusions based solely on correlation analysis.

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