Macroeconomic News and Bitcoin prices: A review of the Literature

Macroeconomic News and Bitcoin prices: A review of the Literature


Much debate has been taking place to understand if Bitcoin, and cryptoasset markets more generally, reflects shocks on the macroeconomy or changes in investors’ beliefs about aggregate economic prospects at large. While much research has been focusing on the impact of macroeconomic news on returns on traditional financial assets, to date, the evidence on the response of Bitcoin, and cryptos at large, to macroeconomic shocks and announcements has been quite sparse. The reason is twofold: first, given the relatively short history of Bitcoin, which has created in the aftermath of the great financial crisis, and the relatively uneventful global economic history from 2009 till the outbreak of the COVID-19 crisis, there has not been enough time-series variation in the data to spot sensible correlations on macro level. Second, the conventional wisdom is that Bitcoin does not represent a claim on the state of the economy, at least a priori. For this reason, at least theoretically, there should be no reason for Bitcoin, and cryptos at large, to respond to macroeconomic shocks. To put it differently, Bitcoin should react to unexpected economic changes because these ultimately might affect financing conditions, the cost of capital and leverage, and ultimately investors’ risk aversion. Nevertheless, the question remains if news on macroeconomic conditions, whether anticipated or not, help to predict the dynamics of risk and returns in cryptoasset markets. Understanding this link could help to improve investment decision making processes and create more resilient risk management. In this article we review some of the existing literature on the relationship between macroeconomic news on the dynamics of Bitcoin prices and cryptos more broadly. A particular emphasis is on the effect of macroeconomic announcements, rather than news sentiment and investors’ attention to news.1

News and asset class returns

Over the last few decades, economists began to recognize the importance of impulses and propagation mechanisms for explaining both business cycle fluctuations and the low-frequency dynamics of financial returns. A particular emphasis has been put on unexpected outcomes of scheduled announcements. For example, a higher-than-expected inflation figure during a regular data release, or unscheduled events, for example a sudden shift in monetary policy stance as a response to critical events and/or developments in the macroeconomy or financial markets.1

1 An example is the emergency meetings of the Federal Reserve Bank during the great financial crisis.

The evidence on the effect of macroeconomic announcements on traditional asset classes is rather large. For instance, Watcher and Zhu (2018) provide evidence that a large proportion of the total equity premium, meaning the stock returns in excess of the risk-free rate, mostly materializes on days with macroeconomic announcements, despite the small number of such days. In this respect, the relation between market betas and expected returns is far stronger on announcement days as compared with non-announcement days. Similarly, Gilbert (2011) shows that there exists an empirical relation between stock returns on macroeconomic news announcement days and the future revisions of the released data, although the relationship is asymmetric over the business cycle. 

However, the evidence is not always clear cut, at least when it comes to the equity market. For instance, by focusing on newspaper coverage of macroeconomic news, both at the intensive and the extensive margin, Birz and Lott (2011) shows that news about GDP and unemployment do affect stock returns. While much of the recent literature is on equity markets, a large portion of both theoretical and empirical research has been focusing on other traditional asset classes, such as U.S. futures markets (Evans 2011), options markets (Verousis, ap Gwilym, and Chen 2016), Treasury bond yields (Altavilla, Pagano, and Simonelli 2017), foreign exchange markets (Faust et al. 2007), and S&P ETFs (Scholtus, Van Dijk, and Frijns 2014), to name a few.

However, being a much more recent asset class, the literature on cryptoasset markets is to date quite sparse. Among others, some exceptions are Corbet et al. (2020), Lyócsa et al. (2020), Pyo and Lee (2020) and Aboura (2022). The relatively short history of Bitcoin incentivised the use of ‘’soft information’’, such as media coverage, rather than macroeconomic shocks, which are by construction more scattered and at lower frequency, to identify the effect of macroeconomic news on prices, volatility, and market activity. For instance, Corbet et al. (2020) constructed a sentiment index based on news stories that follow the announcements of four macroeconomic indicators: GDP, unemployment, consumer price index (CPI) and durable goods. They found that increases in positive news after unemployment and durable goods announcements result in a decrease in Bitcoin returns. Conversely, they discovered an increase in the percentage of negative news surrounding these announcements is linked with an increase in Bitcoin returns. News relating to GDP and CPI were not found to have any statistically significant relationship with Bitcoin returns.

Linking macroeconomic news to Bitcoin returns

The conventional wisdom is that the state of the economy is a key indicator used to predict financial returns, especially over a medium to long horizon. This can be rationalised, at least conceptually, simply within the context of an endowment economy with no production: when the economy is in a bad state, consumption decreases, which leads to less earnings/dividends and higher expected returns in the future. The combined effect of lower earnings and higher expected returns depress current prices. This simple logic has been highlighted at least since Campbell and Shiller (1988). As a result, unexpected changes to macroeconomic fundamentals could result in lower returns on risky assets, higher volatility and a higher price of risk, partly driven by changes in risk aversion (see, e.g., Fama and French, 1989).

Although a priori Bitcoin does not represent a claim on the state of the economy, a similar argument that links Bitcoin returns to macroeconomy shocks can nevertheless be made. Assuming Bitcoin is part of the investment set, during economic downturns, or adverse macroeconomic shocks, consumption needs are prioritised over risky investments, that is risk aversion increases. This very simplistic rationale could possibly explain a mechanical inverse relationship between macroeconomic changes and Bitcoin investments, and therefore returns via the price pressure of outflows.

Even though one could argue that perhaps investors do not necessarily sacrifice their holdings over consumption needs, the state of the economy could possibly change the way investors process information. This interesting point has been highlighted by Kacperczyk et al. (2016). In recessions, aggregate risk is significantly higher and, consequently, investors care more about aggregate shocks. In expansions, aggregate risk is significantly lower and, consequently, investors care more about idiosyncratic shocks. This framework implies that the predictive information of economic fundamentals may be linked to the observed state of the business cycle, and therefore to investment decisions in risky assets. That is to say, information, and macroeconomic announcements in particular, becomes most valuable when uncertainty is higher. In recessions, when aggregate risk is higher, investors will allocate their attention more towards aggregate risk. Any shock to aggregate risk could then have a cascade effect on all risky positions, Bitcoin included. That is, risk on/risk off decisions linked to changes in economic fundamentals almost mechanically generates correlation between unexpected macroeconomic news and returns, even within the context of cryptoasset markets.

Some existing empirical evidence

The empirical evidence on the relationship between Bitcoin returns and macroeconomic fundamentals is mostly anecdotal. However, although somewhat mixed, there is some existing evidence in the academic literature. Such evidence is often based on textual analysis, newspapers coverage and soft information instead of hard data and the identification of macroeconomic shocks as typically implemented in macroeconomics and monetary economics more generally. Nevertheless, some interesting evidence emerges. For instance, based on macroeconomic news coverage, Corbet et al. (2020) shows that positive shocks, or that is news which is more positive than expected on unemployment, seems to have a negative correlation with Bitcoin returns. However, news on output growth and inflation seems to have a rather flat relationship. Flat correlation is not unique in the empirical finance literature. For instance, based on a large set of monthly macroeconomic announcements on several key measures, such as inflation, unemployment, retail sales and non-farm payrolls, Muzic and Grzeta (2022) show that positive shocks regarding non-farm payrolls increased Bitcoin log-returns by 0.15% on average, while negative shocks regarding non-farm payrolls did not affect Bitcoin returns. On the other hand, announcements on inflation and core inflation rate, if the realised value is greater than expected, the price of Bitcoin reacts with mixed movements. This is somewhat puzzling and, of course, all of the caveats associated with a small sample size apply. 

Some significant evidence on the relationship between macroeconomic fundamentals and Bitcoin prices can be found in Pyo and Lee (2020). By looking at the Federal Open Market Committee (FOMC) decisions and a series of macroeconomic announcements, they show that the Bitcoin price increased by approximately 0.26% in absence of announcement. In addition, the Bitcoin price increased by approximately 0.96% on the day before the announcement but decreased by 1% on the announcement day. This seems to be consistent with a pre-FOMC announcement drift which has been highlighted in the literature (see, e.g., Lucca and Moench 2015). Instead, the price change after FOMC announcements is negligible and not significant at conventional statistical levels. Perhaps more interestingly, given the existing economic climate, Marmora (2022) shows by looking to a panel of different countries, that an unexpected focus towards inflation in monetary policy announcements tend to increase both attention towards Bitcoin and, as a result, increasing trading volume. Yet, these announcement-induced Bitcoin trading spikes are only significant in countries that are not normally accustomed to inflation risk.

To a large extent, the empirical evidence is mixed and perhaps not as strong as one would wish, especially in comparison to more traditional asset classes such as equities and treasuries. Nevertheless, the results provided in the literature so far point towards an increasing correlation between macroeconomic announcements, especially in relation to monetary policy decisions. In this respect, more solid academic research on this issue will be surely welcome by both policy makers, market participants, and the public at large.


Conventional wisdom posits that the state of the economy is a key indicator to predict financial returns, especially over a medium to long horizon. In principle, this rationale is intimately related to the value of macroeconomic news and announcements and could be applied to crypto assets as well. That is, crypto asset markets could react to macroeconomic announcements and this reaction should be primarily related to the effect of the state of the economy on risk-taking behaviours. However, the existing evidence is mixed and somewhat inconclusive.

While it is understood that macroeconomic news affects risk taking behaviours, and therefore almost mechanically impacts risk-on assets, it is not yet fully clear how macroeconomic news directly affects adoption and growth in the cryptoasset space. To put it differently, why macroeconomic news should impede, or boost, Bitcoin adoption and diffusion is still mostly an unanswered question. A question that perhaps deserves more solid empirical work.


Some of these aspects have been covered in a previous article:


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Altavilla, C., M. Pagano, and S. Simonelli. 2017. “Bank Exposures and Sovereign Stress Transmission.” Review of Finance 21 (6): 2103–2139.

Birz, Gene, and John R. Lott Jr. “The effect of macroeconomic news on stock returns: New evidence from newspaper coverage.” Journal of Banking & Finance 35.11 (2011): 2791-2800.

Campbell J.Y., Shiller R.J. The dividend-price ratio and expectations of future dividends and discount factors Rev. Financ. Stud., 1 (1988), pp. 195-227

Corbet, Shaen, et al. “The impact of macroeconomic news on Bitcoin returns.” The European Journal of Finance 26.14 (2020): 1396-1416.

Evans, K. P. 2011. “Intraday Jumps and USMacroeconomic News Announcements.” Journal of Banking and Finance 35: 2511–2527.

Fama, Eugene F., and Kenneth R. French. “Business conditions and expected returns on stocks and bonds.” Journal of financial economics 25.1 (1989): 23-49.

Gilbert, Thomas. “Information aggregation around macroeconomic announcements: Revisions matter.” Journal of Financial Economics 101.1 (2011): 114-131.

Lyócsa, Štefan, et al. “Impact of macroeconomic news, regulation and hacking exchange markets on the volatility of bitcoin.” Journal of Economic Dynamics and Control 119 (2020): 103980.

Lucca, David O., and Emanuel Moench. "The pre‐FOMC announcement drift." The Journal of finance 70.1 (2015): 329-371.

Marmora, Paul. "Does monetary policy fuel bitcoin demand? Event-study evidence from emerging markets." Journal of International Financial Markets, Institutions and Money 77 (2022): 101489.

Mužić, Ivan, and Ivan Gržeta. "Expectations of Macroeconomic News Announcements: Bitcoin vs. Traditional Assets." Risks 10.6 (2022): 123.

Kacperczyk M., Van Nieuwerburgh S., Veldkamp L. A rational theory of mutual funds’ attention allocation, Econometrica, 84 (2016), pp. 571-626

Pyo, Sujin, and Jaewook Lee. "Do FOMC and macroeconomic announcements affect Bitcoin prices?." Finance Research Letters 37 (2020): 101386.

Scholtus, M., D. Van Dijk, and B. Frijns. 2014. “Speed, Algorithmic Trading, and Market Quality Around Macroeconomic News Announcements.” Journal of Banking and Finance 38: 89–105.

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Verousis, T., O. ap Gwilym, and X. Chen. 2016. “The Intraday Determination of Liquidity in the Nyse Liffe Equity OptionMarkets.” European Journal of Finance 22 (12): 1164–1188.


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