Author:
(1) Kanis Saengchote, Chulalongkorn Business School, Chulalongkorn University, Phayathai Road, Pathumwan, Bangkok 10330, Thailand. (email: [email protected]).
Table of Links
Abstract and 1. Introduction
2. Data and Methodology
2.1 Bubble Timestamping
2.2 Cryptocurrency-LAND Wealth Effect
3. Results
3.1 Bubble Timestamping
3.2 Cryptocurrency-LAND Wealth Effect
3.3 Granger Causality Test
4. Conclusion and References
Appendix: Bored Ape Yacht Club’s Otherside
ABSTRACT
The rapid rise of cryptocurrency prices led to concerns (e.g. the Financial Stability Board) that this wealth accumulation could detrimentally spill over into other parts of the economy, but evidence is limited. We exploit the tendency for metaverses to issue their own cryptocurrencies along with nonfungible tokens (NFTs) representing virtual real estate ownership (LAND) to provide evidence of the wealth effect. Cryptocurrency prices and their corresponding real estate prices are highly correlated (more than 0.96), and cryptocurrency prices Granger cause LAND prices. This metaverse bubble reminisces the 1920s American real estate bubble that preceded the 1929 stock market crash.
1. Introduction
Crypto Investors Are Wealthier. No One Knows How Much They’re Spending.
It’s time to start contemplating how vast wealth created in cryptocurrencies filters through the rest of the economy.
Telis Demos, Wall Street Journal, February 18, 2022.
The rapid rise in cryptocurrency and crypto asset prices that began in late 2020 led to significant wealth accumulation that could spill over into other parts of the economy. CoinGecko, a crypto asset information aggregator, reported that at the beginning of July 2020, total crypto market capitalization stood at $262.8 million. By mid-November 2021, the figure rose to more than $3 trillion. From some, this is a boon: news articles in December 2021 often discussed how this newfound wealth is related to the boom in luxury goods spending. [1] But for others, this could be a bane: a report by the Financial Stability Board (FSB) released in February 2022 explicitly outlined the “wealth effect” as a vulnerability, where “changes in the value of crypto-assets might impact their investors, with subsequent knock-on effects in the financial system”. As the market collapsed in May 2022, the narrative changed from glamour stories of nouveau riche to how luxury watches previously in shortage were now flooding the market again.[2]
While the wealth effect is a potential systemic risk concern, during the same period, other risky asset classes such as equity also experienced similar movements. In an IMF blogpost in early 2022, Adrian, Iyer and Qureshi (2022) commented that “there’s a growing interconnectedness between virtual assets and financial markets” and showed that the correlation between Bitcoin and the S&P 500 index increased from almost zero in 2017 to 0.34 in 2020 – 2021. [3] This co-movement makes it difficult to disentangle the crypto wealth effect from a general wealth effect. In addition, a February 2022 Wall Steet Journal article suggested that not only it is hard to observe how the crypto millionaires are spending, but such wealth is also hard to spend because crypto assets remain largely unconnected to the financial system, making it challenging to establish the wealth effect spillover.
However, for crypto assetsrecorded directly onto blockchains, the exchange and settlement processes are simpler because they exist in the same system, making it easier to spend the accumulated wealth by acquiring on-chain assets. The rise of crypto market capitalization coincides with an interest in non-fungible tokens (NFTs), unique on-chain units of digital storage that could be used to hold a variety of information including artwork and proof of virtual real estate ownership. Thus, the co-movements between related crypto assets can provide better identification of the wealth effect.
In a related study, Dowling (2022b) analyzed the relationship between cryptocurrencies (unbacked, blockchain-based assets, e.g. Bitcoin and Ether) and three types of NFTs (virtual real estate, digital art and game characters) and found strong evidence of co-movement. We build upon this finding by exploiting a direct relationship between NFTs and cryptocurrencies in virtual real estate platforms (also referred to as “metaverse”), as they tend to issue unbacked, freely floating crypto assets intended as medium of exchange in their corresponding metaverse. They also issue NFT proof of ownership, often referred to as “LAND”. For example, Decentraland – one of the earliest and most successful metaverses developed on the Ethereum blockchain – issues MANA as its cryptocurrency, while The Sandbox – also on Ethereum – issues SAND. [4] Buyers can potentially use LAND to conduct side transactions include leases, but as of August 2022, there is no way to directly earn real estate income in both metaverses.
In this article, we analyze the returns spillover between cryptocurrencies and LAND NFTs to directly investigate the wealth effect, which is also often the focus for research on the economics of art (Goetzmann, Renneboog and Spaenjers, 2011; Pénasse and Renneboog, 2022). Recent articles have documented the economics and returns properties of metaverse real estate (e.g. Goldberg et al., 2021; Dowling, 2022a; Nakavachara and Saengchote, 2022) and their relationship with cryptocurrencies (Dowling, 2022b), but linkages are often analyzed from the perspective of volatility spillovers (e.g. Bouri, Lucey and Roubaud, 2020; Moratis, 2021; Dowling, 2022b), while our focus is on the co-movements in prices and returns.
Our analysis is divided into two steps: first, we document metaverse cryptocurrency price bubbles that could lead to accumulation of wealth using a timestamping algorithm developed by Phillips, Shi and Yu (2015). Researchers have found that cryptocurrencies are prone to media attention (Philippas et al., 2019), psychological fear of missing out (Baur and Dimpfl, 2018) and herding behavior (Bouri, Gupta and Roubaud, 2019), thus they are prone to bubbles. Then, we use the vector autoregression (VAR) model and Granger causality test to examine the lead-lag relationship as evidence of directional wealth spillover effect. Our article is also related to a growing literature on detecting and explaining asset bubbles, which have been conducted in cryptocurrencies (e.g. Corbet, Lucey and Yarovaya, 2018; Bouri, Shahzad and Roubaud, 2019; Shahzad, Anas, and Bouri, 2022), real estate (DeFusco, Nathanson and Zwick, 2022), equity (Phillips, Shi and Yu, 2015; Liao, Peng and Zhu, 2022) and art (Pénasse and Renneboog, 2022).
[1] https://www.bloomberg.com/news/articles/2021-12-15/cryptocurrency-helping-spur-u-s-as-luxury-s-new-growthdriver, accessed on September 9, 2022. [2] https://www.bloomberg.com/news/articles/2022-07-29/the-crypto-collapse-has-flooded-the-market-with-rolexand-patek, accessed on September 9, 2022. [3] https://blogs.imf.org/2022/01/11/crypto-prices-move-more-in-sync-with-stocks-posing-new-risks/, accessed on September 9, 2022. Note: the IMF uses the term “virtual assets” to describe transferable digital information recorded on blockchains. Other common terms used are “digital assets” and “crypto assets”. [4] Details of Decentraland can be found in Goldberg et al. (2021), while details of The Sandbox can be found in Nakavachara and Saengchote (2022).
