Cryptocurrencies are an entirely new asset class, which were given birth to by the launch of Bitcoin in 2009. While the narrative and consensus of the classification of Bitcoin have shifted from electronic, peer-to-peer cash to an electronic, peer-to-peer store of value or “digital gold”, the fundamentals of the vast majority of other cryptographic assets are far less convincing.
Even though these digital tokens hold innovative and potentially highly disruptive promises — such as disintermediation, radical transparency and entirely new models for business and cooperation — the lack of functional networks and intrinsic demand for these assets has paved the way for high levels of speculation.
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The digital asset market generally shows a high correlation between Bitcoin’s price movements with the rest of the market and an apparent lack of fundamentals for individual asset’s price movements, however, quantitative proof for these claims has thus far been lacking.
To fill this knowledge gap, Da Gama Silva, Gomes, Klotzle & Pinto have researched behavioral finance in relation to cryptocurrencies, and presented their findings in the paper “Herding Behavior and Contagion in the Cryptocurrency Market”. In this study, the researchers provide indications of the presence of several herding and contagion effects based on a sample of 50 digital assets over a three and a half year period — the following is a summary of this research.
Humans are inherently social beings that want to belong to a community, which brings us naturally together but also tends to lead to biases in our assessments and actions. Herding behavior is one of these issues and refers to the misguided and rather common practice of being lead by the opinions and behaviors of one’s peers rather than relying on individual decision-making. Herding is popular in behavioral finance for explaining anomalies in financial markets such as excessive volatility, asset bubbles, and subsequent dramatic sell-offs. This is because herding leads to investors being lead by the actions of others, effectively downplaying fundamentals and giving increased weight to more arbitrary criteria. Scholars commonly attribute herding to the fear of missing out on lucrative investments, effectively reducing rationality in investment decisions.
Da Gama Silva, Gomes, et al. state that studying herding behavior is important for understanding anomalies in the prices of cryptocurrencies and for analyzing both the dynamics and relatedness of different digital assets for the creation of portfolios. The approach the researchers took for analyzing the presence of herding in cryptocurrencies is based on the commonly used methodologies for analyzing herding behavior CSAD and CSSD, introduced and applied to the cryptocurrency industry by Farinós, Ibáñez & Vidal-Tomás (2018). These methods measure herding behavior with respect to market consensus and pose that investors are more inclined to suppress individual assessment and be guided by market consensus in times of “extreme” market patterns.
Contagion effects occur when either positive or negative events of one asset or in one specific market impact the performance of other assets or markets. The phenomenon is widely regarded as an indicator of asset or market interdependence and is usually associated with market downturns and financial crisis, as the contagion effect becomes most visible during uncertainty and selloffs.
Most digital assets in the cryptocurrency market target different industries, including cloud storage, cloud computing, supply chain management, asset exchange, and IoT solutions; yet, there is an observable contagion effect in relation the Bitcoin, and to a lesser degree the larger cryptocurrencies in terms of market capitalization. With regards to the cryptocurrency market, contagion refers to the impact of the larger crypto-assets in terms of market capitalization on the wider market. To assess the presence of a contagion effect, Da Gama Silva et al. utilize adaptations of Forbes and Rigobon’s (2002) FR test and extensions of this test.
Herding and Contagion in the Cryptocurrency Market
For the assessment of the presence of both herding behavior and contagion effects, the authors compiled a sample containing 50 crypto-assets, which were chosen based on the high liquidity and market volume, on the digital market between March 2015 to December 2018, using 1,344 daily observations. Data for this was extracted from the CRyptocurrency IndeX (CRIX).
With regards to herding behavior, the authors found indications of herding over the selected years, and although the effect was observed in the sample, extreme results only appeared frequently for adverse herding. The results of the study demonstrate that events and news in the industry impacted herding behavior, however, significant evidence of extreme adverse herding produced the most compelling finding with regards to herding. As the authors conclude, this indicates higher risk aversion among cryptocurrency investors, and as extreme adverse herding happened during market crashes, it was found that investors became more risk-averse following crashing prices and negative news. Additionally, the findings imply that investors were more influenced by negative than by positive news.
Bitcoin was observed to impact the flow of capital in and out of other cryptocurrencies. Also, the assets included in the study were found to fuel herding for smaller assets on the digital market that couldn’t be attributed solely to the dominating cryptocurrency Bitcoin.
Regarding the contagion effect, Da Gama Silva et al. were looking for contagion during times of market crashes and found indications of the existence of the contagion risk for the cryptocurrencies in the sample. Moreover, the authors found evidence for a contagion effect for all the analyzed currencies related to Bitcoin over the chosen period during market downturns.
Although the study didn’t split the sample based on crisis versus non-crisis periods, the authors found indications that contagion was more prevalent during market crashes. The study has provided evidence of a Bitcoin contagion effect for all digital assets in the sample except for two stablecoins, Tether and BITCNY, and ECC over the full period. The former two can be explained by their value being pegged to fiat currencies, making them immune to the cryptocurrency market forces.
Da Gama Silva et al. found that even though herding effects were found to be present in the cryptocurrency space, there is stronger evidence that investors tend to rely on individual assessments and decision making during market downturns. Moreover, they are more affected by negative news than by positive news, which makes sense as, during periods of increased uncertainty, investors become more risk-averse.
The results of the study also provide evidence of what common sense tells us: there is a Bitcoin-related contagion effect. Overall, the price movements of Bitcoin were found to be highly impactful on the cryptocurrency space, which has important implications for portfolio management and risk diversification strategies. This significant impact of Bitcoin can be expected to persist until other digital assets manage to establish price independence based on intrinsic demand for the cryptocurrency and its related network or application.
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