Outlier Events in Major Cryptocurrency Markets: Is There Evidence of Overreaction?

Schaub, Mark

doi:10.3905/jwm.2021.1.155

Cited by 2 publications

(1 citation statement)

References 18 publications

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“…Our revealed results indicate that investors using contrarian strategies (e.g., buying bitcoin and ETH spots as oversold signals emitted BBTS) might achieve advantageous outcomes instead of using momentum strategies (e.g., selling bitcoin and ETH spots as oversold signals emitted BBTS). That is, adopting contrarian strategies would be more effective than adopting momentum strategies in this study, which is consistent with adopting contrarian strategies being effective for trading in cryptocurrency markets [67,81,82] rather than adopting momentum strategies being effective for trading in cryptocurrency markets [83,84].…”

Section: Discussionsupporting

confidence: 84%

Using Big Data Analytics and Heatmap Matrix Visualization to Enhance Cryptocurrency Trading Decisions

Ni,

Chiang,

Day

et al. 2023

Applied Sciences

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Using the Bollinger Bands trading strategy (BBTS), investors are advised to buy (and then sell) Bitcoin and Ethereum spot prices in response to BBTS’s oversold (overbought) signals. As a result of analyzing whether investors would profit from round-turn trading of these two spot prices, this study may reveal the following remarkable outcomes and investment strategies. This study first demonstrated that using our novel design with a heatmap matrix would result in multiple higher returns, all of which were greater than the highest return using the conventional design. We contend that such an impressive finding could be the result of big data analytics and the adaptability of BBTS in our new design. Second, because cryptocurrency spot prices are relatively volatile, such indices may experience a significant rebound from oversold to overbought BBTS signals, resulting in the potential for much higher returns. Third, if history repeats itself, our findings might enhance the profitability of trading these two spots. As such, this study extracts the diverse trading performance of multiple BB trading rules, uses big data analytics to observe and evaluate many outcomes via heatmap visualization, and applies such knowledge to investment practice, which may contribute to the literature. Consequently, this study may cast light on the significance of decision-making through the utilization of big data analytics and heatmap visualization.

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Section: Discussionsupporting

confidence: 84%

Using Big Data Analytics and Heatmap Matrix Visualization to Enhance Cryptocurrency Trading Decisions

Ni,

Chiang,

Day

et al. 2023

Applied Sciences

View full text Add to dashboard Cite

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Overreaction, Underreaction, and Short-Term Efficient Reaction Evidence for Cryptocurrencies

Dias,

Chambino,

Palma

et al. 2023

Advances in Web Technologies and Engineering

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This chapter aims to analyze the price efficiency of Bitcoin (BTC), DASH, EOS, Ethereum (ETH), LISK, Litecoin (LTC), Monero, NEO, QUANTUM, RIPPLE, STELLAR, and ZCASH in their weak form between March 1, 2018 and March 1, 2023 and determine whether they experience overreactions. The results show that cryptocurrencies exhibit positive and negative autocorrelations, which can reduce volatility and moderate price fluctuations. The results also show persistence in cryptocurrency returns, suggesting long-term trends or market patterns that individual and institutional investors can exploit. It is essential to recognize that cryptocurrencies are characterized by a high degree of complexity and instability. Investors need to monitor market trends and make the necessary adjustments to their investment strategies to anticipate market changes.

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Outlier Events in Major Cryptocurrency Markets: Is There Evidence of Overreaction?

Cited by 2 publications

References 18 publications

Using Big Data Analytics and Heatmap Matrix Visualization to Enhance Cryptocurrency Trading Decisions

Using Big Data Analytics and Heatmap Matrix Visualization to Enhance Cryptocurrency Trading Decisions

Overreaction, Underreaction, and Short-Term Efficient Reaction Evidence for Cryptocurrencies

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