Connectedness between Defi assets and equity markets during COVID-19: A sector analysis

Technological Forecasting and Social Change, Journal Year: 2022, Volume and Issue: 187, P. 122174 - 122174

Published: Nov. 14, 2022

Language: Английский

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Effects of investor sentiment on stock volatility: new evidences from multi-source data in China’s green stock markets

Financial Innovation, Journal Year: 2022, Volume and Issue: 8(1)

Published: Aug. 23, 2022

Abstract The effect of investor sentiment on stock volatility is a highly attractive research question in both the academic field and real financial industry. With proposal China's "dual carbon" target, green stocks have gradually become an essential branch Chinese markets. Focusing 106 from new energy, environmental protection, carbon–neutral sectors, we construct two proxies using Internet text trading data, respectively. based posts Eastmoney Guba, comes variety indicators. In addition, divide realized into continuous jump parts, then investigate effects different types volatilities. Our empirical findings show that indices impose significant positive impacts realized, continuous, volatilities, where main factor. We further explore mediating information asymmetry, measured by volume-synchronized probability informed (VPIN), path affecting volatility. It evidenced sentiments are positively correlated with VPIN, they can affect volatilities through VPIN. total sample around coronavirus disease 2019 (COVID-19) pandemic. results reveal market after COVID-19 pandemic more susceptible to sentiments, especially sentiment. study great significance for maintaining stability markets reducing

Language: Английский

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Constructing a positive sentiment index for COVID-19: Evidence from G20 stock markets

International Review of Financial Analysis, Journal Year: 2022, Volume and Issue: 81, P. 102111 - 102111

Published: March 11, 2022

Language: Английский

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When Elon Musk Changes his Tone, Does Bitcoin Adjust Its Tune?

Computational Economics, Journal Year: 2022, Volume and Issue: 62(2), P. 639 - 661

Published: Jan. 13, 2022

Abstract We present a textual analysis that explains how Elon Musk’s sentiments in his Twitter content correlates with price and volatility the Bitcoin market using dynamic conditional correlation-generalized autoregressive heteroscedasticity model, allowing less sensitive to window size than traditional models. After examining 10,850 tweets containing 157,378 words posted from December 2017 May 2021 rigorously controlling other determinants, we found tone of world’s wealthiest person can drive market, having Granger causal relation returns. In addition, Musk is likely use positive tweets, reversal effects exist relationship between prices optimism presented by Tesla’s CEO. However, did not find evidence support linkage volatility. Our results are also robust when different cryptocurrency, i.e., Ether this paper extends existing literature about mechanisms social media generated influential accounts on market.

Language: Английский

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The COVID-19 pandemic uncertainty, investor sentiment, and global equity markets: Evidence from the time-frequency co-movements

The North American Journal of Economics and Finance, Journal Year: 2022, Volume and Issue: 62, P. 101712 - 101712

Published: May 26, 2022

Language: Английский

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Effect of Russia–Ukraine war sentiment on blockchain and FinTech stocks

International Review of Financial Analysis, Journal Year: 2023, Volume and Issue: 90, P. 102948 - 102948

Published: Sept. 21, 2023

Language: Английский

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Tail-event driven NETwork dependence in emerging markets

Emerging Markets Review, Journal Year: 2022, Volume and Issue: 55, P. 100971 - 100971

Published: Nov. 12, 2022

This paper employs the Tail Event NETwork (TENET) to identify financial markets with greater potential risk, and simultaneously investigate interdependence between them. We find strong time-varying connectedness across 23 emerging during main crisis episodes, including most recent COVID-19 pandemic, using data from January 1995 May 2021. The network analysis revealed that European are top risk transmitters, whereas Asian receivers. China showed disconnection network, reflecting its diversification for investors. Our findings offer several policy regulatory implications.

Language: Английский

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COVID-19 and stock returns: Evidence from the Markov switching dependence approach

Research in International Business and Finance, Journal Year: 2023, Volume and Issue: 64, P. 101882 - 101882

Published: Jan. 1, 2023

This paper aims to investigate the regime-switching and time-varying dependence between COVID-19 pandemic US stock markets using a Markov-switching framework. It makes two contributions empirical literature by showing that: (a) variations of daily reported cases cumulative deaths induced asymmetric lower (left) upper (right) tail with markets, its left right exhibited significant trends; (b) behaviours, switching probabilities in higher stage all being greater than after 1 December 2019. Moreover, given that there is concurrent but financial market reaction any unexpected emergence transmittable respirational disease or natural calamity, outcomes have some vital implications players policymakers.

Language: Английский

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Do perceived risks and benefits impact trust and willingness to adopt CBDCs?

Research in International Business and Finance, Journal Year: 2023, Volume and Issue: 66, P. 101993 - 101993

Published: May 23, 2023

Language: Английский

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Google search trends and stock markets: Sentiment, attention or uncertainty?

International Review of Financial Analysis, Journal Year: 2023, Volume and Issue: 91, P. 102549 - 102549

Published: Jan. 31, 2023

Keyword based measures purporting to reflect investor sentiment attention or uncertainty have been increasingly used model stock market behaviour. We investigate and shed light on the narrative reflected by Google search trends (GST) constructing a neutral general market-related GST index. To do so e apply elastic net regression select relevant terms using sample of 77 international markets. The index peaks around significant events that impacted global financial markets moves closely with established is predominantly correlated in differences implying an narrative. Returns volatility for developed emerging frontier widely changing volumes relationships conform prior expectations associated uncertainty. Our performs well relative existing keyword-based its ability approximate predict systematic drivers factor dispersion underlying return both in-sample out-of-sample. study contributes understanding information their relationship points towards generalisability thus facilitating development further applications data.

Language: Английский

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