Editor’s introduction

The 44th issue of Financial Innovation (FIN), Volume 11, No.2 (2024) presents 29 papers contributed by authors and co-authors from 18 countries: Australia, Austria, Canada, China, France, Ireland, Israel, Italy, New Zealand, Pakistan, Poland, Republic of Korea, Saudi Arabia, South Africa, Spain, Turkey, United States and Vietnam. These papers can be mainly categorized into three sub-themes: Financial Stability and Risk Management, Market Sentiment and Behavioral Finance, and Economic Policy and Its Impact.

• Financial Stability and Risk Management

Cunado et al. (2024) analyze pre- and post-COVID-19 energy and metal price links, finding stronger interconnectedness post-pandemic. Initially, crude oil drove shocks, shifting to heating oil, gold, and silver during COVID-19, with natural gas and palladium as key receivers. Results indicate fewer hedging opportunities and a shift in crude oil's role during crises. Mba (2024) evaluates systemic risk using CoVaR, vine copula, and APARCH-DCC, highlighting its robustness and the notable systemic risk in cryptocurrency portfolios, advocating for diverse methods to enhance risk assessment accuracy. Polat (2024) studies US sectoral returns (2020–2023) with TVP-VAR, revealing strong interconnectivity, negative spillovers, the industry sector's key role in shock transmission, and portfolio strategies' effectiveness in managing asymmetries for risk and optimization. Wang and Zhou (2024) create a workflow to predict China's systemic financial crisis and analyze macroeconomic impacts, providing crucial crisis prediction tools for policymakers to improve financial stability. Ullah et al. (2024) examine governance and macroeconomic impacts on financial stability in 122 countries (2013–2020), revealing positive effects from interest rates, GDP growth, and governance, but negative from inflation and the rule of law, underscoring the importance of regulatory governance and macroeconomic health. Mozumder et al. (2024) analyze Lévy vs. extreme value models with 2007–08 crisis data, indicating EV's simplicity may not always outperform Lévy's complexity, stressing a need to balance simplicity with adequacy for effective risk management. D'Amico et al. (2024) explore market crisis risk indicators using high-frequency Nasdaq data, comparing drawdown measures to unveil insights on liquidity risk. Feder-Sempach et al. (2024) study gold, bitcoin, and currencies in crises with a volatility model, identifying the Japanese yen as the top safe-haven and creating a new safe-haven asset classification. Laborda et al. (2024) link ETFs to equity bubbles and market dynamics through S&P 500 and VIX analysis from 1994 to 2020 using quantile cointegration models. Jin (2024) uses a quantile connectedness approach to show China’s systemically important banks are more interconnected in bullish than bearish markets, offering insights for regulatory policy and risk management. Wang et al. (2024) improve Value at Risk and Expected Shortfall estimates by combining quantile regression with “Mogrifier” RNNs and GANs for financial asset analysis and future risk simulation, surpassing current models.

Leccadito et al. (2024) assess the dynamic Gerber model for VaR and ES predictions, highlighting its effectiveness in handling return asymmetries and fat tails, proving superior for diversified portfolios and beneficial for market risk management. Zhong et al. (2024) discover that increasing supply chain transparency, especially regarding suppliers, lowers stock price crash risk by limiting tax avoidance and earnings management, especially in firms prone to concealing negative information, highlighting its importance in financial risk management. Jing et al. (2024) present a new predictor based on the U.S. stock market's daily return minimum, showing significant forecast ability for 17 MSCI markets (1972–2022), especially in crises, but less effective during COVID-19, highlighting non-financial crisis impacts on predictability.

• Market Sentiment and Behavioral Finance

Li et al. (2024) leverage NLP and deep learning on various text data sources to forecast stock prices, showing sentiment-based strategies boost forecasting accuracy and investment returns. Zhang et al. (2024) discover cryptocurrency returns increase during Chinese holidays with positive social media sentiment, but high investor sentiment reduces this effect, implying a need for policies to ensure market stability and protect investors. Lu et al. (2024) show that textual and facial emotions in crowdfunding pitches affect funding success, with facial emotions enhancing the impact of textual ones. Liu et al. (2024) find cleantech crowdfunding success is boosted by clear, unambiguous project descriptions, particularly in complex information settings, advising founders to use straightforward narratives to attract investment. Ayala et al. (2024) review 56 studies showing Google Search Volume Index positively correlates with market volatility and trading volume, suggesting it's an effective indicator of investor attention and can improve market movement forecasts. Chebbi et al. (2024) find Twitter sentiment on US financial stocks reacts asymmetrically and varies with COVID-19 and state responses, showing complex impacts of emergency actions on investor sentiment-stock return dynamics. Liu et al. (2024) analyze the "lie game" on social media's impact on Chinese stocks, showing a cycle where investor sentiment boosts market behavior and vice versa, with positive sentiment mitigating negative financial effects during significant events.

• Economic Policy and Its Impact

Golpe et al. (2024) study the crude oil-refined products price relationship using causality tests, revealing varying market integration influenced by supply and demand. Qadan and Cohen (2024) find that uncertainty in interest rates, measured by VIX-style volatility of 10-year U.S. Treasury futures, forecasts a drop and increased volatility in oil prices, guiding policymakers in inflation and uncertainty management strategies. Okorie and Lin (2024) analyze the economic and environmental impacts of the 2020 oil price shock and COVID-19 on Nigeria, revealing output declines, sectoral effects, environmental improvements, and a revenue-abatement paradox, with fiscal stimulus–response packages soften the shocks' impact, offering insights for other developing oil-reliant economies. Ahmed et al. (2024) study construction investments in Saudi Arabia, showing immediate GDP and investment boosts but stressing the need for long-term strategies and policy oversight for sustained growth and varied sectoral impacts. Sarker (2024) analyzes FDI and trade's impact on Bangladesh's economy during crises, highlighting positive effects from FDI and exports, limited impact from imports and total trade, with recommendations for export diversification, FDI incentives, and post-crisis stabilization. Emara and Zecheru (2024) study digitization's influence on inflation in 54 economies (2004–2018), uncovering a nonlinear deflationary effect below a certain level and advising emerging markets to enhance digital infrastructures, human capital, and governance to optimally impact inflation. Vo and Nguyen (2024) analyze Vietnam's sectoral market risks and macroeconomic effects (2012–2022) with VaR and VAR, finding notable inter-sector connectedness and asymmetric macroeconomic responses, informing risk management and investment strategies. O'Donnell et al. (2024) assess COVID-19 monetary policy effects on banking stocks, noting regional differences: U.S. negativity to rate cuts, Chinese positivity to FX news, and European mixed results, guiding policy and market strategies for future crises.