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  1. The risk profiles of investors play an important role in the success of derivative products investments. It is also necessary to determine the appropriate investor profile according to the conditions of a coun...

    Authors: Dadan Rahadian, Anisah Firli, Hasan Dinçer, Serhat Yüksel, Alexey Mikhaylov and Fatih Ecer
    Citation: Financial Innovation 2024 10:37
  2. Most previous studies on the market efficiency of cryptocurrencies consider time evolution but do not provide insights into the potential driving factors. This study addresses this limitation by examining the ...

    Authors: Khaled Mokni, Ghassen El Montasser, Ahdi Noomen Ajmi and Elie Bouri
    Citation: Financial Innovation 2024 10:39
  3. Value at risk (VaR) and expected shortfall (ES) have emerged as standard measures for detecting the market risk of financial assets and play essential roles in investment decisions, external regulations, and r...

    Authors: Jianzhou Wang, Shuai Wang, Mengzheng Lv and He Jiang
    Citation: Financial Innovation 2024 10:36
  4. The role of the construction industry in economic growth has been widely discussed in the extant literature, but existing studies have not investigated the disaggregated impact of construction investments on t...

    Authors: Irfan Ahmed, Khadija Mehrez, Claudio Socci, Stefano Deriu, Naif M. Mathkur and Ian P. Casasr
    Citation: Financial Innovation 2024 10:28
  5. This study assesses the role of mobile money innovations on income inequality and gender inclusion in 42 sub-Saharan African countries from 1980 to 2019 using interactive quantile regressions. It finds that, f...

    Authors: Simplice A. Asongu, Peter Agyemang-Mintah, Joseph Nnanna and Yolande E. Ngoungou
    Citation: Financial Innovation 2024 10:11
  6. The yield on the 10-year U.S. Treasury Note is among the most cited interest rates by investors, policymakers, and financial institutions. We show that the 10-year Treasury yield’s forward-looking volatility, ...

    Authors: Mahmoud Qadan and Gil Cohen
    Citation: Financial Innovation 2024 10:9
  7. This study explores whether the COVID-19 outbreak and Russian–Ukrainian (R–U) conflict have impacted the efficiency of cryptocurrencies. The novelty of this study is the use of the Cramér-von Mises test to exa...

    Authors: Aktham Maghyereh and Mohammad Al-Shboul
    Citation: Financial Innovation 2024 10:8
  8. This study uses complex network analysis to investigate global stock market co-movement during the black swan event of the Coronavirus Disease 2019 (COVID-19) pandemic. We propose a novel method for calculatin...

    Authors: Wenyang Huang, Huiwen Wang, Yigang Wei and Julien Chevallier
    Citation: Financial Innovation 2024 10:7
  9. The central concept of strategic benchmarking is resource management efficiency, which ultimately results in profitability. However, little is known about performance measurement from resource-based perspectiv...

    Authors: Qian Long Kweh, Wen-Min Lu, Kaoru Tone and Hsian-Ming Liu
    Citation: Financial Innovation 2024 10:19
  10. This study attempts to accelerate the learning ability of an artificial electric field algorithm (AEFA) by attributing it with two mechanisms: elitism and opposition-based learning. Elitism advances the conver...

    Authors: Sarat Chandra Nayak, Satchidananda Dehuri and Sung-Bae Cho
    Citation: Financial Innovation 2024 10:5
  11. Financial performance analysis is of vital importance those involved in a business (e.g., shareholders, creditors, partners, and company managers). An accurate and appropriate performance measurement is critic...

    Authors: Mahmut Baydaş, Orhan Emre Elma and Željko Stević
    Citation: Financial Innovation 2024 10:4
  12. The cryptocurrency market is a complex and rapidly evolving financial landscape in which understanding the inter- and intra-asset dependencies among key financial variables, such as return and liquidity, is cr...

    Authors: Mianmian Zhang, Bing Zhu, Ziyuan Li, Siyuan Jin and Yong Xia
    Citation: Financial Innovation 2024 10:3
  13. Using a wavelet coherence approach, this study investigates the relationship between Bitcoin return and Bitcoin-specific sentiment from January 1, 2016 to June 30, 2021, covering the COVID-19 pandemic period. ...

    Authors: Ahmet Faruk Aysan, Erhan Muğaloğlu, Ali Yavuz Polat and Hasan Tekin
    Citation: Financial Innovation 2023 9:124
  14. In this study, we analyze the stock market reaction to 35 events associated with 32 publicly traded companies from six countries that have announced cryptocurrency acquisitions, selling, or acceptance as a mea...

    Authors: André D. Gimenes, Jéfferson A. Colombo and Imran Yousaf
    Citation: Financial Innovation 2023 9:123
  15. Although blockchain technology has received a significant amount of cutting-edge research on constructing a novel carbon trade market in theory, there is little research on using blockchain in carbon emission ...

    Authors: Yi-Ran Wang, Chaoqun Ma, Yi-Shuai Ren and Seema Narayan
    Citation: Financial Innovation 2023 9:122
  16. Credit risk assessment involves conducting a fair review and evaluation of an assessed subject’s solvency and creditworthiness. In the context of real estate enterprises, credit risk assessment provides a basi...

    Authors: Zhen-Song Chen, Jia Zhou, Chen-Ye Zhu, Zhu-Jun Wang, Sheng-Hua Xiong, Rosa M. Rodríguez, Luis Martínez and Mirosław J. Skibniewski
    Citation: Financial Innovation 2023 9:120
  17. This study uses the dynamic conditional correlation to investigate how technology subsector stocks interact with financial assets in the face of economic and financial uncertainty. Our results suggest that str...

    Authors: Linn Arnell, Emma Engström, Gazi Salah Uddin, Md. Bokhtiar Hasan and Sang Hoon Kang
    Citation: Financial Innovation 2023 9:106
  18. This study analyzes the role of financial development (FD) on the impact of technological innovation (TI) on six environmental quality indicators for the 25 economies that are part of the Organization for Econ...

    Authors: Hossein Ali Fakher and Zahoor Ahmed
    Citation: Financial Innovation 2023 9:112
  19. A broad range of companies around the world has welcomed artificial intelligence (AI) technology in daily practices because it provides decision-makers with comprehensive and intuitive messages about their ope...

    Authors: Kuang-Hua Hu, Fu-Hsiang Chen, Ming-Fu Hsu and Gwo-Hshiung Tzeng
    Citation: Financial Innovation 2023 9:117
  20. This paper investigates optimal decisions for private banking development in China under two innovative organizational structures—the big retail mode (BRM) and the independent development mode (IDM). Under the...

    Authors: He Liu, Yun Bai, Zhiguang Huang, Han Qiao and Shouyang Wang
    Citation: Financial Innovation 2023 9:116
  21. In the European Union (EU), the revised Payment Services Directive (PSD2) aims to provide more convenient and customized financial products through open banking (OB) platforms. However, little attention has be...

    Authors: Massimo Preziuso, Franziska Koefer and Michel Ehrenhard
    Citation: Financial Innovation 2023 9:111
  22. The Group Method of Data Handling (GMDH) neural network has demonstrated good performance in data mining, prediction, and optimization. Scholars have used it to forecast stock and real estate investment trust ...

    Authors: Wendi Zhang, Bin Li, Alan Wee-Chung Liew, Eduardo Roca and Tarlok Singh
    Citation: Financial Innovation 2023 9:98
  23. To measure the diversification capability of Bitcoin, this study employs wavelet analysis to investigate the coherence of Bitcoin price with the equity markets of both the emerging and developed economies, con...

    Authors: Rubaiyat Ahsan Bhuiyan, Afzol Husain and Changyong Zhang
    Citation: Financial Innovation 2023 9:100
  24. This study aims to fill the gap in the literature by specifically investigating the impact of country risk on the credit risk of the banking sectors operating in Brazil, Russia, India, China, and South Africa ...

    Authors: Chafic Saliba, Panteha Farmanesh and Seyed Alireza Athari
    Citation: Financial Innovation 2023 9:86
  25. We construct a sovereign default network by employing high-dimensional vector autoregressions obtained by analyzing connectedness in sovereign credit default swap markets. We develop four measures of centralit...

    Authors: Lu Yang, Lei Yang and Xue Cui
    Citation: Financial Innovation 2023 9:83
  26. This study investigates tail dependence among five major cryptocurrencies, namely Bitcoin, Ethereum, Litecoin, Ripple, and Bitcoin Cash, and uncertainties in the gold, oil, and equity markets. Using the cross-...

    Authors: Walid Mensi, Mariya Gubareva, Hee-Un Ko, Xuan Vinh Vo and Sang Hoon Kang
    Citation: Financial Innovation 2023 9:92