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標(biāo)題: Titlebook: Big Data in Finance; Opportunities and Ch Thomas Walker,Frederick Davis,Tyler Schwartz Book 2022 The Editor(s) (if applicable) and The Auth [打印本頁(yè)]

作者: 召集會(huì)議    時(shí)間: 2025-3-21 19:03
書目名稱Big Data in Finance影響因子(影響力)




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書目名稱Big Data in Finance網(wǎng)絡(luò)公開度




書目名稱Big Data in Finance網(wǎng)絡(luò)公開度學(xué)科排名




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書目名稱Big Data in Finance被引頻次學(xué)科排名




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書目名稱Big Data in Finance年度引用學(xué)科排名




書目名稱Big Data in Finance讀者反饋




書目名稱Big Data in Finance讀者反饋學(xué)科排名





作者: 矛盾    時(shí)間: 2025-3-21 21:18
Alternative Datasified as alternative data. Using data sources that are not widely available can provide great value; however, collecting, validating, and maintaining datasets is known to be very costly. The situation is changing with recent advances in big data technologies that allow for new data sources to be co
作者: 不透明    時(shí)間: 2025-3-22 04:02
An Algorithmic Trading Strategy to Balance Profitability and Risk(BII), which has been shown to be able to balance risk and profitability accurately. This indicator is crucial for developing an AT strategy that allows algorithmic traders to use big data to analyze portfolios and seek the BII algorithm‘s highest value. The chapter reviews and analyzes current AT s
作者: Euthyroid    時(shí)間: 2025-3-22 05:12

作者: 為現(xiàn)場(chǎng)    時(shí)間: 2025-3-22 09:34
Ensemble Models Using Symbolic Regression and Genetic Programming for Uncertainty Estimation in ESG els have been shown empirically to have a strong predictive performance and the ability to extrapolate into regions of unknown parameter space or detect changes in the underlying system. This chapter demonstrates how the same technique for quantifying uncertainty is helpful in risk management workfl
作者: minion    時(shí)間: 2025-3-22 16:29

作者: Observe    時(shí)間: 2025-3-22 19:03

作者: consolidate    時(shí)間: 2025-3-22 22:37
Bitcoin: Future or Fad?ternative form of investment. Moreover, Bitcoin also exhibits some investment features similar to collectibles. This chapter shows that the true value of Bitcoin lies not in its speculative nature but in its embedded technology, blockchain, which has the potential to revolutionize traditional financ
作者: optional    時(shí)間: 2025-3-23 02:47
Culture, Digital Assets, and the Economy: A Trans-National Perspectiveionship between financial institutional development and the use of digital assets. Using four ways to measure the use of digital assets: digital payments, mobile payments, using the internet to pay bills, and online shopping, we find that financial institution development is positively related to ea
作者: DALLY    時(shí)間: 2025-3-23 06:34

作者: 存心    時(shí)間: 2025-3-23 11:06

作者: 裁決    時(shí)間: 2025-3-23 16:12
A Data-Informed Approach to Financial Literacy Enhancement Using Cognitive and Behavioral Analyticsl literacy. While it is difficult to arrive at a single and precise definition of financial literacy, it has been popularly used to refer to a combination of financial knowledge, attitude, abilities, and behaviors. This chapter reviews the current literature on financial literacy, focusing specifica
作者: Aggregate    時(shí)間: 2025-3-23 18:02

作者: graphy    時(shí)間: 2025-3-23 22:43

作者: 激怒某人    時(shí)間: 2025-3-24 05:08

作者: single    時(shí)間: 2025-3-24 06:53
1D Computational Spherical Geometrysified as alternative data. Using data sources that are not widely available can provide great value; however, collecting, validating, and maintaining datasets is known to be very costly. The situation is changing with recent advances in big data technologies that allow for new data sources to be co
作者: DALLY    時(shí)間: 2025-3-24 13:01

作者: GUILE    時(shí)間: 2025-3-24 15:02

作者: AMEND    時(shí)間: 2025-3-24 22:40
Solution to Optimal Control Problems,els have been shown empirically to have a strong predictive performance and the ability to extrapolate into regions of unknown parameter space or detect changes in the underlying system. This chapter demonstrates how the same technique for quantifying uncertainty is helpful in risk management workfl
作者: MULTI    時(shí)間: 2025-3-24 23:17

作者: 出生    時(shí)間: 2025-3-25 07:03
Introduction to Geometry and Topologyvestment technologies typically propose passive strategies that match investor objectives and risk profiles at a low cost. This chapter explores how digital advisors lack precision in capturing clients’ attitudes towards risk and exposure. In this context, leveraging big data and artificial intellig
作者: 語(yǔ)源學(xué)    時(shí)間: 2025-3-25 11:18

作者: 不遵守    時(shí)間: 2025-3-25 12:54

作者: 繁殖    時(shí)間: 2025-3-25 17:44

作者: 標(biāo)準(zhǔn)    時(shí)間: 2025-3-25 21:47

作者: 燒瓶    時(shí)間: 2025-3-26 02:29
Spatial-Positioning Technology,l literacy. While it is difficult to arrive at a single and precise definition of financial literacy, it has been popularly used to refer to a combination of financial knowledge, attitude, abilities, and behaviors. This chapter reviews the current literature on financial literacy, focusing specifica
作者: 侵蝕    時(shí)間: 2025-3-26 05:35
Thomas Walker,Frederick Davis,Tyler SchwartzFocuses on advancements made in deep learning and how they can be leveraged with big data.Provides a holistic view of how big data influences the financial sector.Includes practical case studies and c
作者: ARCH    時(shí)間: 2025-3-26 09:39
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作者: 爭(zhēng)議的蘋果    時(shí)間: 2025-3-26 15:29

作者: DEMUR    時(shí)間: 2025-3-26 18:57
Alternative Data job search websites, and social media platforms. Other common types of alternative data include retail transaction data, credit card data, data accessed through the Freedom of Information Act, and satellite imagery. Unlike traditional financial data, alternative data points are not easily quantifia
作者: 黃油沒(méi)有    時(shí)間: 2025-3-26 21:10
High-Frequency Trading and Market Efficiency in the Moroccan Stock Marketcient at these frequencies. Based on these results obtained, the main conclusion from this chapter is that investors with a faster market connection (at the millisecond and second level) and an efficient algorithm can use privileged information to realize returns higher than those of the Moroccan St
作者: cluster    時(shí)間: 2025-3-27 01:20
Ensemble Models Using Symbolic Regression and Genetic Programming for Uncertainty Estimation in ESG dditionally, explicit uncertainty ranges are obtained, using an ensemble modeling approach, at a sufficiently high accuracy level to trust the uncertainty measurement. Future research is necessary to refine the approach presented as more data becomes available.
作者: 宇宙你    時(shí)間: 2025-3-27 06:28
Islamic Finance in Canada Powered by Big Data: A Case Studymely useful in building dynamic and stochastic banking models along with other predictive analytics. This chapter illustrates both the methodology and practical steps for determining the feasibility of a new financial institution in a heavily regulated financial sector of a G8 country. More specific
作者: Judicious    時(shí)間: 2025-3-27 11:53
Assessing the Carbon Footprint of Cryptoassets: Evidence from a Bivariate VAR Model mining was responsible for approximately 43 million metric tons of carbon in 2020 (the equivalent to 0.14% of the global total yearly carbon emissions in that year). Using an impulse-response analysis, we also find that the impact of one standard deviation shock in Bitcoin‘s trading volume on the n
作者: Fantasy    時(shí)間: 2025-3-27 14:07
A Data-Informed Approach to Financial Literacy Enhancement Using Cognitive and Behavioral Analyticsortance of financial confidence as a driver for behavioral outcomes among learners, as well as population-level heterogeneities involved in financial knowledge, confidence, and behavior. We draw on these insights to recommend to policymakers and educators how to design and derive value from similar
作者: 蚊帳    時(shí)間: 2025-3-27 19:14

作者: Morose    時(shí)間: 2025-3-28 00:41

作者: 過(guò)份好問(wèn)    時(shí)間: 2025-3-28 02:42

作者: persistence    時(shí)間: 2025-3-28 06:23
https://doi.org/10.1007/978-3-031-02070-4cient at these frequencies. Based on these results obtained, the main conclusion from this chapter is that investors with a faster market connection (at the millisecond and second level) and an efficient algorithm can use privileged information to realize returns higher than those of the Moroccan St
作者: Amorous    時(shí)間: 2025-3-28 11:21

作者: Liability    時(shí)間: 2025-3-28 14:48
Radioactive Decay and Rock Ages,mely useful in building dynamic and stochastic banking models along with other predictive analytics. This chapter illustrates both the methodology and practical steps for determining the feasibility of a new financial institution in a heavily regulated financial sector of a G8 country. More specific
作者: 錯(cuò)    時(shí)間: 2025-3-28 22:22
,Earthquakes and Earth’s Structure, mining was responsible for approximately 43 million metric tons of carbon in 2020 (the equivalent to 0.14% of the global total yearly carbon emissions in that year). Using an impulse-response analysis, we also find that the impact of one standard deviation shock in Bitcoin‘s trading volume on the n
作者: HARP    時(shí)間: 2025-3-29 03:00
Spatial-Positioning Technology,ortance of financial confidence as a driver for behavioral outcomes among learners, as well as population-level heterogeneities involved in financial knowledge, confidence, and behavior. We draw on these insights to recommend to policymakers and educators how to design and derive value from similar
作者: 軌道    時(shí)間: 2025-3-29 04:29

作者: 商談    時(shí)間: 2025-3-29 10:39
Book 2022ld of finance. While the general use of big data has been the subject of frequent discussions, this book will take a more focused look at big data applications in the financial sector. With contributions from researchers, practitioners, and entrepreneurs involved at the forefront of big data in fina
作者: bibliophile    時(shí)間: 2025-3-29 12:52

作者: cataract    時(shí)間: 2025-3-29 19:34

作者: FIS    時(shí)間: 2025-3-29 21:29
https://doi.org/10.1007/978-3-030-63696-8res the motivations behind these changes, discusses the significant evolution in data and analytics that enable the development of new credit quality indicators, and highlights the privacy and ethical challenges of using new and emerging credit assessments in the age of big data.




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