arXiv - QuantFin - General Finance最新文献_第2页

Degree of Irrationality: Sentiment and Implied Volatility Surface 非理性程度：情绪和隐含波动率表面

arXiv - QuantFin - General Finance Pub Date : 2024-05-20 DOI: arxiv-2405.11730

Jiahao Weng, Yan Xie

引用次数: 0

Central Bank Digital Currency: The Advent of its IT Governance in the financial markets 中央银行数字货币：金融市场的 IT 治理时代即将到来

arXiv - QuantFin - General Finance Pub Date : 2024-05-17 DOI: arxiv-2407.07898

Carlos Alberto Durigan Junior, Mauro De Mesquita Spinola, Rodrigo Franco Gonçalves, Fernando José Barbin Laurindo

{"title":"Central Bank Digital Currency: The Advent of its IT Governance in the financial markets","authors":"Carlos Alberto Durigan Junior, Mauro De Mesquita Spinola, Rodrigo Franco Gonçalves, Fernando José Barbin Laurindo","doi":"arxiv-2407.07898","DOIUrl":"https://doi.org/arxiv-2407.07898","url":null,"abstract":"Central Bank Digital Currency (CBDC) can be defined as a virtual currency\u0000based on node network and digital encryption algorithm issued by a country\u0000which has a legal credit protection. CBDCs are supported by Distributed Ledger\u0000Technologies (DLTs), and they may allow a universal means of payments for the\u0000digital era. There are many ways to proceed, they all require central banks to\u0000develop technological expertise. Considering these points, it is important to\u0000understand the new IT governance in the financial markets due to CBDC and\u0000digital economy. Information Technology is an essential driver that will allow\u0000the new financial industry design. This paper has the objective to answer two\u0000questions through an updated Systematic Literature Review (SLR). The first\u0000question is What IT resources and tools have been considered or applied to set\u0000the governance of CBDC adoption? The second; Identify IT governance models in\u0000the financial market due to CBDC adoption. Bank for International Settlements\u0000(BIS) publications, Scopus and Web of Science were considered as sources of\u0000studies. After the strings and including criteria were applied, fourteen papers\u0000were analyzed. This paper finds many IT resources used in the CBDC adoption and\u0000some preliminary IT design related to the IT governance of CBDC, in the results\u0000and discussion section the findings are more detailed. Finally, limitations and\u0000future work are considered. Keywords: Blockchain, Central Bank Digital Currency\u0000(CBDC), Digital Economy, Distributed Ledger Technology (DLT), Information\u0000Technology (IT), IT governance.","PeriodicalId":501372,"journal":{"name":"arXiv - QuantFin - General Finance","volume":"9 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141609742","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The Impact of Financial Literacy, Social Capital, and Financial Technology on Financial Inclusion of Indonesian Students 金融知识、社会资本和金融技术对印度尼西亚学生金融包容性的影响

arXiv - QuantFin - General Finance Pub Date : 2024-05-10 DOI: arxiv-2405.06570

Gen Norman Thomas, Siti Mutiara Ramadhanti Nur, Lely Indriaty

{"title":"The Impact of Financial Literacy, Social Capital, and Financial Technology on Financial Inclusion of Indonesian Students","authors":"Gen Norman Thomas, Siti Mutiara Ramadhanti Nur, Lely Indriaty","doi":"arxiv-2405.06570","DOIUrl":"https://doi.org/arxiv-2405.06570","url":null,"abstract":"This study aims to analyze the impact of financial literacy, social capital\u0000and financial technology on financial inclusion. The research method used a\u0000quantitative research method, in which questionnaires were distributed to 100\u0000active students in the economics faculty at 7 private colleges in Tangerang,\u0000Indonesia. Based on the results of data processing using SPSS version 23, it\u0000results that financial literacy, social capital and financial technology\u0000partially have a positive and significant influence on financial inclusion. The\u0000results of this study provide input that financial literacy needs to be\u0000increased because it is not yet equivalent to financial inclusion, and reducing\u0000the gap between financial literacy and financial inclusion is only 2.74%.\u0000Another benefit of this research is to give an understanding to students that\u0000students should be independent actors or users of financial technology products\u0000and that students should become pioneers in delivering financial knowledge,\u0000financial behavior and financial attitudes to the wider community.","PeriodicalId":501372,"journal":{"name":"arXiv - QuantFin - General Finance","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140929300","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Entropy and Economics 熵与经济学

arXiv - QuantFin - General Finance Pub Date : 2024-05-07 DOI: arxiv-2407.00022

Martin Pomares Calero

引用次数: 0

Transforming Investment Strategies and Strategic Decision-Making: Unveiling a Novel Methodology for Enhanced Performance and Risk Management in Financial Markets 变革投资战略和战略决策：揭示提高金融市场绩效和风险管理的新方法论

arXiv - QuantFin - General Finance Pub Date : 2024-05-03 DOI: arxiv-2405.01892

Tian Tian, Ricky Cooper, Jiahao Deng, Qingquan Zhang

{"title":"Transforming Investment Strategies and Strategic Decision-Making: Unveiling a Novel Methodology for Enhanced Performance and Risk Management in Financial Markets","authors":"Tian Tian, Ricky Cooper, Jiahao Deng, Qingquan Zhang","doi":"arxiv-2405.01892","DOIUrl":"https://doi.org/arxiv-2405.01892","url":null,"abstract":"This paper introduces a novel methodology for index return forecasting,\u0000blending highly correlated stock prices, advanced deep learning techniques, and\u0000intricate factor integration. Departing from conventional cap-weighted\u0000approaches, our innovative framework promises to reimagine traditional\u0000methodologies, offering heightened diversification, amplified performance\u0000capture, and nuanced market depiction. At its core lies the intricate\u0000identification of highly correlated company clusters, fueling predictive\u0000accuracy and robustness. By harnessing these interconnected constellations, we\u0000unlock a profound comprehension of market dynamics, bestowing both investment\u0000entities and individual enterprises with invaluable performance insights.\u0000Moreover, our methodology integrates pivotal factors such as indexes and ETFs,\u0000seamlessly woven with Hierarchical Risk Parity (HRP) portfolio optimization, to\u0000elevate performance and fortify risk management. This comprehensive\u0000amalgamation refines risk diversification, fortifying portfolio resilience\u0000against turbulent market forces. The implications reverberate resoundingly.\u0000Investment entities stand poised to calibrate against competitors with surgical\u0000precision, tactically sidestepping industry-specific pitfalls, and sculpting\u0000bespoke investment strategies to capitalize on market fluctuations.\u0000Concurrently, individual enterprises find empowerment in aligning strategic\u0000endeavors with market trajectories, discerning key competitors, and navigating\u0000volatility with steadfast resilience. In essence, this research marks a pivotal\u0000moment in economic discourse, unveiling novel methodologies poised to redefine\u0000decision-making paradigms and elevate performance benchmarks for both\u0000investment entities and individual enterprises navigating the intricate\u0000tapestry of financial realms.","PeriodicalId":501372,"journal":{"name":"arXiv - QuantFin - General Finance","volume":"14 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140929306","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

NumLLM: Numeric-Sensitive Large Language Model for Chinese Finance NumLLM：对数字敏感的中文金融大语言模型

arXiv - QuantFin - General Finance Pub Date : 2024-05-01 DOI: arxiv-2405.00566

Huan-Yi Su, Ke Wu, Yu-Hao Huang, Wu-Jun Li

{"title":"NumLLM: Numeric-Sensitive Large Language Model for Chinese Finance","authors":"Huan-Yi Su, Ke Wu, Yu-Hao Huang, Wu-Jun Li","doi":"arxiv-2405.00566","DOIUrl":"https://doi.org/arxiv-2405.00566","url":null,"abstract":"Recently, many works have proposed various financial large language models\u0000(FinLLMs) by pre-training from scratch or fine-tuning open-sourced LLMs on\u0000financial corpora. However, existing FinLLMs exhibit unsatisfactory performance\u0000in understanding financial text when numeric variables are involved in\u0000questions. In this paper, we propose a novel LLM, called numeric-sensitive\u0000large language model (NumLLM), for Chinese finance. We first construct a\u0000financial corpus from financial textbooks which is essential for improving\u0000numeric capability of LLMs during fine-tuning. After that, we train two\u0000individual low-rank adaptation (LoRA) modules by fine-tuning on our constructed\u0000financial corpus. One module is for adapting general-purpose LLMs to financial\u0000domain, and the other module is for enhancing the ability of NumLLM to\u0000understand financial text with numeric variables. Lastly, we merge the two LoRA\u0000modules into the foundation model to obtain NumLLM for inference. Experiments\u0000on financial question-answering benchmark show that NumLLM can boost the\u0000performance of the foundation model and can achieve the best overall\u0000performance compared to all baselines, on both numeric and non-numeric\u0000questions.","PeriodicalId":501372,"journal":{"name":"arXiv - QuantFin - General Finance","volume":"12 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140830407","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The Shape of Money Laundering: Subgraph Representation Learning on the Blockchain with the Elliptic2 Dataset 洗钱的形状：利用 Elliptic2 数据集在区块链上进行子图表示学习

arXiv - QuantFin - General Finance Pub Date : 2024-04-29 DOI: arxiv-2404.19109

Claudio Bellei, Muhua Xu, Ross Phillips, Tom Robinson, Mark Weber, Tim Kaler, Charles E. Leiserson, Arvind, Jie Chen

{"title":"The Shape of Money Laundering: Subgraph Representation Learning on the Blockchain with the Elliptic2 Dataset","authors":"Claudio Bellei, Muhua Xu, Ross Phillips, Tom Robinson, Mark Weber, Tim Kaler, Charles E. Leiserson, Arvind, Jie Chen","doi":"arxiv-2404.19109","DOIUrl":"https://doi.org/arxiv-2404.19109","url":null,"abstract":"Subgraph representation learning is a technique for analyzing local\u0000structures (or shapes) within complex networks. Enabled by recent developments\u0000in scalable Graph Neural Networks (GNNs), this approach encodes relational\u0000information at a subgroup level (multiple connected nodes) rather than at a\u0000node level of abstraction. We posit that certain domain applications, such as\u0000anti-money laundering (AML), are inherently subgraph problems and mainstream\u0000graph techniques have been operating at a suboptimal level of abstraction. This\u0000is due in part to the scarcity of annotated datasets of real-world size and\u0000complexity, as well as the lack of software tools for managing subgraph GNN\u0000workflows at scale. To enable work in fundamental algorithms as well as domain\u0000applications in AML and beyond, we introduce Elliptic2, a large graph dataset\u0000containing 122K labeled subgraphs of Bitcoin clusters within a background graph\u0000consisting of 49M node clusters and 196M edge transactions. The dataset\u0000provides subgraphs known to be linked to illicit activity for learning the set\u0000of \"shapes\" that money laundering exhibits in cryptocurrency and accurately\u0000classifying new criminal activity. Along with the dataset we share our graph\u0000techniques, software tooling, promising early experimental results, and new\u0000domain insights already gleaned from this approach. Taken together, we find\u0000immediate practical value in this approach and the potential for a new standard\u0000in anti-money laundering and forensic analytics in cryptocurrencies and other\u0000financial networks.","PeriodicalId":501372,"journal":{"name":"arXiv - QuantFin - General Finance","volume":"43 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140830274","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Joint Liability Model with Adaptation to Climate Change 适应气候变化的共同责任模式

arXiv - QuantFin - General Finance Pub Date : 2024-04-22 DOI: arxiv-2404.13818

Jiayue Zhang, Ken Seng Tan, Tony S. Wirjanto, Lysa Porth

引用次数: 0

RD2Bench: Toward Data-Centric Automatic R&D RD2Bench：实现以数据为中心的自动研发

arXiv - QuantFin - General Finance Pub Date : 2024-04-17 DOI: arxiv-2404.11276

Haotian Chen, Xinjie Shen, Zeqi Ye, Xiao Yang, Xu Yang, Weiqing Liu, Jiang Bian

{"title":"RD2Bench: Toward Data-Centric Automatic R&D","authors":"Haotian Chen, Xinjie Shen, Zeqi Ye, Xiao Yang, Xu Yang, Weiqing Liu, Jiang Bian","doi":"arxiv-2404.11276","DOIUrl":"https://doi.org/arxiv-2404.11276","url":null,"abstract":"The progress of humanity is driven by those successful discoveries\u0000accompanied by countless failed experiments. Researchers often seek the\u0000potential research directions by reading and then verifying them through\u0000experiments. The process imposes a significant burden on researchers. In the\u0000past decade, the data-driven black-box deep learning method demonstrates its\u0000effectiveness in a wide range of real-world scenarios, which exacerbates the\u0000experimental burden of researchers and thus renders the potential successful\u0000discoveries veiled. Therefore, automating such a research and development (R&D)\u0000process is an urgent need. In this paper, we serve as the first effort to\u0000formalize the goal by proposing a Real-world Data-centric automatic R&D\u0000Benchmark, namely RD2Bench. RD2Bench benchmarks all the operations in\u0000data-centric automatic R&D (D-CARD) as a whole to navigate future work toward\u0000our goal directly. We focuses on evaluating the interaction and synergistic\u0000effects of various model capabilities and aiding to select the well-performed\u0000trustworthy models. Although RD2Bench is very challenging to the\u0000state-of-the-art (SOTA) large language model (LLM) named GPT-4, indicating\u0000ample research opportunities and more research efforts, LLMs possess promising\u0000potential to bring more significant development to D-CARD: They are able to\u0000implement some simple methods without adopting any additional techniques. We\u0000appeal to future work to take developing techniques for tackling automatic R&D\u0000into consideration, thus bringing the opportunities of the potential\u0000revolutionary upgrade to human productivity.","PeriodicalId":501372,"journal":{"name":"arXiv - QuantFin - General Finance","volume":"3 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140616511","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Piercing the Veil of TVL: DeFi Reappraised 揭开 TVL 的面纱：重新评价 DeFi

arXiv - QuantFin - General Finance Pub Date : 2024-04-17 DOI: arxiv-2404.11745

Yichen Luo, Yebo Feng, Jiahua Xu, Paolo Tasca

{"title":"Piercing the Veil of TVL: DeFi Reappraised","authors":"Yichen Luo, Yebo Feng, Jiahua Xu, Paolo Tasca","doi":"arxiv-2404.11745","DOIUrl":"https://doi.org/arxiv-2404.11745","url":null,"abstract":"Total value locked (TVL) is widely used to measure the size and popularity of\u0000protocols and the broader ecosystem in decentralized finance (DeFi). However,\u0000the prevalent TVL calculation framework suffers from a \"double counting\" issue\u0000that results in an inflated metric. We find existing methodologies addressing\u0000double counting either inconsistent or flawed. To mitigate the double counting\u0000issue, we formalize the TVL framework and propose a new framework, total value\u0000redeemable (TVR), designed to accurately assess the true value within\u0000individual DeFi protocol and DeFi systems. The formalization of TVL indicates\u0000that decentralized financial contagion propagates through derivative tokens\u0000across the complex network of DeFi protocols and escalates liquidations and\u0000stablecoin depegging during market turmoil. By mirroring the concept of money\u0000multiplier in traditional finance (TradFi), we construct the DeFi multiplier to\u0000quantify the double counting in TVL. Our empirical analysis demonstrates a\u0000notable enhancement in the performance of TVR relative to TVL. Specifically,\u0000during the peak of DeFi activity on December 2, 2021, the discrepancy between\u0000TVL and TVR widened to $139.87 billion, resulting in a TVL-to-TVR ratio of\u0000approximately 2. We further show that TVR is a more stable metric than TVL,\u0000especially during market turmoil. For instance, a 25% decrease in the price of\u0000Ether (ETH) results in an overestimation of the DeFi market value by more than\u0000$1 billion when measuring using TVL as opposed to TVR. Overall, our findings\u0000suggest that TVR provides a more reliable and stable metric compared to the\u0000traditional TVL calculation.","PeriodicalId":501372,"journal":{"name":"arXiv - QuantFin - General Finance","volume":"28 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140626801","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0