Journal of Finance and Data Science最新文献_第9页

Fuel up with OATmeals! The case of the French nominal yield curve 用燕麦片补充能量!法国名义收益率曲线的例子

Journal of Finance and Data Science Pub Date : 2020-11-01 DOI: 10.1016/j.jfds.2020.07.001

Olesya V. Grishchenko , Franck Moraux , Olga Pakulyak

引用次数: 1

Should asset managers pay for economic research? A machine learning evaluation 资产管理公司应该为经济研究付费吗?机器学习评估

Journal of Finance and Data Science Pub Date : 2020-11-01 DOI: 10.1016/j.jfds.2020.08.001

Krzysztof Rybinski

{"title":"Should asset managers pay for economic research? A machine learning evaluation","authors":"Krzysztof Rybinski","doi":"10.1016/j.jfds.2020.08.001","DOIUrl":"10.1016/j.jfds.2020.08.001","url":null,"abstract":"<div><p>This paper presents the first-ever comparison of the forecasting power of two types of narratives: articles in a major daily newspaper and regular research reports released by professional forecasters. The applied testing methodology developed in <sup>22</sup> and extended in this paper includes two natural language processing (NLP) techniques – the sentiment analysis and the wordscores model – that are used to convert the text corpora into the NLP indices. These indices are explanatory variables in linear regression, Granger causality test, vector autoregressive model and random forest model. The paper extends this methodology by applying Latent Dirichlet Allocation (LDA) to the newspaper corpus to filter out articles that discuss topics not relevant for economic and financial analysis. The forecasting test is conducted for two major banks in Poland – BZ WBK and mbank and for major daily newspaper Rzeczpospolita, in Polish. It is shown that mbank narratives have the best forecasting power, while BZ WBK and Rzeczpospolita trade second and third place depending on the model applied. In the vast majority of analyzed cases adding an NLP index to the model improves the forecast accuracy. The answer to the title question is – it depends. Before paying for economic research asset managers are advised to apply methods such as presented in this paper to evaluate whether sell-side research offers any forecasting value in comparison with a newspaper.</p></div>","PeriodicalId":36340,"journal":{"name":"Journal of Finance and Data Science","volume":"6 ","pages":"Pages 31-48"},"PeriodicalIF":0.0,"publicationDate":"2020-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.jfds.2020.08.001","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117330867","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Rollover risk and credit spreads in the financial crisis of 2008 2008年金融危机中的展期风险和信贷息差

Journal of Finance and Data Science Pub Date : 2020-11-01 DOI: 10.1016/j.jfds.2020.06.001

Grace Xing Hu

引用次数: 13

Forecasting multinomial stock returns using machine learning methods 使用机器学习方法预测多项股票收益

Journal of Finance and Data Science Pub Date : 2020-11-01 DOI: 10.1016/j.jfds.2020.09.001

Lauri Nevasalmi

引用次数: 0

Detection of rare events: A machine learning toolkit with an application to banking crises 罕见事件的检测:一个应用于银行危机的机器学习工具包

Journal of Finance and Data Science Pub Date : 2019-12-01 DOI: 10.1016/j.jfds.2020.04.001

Jérôme Coffinet , Jean-Noël Kien

引用次数: 4

Predicting bitcoin returns using high-dimensional technical indicators 利用高维技术指标预测比特币收益

Journal of Finance and Data Science Pub Date : 2019-09-01 DOI: 10.1016/j.jfds.2018.10.001

Jing-Zhi Huang , William Huang , Jun Ni

引用次数: 94

Quadratic hedging strategies for private equity fund payment streams 私人股本基金支付流的二次对冲策略

Journal of Finance and Data Science Pub Date : 2019-09-01 DOI: 10.1016/j.jfds.2019.08.002

Christian Tausch

引用次数: 0

WITHDRAWN:Investor's anticipation and future market movement: Evidence of self-fulfilling prophecy effect from the The Chinese stock market 撤回:投资者预期与未来市场走势:中国股市自我实现预言效应的证据

Journal of Finance and Data Science Pub Date : 2019-09-01 DOI: 10.1016/j.jfds.2019.04.002

Yun Wan , Xiaoguang Yang

引用次数: 0

Efficiency and technology gaps in Indian banking sector: Application of meta-frontier directional distance function DEA approach 印度银行业效率与技术差距:元前沿定向距离函数DEA方法的应用

Journal of Finance and Data Science Pub Date : 2019-09-01 DOI: 10.1016/j.jfds.2018.08.002

Jatin Goyal , Manjit Singh , Rajdeep Singh , Arun Aggarwal

{"title":"Efficiency and technology gaps in Indian banking sector: Application of meta-frontier directional distance function DEA approach","authors":"Jatin Goyal , Manjit Singh , Rajdeep Singh , Arun Aggarwal","doi":"10.1016/j.jfds.2018.08.002","DOIUrl":"10.1016/j.jfds.2018.08.002","url":null,"abstract":"<div><p>Government of India aims at making the Indian Banks internationally competitive. In the wake of intense competition and changing global and national business environment, the efficiency issues have emerged as an important pillar of success in the Indian banking sector. Therefore, it is an essential task to comprehend the efficiency levels of the overall Indian banking sector and also across different ownership structures (viz. Public, Private and Foreign). The present study endeavors to carry out an assessment of intra-sector efficiency in the Indian banking sector based on a cross-sectional data of 66 banks for the year 2015-16. The authors employ directional distance function based meta-frontier DEA approach and the results reveal that the Indian banking sector is 73.44% efficient. It also confirms the existence of different production functions across different ownership structures of the industry. Among the different ownership structures, the group frontier of foreign banks coincides with the meta-frontier. The group frontier of private sector banks is the second closest to the meta-frontier and public sector banks are found to be the laggards in the overall industry. The study gains special significance in the backdrop of the recommendations floated by the Reserve Bank of India and Ministry of Finance (Government of India) to consolidate the public sector banks in order to retain fewer but healthier banks. The finding of the study fully support these recommendations and affirms that consolidation in the industry will bring positive synergies and will lead to the enhancement of efficiency levels in the industry.</p></div>","PeriodicalId":36340,"journal":{"name":"Journal of Finance and Data Science","volume":"5 3","pages":"Pages 156-172"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.jfds.2018.08.002","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114338707","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 32

Volatility transmission in the Nigerian financial market 尼日利亚金融市场的波动传导

Journal of Finance and Data Science Pub Date : 2019-06-01 DOI: 10.1016/j.jfds.2019.01.003

Ismail O. Fasanya , Mary A. Akinde

{"title":"Volatility transmission in the Nigerian financial market","authors":"Ismail O. Fasanya , Mary A. Akinde","doi":"10.1016/j.jfds.2019.01.003","DOIUrl":"https://doi.org/10.1016/j.jfds.2019.01.003","url":null,"abstract":"<div><p>This paper examines the return and volatility spillovers in the Nigerian Financial market. We specifically analyse the spillovers in the capital market, money market and foreign exchange market utilizing monthly data for the period January 2002 to June 2017. The paper employs the Diebold and Yilmaz (DY hereafter) (2009, 2012) approach to compute the total spillover, directional spillover, and net spillover indexes. We also consider the rolling window analyses to capture the secular and cyclical movement in the financial markets over the period of consideration. The paper observes weak degree of interdependence as well as cross-market spillovers among the financial instruments.</p><p>The stock market is the largest net receiver and sender of return spillovers to other markets, while the foreign exchange market is the net giver of volatility spillovers followed by the money market, and the stock market is the net recipient. In addition, return spillovers unveils slight trends and bursts while volatility spillovers show significant bursts but no trends. Concomitantly, the significant burst was attributed to the removal of currency peg in 2016 by the Central Bank of Nigeria. Our results are robust to the different VAR lag structure.</p></div>","PeriodicalId":36340,"journal":{"name":"Journal of Finance and Data Science","volume":"5 2","pages":"Pages 99-115"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.jfds.2019.01.003","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91961006","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 12