Journal of Finance and Data Science最新文献_第10页

An empirical study of the self-fulfilling prophecy effect in Chinese stock market 中国股市自我实现预言效应的实证研究

Journal of Finance and Data Science Pub Date : 2019-06-01 DOI: 10.1016/j.jfds.2019.04.001

Yun Wan , Xiaoguang Yang

引用次数: 3

Can artificial intelligence enhance the Bitcoin bonanza 人工智能能增强比特币的繁荣吗

Journal of Finance and Data Science Pub Date : 2019-06-01 DOI: 10.1016/j.jfds.2019.01.002

Matheus José Silva de Souza , Fahad W. Almudhaf , Bruno Miranda Henrique , Ana Beatriz Silveira Negredo , Danilo Guimarães Franco Ramos , Vinicius Amorim Sobreiro , Herbert Kimura

引用次数: 26

COSMOS trader – Chaotic Neuro-oscillatory multiagent financial prediction and trading system COSMOS交易员-混沌神经振荡多智能体金融预测和交易系统

Journal of Finance and Data Science Pub Date : 2019-06-01 DOI: 10.1016/j.jfds.2019.01.001

Raymond S.T. Lee

{"title":"COSMOS trader – Chaotic Neuro-oscillatory multiagent financial prediction and trading system","authors":"Raymond S.T. Lee","doi":"10.1016/j.jfds.2019.01.001","DOIUrl":"https://doi.org/10.1016/j.jfds.2019.01.001","url":null,"abstract":"<div><p>Over the years, financial engineering ranging from the study of financial signals to the modelling of financial prediction is one of the most stimulating topics for both academia and financial community. Not only because of its importance in terms of financial and commercial values, but more it vitally poses a real challenge to worldwide researchers and quants owing to its highly chaotic and almost unpredictable nature.</p><p>This paper devises an innovative Chaotic Oscillatory Multi-agent-based Neuro-computing System (a.k.a. COSMOS) for worldwide financial prediction and intelligent trading. With the adoption of author's theoretical works on Lee-oscillator with profound transient-chaotic property, COSMOS effectively integrates chaotic neural oscillator technology into: 1) COSMOS Forecaster - Chaotic FFBP-based Time-series Supervised-learning agent for worldwide financial forecast and; 2) COSMOS Trader - Chaotic RBF-based Actor-Critic Reinforcement-learning agents for the optimization of trading strategies. COSMOS not only provides a fast reinforcement learning and forecast solution, more prominently it successfully resolves the massive data over-training and deadlock problems which usually imposed by traditional recurrent neural networks and RBF networks using classical sigmoid or gaussian-based activation functions.</p><p>From the implementation perspective, COSMOS is integrated with 2048-trading day time-series financial data and 39 major financial signals as input signals for the real-time prediction and intelligent agent trading of 129 worldwide financial products which consists of: 9 major cryptocurrencies, 84 forex, 19 major commodities and 17 worldwide financial indices. In terms of system performance, past 500-day average daily forecast performance of COSMOS attained less 1% forecast percentage errors and with promising results of 8–13% monthly average returns.</p></div>","PeriodicalId":36340,"journal":{"name":"Journal of Finance and Data Science","volume":"5 2","pages":"Pages 61-82"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.jfds.2019.01.001","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"92080387","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: 17

WITHDRAWN: Forecasting performance of smooth transition autoregressive (STAR) model on travel and leisure stock index 摘要:平滑过渡自回归(STAR)模型对旅游休闲股票指数的预测效果

Journal of Finance and Data Science Pub Date : 2019-03-01 DOI: 10.1016/j.jfds.2018.02.004

Usman M. Umer , Tuba Sevil , Güven Sevil

引用次数: 2

An ability to forecast market liquidity – Evidence from South East Asia Mutual fund industry 预测市场流动性的能力——来自东南亚共同基金行业的证据

Journal of Finance and Data Science Pub Date : 2019-03-01 DOI: 10.1016/j.jfds.2018.10.002

Woraphon Wattanatorn , Pimpika Tansupswatdikul

引用次数: 6

Improving trading technical analysis with TensorFlow Long Short-Term Memory (LSTM) Neural Network 用TensorFlow长短期记忆(LSTM)神经网络改进交易技术分析

Journal of Finance and Data Science Pub Date : 2019-03-01 DOI: 10.1016/j.jfds.2018.10.003

Chenjie Sang, Massimo Di Pierro

引用次数: 46

The value of publicly available predicted earnings surprises 可公开获得的预期收益的价值令人惊讶

Journal of Finance and Data Science Pub Date : 2019-03-01 DOI: 10.1016/j.jfds.2018.10.004

Samuel J. Frame , Robin Tu , Jessica M. Martin , Justin M. Berding

{"title":"The value of publicly available predicted earnings surprises","authors":"Samuel J. Frame , Robin Tu , Jessica M. Martin , Justin M. Berding","doi":"10.1016/j.jfds.2018.10.004","DOIUrl":"https://doi.org/10.1016/j.jfds.2018.10.004","url":null,"abstract":"<div><p>This paper demonstrates how to collect and manage free predicted earnings surprises available in the public domain. The predicted earnings surprises we collect are expected to be more accurate than the corresponding consensus estimates and other predicted earnings, but have not been studied in the academic literature until very recently. We find a number of unexpected and problematic idiosyncrasies with the source of the data and the predicted earnings surprises themselves. The data are hard to work with, perhaps by design, and contain both big and small extreme values that are unexpected given their origin. It is unclear how these observations are selected for public release. After the data science exercise of managing and merging the predicted earnings surprises with other freely available public information (specifically ticker symbols and return data), we examine the predicted earnings surprises and investigate how the predicted earnings surprises affect short-term stock prices. We find evidence of a linear association between the predicted earnings surprises and subsequent short-term returns, although the significance is driven by extreme outliers. Most importantly, we use the predicted earnings surprises to form short-term trading strategies. The most profitable trading strategy that exploits the predicted earnings surprises is a contrarian trading strategy.</p></div>","PeriodicalId":36340,"journal":{"name":"Journal of Finance and Data Science","volume":"5 1","pages":"Pages 33-47"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.jfds.2018.10.004","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"92031172","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: 0

Testing market response to auditor change filings: A comparison of machine learning classifiers 测试市场对审计师变更文件的反应:机器学习分类器的比较

Journal of Finance and Data Science Pub Date : 2019-03-01 DOI: 10.1016/j.jfds.2018.08.001

Richard Holowczak , David Louton , Hakan Saraoglu

引用次数: 5

Index option returns and systemic equity risk 指数期权收益与系统性股票风险

Journal of Finance and Data Science Pub Date : 2018-12-01 DOI: 10.1016/j.jfds.2018.05.001

Weiping Li , Tim Krehbiel

{"title":"Index option returns and systemic equity risk","authors":"Weiping Li , Tim Krehbiel","doi":"10.1016/j.jfds.2018.05.001","DOIUrl":"10.1016/j.jfds.2018.05.001","url":null,"abstract":"<div><p>In an environment characterized by stochastic variances and correlations, we demonstrate through construction of the equilibrium index option value from constituent components, that the generalized PDE identifies the stochastic elements differentially affecting index option prices relative to prices of aggregated constituent stock options. A unified treatment of the generalized partial differential system for index and constituent stock options in <span>Theorem 1</span> illustrates that nonlinear interactive terms emanating from stochastic correlation affect index option price and return essentially different from contributions to the aggregated risks of the constituent stock options. Our study contributes to the growing evidence of priced correlation risk in markets for index and constituent stock options.</p><p><span>Theorem 1</span> illustrates the pricing differential, while <span>Proposition 1</span> illustrates that the pricing differential produces a quantifiable metric of the measure of the nonlinear interactive terms. The quantifiable metric is constructed from the difference between the model free implied variance of the index and a weighted aggregate of the model free implied variances of the constituent stocks. <span>Proposition 2</span> identifies that index variance risk premium includes additional significant contributions from the nonlinear interactive risks not present in the aggregated returns of the constituent stocks. The nonlinear interactive risks produce a wedge between the instantaneous expected excess index and aggregated stock option returns.</p></div>","PeriodicalId":36340,"journal":{"name":"Journal of Finance and Data Science","volume":"4 4","pages":"Pages 273-298"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.jfds.2018.05.001","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125505724","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: 0

Does public expenditure on education promote Tunisian and Moroccan GDP per capita? ARDL approach 教育方面的公共支出是否促进了突尼斯和摩洛哥的人均GDP ?ARDL方法

Journal of Finance and Data Science Pub Date : 2018-12-01 DOI: 10.1016/j.jfds.2018.02.005

Adel Ifa , Imène Guetat

引用次数: 47