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Most Downloaded The Journal of Finance and Data Science Articles

The most downloaded articles from ScienceDirect in the last 90 days.

1. Selecting appropriate methodological framework for time series data analysis

June 2018
Min B. Shrestha | Guna R. Bhatta

Economists face method selection problem while working with time series data. As time series data may possess specific properties such as trend and structural break, common methods used to analyze other...

2. Twitter as a tool for forecasting stock market movements: A short-window event study

June 2018
Tahir M. Nisar | Man Yeung

In order to explore the relationship between politics-related sentiment and FTSE 100 movements, we conducted a short-window event study of a UK based political event. We collected a sample of over 60,000...

3. A hybrid stock trading framework integrating technical analysis with machine learning techniques

March 2016
Rajashree Dash | Pradipta Kishore Dash

In this paper, a novel decision support system using a computational efficient functional link artificial neural network (CEFLANN) and a set of rules is proposed to generate the trading decisions more...

4. Stock price prediction using support vector regression on daily and up to the minute prices

September 2018
Bruno Miranda Henrique | Vinicius Amorim Sobreiro | Herbert Kimura

The purpose of predictive stock price systems is to provide abnormal returns for financial market operators and serve as a basis for risk management tools. Although the Efficient Market Hypothesis (EMH)...

5. Predicting bitcoin returns using high-dimensional technical indicators

September 2019
Jing-Zhi Huang | William Huang | Jun Ni

There has been much debate about whether returns on financial assets, such as stock returns or commodity returns, are predictable; however, few studies have investigated cryptocurrency return predictability....

6. Improving trading technical analysis with TensorFlow Long Short-Term Memory (LSTM) Neural Network

March 2019
Chenjie Sang | Massimo Di Pierro

In this paper we utilize a Long Short-Term Memory Neural Network to learn from and improve upon traditional trading algorithms used in technical analysis. The rationale behind our study is that the...

7. Financial news predicts stock market volatility better than close price

June 2018
Adam Atkins | Mahesan Niranjan | Enrico Gerding

The behaviour of time series data from financial markets is influenced by a rich mixture of quantitative information from the dynamics of the system, captured in its past behaviour, and qualitative...

8. An overview on data representation learning: From traditional feature learning to recent deep learning

December 2016
Guoqiang Zhong | Li-Na Wang | Xiao Ling | Junyu Dong

Since about 100 years ago, to learn the intrinsic structure of data, many representation learning approaches have been proposed, either linear or nonlinear, either supervised or unsupervised, either...

9. Big data based fraud risk management at Alibaba

December 2015
Jidong Chen | Ye Tao | Haoran Wang | Tao Chen

With development of mobile internet and finance, fraud risk comes in all shapes and sizes. This paper is to introduce the Fraud Risk Management at Alibaba under big data. Alibaba has built a fraud risk...

10. Textual analysis and machine leaning: Crack unstructured data in finance and accounting

September 2016
Li Guo | Feng Shi | Jun Tu

In finance and accounting, relative to quantitative methods traditionally used, textual analysis becomes popular recently despite of its substantially less precise manner. In an overview of the literature,...

11. The effects of mergers and acquisitions on stock price behavior in banking sector of Pakistan

March 2018
Zahoor Rahman | Arshad Ali | Khalil Jebran

Mergers and Acquisitions are considered as one of the useful strategies for growth and expansion of businesses. These strategies have widely been adopted in developed economies while are quite often...

12. The extent of voluntary disclosure and its determinants in emerging markets: Evidence from Egypt

Mostafa I. Elfeky

The primary objective of this study is to test a theoretical framework relating eight major corporate governance determinants with the extent of the voluntary disclosure provided by listed firms listed...

13. A case study on loan loss analysis of a community bank

December 2015
Weiping Li | Philip McMahan

In this paper, we perform a case study on a community bank from the aspect of the terms structure of the banks historical loan losses and the loan quality rating matrix used by the bank. The data source...

14. Can artificial intelligence enhance the Bitcoin bonanza

June 2019
Matheus José Silva de Souza | Fahad W. Almudhaf | Bruno Miranda Henrique | Ana Beatriz Silveira Negredo | Danilo Guimarães Franco Ramos | Vinicius Amorim Sobreiro | Herbert Kimura

This paper aims to investigate how Machine Learning (ML) techniques perform in the prediction of cryptocurrency prices. We answer if Support Vector Machines (SVM) and Artificial Neural Networks (ANN)...

15. Auto insurance fraud detection using unsupervised spectral ranking for anomaly

March 2016
Ke Nian | Haofan Zhang | Aditya Tayal | Thomas Coleman | Yuying Li

For many data mining problems, obtaining labels is costly and time consuming, if not practically infeasible. In addition, unlabeled data often includes categorical or ordinal features which, compared...

16. Latency critical big data computing in finance

December 2015
Xinhui Tian | Rui Han | Lei Wang | Gang Lu | Jianfeng Zhan

Analytics based on big data computing can benefit today's banking and financial organizations on many aspects, and provide much valuable information for organizations to achieve more intelligent trading,...

17. Foreign exchange market microstructure and the WM/Reuters 4 pm fix

March 2016
P.S. Michelberger | J.H. Witte

A market fix serves as a benchmark for foreign exchange (FX) execution, and is employed by many institutional investors to establish an exact reference at which execution takes place. The currently...

18. Detection of rare events: A machine learning toolkit with an application to banking crises

December 2019
Jérôme Coffinet | Jean-Noël Kien

We propose a machine learning toolkit applied to the detection of rare events, namely banking crises. For this purpose, we consider a broad set of macroeconomic series (credit-to-GDP gap, house prices,...

19. Regulatory learning: How to supervise machine learning models? An application to credit scoring

September 2018
Dominique Guégan | Bertrand Hassani

The arrival of Big Data strategies is threatening the latest trends in financial regulation related to the simplification of models and the enhancement of the comparability of approaches chosen by financial...

20. Efficiency and technology gaps in Indian banking sector: Application of meta-frontier directional distance function DEA approach

September 2019
Jatin Goyal | Manjit Singh | Rajdeep Singh | Arun Aggarwal

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...

21. The effect of firm and stock characteristics on stock returns: Stock market crash analysis

June 2016
Rizaldi Fauzi | Imam Wahyudi

This study aims to determine characteristics of stocks and firms that are deliberately affected by stock market crash occurring in Indonesia. The study uses data for three major stock market crashes...

22. Pricing and hedging of arithmetic Asian options via the Edgeworth series expansion approach

March 2016
Weiping Li | Su Chen

In this paper, we derive a pricing formula for arithmetic Asian options by using the Edgeworth series expansion. Our pricing formula consists of a Black-Scholes-Merton type formula and a finite sum...

23. Does public expenditure on education promote Tunisian and Moroccan GDP per capita? ARDL approach

December 2018
Adel Ifa | Imène Guetat

This paper aims to analyze the impact of public education expenditures on GDP per capita of Tunisia and Morocco during the period 1980–2015. This study is based on the Auto-Regressive Distributive Lags...

24. Daily value-at-risk modeling and forecast evaluation: The realized volatility approach

September 2016
Zhen Yao Wong | Wen Cheong Chin | Siow Hooi Tan

One of the main applications of conditional volatility modeling and forecasting of financial assets is the value-at-risk (VaR) estimation that is used by financial institutions for reporting the daily...

25. An equity fund recommendation system by combing transfer learning and the utility function of the prospect theory

December 2018
Li Zhang | Han Zhang | SuMin Hao

Investors in financial markets are often at a loss when facing a huge range of products. For financial institutions also, how to recommend products to the right investors, especially those without previous...

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